A test information management device manages test information relating to a test carried out by receiving a test signal output from a first device in a second device. The test information management device includes a linker configured to link together first information including information representing an output state of the test signal in the first device and second information including image information representing reception results of the test signal in the second device using at least one of identification information for identifying the first device or the second device and times at which the first information and the second information are generated.

A vehicle diagnostics technology is provided. Further, a vehicle fault diagnostic method, an on-board diagnostic apparatus, and a related system that are used for advanced intelligent driving are provided. In an example method, a first diagnostic module monitors and records first fault information, and a second diagnostic module monitors and records second fault information. The second diagnostic module sends the second fault information to the first diagnostic module. The example method further includes the first diagnostic module communicating with a master computer through a first communication interface and the second diagnostic module communicating with the master computer through a second communication interface.

A real-time control system includes a faulty variable identification technique to implement a data-driven fault detection function that provides an operator with information that enables a higher level of situational awareness of the current and likely future operating conditions of the process plant. The faulty variable identification technique enables an operator to recognize when a process plant component is behaving abnormally to potentially take action, in a current time step, to alleviate the underlying cause of the problem, thus reducing the likelihood of or preventing a stall of the process control system or a failure of the process plant component.

Diagnostic and response systems and methods for a fluid power system acquire data from pressure and temperature sensors disposed in the fluid power system, analyze the data in a failure algorithm to build a history of cumulative damage to hoses in the fluid power system, communicates an indication of potential imminent hose failure to a central location when a level of the cumulative damage indicates imminent failure of a hose, analyze the information at the central location to determine an appropriate response, and transmit information about the fluid power system, including location, and identification of the hose about to fail to a response unit. The response unit responds to the location and replaces the component prior to failure, or the communication might include information that the hose has failed, such that the response unit replaces the failed hose to return the fluid power system to normal operation.

An abnormality diagnosis system configured to diagnose an abnormality of an electric drive system mounted on a mobile body to drive a motor for moving the mobile body, includes: an information acquisition unit configured to acquire a motor output information which is information related to an output state of the motor; an output state determination unit configured to determine whether the output state of the motor is in a low output state that does not contribute to a movement of the mobile body by using the motor output information; and a diagnosis execution unit configured to diagnose an abnormality of the electric drive system when it is determined that the motor is in the low output state.

The present invention discloses a method and device for monitoring a closed-loop control system and a closed-loop control system. The method comprises: acquiring a motion information value of a servo motor of the closed-loop control system in real time; comparing the motion information value with a corresponding preset threshold during the period T, and controlling the closed-loop control system to be closed when the motion information value is greater than the preset threshold; wherein T is the time required for the actuator of the closed-loop control system to complete the motion; and the preset threshold is a maximum motion threshold of the servo motor during the period T. The present invention can stop the operation of the machine when the galloping phenomenon is about to occur in the closed-loop control system, avoiding loss caused by machine damage.

An information storage system and apparatus relate to the field of automatic control technologies in order to resolve a problem that there is little information for diagnosing a fault that is stored using a freeze frame. The system includes at least one subcontroller configured to obtain a parameter value corresponding to a parameter, and send the parameter and the parameter value corresponding to the parameter to a management controller, the management controller configured to send the received parameter and the received parameter value corresponding to the parameter to a vehicle-intelligent device, and the vehicle-intelligent device is configured to receive and store the parameter and the parameter value corresponding to the parameter, where each subcontroller is coupled to at least one executor, and the management controller is coupled to each subcontroller of the at least one subcontroller.

A diagnostic method localizes technical faults in a motion system that includes a base adapted to receive a motion stage for equipment, a machine frame resting on the floor, dampers adapted to support the base, and an active isolation system arranged between the base and the machine frame. The active isolation system and the base form a mechanical system. The active isolation system includes actuators, adapted to impart six degree-of-freedom (DOF) motion to the base in a reference frame, and inertial sensors adapted to provide a six DOF measurement of the base's motion. The method includes: i) applying a control signal for actuating or contributing to the actuation of the actuators of the active isolation system to impart a motion to the base; ii) obtaining, with the inertial sensors, a six DOF measurement of the base's motion relative to a reference point; iii) creating a measured process sensitivity matrix of the mechanical system using the six DOF measurement; and iv) determining, based on the measured process sensitivity matrix, whether all the actuators and sensors of the active isolation system are working as expected and/or whether there is a pivot point impeding the movement of the base.

Provided are a deterioration diagnosis device and deterioration diagnosis method that make it possible to carry out accurate deterioration diagnosis that takes into consideration not only vibration quantity but also other vibration factors such as vibration cycle. This deterioration diagnosis device is provided separately from or so as to be integrated with an electric motor control device comprising a power converter for outputting power for driving an electric motor connected to a device to be driven, a position controller for outputting a speed command value corresponding to the deviation between a position command value and an electric motor position detection value, a speed controller for outputting a torque current command value corresponding to the deviation between the speed command value and an electric motor speed detection value, and a current controller for adjusting the output current of the power converter according to the deviation between the torque current command value and a detection value for the torque current supplied to the electric motor. The deterioration diagnosis device comprises a deterioration diagnosis unit for carrying out electric motor deterioration diagnosis corresponding to electric motor driving information and a vibration information storage device for storing the diagnosis results of the deterioration diagnosis unit. The deterioration diagnosis unit stores a plurality of types of information relating to the electric motor vibration state that have been calculated from the driving information in the vibration information storage device and determines that vibration has occurred if the information relating to the vibration state of the electric motor is larger than a prescribed threshold.

Systems and methods for real-time monitoring and control of well operations at a well site use machine learning (ML) based analytics at the well site. The systems and methods perform ML-based analytics on data from the well site via an edge device directly at the well site to detect operations that fall outside expected norms and automatically respond to such abnormal operations. The edge device can issue alerts regarding the abnormal operations and take predefined steps to reduce potential damage resulting from such abnormal operations. The edge device can also anticipate failures and a time to failure by performing ML-based analytics on operations data from the well site using normal operations data. This can help decrease downtime and minimize lost productivity and cost as well as reduce health and safety risks for field personnel.