A fault condition is diagnosed in an electric machine that includes a rotor and a plurality of permanent magnets. To do so, the rotor is rotated so that each of the plurality of permanent magnets passes a magnetic flux density sensor, and the values of magnetic flux density are measured using the magnetic flux density sensor at a plurality of positions of the rotor. The measured values of magnetic flux density are analyzed and a magnitude of a peak amplitude is compared in a time or frequency domain with a reference value. If the peak amplitude is below the reference value, the electric machine is determined to have a fault condition.

A system and method for performing vector magnetometry are described. A method can include illuminating diamond with a modulated optical signal and a modulated microwave (MW) signal. A first, bias magnetic field is also applied to the diamond. Light emitted from the diamond in response to the optical signal, the MW signal, and the first magnetic field is detected via a single detector at a fixed position relative to the diamond. A modulation of the detected light encodes information corresponding to a plurality of nitrogen vacancy (NV) axes of the diamond.

The invention relates to a method for measuring ageing of permanent magnets of a synchronous machine comprising a stator and a rotor, the machine being fitted with at least one angular position sensor of the rotor, the rotor comprising the permanent magnets provided to move said rotor around the stator, the angular position sensor comprising at least two fixed magnetic induction measurement sensors extending to an axial end of the rotor, facing and immediately adjacent to the axial edges of the permanent magnets, characterized in that the method consists of: j1) determining, while stopped or during a laden or unladen rotation phase of the synchronous machine, the maximum value of the magnetic induction using the magnetic induction measurement sensors and the electronic unit; j2) comparing the measured maximum magnetic induction value with a reference value; and j3) if the maximum magnetic induction value is less than the reference value, presenting a difference determined with respect to said reference value in order to generate warning information S using the electronics unit and, if this is not the case, returning to step j1).

A magnetic field sensing apparatus including a magnetic flux concentrator, a plurality of magnetoresistance units, and a plurality of magnetization direction setting elements is provided. The magnetic flux concentrator has a top surface, a bottom surface opposite to the top surface, and a plurality of side surfaces connecting the top surface and the bottom surface. The magnetoresistance units are respectively disposed beside the side surfaces. The magnetoresistance units are electrically connected to form an unchangeable Wheatstone full bridge. The magnetization direction setting elements set the magnetization directions of the magnetoresistance units into three different combinations in three different periods, respectively, so as to enable the unchangeable Wheatstone full bridge to respectively measure the magnetic field components in the three different directions in the three different periods.

Aspects of the subject technology relate to systems, methods, and computer-readable media for corrosion analysis using magnetic flux leakage measurements. The present technology can magnetic flux leakage data obtained by a magnetic flux leakage tool placed in a pipe within a wellbore and convert the magnetic flux leakage data into image data. Further, the present technology can provide the image data to a machine learning model. The machine learning model is configured to identify one or more physical parameters associated with corrosion present on the pipe.

Aspects of the subject technology relate to systems, methods, and computer-readable media for corrosion analysis using magnetic flux leakage measurements. The present technology can magnetic flux leakage data obtained by a magnetic flux leakage tool placed in a pipe within a wellbore and convert the magnetic flux leakage data into image data. Further, the present technology can provide the image data to a machine learning model. The machine learning model is configured to identify one or more physical parameters associated with corrosion present on the pipe.

Examples are described herein for detecting, and outputting audio signals to, wearable audio output devices. In various examples, a device may include a time-of-flight (ToF) sensor and a processor. The processor may analyze ToF sensor data generated by the ToF sensor. Based on the analysis, the processor may detect a wearable audio output device worn by an individual. In response to detecting the wearable audio output device, the processor may output an audio signal to the wearable audio output device.

An apparatus comprising at least one first signal loop configured to receive a first signal; at least one second signal loop magnetically coupled with the first signal loop configured to generate a second signal; a signal processor configured to monitor the second signal and determine the presence of at least one metal object dependent on the second signal.

A magnetic field sensing apparatus including a magnetic flux concentrator and a plurality of magnetoresistance units is provided. The magnetic flux concentrator has a top surface, a bottom surface opposite to the top surface, and a plurality of side surfaces connecting the top surface and the bottom surface. The magnetoresistance units are respectively disposed beside the side surfaces. The magnetoresistance units are electrically connected to form at least one kind of Wheatstone full bridge in three different periods, so as to measure magnetic field components in three different directions, respectively, and to cause the at least one kind of Wheatstone full bridge to output three signals corresponding to the magnetic field components in the three different directions, respectively.

A system includes an electronic contact lens that obtains sensor measurements from integrated motion sensors or other types of sensors and a processing module that estimates a mental state of an individual based on the sensor measurements. The processing module identifies patterns of eye movements and analyzes how these patterns change over time. Based on anatomical relationships between eye movement and mental state, the processing module estimates characteristics of the individual such as fatigue, intoxication, injury, or a medical condition that have known effects on eye movement patterns. The electronic contact lens system generates an output indicative of the estimated mental state to alert the individual to the detected condition or to initiate an automated action.