An automatic robot control system and methods relating thereto are described. These systems include components such as a touch screen panel (“TSP”) robot controller for controlling a TSP robot, a camera robot controller for controlling a camera robot and an audio robot controller for controlling an audio robot. The TSP robot operates inside a TSP testing subsystem, the camera robot operates inside a camera testing subsystem, and the audio robot operates inside an audio testing subsystem. Inside the audio testing subsystem, an audio signals measurement system, using a bi-directional coupling, controls the operation of the audio robot controller. In this control scheme, a test application controller is designed to control the different types of subsystem robots. Methods relating to TSP, camera, and audio robots, and their controllers, taken individually or in combination, for automatic testing of device functionalities are also described.

A diagnostic service system includes one or plurality of factory monitoring systems configured to perform monitoring of at least one machine; a service center management device that is connected with the one or plurality of factory monitoring systems via a network; one or plurality of service centers that are connected with the service center management device; and a plurality of service terminals connected with one service center or each of the plurality of service centers via a service control. The plurality of service terminals are used by each responder capable of fault diagnosis of the machine, and when fault of a machine occurs, one of the plurality of service terminals is selected via the service center management device and the one service center or plurality of service centers.

A method for line assignment of a short-circuit of a broadband lambda sensor having an upper or a lower short-circuit potential, wherein the broadband lambda sensor has a sensor and multiple sensor lines. The method comprises establishing a conductive connection of at least one sensor line of the multiple sensor lines via a limiting resistor to a reference potential; comparing a sensor line potential of at least one sensor line to be checked of the multiple sensor lines to the reference potential or the short-circuit potentials; classifying (105) the at least one sensor line to be checked as not short-circuited with the upper or the lower short-circuit potential if it is established upon the comparison that the at least one sensor line potential is inside the reference potential range or if it is outside the short-circuit potential ranges; and assigning the short-circuit to at least one sensor line not classified as not short-circuited.

An accelerated loading road-testing system includes a plurality of loading mechanisms. The plurality of loading mechanisms are sequentially arranged along a first direction. The loading mechanism includes a supporting frame, a sliding assembly, and a loading assembly. The supporting frame includes a horizontal supporting beam disposed along a second direction. The horizontal supporting beam has a sliding state in which the horizontal supporting beam slides along a third direction, and a static state in which the horizontal supporting beam is static. The sliding assembly is slidable on the horizontal supporting beam along the second direction. The loading assembly includes a telescopic cylinder and a loading head. A first end of the telescopic cylinder is hinged to the sliding assembly, the second end of the telescopic cylinder is securely connected to the loading head, the telescopic cylinder is configured to always drive the loading head to move along the third direction.

An equipment state monitoring device projects a plurality of pieces of actual measurement data indicating a state value of equipment to a dimensionless space in which a plurality of display shapes indicating a respective plurality of pieces of normal information indicating a normal state of the equipment are represented by a common shape, and estimates a distribution of a state of the equipment on the basis of the plurality of pieces of actual measurement data projected to the dimensionless space. Further, both or one of the normal information in the dimensionless space and the actual measurement data in the dimensionless space is corrected on the basis of the relationship between actual measurement data indicating the normal state of the equipment in the dimensionless space and the display shape indicating the normal information in the dimensionless space.

Rotating machinery is evaluated by calculating a boundary condition based on a measured value of a parameter related to an operating state of the rotating machinery, and calculating an evaluation value corresponding to the calculated boundary condition based on the reduced order model, during operation of the rotating machinery. The reduced order model is created based on a prediction model including a heat transfer model and a structural model of the rotating machinery for predicting an evaluation value of the rotating machinery corresponding to the boundary condition.

A road surface state determination device includes a tire-side device and a vehicle-body-side system. The tire-side device is attached to a back surface of a tread of each of a plurality of tires included in a vehicle. The vehicle-body-side system is included in a body of the vehicle. The tire-side device outputs a detection signal corresponding to a magnitude of vibration applied to the tire. The tire-side device generates road surface data indicative of a road surface state appearing in a waveform of the detection signal. The tire-side device transmits the road surface data. The vehicle-body-side system performs bidirectional communication with the tire-side device and receives the road surface data. The vehicle-body-side system determines the road surface state of a road surface on which the vehicle is traveling based on the road surface data.

A machining accuracy diagnosing device includes a temperature regulation operating pattern setting unit, a cutting condition setting unit, a temperature information acquiring unit, and a machining accuracy influence amount predicting unit. The temperature regulation operating pattern setting unit sets an operating pattern of a temperature regulating unit. The cutting condition setting unit sets a scheduled machining start time and a scheduled machining end time. The temperature information acquiring unit acquires an influencing temperature of the temperature regulating unit on the machine body temperature and/or an air temperature outside the plant. The machining accuracy influence amount predicting unit predicts an influence amount of the temperature regulating unit on the machining accuracy based on the operating pattern, the scheduled machining start time and the scheduled machining end time, and at least one of the influencing temperature and/or the air temperature outside the plant and a set temperature of the temperature regulating unit.

A system for measuring pump efficiency includes a pump configured to pump a fluid, a suction pipe disposed upstream of a suction side of the pump, a discharge pipe disposed downstream of a discharge side of the pump, a first pipe section disposed between the suction pipe and the suction side of the pump, and a second pipe section disposed between the discharge pipe and the discharge side of the pump. Each of the first pipe section and the second pipe section includes a temperature sensing pipe liner configured to measure a temperature of the fluid in the first pipe section, and a thermal insulator disposed radially outward of the temperature sensing pipe liner.

Based on measurements of forces and rotational velocity experienced by a drill bit during drilling, drilling behavior is detected and identified. Measurements of forces on a drill bit including torque on bit (TOB), weight on bit (WOB), etc. and measurements of rotational velocity (rotations per minute or RPM) are acquired in real time at the drill bit. Various measurements are correlated to produce related combinations of measurements, such as WOB-RPM, TOB-RPM, and RPM-time. Based on fitting between the combinations of measurements and curves corresponding to predetermined torsional behavior trends, torsional, axial, and rotational behaviors are classified as functional or dysfunctional. A dysfunction identifier then identifies drill bit dysfunctions, such as high-frequency torsional noise, cutting-induced stick-slip, friction-inducted stick-slip, pipe-induced stick-slip, three-dimensional (3D) coupled vibrations (including subsets high-frequency torsional oscillations and low-frequency torsional oscillations), low-frequency torsional vibration, high-frequency torsional vibration, etc.) based on the functionality of the torsional, axial, and rotational behaviors. Based on drill bit dysfunction identification, dysfunctional drilling behavior can be mitigated.