An autocalibration method includes generating at least one sensor signal in response to measuring a physical quantity; compensating the at least one sensor signal based on at least one compensation parameter to generate at least one compensated sensor signal; generating the at least one compensation parameter based on the at least one sensor signal or the at least one compensated sensor signal; comparing each of the at least one compensation parameter to a respective tolerance range; on a condition that each of the at least one compensation parameter is within its respective tolerance range, transmitting the at least one compensation parameter as at least one validated compensation parameter to be used for compensating the at least one sensor signal; and on a condition that at least one of the at least one compensation parameter is not within its respective tolerance range, generating a fault detection signal.

Systems and methods are described for estimating a state of a process and an input to the process using a sensor network. Each sensor node in the sensor network is directly to one or more adjacent sensor nodes and indirectly coupled to the remaining sensor nodes through the one or more adjacent sensor nodes. Each sensor node iteratively calculates a new estimated state based on estimations of the state and the input to the process calculated by the sensor node in a previous iteration. The new estimated state is then adjusted based on a difference between a predicted and actual output of a sensor and is further adjusted based on differences between a previous estimated state calculated by the sensor node and estimated states calculated by adjacent sensor nodes.

An electronic device includes a rotating body coupled to a bezel part to be rotatable and including a plurality of magnets, a pair of Hall sensors configured to sense a magnetic field caused by the plurality of magnets, a magnetic sensor disposed in an internal space, and a processor configured to calibrate, based on first magnetic field data, second magnetic field data based on a calculated offset value.

Systems and methods are provided for improving statistical and machine learning drift detection models that monitor computing health of a data center environment. For example, the system can receive streams of sensor data from a plurality of sensors in a data center; clean the streams of sensor data; generate, using a machine learning (ML) model, an anomaly score and a dynamic threshold value based on the cleaned streams of sensor data; determine, using the ML model and based on the anomaly score and the dynamic threshold value, a correctness indicator for a first sensor in the plurality of sensors; and using the correctness indicator, correct the first 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.

This disclosure is directed to methods, computer program products, and systems for calibrating one or more remote sensing devices in an environment. The disclosed technology relates to a calibration device configured to determine measurement data within an environment. The calibration device may transmit the measurement values, or other calibration data items, to a remote sensing device via a wireless link while the remote sensing device stays with a structure in which the remote sensing device is commissioned to operate. In response to receiving the calibration data items, the remote sensing device may adjust one or more settings of the remote sensing device in order to satisfy a calibration threshold.

An autocalibration method includes generating at least one sensor signal in response to measuring a physical quantity; compensating the at least one sensor signal based on at least one compensation parameter to generate at least one compensated sensor signal; generating the at least one compensation parameter based on the at least one sensor signal or the at least one compensated sensor signal; comparing each of the at least one compensation parameter to a respective tolerance range; on a condition that each of the at least one compensation parameter is within its respective tolerance range, transmitting the at least one compensation parameter as at least one validated compensation parameter to be used for compensating the at least one sensor signal; and on a condition that at least one of the at least one compensation parameter is not within its respective tolerance range, generating a fault detection signal.

A position sensing device for measuring a position, comprises a position sensing device for measuring a position; a plurality of sensors arranged to produce sense signals each being a function of an input phase representative of a position to be measured; a combiner circuit arranged to generate an error signal by combining the sense signals according to an array of weight factors; a processing block including a loop filter to filter the error signal and arranged to output a phase value representative of the position; and a feedback loop comprising a feedback signal unit arranged for receiving the output phase value and for adjusting based on the received output phase value of the array of weight factors.

A sensor system for detecting a position of a measuring object relative to a sensor, the system including a sensor for the provision of a measured value and an evaluation device for the evaluation of the measured value and for the provision of an evaluation result, wherein the evaluation device includes a comparison device and a timing element, the comparison device is configured for a comparison of a stored measured value with a currently detected measured value, the comparison device is configured for a provision of a control signal to the timing element if a result of the comparison meets a presettable criterion, the timing element is configured in such a way that a time measurement process is continued at the provision of the control signal and the time measurement process is started anew at an absence of the control signal, the timing element is configured in such a way that a trigger signal is output by the timing element on reaching a presettable period of time.

A method and an apparatus for determining a rotation angle of a rotor in a motor with the aid of angle sensors by measurement of reference values and correction of the effected computations. The method is used, for example, in a synchronous motor.