A method, a system, and a computer program for executing high resolution spectrum monitoring. A sensor receives an input signal having a varying frequency content over time. One or more samples of the received input signal are sampled. The samples of the received input signal include one or more swept signal samples generated by sweeping, using a center frequency of the sensor, the received input signal across an entire frequency spectrum associated with the received input signal. Sampling of the samples of the received signal is performed while performing the sweeping. The signal samples are processed.

A frequency spectrum detection system including: a frequency-scan light source, a phase modulator, an optical filter, an optical fiber, a photodetector, a power divider, an electric amplifier, a combiner, an electric filter, and an oscilloscope. The frequency-scan light source, the phase modulator, the optical filter, the photodetector, and the electric amplifier form a ring-shaped optoelectronic oscillator resonant cavity, which is configured to generate a frequency-scan signal. The combiner is configured to receive a signal to be measured. The phase modulator is configured to modulate the combined electrical signal onto a frequency-scan optical signal. The optical filter is configured to selectively attenuate or amplify one sideband of double sidebands of the double-sideband phase-modulated optical signal. The photodetector is configured to detect a signal filtered by the optical filter.

A frequency spectrum detection system including: a frequency-scan light source, a phase modulator, an optical filter, an optical fiber, a photodetector, a power divider, an electric amplifier, a combiner, an electric filter, and an oscilloscope. The frequency-scan light source, the phase modulator, the optical filter, the photodetector, and the electric amplifier form a ring-shaped optoelectronic oscillator resonant cavity, which is configured to generate a frequency-scan signal. The combiner is configured to receive a signal to be measured. The phase modulator is configured to modulate the combined electrical signal onto a frequency-scan optical signal. The optical filter is configured to selectively attenuate or amplify one sideband of double sidebands of the double-sideband phase-modulated optical signal. The photodetector is configured to detect a signal filtered by the optical filter.

A fault arc signal detection method using a convolutional neural network, comprising: enabling a sampling signal subjected to analog-digital conversion to respectively pass through three different band-pass filters; respectively extracting a time-domain feature and a frequency-domain feature from a half wave output of each filter; constructing a two-dimensional feature matrix by means of extracted time-frequency feature vectors from the output of each filter, and stacking the feature matrices corresponding the outputs of the three filters to construct a three-dimensional matrix for each half wave; and processing a multi-channel feature matrix by using a multi-channel two-dimensional convolutional neural network, and determining, according to the output result of the neural network, whether the half wave is an arc. The detection method based on the convolutional neural network has higher accuracy and reliability in recognizing a fault arc half wave, can implement targeted training for different load conditions, and is self-adaptive.

A fault arc signal detection method using a convolutional neural network, comprising: enabling a sampling signal subjected to analog-digital conversion to respectively pass through three different band-pass filters; respectively extracting a time-domain feature and a frequency-domain feature from a half wave output of each filter; constructing a two-dimensional feature matrix by means of extracted time-frequency feature vectors from the output of each filter, and stacking the feature matrices corresponding the outputs of the three filters to construct a three-dimensional matrix for each half wave; and processing a multi-channel feature matrix by using a multi-channel two-dimensional convolutional neural network, and determining, according to the output result of the neural network, whether the half wave is an arc. The detection method based on the convolutional neural network has higher accuracy and reliability in recognizing a fault arc half wave, can implement targeted training for different load conditions, and is self-adaptive.

A wideband spectrum analyzer includes at least one signal input, and at least one signal channel with a first filter module and a second filter module. The first filter module and the second filter module are connected with the at least one signal input downstream of the at least one signal input in a series connection. The first filter module includes first switches, and several different highpass filters being arranged in a parallel connection. The first switches are configured to selectively connect one of the highpass filters with an input of the first filter module and an output of the first filter module. The second filter module includes second switches, and several different lowpass filters being arranged in a parallel connection. The second switches are configured to selectively connect one of the lowpass filters with an input of the second filter module and an output of the second filter module.

A physiological state index calculation system, a physiological state index calculation method, and a non-transitory computer readable medium for capturing subtle changes in a physiological state of a living body are provided. The physiological state index calculation system includes a band-pass filter that filters cerebral blood flow waveform information obtained from a cerebral blood flow of a living body in at least one frequency band, and a complex number conversion unit configured to convert the filtered cerebral blood flow waveform information into a complex number for at least one frequency band. The cerebral blood flow waveform information converted into a complex number by the complex number conversion unit is an oscillator that reflects a physiological state of a living body.

A physiological state index calculation system, a physiological state index calculation method, and a non-transitory computer readable medium for capturing subtle changes in a physiological state of a living body are provided. The physiological state index calculation system includes a band-pass filter that filters cerebral blood flow waveform information obtained from a cerebral blood flow of a living body in at least one frequency band, and a complex number conversion unit configured to convert the filtered cerebral blood flow waveform information into a complex number for at least one frequency band. The cerebral blood flow waveform information converted into a complex number by the complex number conversion unit is an oscillator that reflects a physiological state of a living body.

Systems and methods relate to electric propulsor fault detection. An exemplary system includes at least a first inverter configured to accept a direct current and produce an alternating current, a first propulsor, a first motor operatively connected with the first propulsor and powered by the alternating current, and at least a noise monitoring circuit electrically connected with the direct current and configured to detect electromagnetic noise and disengage the at least an inverter as a function of the electromagnetic noise.

Systems and methods relate to electric propulsor fault detection. An exemplary system includes at least a first inverter configured to accept a direct current and produce an alternating current, a first propulsor, a first motor operatively connected with the first propulsor and powered by the alternating current, and at least a noise monitoring circuit electrically connected with the direct current and configured to detect electromagnetic noise and disengage the at least an inverter as a function of the electromagnetic noise.