Abstract: A vehicle apparatus onboard a vehicle identifies a human operator-free trip trigger corresponding to a human operator-free trip the vehicle is to take. The vehicle is located at an origin location of the human operator-free trip. Responsive to the vehicle apparatus identifying the human operator-free trip trigger, a candidate destination location for the human operator-free trip is identified. A candidate route from the origin location to the candidate destination location is generated. The vehicle apparatus provides a trip request including the candidate route to an approval apparatus. The vehicle apparatus receives a message from the approval apparatus. Responsive to determining that the message comprises an approval of the candidate route, the vehicle apparatus controls one or more systems of the vehicle to cause the vehicle to traverse the candidate route from the origin location to the candidate destination location.

Abstract: The present disclosure provides a method in a data processing system that includes at least one processor and at least one memory. The at least one memory includes instructions executed by the at least one processor to implement a driving encounter recognition system. The method includes receiving information, from one or more sensors coupled to a first vehicle, determining first trajectory information associated with the first vehicle and second trajectory information associated with a second vehicle, extracting a feature vector, providing the feature vector to a trained classifier, the classifier trained using unsupervised learning based on a plurality of feature vectors, and receiving, from the trained classifier, a classification of the current driving encounter in order to facilitate the first vehicle to perform a maneuver based on the current driving encounter.

Abstract: A LIDAR scanning system uses a combination of a laser emitter, a scanning mirror which scans in a first plane, a diffuser which diffuses emitted laser beams in a second plane, perpendicular to the first plane. A focusing optic focuses a reflection of a laser beam, reflected off of an object, onto a detector. The focusing optic focuses the reflection of the reflection of the laser beam at least in the first plane, and may also focus the reflection of the laser beam in the second plane. A peak magnitude of the detector, and a time which the peak occurred, relative to the time at which the laser beam was emitted (“time of flight”), and LIDAR information is generated from peak magnitude and time of flight. The LIDAR scanning system can be used in an autonomous driving vehicle (ADV) to assist in navigating the ADV.

Abstract: A system for providing goods to a customer includes an autonomous vehicle, the autonomous vehicle including a first controller, a camera in communication with the first controller for supplying image data to the controller, a global positioning satellite apparatus for determining a position of the autonomous vehicle in communication with the first controller, and a ranging unit for determining a distance to an object from the autonomous vehicle in communication with the first controller. The system also includes a mobile vending machine affixed to the autonomous vehicle, the mobile vending machine including a second controller, a user interface for taking an order from the customer in communication with the second controller, and a delivery apparatus in communication with the second controller for delivering the order to the customer.

Abstract: Among other things, we describe techniques for generation of dimensionally reduced maps and localization in an environment for navigation of vehicles. The techniques include generating, using one or more sensors of a vehicle located at a spatiotemporal location within an environment, M-dimensional sensor data representing the environment, wherein M is greater than 2. Odometry data is generated representing an operational state of the vehicle. The odometry data is associated with the spatiotemporal location. An N-dimensional map is generated of the environment from the M-dimensional sensor data, wherein N is less than M. The generating of the N-dimensional map comprises extracting an M-dimensional environmental feature of the spatiotemporal location from the M-dimensional sensor data. The M-dimensional environmental feature is associated with the odometry data. An N-dimensional version of the M-dimensional environmental feature is generated.

Abstract: A method of training an artificial neural network having a series of layers and at least one weight matrix encoding connection weights between neurons in successive layers. The method includes receiving, at an input layer of the series of layers, at least one input, generating, at an output layer of the series of layers, at least one output based on the at least one input, generating a reward based on a comparison of between the at least one output and a desired output, and modifying the connection weights based on the reward. Modifying the connection weights includes maintaining a sum of synaptic input weights to each neuron to be substantially constant and maintaining a sum of synaptic output weights from each neuron to be substantially constant.

Abstract: Provided is an electronic device including: a sensing device selected from a group including a radar and a lidar and installed in a vehicle to have a sensing zone directed to outside of the vehicle, the sensing device configured to obtain sensing data about an object; an image obtainer installed in the vehicle to have a field of view directed to the outside of the vehicle, the sensing device configured to obtain image data; and a controller including at least one processor configured to process the sensing data obtained by the sensing device and the image data obtained by the image obtainer, wherein the controller generates a first virtual driving path and a second virtual driving path based on the sensing data and the image data, and when a first boundary of the first virtual driving path and a second boundary of the second virtual driving path are located at different positions, provides a virtual driving path having a boundary closest to the vehicle between the first virtual driving path and the second vir

Abstract: The disclosure relates to an electronic device (e.g., a mobile robot). An electronic device is provided. The electronic device includes a speaker, a microphone, a substrate on which the speaker and the microphone are mounted, a spherical housing defining therein an inner space in which the speaker, the microphone, and the substrate are disposed, a support member configured to be in contact with and support an inner surface of the hosing on one side thereof, and a driver disposed in the inner space of the housing and including at least one power generation actuator and at least one wheel configured to rotate the housing by receiving power from the actuator, wherein the speaker is disposed adjacent to an another side of the support member opposite the one side of the support member, and outputs sound using oscillation of the surface of the housing. In addition, an electronic device according to various embodiments may be applied.

Abstract: An automatic program-correction device includes: a clearance detecting unit that detects an amount of clearance between a robot and a peripheral device in an operation program; a near-miss detecting unit that detects a near-miss section; a closest-point detecting unit that detects a pair of closest points, in the near-miss section; and a program updating unit that generates a new operation program having an intermediate teaching point to which the closest points have been moved, along a straight line passing through the detected pair of closest points, until the amount of clearance becomes greater than a minimum amount of clearance and equal to or less than the threshold. While gradually reducing, from the threshold, the amount of clearance at the intermediate teaching point, the program updating unit obtains an intermediate teaching point that provides a maximum amount of clearance at which a new near-miss section is not detected.

Abstract: A vehicle control system includes a vehicle control apparatus configured to set a target trajectory of a vehicle in autonomous driving, a manual driving database configured to contain manual driving trajectory information that indicates a manual driving trajectory that is a trajectory of the vehicle in manual driving, a weight acquisition device configured to acquire weight information that indicates weights of the target trajectory and manual driving trajectory, the weights being designated by a user of the vehicle, and a trajectory adjusting device configured to determine an integrated target trajectory by integrating the target trajectory and the manual driving trajectory based on the weights indicated by the weight information. The vehicle control apparatus is configured to control the autonomous driving of the vehicle such that the vehicle follows the integrated target trajectory.

Abstract: The embodiments of the present disclosure provide a method and an apparatus for providing vehicle information, a device and a storage medium for implementing the method. The method includes: acquiring a first time period expected for a first vehicle to wait before supplement of energy for the first vehicle is to be commenced; determining a second time period expected to be required during the supplement of the energy for the first vehicle based on an amount of the energy to be supplemented for the first vehicle; determining a third time period expected to require for completing the supplement of the energy for the first vehicle based on the first time period and the second time period; and providing the third time period.

Abstract: An information processing apparatus, an information processing method, and an information medium control motion of a moving body according to position information corresponding to a predetermined array pattern. An information processing apparatus includes an information acquisition unit acquires position information from a sensor configured to read a predetermined array pattern, and a motion control unit controls motion of a first moving body including movement in a real space based on the position information.

Abstract: Among other things, we describe techniques for adjusting lateral clearance for a vehicle using a multi-dimensional envelope. A trajectory is generated for the vehicle. A multi-dimensional envelope is generated indicating a drivable region for the vehicle and containing the trajectory. One or more objects are identified located along or adjacent to the trajectory. At least one dimension of the generated multi-dimensional envelope is adjusted to adjust a lateral clearance between the vehicle and the identified one or more objects. A control module of the vehicle navigates the vehicle along the multi-dimensional envelope.

Abstract: A safety system for a vehicle may include one or more processors configured to determine uncertainty data indicating uncertainty in one or more predictions from a driving model during operation of a vehicle; change or update one or more of the driving model parameters to one or more changed or updated driving model parameters based on the determined uncertainty data; and provide the one or more changed or updated driving model parameters to a control system of the vehicle for controlling the vehicle to operate in accordance with the driving model including the one or more changed or updated driving model parameters.

Abstract: Provided are an electronic apparatus and a method for recognizing, based on ambient road information of a vehicle and field of view information of the vehicle, a hidden region that is a region where another vehicle is possibly present in an area hidden from a field of view of the vehicle by an external object In the present disclosure, one or more of an electronic apparatus, a vehicle, a vehicular terminal, and the autonomous driving vehicle may be associated with an artificial intelligence module, an unmanned aerial vehicle (UAV), a robot, an augmented reality (AR) device, a virtual reality (VR) device, a 5G service-related device, and the like.

Abstract: A proceedable direction detection apparatus includes a processor. The processor inputs an image acquired from an image capturing unit mounted on a vehicle into a classifier that is pre-trained to output a proceedable certainty degree indicating a proceedable probability of each relative bearing with respect to a predetermined direction relative to a vehicle based on a display status of a traffic signal in the image. The processor calculates, using the classifier, the proceedable certainty degree of each relative bearing based on the display status of the traffic signal in the image. The processor determines the direction in which the vehicle can proceed based on a proceedable certainty degree of each relative bearing.

Abstract: At least one of an autonomous vehicle, a user terminal, and a server may be connected or converged with an artificial intelligence (AI) module, an unmanned aerial vehicle (UAV), a robot, an augmented reality (AR) device, a virtual reality (VR) device, a device associated with a 5G service, and the like. A vehicle control method of the present disclosure may include identifying a driving route, identifying whether other vehicle is on the driving route, transmitting a first request message based on information on the driving route, identifying whether a first response message to the first request message is received from the other vehicle, and transmitting, when the first response message is received, a second request message requesting a movement based on the information on the driving route, to the other vehicle based on the first response message.

Abstract: The present disclosure provides a chassis structure for a robot and a robot with the same. The low speed motor provided with an extra encoder is used to compose a driving wheel so as to drive a driven wheel and a chassis to move; a driver module is used to drive the driving wheel through a low speed motor in response to the control of a control processing module, and obtain rotational parameters of the low speed motor through the encoder to output to the control processing module; the control processing module is used to control the driving wheel to rotate through the driver module so as to drive the chassis to move, calculate a movement path of the chassis based on the rotational parameters of the low speed motor, thereby adjusting the movement path of the chassis. In the present disclosure, since there is no transmission mechanism, the efficiency of transmission is improved.

Abstract: Systems, methods, and machine readable media are provided for automatic charging and swapping power sources for an Autonomous Vehicle (AV). A determination is made whether a current first power source installed in an AV has sufficient power to complete a task assigned to the AV. In response to determining the first power source has insufficient power to complete the assigned task, the AV is directed to a location of a power source repository. The AV is positioned proximate a power source swapping unit of the power source repository where the first power source is removed from the AV and a second power source stored at the power source repository is installed into the AV.

Abstract: Various embodiments are directed to a method for docking a robotic platform. The method may include receiving a robotic platform onto a ramp of a docking station. The docking station may include the ramp, a roller assembly, a base pad, and a roller backstop assembly. The ramp may have a first side and a second side opposing the first side. The method may further include guiding, by the roller assembly, the robotic platform as the robotic platform is being driven onto ramp such that the robotic platform continues powered travel over the ramp when the robotic platform approaches the ramp within an angle range of 0 and 15 degrees with respect to either of the first and second sides of the ramp. The method may further include receiving, by the roller backstop assembly, the robotic platform from the roller assembly and then docking the robotic platform.

Abstract: In one embodiment, a method includes receiving sensor data from one or more sensors of each of one or more vehicles, processing a combination of the sensor data to generate an assessment of an area surrounding the one or more vehicles based on one or more points-of-view of the area, the one or more points-of-view of the area generated based on synchronizing the combination of the sensor data, and detecting an occurrence of an event based on the assessment of the area. The method further includes identifying one or more instructions corresponding to the event, the instructions associated with a particular vehicle and sending one or more executable instructions based on the instructions to the particular vehicle.

Abstract: The present disclosure provides a path tracking method as well as a mobile robot using the same. The method includes: obtaining a preset path and a current position of the mobile device; determining a forward-looking path point corresponding to the current position on the preset path; obtaining a path curvature corresponding to the forward-looking path point; and determining an adjustment velocity of the mobile device at the current position based on the path curvature corresponding to the forward-looking path point. In this manner, the adjustment velocity of the mobile device can be determined based on the curvature of the path, so as to adjust the velocity of the mobile device and improve the stability of path tracking of the mobile device at different path curvatures.

Abstract: A method for finding at least one trigger for human intervention in a control of a vehicle, the method may include receiving, from a plurality of vehicles, and by an I/O module of a computerized system, visual information acquired during situations that are suspected as situations that require human intervention in the control of at least one of the plurality of vehicles; determining, based at least on the visual information, the at least one trigger for human intervention; and transmitting to one or more of the plurality of vehicles, the at least one trigger.

Abstract: A method for controlling a motion of a robot based on map prediction mainly carries out estimation and calculation for a wall surface by combining an external sensor with internal map information about a robot, so as at least to enable the robot to walk along the estimated wall surface. The method for controlling the motion of the robot based on map prediction can be adapted to various different wall surfaces based on map prediction, including different colors and shapes, thereby reducing an operation time; and the accuracy of map prediction can be continuously corrected during an operation process, thereby realizing a good wall-following behavior.

Abstract: The technology relates to controlling a vehicle based on a railroad light's activation status. In one example, one or more processors receive images of a railroad light. The one or more processors determine, based on the images of the railroad light, the illumination status of a pair of lights of the railroad light over a period of time as the vehicle approaches the railroad light. The one or more processors determine based on the illumination status of the pair of lights, a confidence level, wherein the confidence level indicates the likelihood the railroad light is active. The vehicle is controlled as it approaches the railroad light based on the confidence level.

Abstract: A system and method are provided for aiding an operator in operating a vehicle. In one embodiment, a system includes a sensor system configured to generate sensor data sensed from an environment of the vehicle. The system further includes a control module configured to, by a processor, to determine a scene of the environment based on the sensor data, determine a terrain feature in the environment based on the sensor data, alter a graphic of a vehicle component based on the terrain feature, and generate display data to display the altered graphic and the terrain feature in the scene for viewing by the operator of the vehicle.

Abstract: A method is provided for generating a representation of an environment. Methods may include: determining location information of a vehicle including a road segment and a direction of travel; identifying features of the road segment based on sensor data from sensors carried by the vehicle; projecting the features of the road segment onto a ground plane of the road segment; defining bins across a width of the road segment; laterally positioning the defined bins relative to a determination of positions of the features of the road segment; consolidating detected features of each bin to define features of the road segment; and guiding an autonomous vehicle along the road segment based, at least in part, on the consolidated detected features of the road segment.

Abstract: A method for assisting operation of a vehicle traveling on a roadway includes acquiring visual images around the vehicle with at least one visual camera having a field of view and acquiring thermal images around the vehicle with at least one thermal camera having the field of view. The thermal images are superimposed over the visual images to produce composite images. An object is detected in the composite images. A vehicle assist system adjusts at least one of a direction of travel and speed of the vehicle in response to detecting the object.

Abstract: A control unit for a vehicle for analyzing localization systems, the control unit being connectable in a data-conducting manner to at least two localization systems which are operable independently of one another for ascertaining system-specific positions, each localization system including at least one sensor, the control unit being configured to evaluate pieces of position information ascertained by the localization systems by subjecting them to a plausibility check. Also described are a related method and a sensor system.

Abstract: An information processing device includes: a memory; and a processor coupled to the memory and configured to: acquire a first image at a first time and a second image at a second time later than the first time from a monocular camera mounted on a vehicle; calculate an amount of movement of the vehicle, based on a sensor value acquired during a measurement period between the first time and the second time; output a result of distance measurement using a first distance measurement method to perform distance measurement using the first image or the second image, or a second distance measurement method to perform distance measurement using the first image and the second image, depending on the amount of movement; and output a result of calculation of a route to guide the vehicle to a parking space, based on the result of distance measurement.

Abstract: Methods and systems provide infrastructure information including subsurface images captured by ground penetrating radar (GPR) carried by vehicles including mobile data processing devices. Computer readable data further includes location information for the subsurface images based on a location of the vehicle and can include GPS, images and video. The computer readable data can be wirelessly transmitted to a remote server for storage in a database and for retrieval by registered users for display of infrastructure information including subsurface images captured by GPR, based on the received and stored computer readable data. The subsurface images and the location information can be provided for infrastructure where changes are detected based on previously stored infrastructure information related to the location where the subsurface images are captured by GPRs and reported to the server.

Abstract: A marker system (1) including a sensor array (21) for detecting a magnetic marker laid in a road, a tag reader (34) which acquires marker position information indicating a laying position of the magnetic marker, an IMU (22) which estimates a relative position of a vehicle by inertial navigation calculation, and a control unit (32) which performs an arithmetic process for identifying a position of the vehicle based on the laying position of the detected magnetic marker, and also identifies the position of the vehicle after passage over the magnetic marker based on a relative position of the vehicle estimated by the IMU (22), thereby allowing stable identification of its own vehicle position without being affected by surrounding environment.

Abstract: A wearable headset information handling system infrared emitter power optimization system may comprise a memory storing an association between an active infrared (IR) light emitter mounted to the wearable headset and a calibration intensity at which the IR light emitter emits light during a calibration phase, wherein the active IR light emitter is identified based on its position with respect to the field of view of the wearable headset. A SLAM engine may determine a calibration distance between the active IR light emitter and a first farthest identified object and determine an image projection distance between the active IR light emitter and a nearby virtual object. The processor may determine a first light intensity cap for the active IR light emitter based on the calibration distance, the calibration intensity, and the image projection distance, and the active IR light emitter may emit light according to the first light intensity cap.

Abstract: The present disclosure discloses method and an Electronic Control Unit (ECU) (101) of autonomous vehicle for determining an accurate position. The ECU (101) determines centroid coordinate from Global Positioning System (GPS) points, relative to autonomous vehicle and identifies approximate location and orientation of vehicle on pre-generated map based on centroid coordinate and Inertial Measurement Unit (IMU) data. Distance and direction of surrounding static infrastructure is identified from location and orientation of autonomous vehicle based on road boundaries analysis and data associated with objects adjacent to autonomous vehicle. A plurality of lidar reflection reference points are identified within distance and direction of static infrastructure based on heading direction of autonomous vehicle. Position of lidar reflection reference points are detected from iteratively selected shift positions from centroid coordinate.

Abstract: A method for operating an automatically moving robot, wherein a map of the surroundings of the robot is generated using measurement data captured within the surroundings, and a control command is generated using the generated map, the current position of the robot within the surroundings, and a determined behavior of the robot. The robot is moved using the generated control command, and data which is relevant to the navigation of the robot is at least partly transmitted to an external computing device for processing. In order to reduce the computing capacity and/or storage capacity required within the robot, the external computing device determines a desired behavior of the robot as the basis for the control command based on the map and the current position of the robot.

Abstract: A map information system includes: an in-vehicle device that executes automated driving control of a vehicle; and an external device having external map information used for the automated driving control. The in-vehicle device includes: a memory device in which map information is stored; and a control device configured to execute the automated driving control based on the map information stored in the memory device, The control device is further configured to: determine whether or not a takeover occurs during the automated driving control; set an upload target area including the takeover occurrence position, in a case where the takeover occurs during the automated driving control; and upload the map information regarding the upload target area to the external device. The external device updates the external map information based on the map information uploaded from the in-vehicle device.

Abstract: A method for verifying a digital-map of a more highly-automated-vehicle (HAV), especially of an HAV, including: S1—providing a digital-map or a highly accurate digital-map, in an HAV driver-assistance-system; S2—determining a present vehicle-position and locating the vehicle-position in the digital-map; S3—providing at least one setpoint-feature-property of at least one feature in an HAV-environment; S4—detecting at least one actual-feature-property of a feature in the HAV-environment based at least in part on the setpoint-feature-property, the detection being performed with at least one sensor; S5—comparing the actual-feature-property to the setpoint-feature-property and determining at least one difference-value based on the comparison; S6—verifying the digital-map based at least in part on the difference-value, the digital-map being classified as not up-to-date if the difference-value reaches/exceeds a specified-threshold-value of a deviation, and being classified as up-to-date if the difference-value remai

Abstract: A system for controlling a fleet of unmanned vehicles includes a plurality of unmanned vehicles connected to a computing device. The computing device stores a dynamic attribute and a static attribute respective to each of the plurality of unmanned vehicles. The computing device is configured to: receive a task request including (i) an item identifier of an item, (ii) an action type defining an action to be performed respective to the item, and (iii) a location identifier of a location at which to perform the action; responsive to receiving the request, retrieve the stored dynamic attributes and static attributes; based on a comparison of the task request with the dynamic attributes and the static attributes, select one of the plurality of unmanned vehicles; and transmit, via the network, a command to the selected unmanned vehicle to perform the action respective to the item at the location.

Abstract: Systems and methods for evaluating and deploying fleets of autonomous in operational domains are described. A computing system may obtain data indicative of one or more capabilities of at least one autonomous vehicle, data indicative of vehicle service dynamics in an operational domain over a period of time, and determining a plurality of resource performance parameters respectively for a plurality of autonomous vehicle fleets associated with potential deployment in the operational domain. Each autonomous vehicle fleet can be associated with a different number of autonomous vehicles The resource performance parameter for each autonomous vehicle fleet can be based at least in part on the one or more capabilities of the at least one autonomous vehicle and the vehicle service dynamics in the operational domain. The computing system can initiate an action associated with the operational domain based at least in part on the plurality of resource performance parameters.

Abstract: Systems and methods for a swarm management framework are described. According to one embodiment, a swarm management framework includes a goal module, a target module, a negotiation module, and a perception module. The goal module determines a cooperation goal. The target module identifies a vehicle associated with the cooperation goal and sends a swarm request to the vehicle to join a swarm. The negotiation module receives a swarm acceptance from the vehicle. The perception module determines a cooperative action for the vehicle relative to the swarm.

Abstract: V2V communication-less truck platooning.

Abstract: A system and method for cleaning a beach includes a master autonomous vehicle that includes a controller, a camera, a GPS unit, a ranging unit, and a wireless communication unit. The system further includes at least one client autonomous vehicle in wireless communication with and operated by the controller of the master autonomous vehicle and a plurality of beach cleaners attached to the autonomous vehicles. The autonomous vehicles may detect and avoid obstacles on the beach being cleaned and each other.

Abstract: A method for controlling palm landing of an unmanned aerial vehicle (“UAV”) includes detecting a flight status of the UAV under a predetermined condition. The method also includes controlling the UAV to land on a palm of a user when the flight status is a hover state and when the palm is located under the UAV.

Abstract: Disclosed in the present invention is a double-spring and high-precision hysteretic pressure control valve, including an upper valve body, a lower valve body, a double-spring pressure adjustment valve, a spring energy storage linkage mechanism, and a main valve. The double-spring pressure adjustment valve includes a rough adjustment stud, a rough adjustment spring, a fine adjustment stud, a fine adjustment spring, a spring guide sleeve, and a pressure adjustment valve spool. The spring energy storage linkage mechanism includes a guide block, a valve spool control linkage, a tension spring, and a tension spring shift lever and a tension spring sliding hook. The valve spool control linkage is connected to the guide block at one end, and connected to a main valve spool drive rod via a pin at the other end.

Abstract: A solenoid valve control apparatus includes a basic electric current value set portion configured to set a basic electric current value every first cycle, a dither electric current value set portion configured to set a dither electric current value of which a cycle corresponds to a dither cycle, a target electric current value set portion configured to set a target electric current value, an electric current detection portion configured to detect an actual electric current value, a duty ratio set portion configured to set a duty ratio every second cycle which is longer than the dither cycle, and a PWM control portion configured to perform PWM control on the solenoid on the basis of the duty ratio.

Abstract: A diagnostics system, for mass flow controller calibration, comprising a controller communicable coupled to a sensor(s) and a valve. The controller controls the valve based on a predetermined set point value and communication from the at least one sensor. The controller determines a number of set point value adjustments and compares results of a calibration operation and a set point value plus a tolerance value. The controller generates a notification message indicating at least one of the predetermined number of set point value adjustments and results of the comparing. The controller calibrates the mass flow controller based on, at least in part, one of a predetermined number of set point value adjustments, results of the comparison, and user input. The notification message can comprise temperature values, valve drive values, sensor flow rate values, gas flow hours, and a remaining number of set point adjustments based on a total fluid hours.

Abstract: A method of determining and controlling a weight flow in an environmental control system includes sensing, using a turbine inlet temperature sensor, a turbine inlet temperature. A turbine inlet pressure is sensed using a turbine inlet pressure sensor. A turbine outlet pressure is sensed using a turbine outlet pressure sensor. A rotational shaft speed of a shaft is sensed using a rotational shaft speed sensor. The sensed turbine inlet temperature, the sensed turbine inlet pressure, the sensed turbine outlet pressure, and the sensed rotational shaft speed are received by a controller. A flow coefficient is determined by the controller using the turbine inlet pressure, the turbine outlet pressure, the shaft speed, and a Turbine Flow Coefficient Map. A weight flow through the turbine is determined by the controller using the flow coefficient, the turbine inlet temperature, a nozzle area, and the turbine inlet pressure.

Abstract: The system and method for wireless water leak detection provides for manual prevention of external action, such as an external alarm and/or valve shut-off, if a leak sensor can be reached by a respondent within a pre-set time threshold. Upon detection of a leak by a leak sensor, a local alarm, such as an audible alarm or the like, is initiated. Additionally, at the time of detection, a first time is recorded. A first alarm signal is transmitted from the leak sensor to a base station. The first alarm signal includes data representative of the recorded first time. If manual input is not received by the leak sensor within a pre-set time threshold measured from the first time, then the base station transmits a second alarm signal to at least one external device, and may further wirelessly transmit a shut-off signal to a valve controller for closing an associated valve.

Abstract: A submersible well pump assembly has a communication path for communicating motor lubricant to an interior of a pressure equalizer. A check valve passage with a check valve leads from the communication path to a pressure equalizing chamber. A dip tube has a dip tube inlet at the check valve passage below the check valve and a dip tube outlet in the pressure equalizing chamber. The dip tube is filled with motor lubricant to retard migration of well fluid from the pressure equalizing chamber into contact with the check valve.

Abstract: A fluid regulator includes a balance port regulator valve and an actuator coupled to the regulator valve. The regulator valve has an inlet, an outlet, a valve port disposed between the inlet and the outlet, and a valve disc movable along a longitudinal axis between a closed position in which the valve disc sealingly engages the valve port and an open position in which the valve disc is spaced apart from the valve port. The actuator is responsive to fluid pressure to move an actuator stem along the longitudinal axis. A connector assembly operably and removably connects the valve disc to the actuator stem.