INTELLIGENT COMPRESSED AIR SYSTEM AND METHOD

Abstract

A system includes at least one sensor device in a compressed air line, at least one smart control valve in the compressed air line, and at least one processor to receive sensor data associated with the compressed air line from the at least one sensor device, store the sensor data, compare the sensor data from the at least one sensor device with a threshold to determine whether there is one of productive demand and non-productive demand from a demand source connected to the compressed air line, send a command to the at least one smart control valve based on the one of the productive demand and the non-productive demand from the demand source, and operate the at least one smart control valve based on the command to open the smart control valve when there is productive demand and close the smart control valve when there is non-productive demand.

Description

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of priority to U.S. Appl. No. 62/729,465 filed Sep. 11, 2018, entitled “Apparatus and Method for the Remote Control of Flow Distribution and Fluid Condition Monitoring in a Fluid Delivery System,” the entire contents of which is hereby incorporated herein by reference.

BACKGROUND

According to the Compressed Air & Gas Institute, there is over $3.2 billion that is wasted each year because of inefficiencies associated with compressed air systems. Although popular, compressed air systems are one of the least efficient power sources used in manufacturing.

It is known that leaks are a significant source of wasted energy in a compressed air system. Twenty to thirty percent of an air compressor's output may be wasted over the life of the air compressor. The leaks may cause problems including excessive financial costs, burdens associated with excess use, and a shorter life of air supply equipment due to overuse. Current solutions may address leaks at a supply side of a compressed air system (e.g., compressors or air treatment) or may address leaks at a demand side of the compressed air system (e.g., nozzles, pneumatics).

It is with these issues in mind, among others, that various aspects of the disclosure were conceived.

SUMMARY

According to one aspect, an intelligent compressed air system provides a supply side system that may provide a supply of compressed air, compressed gas, or another fluid. The supply side system may be located at a facility and include one or more distribution components that distribute the compressed air such as one or more compressed air lines. Each of the one or more lines may provide a supply of compressed air to a demand source such as a machine or tool. The demand source may be a productive demand when in use and may be a non-productive demand when not in use. Each line may have one or more associated smart control valves that can open and close and one or more sensors that may determine flow and other information associated with the line. The smart control valves and the sensor devices may communicate with a computing device using a communications network. As an example, the sensor device may determine that there is reduced demand at a demand source at a particular time and send data to the computing device. The computing device may send a command to an associated smart control valve and the smart control valve may close to reduce or stop flow of compressed air to the demand source. As another example, the computing device may send a command to the associated smart control valve at a particular time (e.g., 8 a.m.) when a plant is opening and an associated machine or tool is in use. The smart control valve may open to increase flow of compressed air to the demand source. As another example, the computing device may send a command to the associated smart control valve at a particular time (e.g., 5 p.m.) when a plant is closing and an associated machine or tool is not in use. The smart control valve may close to reduce or stop flow of compressed air to the demand source. This may reduce waste for the facility thereby saving use of resources and electricity, and provide financial savings and benefits for the facility.

According to an aspect, an intelligent compressed air system includes at least one sensor device in a compressed air line, at least one smart control valve in the compressed air line, and at least one processor to receive sensor data associated with the compressed air line from the at least one sensor device, store the sensor data in a computer-readable storage medium, compare the sensor data from the at least one sensor device with a threshold to determine whether there is one of productive demand and non-productive demand from a demand source connected to the compressed air line, send a command to the at least one smart control valve based on the one of the productive demand and the non-productive demand from the demand source, and operate the at least one smart control valve based on the command to open the smart control valve when there is productive demand and close the smart control valve when there is non-productive demand.

According to another aspect, a method includes receiving, by at least one processor, sensor data associated with a compressed air line from at least one sensor device, storing, by the at least one processor, the sensor data in a computer-readable storage medium, comparing, by the at least one processor, the sensor data from the at least one sensor device with a threshold to determine whether there is one of productive demand and non-productive demand from a demand source connected to the compressed air line, sending, by the at least one processor, a command to at least one smart control valve in the compressed air line based on the one of the productive demand and the non-productive demand from the demand source, and operating, by the at least one processor, the at least one smart control valve based on the command to open the smart control valve when there is productive demand and close the smart control valve when there is non-productive demand.

According to an additional aspect, a non-transitory computer-readable storage medium includes instructions stored thereon that, when executed by a computing device cause the computing device to perform operations, the operations including receiving sensor data associated with a compressed air line from at least one sensor device, storing the sensor data in the non-transitory computer-readable storage medium, comparing the sensor data from the at least one sensor device with a threshold to determine whether there is one of productive demand and non-productive demand from a demand source connected to the compressed air line, sending a command to at least one smart control valve in the compressed air line based on the one of the productive demand and the non-productive demand from the demand source, and operating the at least one smart control valve based on the command to open the smart control valve when there is productive demand and close the smart control valve when there is non-productive demand.

These and other aspects, features, and benefits of the present disclosure will become apparent from the following detailed written description of the preferred embodiments and aspects taken in conjunction with the following drawings, although variations and modifications thereto may be effected without departing from the spirit and scope of the novel concepts of the disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings illustrate embodiments and/or aspects of the disclosure and, together with the written description, serve to explain the principles of the disclosure. Wherever possible, the same reference numbers are used throughout the drawings to refer to the same or like elements of an embodiment, and wherein:

FIG. 1 is a block diagram of an intelligent compressed air system according to an example embodiment.

FIG. 2 illustrates a graph that shows a compressed air audit for a facility according to an example embodiment.

FIG. 3 illustrates a block diagram of a computing device of the intelligent compressed air system having an intelligent compressed air application according to an example embodiment.

FIG. 4 illustrates a flowchart of a process for operating the intelligent compressed air system according to an example embodiment.

FIG. 5 illustrates a usage graph associated with a plant that is determined by the intelligent compressed air system according to an example embodiment.

FIG. 6 illustrates a graphical user interface of the intelligent compressed air application according to an example embodiment.

FIG. 7 illustrates a block diagram of a computing device according to an example embodiment.

DETAILED DESCRIPTION

Aspects of a method and system for providing intelligent and efficient usage of compressed air or gas includes a supply side system that may provide a supply of compressed air, gas, or another fluid. The supply side system may be located at a facility and include one or more distribution components that distribute the compressed air such as one or more lines. Each of the one or more lines may provide a supply of compressed air to a demand source such as a machine or tool. The demand source may be a productive demand when in use and may be a non-productive demand when not in use.

Each line may have one or more associated smart control valves that can open and close and one or more sensors that may determine flow and other information associated with the line. The smart control valves and the sensor devices may communicate with a computing device using a communications network. As an example, the sensor device may send data to the computing device that indicates that there is reduced demand at a demand source at a particular time. Based on the data, the computing device may send a command to an associated smart control valve and the smart control valve may close to reduce or stop flow of compressed air to the demand source.

In another example, the computing device may send a command to an associated smart control valve based on a scheduled opening or closing of the valve at a particular time according to schedule data. As an example, the smart control valve may be opened when an associated demand source is in use (e.g., operating hours of a facility) and the smart control valve may be closed when the demand source is not in use (e.g., non-operating hours for the facility). This may reduce waste for the facility thereby saving use of resources and electricity, and provide financial savings and benefits for the facility.

Current solutions that address efficient usage of compressed air include low flow air nozzles, high efficiency pneumatics, variable speed drive compressors (VSD), compressor control systems, and high efficiency air dryers. However, these solutions are associated entirely on the demand side or on the supply side. There are significant overlooked savings and efficiencies that are associated with the compressed air distribution network. By creating a smart and intelligent distribution network that is connected to a communications network including one or more computing devices, the system and method discussed herein can achieve better results and savings including energy savings and financial savings.

Increasing the efficiency of the compressed air distribution network will directly increase the lifetime of a supply side system. By supplying less air to the system, an associated compressor can run at a lower average rate. As a result, the supply side system may have a longer lifetime. Over a ten year period, electricity may represent about 75% of the financial cost of running a compressed air system. However, maintenance may be around 12% of the financial cost and equipment may be about 12%. By increasing the efficiency, this may have a direct effect on the entire cost of running the system.

Based on previous studies, it has been determined that a total amount of energy to run an example compressed air system may be approximately $17,000 a year. A leak rate of the system was determined to be around 28% of the average demand of the system. Such leaks are a significant source of wasted energy in a compressed air system and typically waste as much as 20-30% of an air compressor's output as in this example. By eliminating or reducing the leak rate of the system, this may result in $5,000 in potential savings a year.

FIG. 1 shows a block diagram of an intelligent compressed air system 100 according to an example embodiment. The intelligent compressed air system 100 may include a an intelligent compressed air apparatus 101 that may include one or more smart control valves 102, one or more sensor devices 104, a communications network 106, and at least one computing device 108.

The intelligent compressed air apparatus 101 may be located between a supply side system 110 and one or more demand sources or fluid devices at a facility. The one or more demand sources may be used at the facility for up to twenty-four hours a day and may leak an amount of fluid while idle. The supply side system 110 may be a source of a fluid such as a compressor.

The intelligent compressed air apparatus 101 may be added or combined with a pre-existing fluid delivery or compressed air system in a facility. The facility may be a factory or a plant such as a manufacturing plant and the one or more demand sources may be a machine or a tool that may use a consumable such as compressed air or another fluid. In one example, the facility may be a vehicle assembly plant where vehicles move down an assembly line having one or more machines or tools. The machine may be a robot, a metalworking machine tool such as a stamping press, or a computer numerical control (CNC) machine that may be used to process a material such as metal, plastic, wood, ceramic, or another material. In another example, the facility may be an industrial facility that molds widgets using one or more machines or tools. The facility may be any location where compressed air, gas, or fluid may be used such as a school building, an aircraft carrier, a cruise ship, or a battleship, among others.

The supply side system 110 may be a centrally available compressor that powers the one or more demand sources such as cylinders, air motors, and other pneumatic devices. The demand source may be a pneumatic device that makes use of the compressed air or fluid such as a handheld tool including a wrench, a screw driver, air nozzle for cleaning, or an industrial machine such as a motor, a turbine, robotics, process controls, an entire assembly line, or another type of pneumatic device.

The one or more smart control valves 102 may control flow distribution in the intelligent compressed air system 100. The smart control valve 102 may be an electronically controlled valve and have a relay to open or close the valve. The smart control valve 102 may be flow control valve such as a ball valve, a butterfly valve, a solenoid valve, or another type of valve that may be located in a line of the facility. The line may be used to distribute compressed air, compressed gas, or another fluid from the supply side system 110 to one or more demand sources. The smart control valve may include a computing device that is connected to a motor, an actuator, or a motorized system that may operate the smart control valve 102. In addition, the smart control valve 102 may have a power device that powers the smart control valve 102. Each smart control valve 102 may be operated and controlled remotely. In other words, each smart control valve 102 may be operated by a client computing device that is in communication with the computing device 108 via the communication network 106.

As a result, the smart control valves 102 may quickly and remotely close-off branches and lines in the intelligent compressed air system 100 when they are not in use to reduce a number of active leak points in the intelligent compressed air system 100 at the facility. By reducing the number of potential leak points in the intelligent compressed air system 100, the facility can reduce an amount of fluid or compressed air and energy that is lost. The one or more smart control valves 102 may operate based on a schedule or systematic plan that may take into account which demand points are active and working, which demand points are idle, shift changes at the facility, operating hours at the facility, and cycle times, among other factors, in order to automate the one or more smart control valves and associated energy savings.

The facility may anticipate a standard leak rate of 20 or 30% of total demand. As an example, before operating hours at the facility, without the smart control valves 102 or when the smart control valves 102 are open, machines and tools that are connected to the lines may continually leak at the standard leak rate. However, during the hours of operation, the machines and tools may be used at a peak rate (e.g., 60% of capacity) and a higher amount of compressed air may be used. In other words, the leaks associated with demand points may continually be present. However, if a demand point is in use, the leak associated with the demand point becomes part of the active demand.

At certain times such as off shifts, shift changes, lunches, or in between cycle times, the machines, robotics, and tools may not be used. The facility can take this usage into consideration to minimize the air lost through leaks by closing the one or more smart control valves 102 that supply compressed air to the machines and tools when they are not in use. As an example, one robotic arm may perform a motion such as rotate a component and do this two seconds of every minute. Adding the one or more smart control valves 102 upstream can eliminate leaks for fifty-eight seconds of each minute when idle. Each worker or employee that uses the machines and tools does not have to provide input to the intelligent compressed air system 100 and indicate when the machines and tools are in use. Rather, the intelligent compressed air system 100 may determine and predict when the machines and tools are in use based on current real-time usage and other data such as the schedule data, plan data, machine learning, and other information.

As an example, the sensor device 104 may be a flow sensor and/or a pressure sensor that may be located in or along a line of the facility. In another example, the sensor device 104 may be a temperature sensor, a pressure sensor, and/or a humidity sensor. As an example, the sensor device 104 may be a constant temperature anemometer (CTA). The sensor device 104 may be in communication with the smart control valve 102 and also may have a computing device that may send data and information to the computing device 108. Although FIG. 1 shows that the sensor device 104 is located closer to the demand source than the smart control valve 102, they may be arranged in another order or in another way.

As an example, the sensor device 104 may be a constant temperature anemometer (CTA) and utilize King's Law and the following equation to determine flow velocity where U=Constant Temperature Anemometer (CTA) output, U₀=Free convection offset, k=Fluid constant, and v=Fluid velocity.

U=U₀*SQRT(1+k*vⁿ), where n=0.2 . . . 0.5  Equation:

In one example, the k value and the n value may be determined from experimental results. While each sensor device 104 may have different readings, the sensor device 104 may generally be used to determine if the flow is in a leak profile or a demand profile. The difference between a leak state and a demand state in the flow is determinable by the sensor device 104.

As an example, the sensor device 104 may be inserted into the flow stream in one of the lines of the intelligent compressed air system 100. The sensor device 104 may be inserted at a depth in the line such that a center of the sensor device 104 and an associated probe sits at a center of the flow. In another example, the sensor device 104 may be inserted at ⅔ of the center of the flow or in another location.

In one example, the computing device 108 may be housed in a housing and installed in a location in the facility near or along one or more of the distribution components that distribute the compressed air such as the one or more lines of the facility. The computing device 108 may execute an intelligent compressed air application that receives data and information from the one or more sensor devices 104. Based on the data and information from the one or more sensor devices 104, the intelligent compressed air application may operate the one or more smart control valves 102. The intelligent compressed air application may use a variety of information to operate the one or more smart control valves 102.

The one or more smart control valves 102 may be operated using scheduled or systematic, remote or manual control. The intelligent compressed air application may use data including real-time information obtained from the one or more sensor devices 104 and other sources of information such as schedule information for the facility (e.g., worker schedule information for the facility), historical usage information for the facility, historical usage information from other facilities, and other information. As a result, the intelligent compressed air application may reduce waste for the facility thereby saving use of resources and electricity, and provide financial savings and benefits for the facility.

The communication network 106 can be the Internet, an intranet, or another wired or wireless communication network. For example, the communication network 106 may include a cellular network such as Mobile Communications (GSM) network, a code division multiple access (CDMA) network, 3^rd Generation Partnership Project (GPP) network, an Internet Protocol (IP) network, a wireless application protocol (WAP) network, a WiFi network, a Bluetooth network, a satellite communications network, or an IEEE 802.11 standards network, as well as various communications thereof. Other conventional and/or later developed wired and wireless networks may also be used.

The smart control valve 102 includes at least one processor to process data and memory to store data. The smart control valve 102 may include a Single Board Computer (SBC) or a System on a Chip (SOC). Alternatively, the smart control valve 102 may include a Raspberry or Arduino® based computing device. The processor processes communications, builds communications, retrieves data from memory, and stores data to memory. The processor and the memory are hardware. The memory may include volatile and/or non-volatile memory, e.g., a computer-readable storage medium such as a cache, random access memory (RAM), read only memory (ROM), flash memory, or other memory to store data and/or computer-readable executable instructions such as the intelligent compressed air application. In addition, the smart control valve 102 may include at least one communications interface to transmit and receive communications, messages, and/or signals.

The sensor device 104 includes at least one processor to process data and memory to store data. In one example, the sensor device 104 may include a Raspberry Pi® or Arduino® based computing device. The processor processes communications, builds communications, retrieves data from memory, and stores data to memory. The processor and the memory are hardware. The memory may include volatile and/or non-volatile memory, e.g., a computer-readable storage medium such as a cache, random access memory (RAM), read only memory (ROM), flash memory, or other memory to store data and/or computer-readable executable instructions such as the intelligent compressed air application. In addition, the sensor device 104 further includes at least one communications interface to transmit and receive communications, messages, and/or signals.

The at least one computing device 108 may be a server computing device and includes at least one processor to process data and memory to store data. The at least one computing device 108 may include a cloud based computing device. In one example, the computing device 108 may be a Raspberry Pi® or Arduino® based computing device. The processor processes communications, builds communications, retrieves data from memory, and stores data to memory. The processor and the memory are hardware. The memory may include volatile and/or non-volatile memory, e.g., a computer-readable storage medium such as a cache, random access memory (RAM), read only memory (ROM), flash memory, or other memory to store data and/or computer-readable executable instructions such as the intelligent compressed air application. In addition, the at least one computing device 108 further includes at least one communications interface to transmit and receive communications, messages, and/or signals.

The at least one computing device 108 may include a display and an input device. The display is used to display visual components of the intelligent compressed air application, such as at a user interface. In one example, the user interface may display a user interface of the intelligent compressed air application and a representation of the requested resources received from the computing device 108. The display can include a cathode-ray tube display, a liquid-crystal display, a light-emitting diode display, a touch screen display, and/or other displays.

The input device is used to interact with the intelligent compressed air application or otherwise provide inputs to the computing device 108 and may include a mouse, a keyboard, a trackpad, and/or the like. The input device may be included within the display if the display is a touch screen display. The input device allows a user of the computing device 108 to manipulate the user interface of the intelligent compressed air application or otherwise provide inputs to the computing device 108.

As an example, FIG. 1 shows three different smart control valves 102 and three different sensor devices 104. In this example, the supply side system 110 has a header that connects via connection points to one or more branches or lines. The supply side system 110 may deliver a fluid such as compressed air to one or more locations or destinations including one or more machines or tools.

In FIG. 1 there are three branches, each for an individual point of demand, only two of which are productive. The third point of demand can be viewed as leaks occurring at a machine or assembly line that is idle and currently not in use. As an example, FIG. 1 may show a factory or a portion of a factory during a shift, where the overall utilization rate is 66.7%. However, without the smart control valve 102, the non-productive demand would receive compressed air from the supply side system 110 and contribute to the overall energy demand. This would lead to a lower overall efficiency of the system 100 and an amount of wasted air released to the atmosphere.

The smart control valves 102 and the sensor devices 104 are arranged between the supply side system 110 and one or more demand sources at a facility. A first demand source, such as a machine or tool, may currently have a non-productive demand 114. As shown in FIG. 1, the sensor device 104 receives data associated with the compressed air distribution line. The data may be sent to the computing device 108 and indicate that there is non-productive demand. The computing device 108 may compare the sensor data from the sensor device 104 with a threshold to determine that there is non-productive demand 114 from the demand source connected to the compressed air line. The computing device 108 may send a command to the smart control valve 102 based on the non-productive demand 114 from the demand source and operate the smart control valve. In the example, the smart control valve 102 may close when there is non-productive demand 114. This is indicated in FIG. 1 by the dashed line. FIG. 1 shows that there is one machine of the three shown with non-productive demand 114.

Alternatively, the data may be sent to the computing device 108 that indicates that there is productive demand 112 by the demand source such as a machine or tool. The computing device 108 may compare the sensor data from the sensor device with a threshold to determine that there is productive demand 112 from the demand source connected to the compressed air line. The computing device 108 may send a command to the smart control valve 102 based on the productive demand 112 from the demand source and operate the smart control valve 102. In the example, the smart control valve 102 may open when there is productive demand 112. This is indicated in FIG. 1 by the solid line. FIG. 1 shows that there is one machine and one tool (e.g., two of the three shown) that has productive demand 112.

FIG. 2 illustrates a graph 200 that shows a compressed air audit for a facility according to an example embodiment. The graph 200 illustrates a flow rate of compressed air over time at an example manufacturing facility. A total capacity is shown as 740 cubic feet/minute (cfm) and a maximum plant demand is shown as 380 cfm. Thus, there is an available capacity of 360 cfm. The production demand is shown as 210 cfm and an average leak level based on non-productive load associated with leaks is shown as 170 cfm.

FIG. 2 shows each day of a number of days (e.g., nine). FIG. 2 shows nine different days of use of compressed air at the facility. As shown in FIG. 2, the demand is generally at or above a leak level. The intelligent compressed air apparatus 101 may be used by the facility to eliminate leaks and usage outside of a production period, e.g., when machines/tools are in use by staff and employees at the facility. In one example, the production period may be a period of time each day when the facility is staffed by employees and tools and demand sources are in use at the facility.

As an example, the intelligent compressed air apparatus 101 may be used by the facility to save approximately $50,000 based on the following equation: Leak rate in cubic feet/hour multiplied by an amount of time at idle demand per week multiplied by a number of work weeks per year=amount of compressed air saved per year. As an example, this may be 170 cubic feet/minute*60 minutes/hour*((14 hours a day*five days a week)+(forty eight hours a weekend))*52 weeks a year=62,587,200 cubic feet per year. As an example, a standard rate may be $0.75/1000 cubic feet. As a result, the intelligent air compression apparatus 101 may save the facility $46,940.40 per year.

FIG. 3 illustrates a block diagram of the computing device 108 of the intelligent compressed air system 100 having an intelligent compressed air application 306 according to an example embodiment. The computing device 108 may be a computer having a processor 302 and memory, such as a laptop, desktop, tablet computer, mobile computing device (e.g., a smartphone), or a dedicated electronic device having a processor and memory. The one or more processors 302 process machine/computer-readable executable instructions and data, and the memory stores machine/computer-readable executable instructions and data including one or more applications, including a component of the intelligent compressed air application 306. The processor 302 and memory are hardware. The memory includes random access memory (RAM) and non-transitory memory, e.g., a non-transitory computer-readable storage medium such as one or more flash storages or hard drives. The non-transitory memory may include any tangible computer-readable medium including, for example, magnetic and/or optical disks, flash drives, and the like. Additionally, the memory may also include a dedicated file server having one or more dedicated processors, random access memory (RAM), a Redundant Array of Inexpensive/Independent Disks (RAID) hard drive configuration, and an Ethernet interface or other communication interface, among other components.

The computing device 108 uses the intelligent compressed air application 306 to transmit data and messages and receive messages, data, and/or resources from one or more client computing devices. As an example, the data may be sensor data associated with the one or more sensor devices 104, command data associated with the one or more smart control valves 102, schedule data, rule data associated with the one or more smart control valves, and other information and data.

The computing device 108 includes computer readable media (CRM) 304 in memory on which the intelligent compressed air application 306 or other user interface or application is stored. The computer readable media may include volatile media, nonvolatile media, removable media, non-removable media, and/or another available medium that can be accessed by the processor 302. By way of example and not limitation, the computer readable media comprises computer storage media and communication media. Computer storage media includes non-transitory storage memory, volatile media, nonvolatile media, removable media, and/or non-removable media implemented in a method or technology for storage of information, such as computer/machine-readable/executable instructions, data structures, program modules, or other data. Communication media may embody computer/machine-readable/executable instructions, data structures, program modules, or other data and include an information delivery media or system, both of which are hardware.

The intelligent compressed air application 306 may include a sensor data receiver module 308 for receiving sensor data from the one or more sensor devices 104. As an example, the sensor devices 104 may send sensor data using the communication network 106 to the sensor data receiver module 308. The sensor data receiver module 308 may store the sensor data in the computer readable media 304 and/or in another location. The sensor data may include a current value of flow rate through an associated compressed air line as well as other data such as temperature data, temperature data, pressure data, and humidity data, among other data.

In one example, the sensor data receiver module 308 may use pseudocode such as the following example below. In the example below, the computing device 108 may read the sensor data, convert the sensor data to cfm, and send the sensor data to the user interface module 314 for display.

import socket
import paho.mqtt.client as mqtt
import json
import time
from mcp3208 import MCP3208
adc = MCP3208( )
THINGSBOARD_HOST = ‘example.compute.amazonaws.com’
ACCESS_TOKEN = ‘12345’
print(‘running’)
sensor_data = {‘flow’: 0}
client = mqtt.Client( )
print(‘1’)
client.username_pw_set(ACCESS_TOKEN)
def publish( ):
client.connect(THINGSBOARD_HOST, 1883, 1)
print(i)
client.loop_start( )
time.sleep(4)
flow = adc.read(1)
sensor_data[‘flow’] = flow
client.publish(‘v1/devices/me/telemetry’,json.dumps(sensor_data),1)
print(‘published’)
client.loop_stop( )
else:
return
try:
print(‘started’)
while True:
publish( )
except KeyboardInterrupt:
pass
client.disconnect( )
client.loop_stop( )
print(‘disconnected’)

The intelligent compressed air application 306 may further include a control valve controller module 310 for sending one or more commands to the one or more smart control valves 102 based on the sensor data and other information. As an example, the control valve controller module 310 may compare the sensor data from the at least one sensor device 104 with a threshold to determine whether there is one of productive demand 112 and non-productive demand 114 from a demand source connected to the compressed air line such as a machine or tool.

The control valve controller module 310 may send a command to the at least one smart control valve 102 based on the one of the productive demand 112 and the non-productive demand 114 from the demand source and operate the at least one smart control valve 102 based on the command to open the smart control valve 102 when there is productive demand 112 and close the smart control valve 102 when there is non-productive demand 114.

The intelligent compressed air application 306 may include a scheduling module 312 for receiving schedule information from a user of the system 100. As an example, the schedule information may include information associated with the facility as a whole such as operating hours of the facility and days of operation of the facility. In addition, the schedule information may include control valve open/close commands that may occur at a particular time. The schedule information may include a timed pattern of opening and closing the smart control valves at a same time each day when the facility is in operation.

As an example, a first control valve located in a compressed air line of the facility may open when the facility opens each morning at 6 a.m. The first control valve may remain open until the facility ceases production at 5 p.m. each day and at that time the first control valve may close. The control valve controller module 310 may use the schedule information to operate the at least one smart control valve 102. In addition, the control valve controller module 310 may use historical information to operate the at least one smart control valve 102, rule information to operate the at least one smart control valve 102, and also may use machine learning to operate the at least one smart control valve 102 autonomously.

As an example, the rule information may include one or more rules such as a rule that if a sensor device 104 detects that an associated machine or tool has no demand for a particular period of time, e.g., thirty minutes, the associated smart control valve 102 may close. As another example, if a sensor device 104 detects that an associated machine or tool has demand when the associated smart control valve 102 is closed, then the associated smart control valve 102 may open after a number of seconds, e.g., five seconds. As another example, if a sensor device 104 detects an air usage increase or decrease for a particular period of time, then the computing device 108 may send one or more alerts to a client computing device. The alerts may be push notifications, emails, and/or another type of automated alert that may be sent to a user of a client computing device.

The intelligent compressed air application 306 may include a user interface module 314. The user interface module 314 receives requests or other communications from the client computing devices and transmits a representation of requested information, user interface elements, and other data and communications to the client computing device for display. As an example, the user interface module 314 generates a native and/or web-based graphical user interface (GUI) that accepts input and provides output by generating content that is transmitted via the communications network 106 and viewed by a user of the client computing device or the computing device 108. The user interface module 314 may provide realtime, automatically and dynamically refreshed information to the user of the client computing device using Java, Javascript, AJAX (Asynchronous Javascript and XML), ASP.NET, Microsoft .NET, and/or node.js, among others. The user interface module 314 may send data to other modules of the intelligent compressed air application 306 of the computing device 108 and retrieve data from other modules of the intelligent compressed air application 306 of the computing device asynchronously without interfering with the display and behavior of the intelligent compressed air application 306 displayed by the client computing device or the computing device 108. As an example, data may be retrieved using XMLHttpRequest objects or using WebSockets.

FIG. 4 illustrates a flowchart of a process 400 for operating the intelligent compressed air system 100, according to an example embodiment. In step 402, the computing device 108 may receive sensor data from the least one sensor device 104 in a compressed air line. The compressed air line may be between the supply side system 110 and a demand source and may be one compressed air line in a facility of one or more compressed air lines. The at least one sensor device 104 may be a flow sensor and/or a pressure sensor in one of the compressed air lines.

In step 404, the computing device 108 may determine if there is currently productive demand 112 or non-productive demand 114 from the demand source based on the sensor data from the least one sensor device 104. The computing device 108 may compare the sensor data from the at least one sensor device 104 with a threshold to determine whether there is the productive demand 112 or non-productive demand 114 from the demand source connected to the compressed air line.

In step 406, the computing device 108 may store the sensor data in the computer readable media 304 and/or in another location. In step 408, the computing device 108 may send a command to the at least one smart control valve 102 based on the one of the productive demand 112 and the non-productive demand 114 from the demand source. In addition, the computing device 108 may receive a schedule associated with a facility and send the command to the at least one smart control valve 102 based on the schedule associated with the facility. As another example, the computing device 108 may receive at least one conditional rule associated with the compressed air line and send the command to the at least one smart control valve 102 based on the at least one conditional rule. As another example, the computing device 108 may receive historical data associated with the compressed air line and send the command to the at least one smart control valve 102 based on the historical data. Over time, the computing device 108 may use machine learning to train the smart control valve 102 using the historical data or environmental data. The historical data or environmental data may be key card access data for the facility, heating, ventilation, and air conditioning (HVAC) data, process parameter data, or another type of data.

In step 410, the computing device 108 may operate the at least one smart control valve 102 based on the command to open the smart control valve 102 when there is productive demand 112 and close the smart control valve 102 when there is non-productive demand 114. The smart control valve 102 may be a flow control valve such as one of a ball valve, a butterfly valve, and a solenoid valve that is connected to a motorized system to operate the smart control valve.

In step 412, the computing device 108 may send a graphical user interface representing data associated with the system 100 to a client computing device for display on a display device. An example of a graphical user interface is shown in FIG. 6.

FIG. 5 illustrates a usage graph 500 associated with a plant or facility that is determined by the intelligent compressed air system 100 according to an example embodiment. As shown in FIG. 5, there is a main flow rate of a fluid such as compressed air through one or more lines at a facility or plant. FIG. 5 shows a line on the usage graph that indicates a flow rate in cfm over a period of time. As an example, FIG. 5 shows flow rate in the line from Jul. 5, 2019 at 20:29 to Jul. 6, 2019 at 18:29:04.

FIG. 6 illustrates a graphical user interface 600 of the intelligent compressed air application 306 according to an example embodiment. FIG. 6 shows a representation of a floor layout at a facility or plant and may indicate a current status of each smart control valve such as whether the valve is open or closed. FIG. 6 shows that there is a valve A and a valve B on the floor of the plant. In one example, the valve A and the valve B may be a user interface element that when selected by a user of a client computing device displays a graph associated with the valve such as shown in FIG. 5. In addition, each of the sensor devices 104 associated with the facility or plant may have a selectable user interface element. The user may select a user interface element associated with each of the sensor devices 104 to view information associated with the sensor device such as leak information. The user of the client computing device may provide input to the graphical user interface 600 using a mouse, keyboard, or touchscreen, among other input devices.

In addition, FIG. 6 shows an interface that allows a user to set and view a schedule associated with the intelligent compressed air system 100 at the plant. FIG. 6 shows a schedule of the intelligent compressed air system 100 from Aug. 4 to Aug. 9, 2019. As shown in FIG. 6, a first valve is scheduled to open at 6 a.m. on Monday, August 5, Tuesday, August 6, Wednesday, August 7, Thursday, August 8, and Friday, August 9. A second valve is scheduled to open at 4:21 p.m. on Monday, August 5, Tuesday, August 6, Wednesday, August 7, Thursday, August 8, and Friday, August 9. The first valve and the second valve are scheduled to close at 5:20 p.m. on Monday, August 5, Tuesday, August 6, Wednesday, August 7, Thursday, August 8, and Friday, August 9. On Saturday August 10, the second valve is scheduled to open at 4:21 p.m. and close at 5:20 p.m.

FIG. 6 illustrates user interface elements that allow a user to add a scheduled event and search for scheduled events. In addition, the user interface may be displayed as a calendar view and may display a list of events.

FIG. 7 illustrates an example computing system 700 that may implement various systems, such as the smart control valve 102, the sensor device 104, the computing device 108, and the methods discussed herein, such as process 400. A general purpose computer system 700 is capable of executing a computer program product to execute a computer process. Data and program files may be input to the computer system 700, which reads the files and executes the programs therein. Some of the elements of a general purpose computer system 700 are shown in FIG. 7 wherein a processor 702 is shown having an input/output (I/O) section 704, a central processing unit (CPU) 706, and a memory section 708. There may be one or more processors 702, such that the processor 702 of the computing system 700 comprises a single central-processing unit 706, or a plurality of processing units, commonly referred to as a parallel processing environment. The computer system 700 may be a conventional computer, a server, a distributed computer, or any other type of computer, such as one or more external computers made available via a cloud computing architecture. The presently described technology is optionally implemented in software devices loaded in memory 708, stored on a configured DVD/CD-ROM 710 or storage unit 712, and/or communicated via a wired or wireless network link 714, thereby transforming the computer system 700 in FIG. 7 to a special purpose machine for implementing the described operations.

The memory section 708 may be volatile media, nonvolatile media, removable media, non-removable media, and/or other media or mediums that can be accessed by a general purpose or special purpose computing device. For example, the memory section 708 may include non-transitory computer storage media and communication media. Non-transitory computer storage media further may include volatile, nonvolatile, removable, and/or non-removable media implemented in a method or technology for the storage (and retrieval) of information, such as computer/machine-readable/executable instructions, data and data structures, engines, program modules, and/or other data. Communication media may, for example, embody computer/machine-readable/executable, data structures, program modules, algorithms, and/or other data. The communication media may also include an information delivery technology. The communication media may include wired and/or wireless connections and technologies and be used to transmit and/or receive wired and/or wireless communications.

The I/O section 704 is connected to one or more user-interface devices (e.g., a keyboard 716 and a display unit 718), a disc storage unit 712, and a disc drive unit 720. Generally, the disc drive unit 720 is a DVD/CD-ROM drive unit capable of reading the DVD/CD-ROM medium 710, which typically contains programs and data 722. Computer program products containing mechanisms to effectuate the systems and methods in accordance with the presently described technology may reside in the memory section 704, on a disc storage unit 712, on the DVD/CD-ROM medium 710 of the computer system 700, or on external storage devices made available via a cloud computing architecture with such computer program products, including one or more database management products, web server products, application server products, and/or other additional software components. Alternatively, a disc drive unit 720 may be replaced or supplemented by another storage medium drive unit. The network adapter 724 is capable of connecting the computer system 700 to a network via the network link 714, through which the computer system can receive instructions and data. Examples of such systems include personal computers, Intel or PowerPC-based computing systems, AMD-based computing systems, ARM-based computing systems, and other systems running a Windows-based, a UNIX-based, or other operating system. It should be understood that computing systems may also embody devices such as Personal Digital Assistants (PDAs), mobile phones, tablets or slates, multimedia consoles, gaming consoles, set top boxes, etc.

When used in a LAN-networking environment, the computer system 700 is connected (by wired connection and/or wirelessly) to a local network through the network interface or adapter 724, which is one type of communications device. When used in a WAN-networking environment, the computer system 700 typically includes a modem, a network adapter, or any other type of communications device for establishing communications over the wide area network. In a networked environment, program modules depicted relative to the computer system 700 or portions thereof, may be stored in a remote memory storage device. It is appreciated that the network connections shown are examples of communications devices for and other means of establishing a communications link between the computers may be used.

In an example implementation, source code executed by the intelligent compressed air system 100, a plurality of internal and external databases, source databases, and/or cached data on servers are stored in memory of the smart control valve 102, memory of the sensor device 104, memory of the computing device 108, or other storage systems, such as the disk storage unit 712 or the DVD/CD-ROM medium 710, and/or other external storage devices made available and accessible via a network architecture. The source code executed by the computing system 700 may be embodied by instructions stored on such storage systems and executed by the processor 702.

Some or all of the operations described herein may be performed by the processor 702, which is hardware. Further, local computing systems, remote data sources and/or services, and other associated logic represent firmware, hardware, and/or software configured to control operations of the at least one smart control valve 102, the at least one sensor device 104, the at least one computing device 108, and/or other components. Such services may be implemented using a general purpose computer and specialized software (such as a server executing service software), a special purpose computing system and specialized software (such as a mobile device or network appliance executing service software), or other computing configurations. In addition, one or more functionalities disclosed herein may be generated by the processor 702 and a user may interact with a Graphical User Interface (GUI) using one or more user-interface devices (e.g., the keyboard 716, the display unit 718, and the user devices 704) with some of the data in use directly coming from online sources and data stores. The system set forth in FIG. 7 is but one possible example of a computer system that may employ or be configured in accordance with aspects of the present disclosure.

In the present disclosure, the methods disclosed may be implemented as sets of instructions or software readable by a device. Further, it is understood that the specific order or hierarchy of steps in the methods disclosed are instances of example approaches. Based upon design preferences, it is understood that the specific order or hierarchy of steps in the method can be rearranged while remaining within the disclosed subject matter. The accompanying method claims present elements of the various steps in a sample order, and are not necessarily meant to be limited to the specific order or hierarchy presented.

The described disclosure may be provided as a computer program product, or software, that may include a non-transitory machine-readable medium having stored thereon executable instructions, which may be used to program a computer system (or other electronic devices) to perform a process according to the present disclosure. A non-transitory machine-readable medium includes any mechanism for storing information in a form (e.g., software, processing application) readable by a machine (e.g., a computer). The non-transitory machine-readable medium may include, but is not limited to, magnetic storage medium, optical storage medium (e.g., CD-ROM); magneto-optical storage medium, read only memory (ROM); random access memory (RAM); erasable programmable memory (e.g., EPROM and EEPROM); flash memory; or other types of medium suitable for storing electronic executable instructions.

The description above includes example systems, methods, techniques, instruction sequences, and/or computer program products that embody techniques of the present disclosure. However, it is understood that the described disclosure may be practiced without these specific details.

It is believed that the present disclosure and many of its attendant advantages will be understood by the foregoing description, and it will be apparent that various changes may be made in the form, construction and arrangement of the components without departing from the disclosed subject matter or without sacrificing all of its material advantages. The form described is merely explanatory, and it is the intention of the following claims to encompass and include such changes.

While the present disclosure has been described with reference to various embodiments, it will be understood that these embodiments are illustrative and that the scope of the disclosure is not limited to them. Many variations, modifications, additions, and improvements are possible. More generally, embodiments in accordance with the present disclosure have been described in the context of particular implementations. Functionality may be separated or combined in blocks differently in various embodiments of the disclosure or described with different terminology. These and other variations, modifications, additions, and improvements may fall within the scope of the disclosure as defined in the claims that follow.

Claims

1. A system comprising:

at least one sensor device in a compressed air line;

at least one smart control valve in the compressed air line; and

at least one processor to: receive sensor data associated with the compressed air line from the at least one sensor device; store the sensor data in a computer-readable storage medium; compare the sensor data from the at least one sensor device with a threshold to determine whether there is one of productive demand and non-productive demand from a demand source connected to the compressed air line; send a command to the at least one smart control valve based on the one of the productive demand and the non-productive demand from the demand source; and operate the at least one smart control valve based on the command to open the smart control valve when there is productive demand and close the smart control valve when there is non-productive demand.

2. The system of claim 1, wherein the at least one sensor device comprises one of a flow sensor and a pressure sensor in the compressed air line.

3. The system of claim 1, wherein the smart control valve comprises a flow control valve that is connected to a motorized system to operate the smart control valve.

4. The system of claim 1, the at least one processor further to receive a schedule associated with a facility and send the command to the at least one smart control valve based on the schedule associated with the facility.

5. The system of claim 1, the at least one processor further to receive at least one conditional rule associated with the compressed air line and send the command to the at least one smart control valve based on the at least one conditional rule.

6. The system of claim 1, the at least one processor further to receive historical data associated with the compressed air line and send the command to the at least one smart control valve based on the historical data.

7. The system of claim 1, the at least one processor to send a graphical user interface that represents the sensor data associated with the compressed air line to a client computing device.

8. A method comprising:

receiving, by at least one processor, sensor data associated with a compressed air line from at least one sensor device;

storing, by the at least one processor, the sensor data in a computer-readable storage medium;

comparing, by the at least one processor, the sensor data from the at least one sensor device with a threshold to determine whether there is one of productive demand and non-productive demand from a demand source connected to the compressed air line;

sending, by the at least one processor, a command to at least one smart control valve in the compressed air line based on the one of the productive demand and the non-productive demand from the demand source; and

operating, by the at least one processor, the at least one smart control valve based on the command to open the smart control valve when there is productive demand and close the smart control valve when there is non-productive demand.

9. The method of claim 8, wherein the at least one sensor device comprises one of a flow sensor and a pressure sensor in the compressed air line.

10. The method of claim 8, wherein the smart control valve comprises a flow control valve that is connected to a motorized system to operate the smart control valve.

11. The method of claim 8, further comprising receiving a schedule associated with a facility and sending the command to the at least one smart control valve based on the schedule associated with the facility.

12. The method of claim 8, further comprising receiving at least one conditional rule associated with the compressed air line and sending the command to the at least one smart control valve based on the at least one conditional rule.

13. The method of claim 8, further comprising receiving historical data associated with the compressed air line and sending the command to the at least one smart control valve based on the historical data.

14. The method of claim 8, further comprising sending a graphical user interface that represents the sensor data associated with the compressed air line to a client computing device.

15. A non-transitory computer-readable storage medium, having instructions stored thereon that, when executed by a computing device cause the computing device to perform operations, the operations comprising:

receiving sensor data associated with a compressed air line from at least one sensor device;

storing the sensor data in the non-transitory computer-readable storage medium;

comparing the sensor data from the at least one sensor device with a threshold to determine whether there is one of productive demand and non-productive demand from a demand source connected to the compressed air line;

sending a command to at least one smart control valve in the compressed air line based on the one of the productive demand and the non-productive demand from the demand source; and

operating the at least one smart control valve based on the command to open the smart control valve when there is productive demand and close the smart control valve when there is non-productive demand.

16. The non-transitory computer-readable storage medium of claim 15, wherein the at least one sensor device comprises one of a flow sensor and a pressure sensor in the compressed air line.

17. The non-transitory computer-readable storage medium of claim 15, wherein the smart control valve comprises a flow control valve that is connected to a motorized system to operate the smart control valve.

18. The non-transitory computer-readable storage medium of claim 15, the operations further comprising receiving a schedule associated with a facility and sending the command to the at least one smart control valve based on the schedule associated with the facility.

19. The non-transitory computer-readable storage medium of claim 15, the operations further comprising receiving at least one conditional rule associated with the compressed air line and sending the command to the at least one smart control valve based on the at least one conditional rule.

20. The non-transitory computer-readable storage medium of claim 15, the operations further comprising receiving historical data associated with the compressed air line and sending the command to the at least one smart control valve based on the historical data.

21. The non-transitory computer-readable storage medium of claim 15, the operations further comprising sending a graphical user interface that represents the sensor data associated with the compressed air line to a client computing device.