A baseline unit for use in a sensor system, the sensor system comprising N force sensors which output N sensor signals, respectively, where N≥1, the baseline unit configured to: monitor a measure of a rate of change of a sensor test signal, the sensor test signal being one of said N sensor signals or a signal derived from one or more of said N sensor signals; and in dependence upon the measure of the rate of change, control a stored baseline setting to control how a baseline test signal is calculated from said N sensor signals using a baseline-calculation method, the baseline-calculation method configured by the currently-stored baseline setting.

A pressure sensor is for positioning within a structure. The pressure sensor may include a pressure sensor integrated circuit (IC) having a pressure sensor circuit responsive to bending, and a transceiver circuit coupled to the pressure sensor circuit. The pressure sensor may include a support body having a recess therein coupled to the pressure sensor IC so that the pressure sensor IC bends into the recess when the pressure sensor IC is subjected to external pressure.

A pressure sensor is for positioning within a structure. The pressure sensor may include a pressure sensor integrated circuit (IC) having a pressure sensor circuit responsive to bending, and a transceiver circuit coupled to the pressure sensor circuit. The pressure sensor may include a support body having a recess therein coupled to the pressure sensor IC so that the pressure sensor IC bends into the recess when the pressure sensor IC is subjected to external pressure.

Methods for determining sensor channel location in distributed sensing of fiber-optic cables are disclosed. In one method, three or more Fiber Bragg-Gratings (FBGs) connected in series by a standard telecommunication fiber and interrogated using an input distributed fiber-optic sensing (DFOS) laser, where the input DFOS laser has a single wavelength. The input DFOS laser operates on a single wavelength that is different than the respective wavelengths of each of the three or more FBGs. The three or more FBGs are interrogated using an input broadband FBG laser. Each FBG reflects a wavelength of laser light that is proportional to the grating size, using an optical time domain reflectometer (OTDR) at the FBG wavelength, the distance to the particular FBG in the optical domain is computed and compared to the physical measurement of the FBG location. The sensor channel locations of the DFOS system are calibrated and constrained using this method.

A torque estimating device of a gas compressor includes a reference torque characteristic storage unit that stores a reference torque characteristic of the gas compressor as a torque characteristic of the gas compressor in a specific operation state, a torque setting unit that sets a torque corresponding to an input speed of rotation of the gas compressor and pressure of a refrigerant discharged from the gas compressor, on the basis of the reference torque characteristic stored in the reference torque characteristic storage unit, and a torque correcting unit that sets a torque at startup of the gas compressor among the torques set by the torque setting unit, by correcting the torque set by the torque setting unit, in accordance with the speed of rotation and an elapsed time from startup.

A load detection apparatus includes a load input portion having a input surface, and an output surface; a flexure element including on annular portion including a contacting portion configured to make contact with at least a part of the output surface, and a support portion; a set of sensors disposed on a reverse surface opposite to a surface provided with the contacting portion in the annular portion, each of the set of sensors being configured to detect distortion corresponding to an input load; a set of calculation portions configured to calculate a set of magnitudes of the load by use of respective detection results obtained by the set of sensors; and an abnormality determination portion configured to determine whether the set of sensors and the set of calculation portions have no abnormality, by comparing the set of magnitudes of the load with each other.

A load detection apparatus includes a load input portion having a input surface, and an output surface; a flexure element including on annular portion including a contacting portion configured to make contact with at least a part of the output surface, and a support portion; a set of sensors disposed on a reverse surface opposite to a surface provided with the contacting portion in the annular portion, each of the set of sensors being configured to detect distortion corresponding to an input load; a set of calculation portions configured to calculate a set of magnitudes of the load by use of respective detection results obtained by the set of sensors; and an abnormality determination portion configured to determine whether the set of sensors and the set of calculation portions have no abnormality, by comparing the set of magnitudes of the load with each other.

Disclosed are a system and methods for calibrating wall shear stress sensors. The system includes an oscillating plate coupled to an actuator and mounted on a rolling elements, and one or more sensors coupled to a height adjusting device. The system can further comprise a height control rod coupled to a height control base and a sensor holder configured to house the one or more sensors and supported on a connector, the connector configured to be rotatably disposed about the height control rod. The system can be calibrated by causing the actuator to oscillate the oscillating plate at a frequency, sensing, using the one or more sensors, shear stress at a wall, the shear stress at the wall being associated with a velocity field, and determining a theoretical wall shear stress based on fluid properties, the frequency, and the height of the one or more sensors above the oscillating plate.

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.

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.