Abstract: A power consumption monitoring device (120) that may be attached to any electrically powered equipment (102). In some examples, the device (120) may include a male and female electrical plug that may be inserted between the equipment (102) and line power (104). In other examples, one or both ends of the device (120) may be hard-wired to the equipment (102) and or to line power (104). The device (120) may include monitoring circuitry and a power cord “pigtail” with one or more wires shielded from the other wires to avoid canceling the inbound and outbound current. Also, part of the shielding (112), or other portion of the pigtail may act as an antenna to communicate between the monitoring circuitry and a gateway (130). The components of the device (120) of this disclosure may be completely implemented within the power cord, such that performance monitoring can be performed on the equipment (102) without the equipment (102) itself including a monitoring device.

Abstract: This disclosure creates a language that may describe how any type of equipment behaves. The scalable language may uniquely identify equipment and components of equipment. The language includes “words” comprising characters that can describe the sequence of operations of the equipment. The characters may describe characteristic signatures in power consumption signals of the equipment as well as components of the equipment over an operational cycle of the equipment. The characters, e.g., “glyphs” or “runes,” may use a scale-free format modeled after typography. These characters may be scaled to give different confidence levels when comparing the characters to monitored power consumption signals. The language also describes how the equipment transitions between events during the sequence of operation. A compiler may use this language to generate programming instructions that may cause processing circuitry to efficiently monitor equipment, including determining a state of health of the equipment.

Abstract: One example provides a device, including: a current sensing mechanism, wherein the current sensing mechanism detects current traveling through a wire of equipment that the device is connected to; an energy harvester electrically coupled to the current sensing mechanism, wherein the energy harvester draws power from a signal associated with the current sensing mechanism; an energy storage unit electrically coupled to the energy harvester, wherein energy harvested from the energy harvester charges the energy storage unit; and a communication device, wherein the communication device transmits information associated with the equipment to another device.

Abstract: One embodiment provides a method, including: receiving, from at least one sensor operatively coupled to a mechanical device, sensor data corresponding to a function of the mechanical device; accessing, from an environmental database, information regarding at least one environmental condition in proximity to a geographical location of the mechanical device; generating, using a processor, a correlative value for the mechanical device, wherein the correlative value identifies a correlation between the sensor data corresponding to a function of the mechanical device and the at least one environmental condition; assigning the correlative value as a baseline correlative value to the mechanical device; monitoring the sensor data corresponding to a function of the mechanical device and the at least one environmental condition and updating the correlative value; identifying, using a processor, the correlative value for the mechanical device has exceeded a predetermined threshold as compared to the baseline correlative

Abstract: One embodiment provides a method, including: receiving, from at least one sensor operatively coupled to a mechanical device, sensor data corresponding to a function of the mechanical device; accessing, from an environmental database, information regarding at least one environmental condition in proximity to a geographical location of the mechanical device; generating, using a processor, a correlative value for the mechanical device, wherein the correlative value identifies a correlation between the sensor data corresponding to a function of the mechanical device and the at least one environmental condition; assigning the correlative value as a baseline correlative value to the mechanical device; monitoring the sensor data corresponding to a function of the mechanical device and the at least one environmental condition and updating the correlative value; identifying, using a processor, the correlative value for the mechanical device has exceeded a predetermined threshold as compared to the baseline correlative

Abstract: One example provides a device, including: a current sensing mechanism, wherein the current sensing mechanism detects current traveling through a wire of equipment that the device is connected to; an energy harvester electrically coupled to the current sensing mechanism, wherein the energy harvester draws power from a signal associated with the current sensing mechanism; an energy storage unit electrically coupled to the energy harvester, wherein energy harvested from the energy harvester charges the energy storage unit; and a communication device, wherein the communication device transmits information associated with the equipment to another device.

Abstract: Systems and approaches for interacting with industrial equipment are provided that include an interface having an input and an output, and a processor coupled to the interface. The processor is configured to link a uniform identification construct to a device and receive a request to access the uniform identification construct. The processor is further configured to translate the uniform identification construct into an internet protocol (IP) address and route the request to the device having the uniform identification construct according to the IP address via the output.

Abstract: Systems and approaches for interacting with industrial equipment are provided that include an interface having an input and an output, and a processor coupled to the interface. The processor is configured to link a uniform identification construct to a device and receive a request to access the uniform identification construct. The processor is further configured to translate the uniform identification construct into an internet protocol (IP) address and route the request to the device having the uniform identification construct according to the IP address via the output.

Abstract: One embodiment provides a method, including: receiving, from at least one sensor operatively coupled to a mechanical device, sensor data corresponding to a function of the mechanical device; accessing, from an environmental database, information regarding at least one environmental condition in proximity to a geographical location of the mechanical device; generating, using a processor, a correlative value for the mechanical device, wherein the correlative value identifies a correlation between the sensor data corresponding to a function of the mechanical device and the at least one environmental condition; assigning the correlative value as a baseline correlative value to the mechanical device; monitoring the sensor data corresponding to a function of the mechanical device and the at least one environmental condition and updating the correlative value; identifying, using a processor, the correlative value for the mechanical device has exceeded a predetermined threshold as compared to the baseline correlative

Abstract: One embodiment provides a method, including: identifying at least one similar mechanical device from a plurality of candidate mechanical devices, wherein the at least one similar mechanical device comprises a mechanical device having at least a subset of characteristics and at least a subset of geographical information similar to the mechanical device; receiving, from a sensor operatively coupled to the mechanical device, sensor data providing information regarding a characteristic related to a mechanical function of the mechanical device; comparing the sensor data of the mechanical device to sensor data of the at least one similar mechanical device; identifying an abnormal operating condition of the mechanical device, wherein the identifying the abnormal operating condition comprises determining the sensor data of the mechanical device is outside a predetermined range threshold; and notifying a user of the identified abnormal operating condition.

Abstract: Systems and approaches for interacting with industrial equipment are provided that include an interface having an input and an output, and a processor coupled to the interface. The processor is configured to link a uniform identification construct to a device and receive a request to access the uniform identification construct. The processor is further configured to translate the uniform identification construct into an internet protocol (IP) address and route the request to the device having the uniform identification construct according to the IP address via the output.

Abstract: A system for storing time series data includes an ingester that prepares metadata indices associated with blocks of incoming time series data and stores the blocks of data in a time series database and the indices in a separate index database. The time series database distributes storage of the data blocks among multiple data nodes. A query layer receives queries and uses the index database to determine which data blocks are needed to process the query, and then requests only those data blocks from the time series database. Processing of the query is performed within the time series database only on those data nodes that contain relevant data, and partial results are passed to an output layer for formation into a final query result.

Abstract: A system for predicting events by associating time series data with other types of non-time series data can include a processor configured to receive a data stream including time series data transmitted from a sensor configured to measure an operating parameter of a component being monitored. The processor identifies sequences of interest in the time series data having predictive value. The processor compares the real-time data stream to a set of known historical patterns that act as effective leading indicators of different alarms and events. The processor extracts any identified sequences of interest from the time series data as an extracted event. The processor quantifies the relationship between the data of the extracted event and the known historical pattern by calculating a confidence level to denote a probability of occurrence of the event by comparing how closely the new time series data matches the data patterns associated with known events.

Abstract: A system for predicting events by associating time series data with other types of non-time series data can include a processor configured to receive a data stream including time series data transmitted from a sensor configured to measure an operating parameter of a component being monitored. The processor identifies sequences of interest in the time series data having predictive value. The processor compares the real-time data stream to a set of pre-existing event data that act as effective leading indicators of different alarms and events. The processor extracts any identified sequences of interest from the time series data as an extracted event. The processor quantifies the relationship between the data of the extracted event and the known historical pattern by calculating a confidence level to denote a probability of occurrence of the event by comparing how closely the new time series data matches the data patterns associated with known events.

Abstract: Approaches are provided where, at a local computing device, time series data is received from an industrial component in a first format. This time series data additionally has a tag or identifier appended thereto and a quality setting. The tag is automatically converted to a descriptor used by an analytic system, and the time series data is converted to a format readable by the analytic system. This format is specified by at least a portion of an analytic system blueprint. The time series data is then transmitted to the analytic system such that the time series data and the descriptor are in a format that do not require additional conversions in order to be processed by the analytic system.

Abstract: Approaches are provided for a case management system where one or more exceptions are detected at an industrial machine. A case is then created which represents the one or more exceptions. Additional exceptions may also be linked to the created case which may occur after the creation of the case. The case is stored in an electronic database. One or more first trigger indications are generated which lead to updates to the case at a first time. The case is then responsively updated with first evidence and a first accompanying interpretation. The first update, trigger indications, evidence, and the accompanying interpretation are then linked in an electronic database to form a first linkage which is interpreted such that the evidence, interpretation, and underlying trigger are examined in the context of each other, and an action may be determined to take in mitigating the issue at the industrial machine.

Abstract: A data storage policy is determined. Time series data is received and a score for the time series data is determined. The score prioritizes the time series data according to a likelihood the time series data will be needed for future use. Based upon the data storage policy and the score, the time series data is stored at one or more data storage devices. The score is updated over time to reflect changing priorities regarding the use of the data.

Abstract: A user query or analytic user is received. The user query or analytic requires one or more portions of time series data from a plurality of transient memories. The time series data is linked together across the transient memories devices. A location of one or more portions of the time series data is identified at the plurality of transient memories. One or more portions of the time series data is automatically retrieved from the transient memories.

Abstract: A system for storing time series data includes an ingester that prepares metadata indices associated with blocks of incoming time series data and stores the blocks of data in a time series database and the indices in a separate index database. The time series database distributes storage of the data blocks among multiple data nodes. A query layer receives queries and uses the index database to determine which data blocks are needed to process the query, and then requests only those data blocks from the time series database. Processing of the query is performed within the time series database only on those data nodes that contain relevant data, and partial results are passed to an output layer for formation into a final query result.

Abstract: A method for performing queries on a distributed time series data storage system is presented. The time series data storage system has a time series database that stores data blocks containing time stamped data across a plurality of computing devices. The system also includes an index database that stores an index associated with the time stamped data in each data block. The method includes the steps of sending a query, requesting indices, returning the indices, preparing a sub-query, forwarding the sub-query to an evaluator, evaluating the sub-query, performing a logical operation on each sub-query's result, receiving the sub-results at an output handler, and combining the sub-results.