A system may include a sensor configured to output a sensor signal indicative of a distance between the sensor and a mechanical member associated with the sensor, a measurement circuit communicatively coupled to the sensor and configured to determine a physical force interaction with the mechanical member based on the sensor signal, and a compensator configured to monitor the sensor signal and to apply a compensation factor to the sensor signal to compensate for changes to properties of the sensor based on at least one of changes in a distance between the sensor and the mechanical member and changes in a temperature associated with the sensor.

A motor shaft is rotated to a predetermined rotation stop position by excitation of two-phase coils out of three-phase coils of a stator coil, and a detection value of a rotation angle sensor at the rotation stop position is acquired. Further, a sensor-error correction parameter for correcting a detection value of the rotation angle sensor in drive control of an electric motor is generated from the acquired detection value of the rotation angle sensor. With this configuration, in rotating a motor rotor to the predetermined rotation stop position, two coils out of the three-phase coils of the stator coil are excited. By sequentially changing the coils being excited, it is possible to cause the motor rotor to stop accurately at the predetermined rotation stop position.

A method for calibrating a magnetic angle sensor includes measuring, for a plurality of angle positions within a 360° rotation of a measurement object, in each case a first sensor signal for a first magnetic field component and a second sensor signal for a second magnetic field component orthogonal to the first magnetic field component, wherein the first and second sensor signals are in each case 360° periodic and representable as a Fourier series with a Fourier component of a fundamental and a Fourier component of a harmonic; determining the Fourier component of the harmonic for the first and second sensor signals based on a difference between a trajectory defined by the measured first and second sensor signals and a circular path; and correcting the angle positions based on the Fourier component of the harmonic determined for the first and second sensor signals.

Embodiments of the present disclosure include methods, apparatuses, systems, and computer program product for enabling multi-point shunt calibration of a sensor device. Multi-point shunt calibration provides at least a first, second, and third simulated calibration output, each simulated calibration output corresponding to an actual reading value and an expected reading value. The simulated calibration outputs are associated with a predefined output sequence, where each simulated calibration output is separated from an adjacent simulated calibration output by an output step size. Some embodiments are configured for automatically outputting each simulated calibration output for a particular period of time before outputting an adjacent simulated calibration output in the predefined output sequence. The various simulated calibration outputs, actual reading values, and/or expected values may be used in determining calibrated reading values for the sensor device.

A method for determining a rotation angle of a magnet includes measuring a 3D magnetic field vector of a magnetic field generated by the magnet, wherein the 3D magnetic field vector describes at least a part of an ellipse in 3D space during a rotational movement of the magnet. The method further includes mapping the measured 3D magnetic field vector to a 2D vector based on a compensation mapping, wherein the compensation mapping is configured to map the ellipse in 3D space to a circle in 2D space. The method further includes determining the rotation angle of the magnet based on the 2D vector.

In some embodiments, a position sensor calibration and linearization system for position sensors is provided. A method of calibrating and linearization of a position sensor includes reading Spatial Angle data from a position sensor at a set of positions of a target swept over receive coils in the position sensor; calculating calibration parameters from the Spatial Angle data; determining an initial position values from the Spatial Angle data and the calibration parameters; determining linearization parameters from the initial position values; and writing the calibration parameters and the linearization parameters into the position sensor.

A sensor circuit for measuring a physical quantity including: a signal acquisition circuit having a sensor to provide an input signal related to the physical quantity; a processing circuit to receive the input signal and for providing an output signal representative of the physical quantity; the processing circuit comprising a closed loop comprising: a first sub-circuit arranged for receiving the input signal and a feedback signal, and configured for providing a first signal; a frequency dependent filter for receiving and filtering the first signal, and for providing the output signal; a second sub-circuit for receiving and converting the filtered signal into the feedback signal using a non-linear function.

In accordance with an embodiment, a method for monitoring a data converter configured to convert data using a calibration determined by a calibration data record includes calibrating the data converter in order to determine a corresponding multiplicity of time associated calibration data records at a multiplicity of different times; and determining a state of the data converter based on comparing at least one of the multiplicity of time associated calibration data records with a comparison data record.

Various embodiments of the present invention utilize systems, methods, and computer program products that perform measurement device calibration management by utilizing calibration offset generation machine learning models that are generated using a model training routine that comprises, for each measurement environment feature value: (i) determining a plurality of inferred measurements by a measurement device in relation to a ground-truth measurement operation via performing the ground-truth measurement operation under simulated measurement conditions characterized at least in part by varying a measurement environment feature that is associated with the measurement environment feature value across a per-feature spectrum for the measurement environment feature; and (ii) generating the calibration offset generation machine learning model based at least in part on comparing the plurality of inferred measurements and a ground-truth measurement output for the ground-truth measurement operation.

A method, system, server and computer program product for the calibration of a sensor of a building. In particular, the method may include: receiving, at the computer system, sensor identification data, the identification data provided by communication of an identifier associated with the sensor and an identification device configured to communicate with the system; receiving, at the computer system, measured data representing a calibration sensor device measured physical phenomenon provided by communication of a portable calibration sensor device with an environment proximate to the sensor, the portable calibration sensor device being configured to communicate with the system; and receiving, at the computer system, sensor data associated with the identification data of the sensor, the sensor data representing a sensor measured physical phenomenon provided by the sensor; calculating, in the computer system, a difference value between the measured data and the sensor data so as to provide calibration data.