1019results about "Frequency measurement arrangement" patented technology

The invention provides a power grid multi-agent large model safety evaluation index calculation method, and relates to the technical field of intelligent control. The method comprises the following steps: acquiring a voltage change rate and a frequency change rate, dividing four stages according to disturbance starting and extreme points, pairing curve trends, judging delay and synchronization characteristics, extracting a continuous change structure, and generating a disturbance subsection evolution structure; according to the method, through staged analysis of node voltage and frequency change trends and combination of trend consistency judgment and abnormal segment identification, dynamic structure reconstruction and trend mapping of a disturbance process are realized, and coherence and precision of index response state identification are improved through trend boundary collection and frequency classification; cooperative characteristic identification is enhanced through the coupling direction and delay analysis of inter-node multi-parameter change, the node adjustment priority is defined through regulation and control response sorting, an adjustment path under multi-dimensional linkage is constructed, and the refined management and control capacity of disturbance response and the pertinence of control decision are improved.

The invention provides a multi-band radio frequency power amplifier dynamic range adaptive test method and a system thereof. The method comprises the following steps: acquiring an output signal frequency spectrum of a tested radio frequency power amplifier, extracting characteristic frequency points including a center frequency and a bandwidth, matching the characteristic frequency points with a preset frequency band database, and automatically loading a test scheme of a corresponding frequency band. According to the method, the frequency bands are automatically matched through spectrum sensing, the test scheme is loaded, the multi-frequency-band characteristics can be rapidly adapted without manual parameter configuration, index missing test is avoided, and the switching efficiency is improved; dynamically optimizing test parameters by using a genetic algorithm, and accurately capturing a nonlinear distortion critical point while balancing coverage and efficiency; by combining multi-dimensional signal analysis and a deep learning model, the problem of missing detection of traditional single-domain analysis is solved, and the abnormal signal recognition capability is remarkably enhanced; through linear model correction, impedance dynamic matching and index threshold iteration, full automation and high precision of the test are realized, the environmental interference influence is effectively reduced, and a self-adaptive test system is constructed.

The invention discloses a power grid visual diagnosis system based on multi-source data fusion, and relates to the field of power grid diagnosis systems. The system comprises an information acquisition module, an electrical fault alarm module, a non-electrical quantity fault alarm module, a fault discrimination module, a communication module and a fault recording module. Firstly, information of a power grid is collected through the information collection module, then the information is transmitted to the electrical fault alarm module and the non-electrical fault alarm module for monitoring, corresponding actions are made when abnormity occurs, then the information is transmitted to the fault judgment module, input information is analyzed, and the fault type is obtained; meanwhile, the fault recording module records and broadcasts the power grid; the communication module collects information of other modules in the system and exchanges information with the monitoring system. According to the method, the abnormal information of the power grid is monitored and alarmed in combination with the multi-source data, and the fault type is judged through the data model, so that the omnibearing monitoring of the power grid is realized, and data support is provided for a subsequent maintenance plan.

The invention relates to the related technical field of distribution transformer insulation aging, in particular to a frequency domain diagnosis method, system and device for distribution transformer insulation aging and a medium, and the method comprises the steps: carrying out the frequency response test of a to-be-tested transformer, and obtaining a first frequency response curve; performing a frequency response simulation test on a transformer equivalent circuit model pre-constructed based on the to-be-tested transformer to obtain a second frequency response curve; constructing a target function based on the deviation of the first frequency response curve and the second frequency response curve; taking element parameters in the equivalent circuit model of the transformer as position vectors, taking the objective function as a fitness function, and adopting a multi-objective particle swarm algorithm to solve the element parameters to obtain optimal values of the element parameters; respectively comparing the optimal values of the element parameters with corresponding normal values to obtain insulation aging degrees; according to the method, the insulation aging degree can be obtained by comparing the element parameters obtained through optimization with the normal unaged element parameters.

The invention relates to the technical field of electrical parameter testing, in particular to a high-low voltage frequency converter testing system which comprises a sampling point calibration module, a frequency cross-grade identification module, a current response re-sequencing module, a dynamic interference blocking module and an operation parameter output module. According to the method, the amplitude of the voltage sampling point is mapped into the trigonometric function curve, the waveform trend is deduced in combination with the amplitude change angle, a time delay calibration mechanism based on periodic trend identification is established, and the sampling point time sequence precision in different gear switching scenes can be effectively adapted. According to a combined judgment mode of the current rise rate direction and the frequency jump amplitude, a cross-cycle dynamic judgment path is constructed, a frequency jump index can be identified from a non-stable operation state, and the perception capability of a non-linear operation behavior is improved. A current response sorting reconstruction process is introduced, and the sorting matching capability of inconsistent response sequences is enhanced through cross analysis of frequency gears, current response directions and load states.

The invention provides a power distribution network abnormal state sensing method and system based on data processing, and relates to the technical field of data processing, and the method comprises the steps: obtaining a target function, and setting a differential evolution parameter; the differential evolution parameters comprise population size, iteration times, variation factors and crossover probability; the configuration of differential evolution parameters is iteratively optimized, various operation data are preprocessed, abnormal value and noise removal and normalization processing are included, and processed data are obtained; and extracting characteristic indexes reflecting the running state of the power distribution network from the processed data, wherein the characteristic indexes comprise statistical characteristics, frequency spectrum characteristics and time frequency characteristics of voltage and current. According to the invention, through real-time data acquisition, feature extraction, state evaluation and abnormity identification and positioning, comprehensive monitoring and timely early warning of the operation state of the power distribution network are realized, and the safety and stability of the power distribution network are effectively improved.

The invention relates to an AC-DC integrated grounding fault positioning method and system, and the method comprises the steps: collecting the potential change data of a DC power supply system and the frequency characteristic data of an AC power supply system, and determining the electrical signal characteristics of stray current corrosion; decomposing the electric signal by using wavelet transform, and extracting direct-current and alternating-current components; determining a fault type according to the component amplitude; analyzing the potential gradient and the stray current flow direction in combination with a line topological structure, and determining the position of a fault point; measuring resistance to determine a grounding loop, and analyzing the correlation between corrosion distribution and electrical parameter characteristics; evaluating the influence of corrosion on the grounding path in combination with the material resistivity; according to the method, faults can be accurately recognized, fault points can be accurately positioned, the corrosion degree and the influence of the corrosion degree on the system can be evaluated, and effective support is provided for safe operation and maintenance of a subway power supply system.

The invention provides a power grid frequency detection method, system and device and a medium, and the method comprises the steps: carrying out the narrowband signal decomposition of an obtained input voltage signal of a power grid through a null-space tracking algorithm, and obtaining a fundamental main mode component of the input voltage signal; performing low-pass processing on the fundamental wave main mode component to obtain a fundamental wave signal of the fundamental wave main mode component; performing discrete Fourier transform on the fundamental wave signal to obtain phase information of the fundamental wave signal; according to the phase information of the fundamental wave signal, calculating phase deviation information of the fundamental wave signal in pre-selected adjacent cyclic waves to obtain frequency estimation information of the power grid; according to the invention, narrow-band decomposition is carried out on an input voltage signal through a null-space tracking algorithm, so that a fundamental main mode can be accurately extracted; and phase deviation information can be determined based on discrete Fourier transform, so that when the interference frequency of the power grid is close to the fundamental frequency, high separation precision can be kept, and the accuracy of power grid frequency estimation can be improved.

The invention relates to a magnetic core loss prediction method and device for a magnetic element, and the method comprises the steps: obtaining historical data sets of different magnetic core materials, thereby considering the influence of the temperature on the magnetic core loss, carrying out the temperature correction of a preset SteinMazz equation according to the historical data sets, obtaining a target SteinMazz equation, and carrying out the prediction of the magnetic core loss of the magnetic element. Therefore, loss prediction can be carried out on the magnetic core material in the historical data set through the target Steinmaz equation, and an updated data set of the prediction value of the temperature factor is obtained. Furthermore, the influence of the magnetic flux density data and the frequency on the magnetic core loss can be considered, the updated data set is merged according to the magnetic core material, the magnetic flux density data and the frequency, a merged data set is obtained, and then the preset prediction model can be trained through the merged data set. The training of the preset prediction model on the magnetic flux density data and frequency is added, so that the predicted magnetic core loss of the target prediction model on the magnetic element better conforms to the actual situation.

The invention discloses a frequency measurement circuit and a frequency measurement method, belongs to the technical field of frequency measurement, and mainly solves the problems that the existing frequency measurement is large in frequency error, low in frequency measurement speed and narrow in frequency measurement bandwidth, and cannot meet the requirements of radar communication. The frequency measurement circuit comprises an FPGA control module, a reference clock circuit connected with the FPGA control module, a DDS frequency output circuit, a phase discrimination frequency control circuit, a frequency mixer connected with the phase discrimination frequency control circuit, and a radio frequency input circuit connected with the frequency mixer. According to the frequency measurement technology, the DDS output frequency is directly collected according to the characteristic that the FPGA collects the low frequency, the DDS output frequency serves as the phase discriminator phase discrimination frequency, frequency measurement is conducted in a phase locking mode, and the frequency measurement precision is high; the phase discriminator is set to have a fixed frequency dividing ratio, the phase discriminator is configured with a fixed register, a DDS frequency sweeping mode is adopted, and the frequency measurement time is short by changing the phase discrimination frequency of the phase discriminator to the output frequency of the phase-locked loop; and the frequency measurement bandwidth is increased by using a radio frequency input frequency division mode.

The invention discloses an electric power system operation state analysis and evaluation method and device, and the method comprises the steps: carrying out the line node division of an electric power system, combining the load time division of a power supply region, and further discriminating the load change based on the load time; meanwhile, fluctuation nodes are identified by using the operation states of the line nodes and the power grid operation fluctuation degree is analyzed, so that the operation stability of the power system is evaluated. According to the method, limitation of traditional overall evaluation is broken through, fine transformation from macroscopic to microscopic and from static analysis to dynamic monitoring is achieved, the actual operation condition of the power system can be comprehensively and accurately reflected, and clear direction guidance is provided for formulating a targeted regulation and control strategy. In addition, the possibility that abnormal operation of the power system is covered can be effectively reduced, and potential risks are reduced to the maximum extent.

The invention discloses a bus voltage multi-dimensional real-time monitoring and analyzing method, system, equipment and medium, and belongs to the technical field of power system monitoring and fault prediction.The method comprises the steps that high-frequency synchronous sampling is conducted on bus voltage signals, discrete time sequence voltage signals are obtained and preprocessed, preprocessed voltage signals are obtained, and the discrete time sequence voltage signals are obtained; the method comprises the following steps: synchronously extracting multi-dimensional characteristic parameters of voltage, obtaining a characteristic parameter set, calculating a health degree index comprehensively representing a voltage state by utilizing a dynamic weighted fusion algorithm based on the characteristic parameter set, calculating an abnormal degree of a current value according to a historical data sequence of the health degree index, and performing fault grade judgment according to the abnormal degree. And performing trend extrapolation based on the health degree index and the historical data sequence of the key parameters in the characteristic parameter set, and generating predictive maintenance suggestions. According to the method, the crossing from passive alarm to predictive maintenance is realized, and the intelligent level and the operation and maintenance reliability of state monitoring of the power system are remarkably improved.

The present application relates to a device and method for surveying a power line-buried path, wherein the device includes a transmitter which selects a balanced / unbalanced voltage to output input and rectified output power as a current pulse in the form of an unmodulated pulse or a frequency-modulated signal when a current pulse signal is transmitted to a conductor (power line) of a public distribution network, and a receiver in which a plurality of magnetic field sensors inductively couple the pulse or the frequency-modulated signal within a near magnetic field distance to obtain a difference value in each direction to obtain a depth.

The invention belongs to the technical field of energy storage, and particularly relates to a portable energy storage power supply offline grid-connected detection and expansion system, which comprises a power grid access module, a multi-rate power grid state detection module, a central control module, a self-adaptive isolation module, an energy management module, an expansion battery interface module and a man-machine interaction and communication module, the multi-rate power grid state detection module is used for providing ultra-fast response to power grid transient abnormity and accurate monitoring of power grid steady-state parameters at the same time, and comprises a transient abnormity rapid detection sub-module and a comprehensive parameter accurate detection sub-module. And the self-adaptive isolation module is directly associated with the transient abnormity rapid detection sub-module. Through a hardware acceleration detection mechanism of the transient abnormity rapid detection sub-module and a high-speed solid-state relay array of the self-adaptive isolation module, the system can respond to transient overvoltage, rapid frequency deviation or zero crossing abnormity and complete isolation action.

The invention discloses a new energy equipment sequence impedance multi-level frequency domain identification method, and relates to the field of power electronic equipment parameter and model frequency domain identification. Complex vector fitting is carried out on frequency domain response data of impedance measurement, an analytical model or an equivalent zero-pole model of power electronic equipment is obtained, and a basis is provided for grid-connected resonance stability analysis and impedance remodeling; comprising the following steps: S1, carrying out sequence impedance frequency scanning of single harmonic disturbance injection to obtain impedance frequency domain response data; s2, performing complex vector fitting to obtain a pole-residue type port frequency domain model; s3, evaluating'grey / black box 'characteristics according to the transparency of the control architecture information; s4, deducing a theoretical sequence impedance model of the grey box equipment, and identifying parameters based on a pole-residue expression; deducing an equivalent zero pole model for the black box equipment or the new energy cluster; compared with traditional qualitative analysis, accurate quantitative analysis and impedance remodeling are achieved, and analysis accuracy and engineering applicability are improved.

The invention relates to a multi-source micro-grid inertial support detection method and device and a storage medium. The method comprises the steps that S1, a discretized original voltage sequential sequence and a discretized original current sequential sequence are collected; s2, respectively extracting a first voltage sequence and a first current sequence corresponding to a measurement moment based on the original voltage sequential sequence and the original current sequential sequence; s3, obtaining a measurement frequency and a voltage and current phase difference based on the first voltage sequence and the first current sequence, and obtaining an active power based on the voltage and current phase difference; s4, obtaining a reference frequency and a reference power based on the measurement frequencies and the active powers at the plurality of measurement moments; and S5, based on the reference frequency and the reference power, combining the measurement frequency and the active power at the measurement moment to obtain the equivalent inertia. Compared with the prior art, the method has the advantages that the measurement accuracy of the equivalent inertia in the multi-source micro-grid environment is improved, and the like.

A test and measurement device has an input port to receive a signal from a device under test (DUT), the signal having a symbol rate, one or more analog-to-digital converters (ADC) to convert the signal to waveform samples at a sampling rate, and one or more processors, when aliasing is present: up-sample a portion of the signal having aliased samples to produce up-sampled samples; use the up-sampled samples to produce a real-time waveform; perform clock recovery on the real-time waveform to produce a recovered clock; and resample the aliased samples to produce a non-aliased waveform.

The invention provides a battery charging and discharging pulse frequency detection method and system, and the method comprises the steps: dividing a pulse current signal of a target battery during charging and discharging into a plurality of pulse signal segments, and determining the static deviation of the current of the target battery during charging and discharging based on the local current characteristics of each pulse signal segment; determining the time domain positioning error of the time interval through the static offset and the pulse width of the pulse current signal; monitoring the surface temperature of the target battery during charging and discharging, and determining the disturbance characteristics of the temperature of the target battery during charging and discharging to the current according to all the monitored temperatures and the pulse current signal; and performing pulse identification on the pulse current signal according to all the time domain positioning errors and disturbance characteristics to obtain an effective pulse time mark sequence of the target battery during charging and discharging, and determining an effective pulse frequency of the target battery during charging and discharging based on the effective pulse time mark sequence. According to the scheme, the influence of current signal drift on pulse frequency detection in the battery charging and discharging process can be reduced.

A sensorless method for machine tool chatter detection. When the machine tool spindle is running, a spindle motor torque signal is analyzed in the time domain to determine whether a bit is currently cutting a workpiece. When not cutting, an air-cut reference signal is stored for later use. When cutting, the spindle motor torque signal, along with positioning servo motor signals, are converted to the frequency domain and filtered. Filtering steps include removal of the air-cut reference signal via spectral subtraction, removal of spindle harmonic components, removal of artificial peaks due to aliasing effects, and removal of artificial peaks due to encoder error effects. After filtering, indicator criteria are evaluated to detect chatter, including a magnitude of the filtered torque signal for servo data and a magnitude ratio of the filtered torque signal to the air-cut reference signal for spindle data. Corrective action is taken when chatter is detected.

The invention discloses a high-power and frequency-adjustable gyrotron loading test system for nuclear fusion, which relates to the technical field of nuclear fusion and comprises a 2-megawatt coaxial gyrotron with adjustable frequency of 170 / 240GHz and a loading test platform. The loading test platform comprises a gyrotron part loading system, a strong magnet system, a vacuumizing system, a power supply system, a load system, a cooling system, a monitoring and diagnosing system and a control system. The component loading system is used for precise assembly; the strong magnet system provides an adjustable strong magnetic field; the vacuumizing system maintains ultrahigh vacuum; the power supply system comprises a cathode power supply and a body power supply, and the body power supply is used as a high-voltage amplifier to realize 10kHz rapid power modulation; the cooling system provides independent active cooling; the load system simulates a real load; comprehensive detection of the monitoring and diagnosis system; and the control system realizes coordinated control and rapid protection. According to the invention, a complete solution is provided for development, test, operation and maintenance of the 2-megawatt-level and frequency-adjustable gyrotron.

The invention provides an identification method for measuring fundamental wave pseudo oscillation by a low-sampling-rate measurement and control device, which belongs to the field of electrical measurement and comprises the following steps of: calculating an impedance deviation coefficient of a capacitor fundamental wave impedance value relative to a capacitor actual impedance value; searching effective maximum values and minimum values of the impedance deviation coefficients, taking the effective maximum values of the adjacent impedance deviation coefficients as analysis intervals, and calculating corresponding oscillation frequencies according to time differences of the analysis intervals; the maximum value and the minimum value threshold value of the impedance deviation coefficient corresponding to the oscillation frequency of each analysis interval are calculated, and the authenticity of measurement oscillation of the measurement and control device is identified according to the relation between the effective maximum value and the minimum value of the impedance deviation coefficient and the corresponding threshold value; the invention further provides a fundamental wave pseudo oscillation identification system measured by the low-sampling-rate measurement and control device. The risk of misjudgment caused by measurement pseudo oscillation of a low-sampling-rate measurement and control device due to high-frequency harmonic aliasing can be solved.

The invention relates to the technical field of quantum measurement, and discloses a high-speed arbitrary adjustable unbiased generalized measurement device for light quantum polarization bits, and the device comprises a high-speed adjustable z-axis rotation device; a high-speed adjustable y-axis rotating device; a measurement intensity high-speed adjusting device; a sigma z basis vector projection measurement device; a unit measuring device; and an electronics post-processing module. According to the invention, sigma z base vector projection measurement is constructed through an optical fiber polarization beam splitter (FPBS), unit measurement is constructed through an optical fiber beam splitter (FBS), and sigma z base vector unbiased generalized measurement with high-speed adjustable measurement intensity is realized in combination with a measurement intensity high-speed adjusting device and an electronics post-processing module. And the rotation of the measurement basis vector on the Bloch ball is realized through the high-speed adjustable z-axis rotating device and the high-speed adjustable y-axis rotating device, so that the high-speed arbitrary adjustable unbiased generalized measurement is realized.

The invention belongs to the technical field of intelligent operation and maintenance of a power system, and particularly relates to an intelligent power grid fault diagnosis system and method based on AI self-adaption, and the system comprises a data collection module, a preprocessing module, a self-adaption AI diagnosis engine, a fault recognition and classification module, a fault positioning module, a decision support and feedback module, and a system self-learning module. Dynamic adjustment of a diagnosis strategy is realized through deep reinforcement learning, topology modeling and fault positioning are performed in combination with a graph neural network, and continuous optimization of a model is realized by adopting an incremental learning mechanism, so that the accuracy, real-time performance and adaptability of fault diagnosis of the smart grid are improved.

The invention discloses a photovoltaic direct current system fault detection method and device based on line spectrum suppression, and the method comprises the steps: extracting a signal peak frequency through a time-frequency spectrum, analyzing the time-frequency stability of the signal peak frequency, and recognizing a periodic line spectrum signal. The method comprises the following steps of: dividing a frequency band by combining envelope on a frequency spectrum and minimum value point detection, decomposing a signal by using empirical wavelet transform, eliminating a modal component containing a line spectrum signal, only retaining a non-stationary modal component related to a fault feature, and reconstructing the non-stationary modal component to obtain a fault feature signal. And extracting statistical features such as root mean square value, variance and kurtosis of the fault feature signal, and comparing the statistical features with a feature threshold to perform fault arc detection. A photovoltaic system direct current arc detection device is designed based on the algorithm, the device effectively solves the problem that periodic signals and ripple noise in a photovoltaic direct current system interfere fault features under the condition that the low-voltage operation fault features are not obvious, and the universality of photovoltaic direct current system fault recognition is improved.

The invention provides a semiconductor circuit test method and test system, and the method comprises the steps: inputting test signals to the circuit input ends of a plurality of semiconductor circuits, and obtaining feedback signals at the circuit output ends; counting and preprocessing the plurality of groups of feedback signals; judging whether the corresponding semiconductor circuit is detected to be qualified or not according to the preprocessed feedback signal and a preset qualification condition; generating frequency fluctuation data of the semiconductor circuit according to the preprocessed feedback signal, and obtaining abnormal fluctuation according to the frequency fluctuation data; and performing qualification prediction on the undetected semiconductor circuit according to the abnormal fluctuation. According to the method, firstly, a machine learning method is adopted to carry out qualification test on part of semiconductor products, and after the test is completed, the number and the position of to-be-detected semiconductors are obtained according to the number and the position of frequency fluctuation semiconductors, so that accurate qualification prediction of to-be-detected semiconductor circuits is realized; and the test efficiency of the semiconductor product is greatly improved while the test precision is ensured.

The invention relates to the technical field of power systems, in particular to a power grid fundamental harmonic and inter-harmonic detection method and device and a storage medium, and can collect power grid signals, arrange discrete samples into sample vectors, apply a Hanning window to the sample vectors for zero filling DFT, and obtain a frequency index of fundamental waves according to a peak value of frequency spectrum amplitude square; setting a harmonic wave search range according to the frequency index of the fundamental wave, and screening the harmonic waves according to the frequency related threshold to obtain a frequency index set of the fundamental wave and the harmonic waves; calculating a residual error between the power grid signal and the fundamental harmonic reconstruction signal, and calculating a residual error ratio; and performing secondary iteration on the residual error to obtain a TF coefficient corresponding to the inter-harmonic. According to the technical scheme, fundamental wave phasor measurement, harmonic detection and inter-harmonic detection can be completed at the same time, the precision is high, and the detection efficiency is high.

The invention relates to the field of power grid monitoring, in particular to a frequency measurement method and terminal for power grid monitoring, and the method comprises the steps: enabling a current sequence, a voltage sequence, a frequency sequence and a temperature sequence collected by the power grid frequency measurement terminal to pass through a temperature prediction model of a physical constraint neural network architecture, so as to generate a temperature prediction value; constructing a differential algebraic constraint term based on a current sequence change rate, a frequency sequence acceleration, a temperature sequence change rate and a temperature prediction value and an energy conservation term based on electromagnetic energy calculation for optimizing and training a temperature prediction model; and calculating a frequency temperature drift value based on the temperature prediction value, and correcting a frequency acquisition value of the power grid according to the frequency temperature drift value. The frequency measurement error caused by the temperature drift effect of the power grid in the high-temperature environment can be counteracted in real time, and the temperature drift suppression capability of power grid monitoring frequency measurement is improved.

A method, processing system and control circuit for driving a linear resonance actuator, LRA, in an electronic device, comprising generating a drive signal to drive the LRA, wherein the frequency of the drive signal is initially set to an initial frequency (fi); determining a phase difference (Δφ) between a voltage and a current over the LRA; and adjusting the frequency of the drive signal using a feedback control loop such that the determined phase difference (Δφ) converges to a non-zero pre-determined phase difference at resonance (Δφ0). The invention further relates to an electronic device with a linear resonant actuator driven using such method,processing system or control circuit.

A performance testing device for a quartz crystal resonator comprises a testing box, an opening is formed in the top of the testing box, the opening is sealed through an upper cover, a transversely-arranged testing plate is installed in the middle of the interior of the testing box, the testing plate is fixedly connected with the testing box through a plurality of supporting springs, and vibration equipment is installed at the bottom of the testing plate. The top of the test plate is provided with a contact pin used for being matched with a quartz crystal resonator, the contact pin is externally connected with a crystal oscillator detection frequency instrument through a wire, a pressing plate is arranged right above the contact pin, the test plate is provided with a vertically arranged guide rod, the pressing plate is transversely and movably sleeved on the guide rod, the guide rod above the pressing plate is provided with a support plate, and the support plate is arranged on the support plate. A pressing bolt matched with the pressing plate is arranged on the supporting plate in a screwed mode, and a reset spring matched with the pressing plate is further arranged on the guide rod below the pressing plate in a sleeved mode. According to the invention, the actual vibration environment can be accurately simulated, so that the influence of vibration at different temperatures on the performance of the quartz crystal resonator can be detected.

The invention relates to the technical field of power monitoring, in particular to an online monitoring method and system for a power control cabinet. The method comprises the following steps: acquiring a time domain signal, tracking a fundamental wave frequency, adjusting a sampling window, and performing Fourier transform to obtain a harmonic amplitude and a phase; harmonic waves are divided into harmonic wave correlation groups according to association rules, harmonic wave phase consistency coefficients are calculated to weight the total energy in the groups, and weighted harmonic wave energy is obtained; total inter-harmonic energy is calculated, and an inter-harmonic structure factor is obtained based on the spectral entropy. And acquiring a real-time load rate and a change rate, and calculating a synchronous change coefficient and a load factor. And summing the weighted harmonic energy and the corrected inter-harmonic energy to obtain total distortion energy, and obtaining a comprehensive distortion index according to the total distortion energy. According to the scheme, the structured inter-harmonics possibly caused by the early failure of the equipment can be found earlier, and the requirements of early warning and predictive maintenance are met.