4135results about "Resistance/reactance/impedence" patented technology

An interface circuit includes a reference voltage generation circuit to generate a reference voltage, a differential voltage signal generation circuit to convert send data input in sending data into a pair of differential voltage signals and output the pair of differential voltage signals based on the reference voltage generated by the reference voltage generation circuit, a receiver to convert a pair of differential voltage signals input in receiving data and output received data, and a receiver test circuit to perform a sensitivity test of the receiver, the receiver test circuit having a resistance circuit to generate a pair of differential voltage signals having a potential difference being necessary for the sensitivity test of the receiver.

The invention relates to the technical field of industrial safety, and discloses an electrolytic aluminum short circuit port operation safety early warning system based on multi-parameter collaborative awareness and intelligent diagnosis, and the system comprises a parameter collaborative awareness module, a dynamic diagnosis module, an early warning decision module, and an execution feedback module. By constructing a multi-dimensional parameter collaborative sensing mechanism, fusing temperature field distribution, current balance degree and insulation state multi-source data in real time and dynamically capturing early abnormal symptoms of a short circuit port, the hysteresis problem of traditional single-parameter threshold monitoring is solved, conversion from passive response to active defense is achieved, and the comprehensiveness and timeliness of operation state monitoring are improved; and meanwhile, based on a historical fault database and a real-time evolution model, a health index is generated and a fault path is predicted, so that maintenance personnel can pre-judge a development trend and a time window of potential risks in advance, and sudden equipment accidents are avoided.

The invention relates to the technical field of bushing detection, and discloses a bushing insulation state detection method based on multi-parameter real-time monitoring. The method comprises the following steps: acquiring multi-dimensional monitoring data such as a partial discharge pulse sequence, dielectric loss angle tangent value fluctuation data and surface leakage current density distribution in a bushing operation environment in real time; carrying out insulation defect feature extraction on the data set, and generating an insulation defect distribution map containing a creeping discharge track, an internal air gap position mark and a carbonization channel density index; high-risk and potential defect areas are divided by adopting a dynamic threshold segmentation algorithm, boundary coordinates are determined, and an insulation state evaluation vector containing parameters such as a surface discharge intensity index and the like is constructed according to the boundary coordinates; and inputting the vector into a pre-trained insulation aging prediction model, and outputting a bushing residual insulation life estimated value and a defect development priority sequence. According to the method, all-around accurate monitoring and pre-judgment of the insulation state of the sleeve are achieved, and scientific support is provided for operation and maintenance decision making of the sleeve.

The invention provides a power distribution network operation risk intelligent identification and early warning method, which comprises the steps of identifying an equipment contact failure probability through an actual wear state, and when the equipment contact failure probability exceeds a safe operation requirement, determining an equipment fault early warning signal through historical fault statistical data, identifying potential equipment failure risk points and extracting risk distribution characteristics; identifying a high-risk equipment node through the equipment fault early warning signal, evaluating whether a cascading fault of adjacent equipment overload is caused after power flow redistribution of a power grid according to the identified high-risk node, extracting a fault propagation path, and determining a system risk level distribution diagram; and carrying out risk area division on the system risk level distribution diagram, identifying key equipment nodes in a high-risk area, extracting a load transfer scheme of the high-risk area, and determining a load distribution path and a power transmission direction.

The invention relates to the technical field of magnetic ring detection, discloses a magnetic ring multi-dimensional nondestructive detection system and method based on multi-frequency composite electromagnetic excitation, and solves the defects of existing magnetic ring detection in the aspects of information acquisition, composite excitation and comprehensive diagnosis. The method comprises the following steps: applying multi-frequency composite excitation, and collecting and preprocessing multi-dimensional response; and extracting features, and carrying out deep learning fusion inversion to obtain magnetic characteristics, material components and defect information. The system comprises a composite excitation module, a multi-mode sensing module, a data acquisition preprocessing module, a data fusion inversion module and a control module. By adopting the technical scheme, comprehensive and efficient nondestructive detection of multi-dimensional electromagnetic information of the magnetic ring is realized, the existing limitation is overcome, and the detection precision and the comprehensive diagnosis capability are remarkably improved.

The invention discloses a multi-condition simulation capacitance detection relay life prediction method, system, equipment and medium, and relates to the technical field of relays, and the method comprises the steps: applying a plurality of simulation conditions to a relay through a programmable driving power supply, simulating the complex conditions in actual operation, and collecting the multi-dimensional parameters of the relay in real time in the execution process of the simulation conditions, extracting characteristic parameters from the collected multi-dimensional parameters, carrying out data preprocessing on the characteristic parameters, constructing a life prediction model, carrying out prediction calculation and reliability grade evaluation on the residual life of the relay by utilizing the life prediction model, and carrying out reliability grade evaluation on the residual life of the relay by monitoring capacitance change between contacts of the relay. And early performance degradation early warning is carried out in combination with a prediction result. According to the invention, through fusion of multi-working-condition simulation, hybrid modeling and capacitance detection, full-chain optimization from data acquisition, accurate prediction to early warning is realized, and the accuracy, timeliness and engineering application value of relay life prediction are improved.

The invention provides a multi-channel contact resistance intelligent test device and method, the contact resistance intelligent test device is integrated with a plurality of different types of resistance test channels, and the resistance test channels comprise a conduction test channel, a static resistance test channel and a dynamic resistance test channel. The device comprises an upper control module used for receiving a channel test parameter of a contact resistor and generating a channel selection test instruction based on the channel test parameter; the multi-channel switching module switches to a target test channel of a corresponding type based on the channel selection test instruction; the resistance measurement module applies current of a corresponding type according to the type of the target test channel, collects the voltage of the target test channel, and obtains a resistance value according to the voltage and the current; and the signal processing module performs noise reduction processing on the resistance value to obtain a target resistance value, and evaluates the change trend of the target resistance value, so that the problems of low test efficiency, dynamic data missing and personal error accumulation of a traditional method are solved, and the subjective deviation of manual interpretation is eliminated.

The invention relates to the technical field of cable positioning, in particular to a one-way grounding fault positioning method based on a signal injection method. The method comprises the following steps: installing an impedance detection unit at a grounding knife switch of a transformer substation, and injecting a controllable AC signal into a power transmission line through a built-in injection coil to enable the line to be in an open circuit state; collecting the injected current signal and performing frequency enhancement to extract the amplitude and phase of a target frequency component; zero-sequence impedance is calculated based on the injection voltage and current, and the zero-sequence impedance is compared with a preset impedance model to judge single-phase grounding; and when a fault is detected, determining a fault distance, a tower position and a grounding phase according to an impedance difference matching result, thereby realizing accurate positioning. According to the invention, by injecting the controllable AC signal into the power transmission line and combining frequency enhancement, phase self-calibration and impedance difference matching analysis, high-sensitivity detection, high-stability signal extraction and high-precision positioning of the single-phase earth fault are realized.

The invention provides an impedance scanning device based on network side voltage dynamic compensation under a three-phase voltage imbalance working condition, and relates to the technical field of new energy station power electronic converter topology and control, the device comprises a three-phase rectifier, a direct current bus capacitor, an inverter, a voltage compensation device, a frequency sweeping device, a circuit breaker and a series transformer part, the three-phase rectifier is connected in series with inverters of the voltage compensation device and the frequency sweep device, a secondary side of a series transformer of the voltage compensation device is connected in series with a network side, a secondary side of a series transformer of the frequency sweep device is connected in series with a grid-connected point, and a primary side of the series transformer is connected to the inverters and is coupled to a secondary side of the series transformer; according to the device, the power grid side voltage is rectified through the voltage compensation unit and is compensated to the grid side after being subjected to single-stage inversion transformation, voltage compensation is achieved through the energy of a power grid when the voltage is unbalanced, and an external energy source or an interference source does not need to be introduced. After compensation, the accuracy of the frequency sweeping result is obviously improved.

The invention belongs to the technical field of transformer operation loss monitoring, and particularly relates to a transformer operation loss condition optimization monitoring method, which comprises the following steps of: calculating an anomaly degree based on oil temperature and vibration characteristics, generating a real-time working condition in combination with load intensity, and associating accumulated operation duration to analyze a real-time operation loss anomaly index; the method comprises the following steps: realizing dynamic correlation between loss and the actual state of equipment, analyzing and extracting fluctuation parameters through a load characteristic change curve, calculating a comprehensive load fluctuation degree, correcting an operation loss abnormal index to eliminate load fluctuation interference, finally determining a dynamic reference threshold according to a historical loss curve, judging continuous overrun through double rules, and triggering early warning. Meanwhile, guide factors such as overload and internal heating abnormity are accurately recognized, corresponding adjustment instructions are output, loss monitoring accuracy and scene adaptability are improved, operation and maintenance closed loop of early warning, guide factors and disposal is achieved, and the method is suitable for transformer full-life-cycle loss monitoring.

The invention relates to the field of lithium battery intelligent monitoring, in particular to a low-temperature-resistant lithium battery BMS monitoring method and system based on cooperative sensing. The method comprises the following steps: acquiring surface temperature distribution, environment temperature and electrochemical parameters of the low-temperature tolerant lithium battery, and constructing a multi-source state characteristic matrix through space-time alignment and data fusion; applying a composite current excitation signal, and combining impedance analysis and spectrum analysis to extract impedance parameters, nonlinear distortion components and electrochemical stress factors to form a multi-dimensional feature vector; obtaining a state monitoring result by utilizing decision level fusion; through multi-sensor fusion and multi-dimensional feature fusion, the special internal state of the low-temperature tolerant lithium battery is comprehensively represented, early risk identification and early warning are carried out aiming at unique electrochemical behavior features of the low-temperature tolerant lithium battery, and compared with a common lithium battery monitoring method, the method has the advantages that the safety is high; and the accuracy, the robustness and the real-time performance of monitoring the state of the low-temperature tolerant lithium battery in the low-temperature environment are remarkably improved.

According to the power cable multi-defect nondestructive testing method and system based on the broadband impedance spectrum, impedance characteristics of a cable under different frequencies are measured, frequency domain data are converted into time domain data through inverse Fourier transform, and accurate positioning and evaluation of internal defects of the cable are achieved; the invention discloses a power cable multi-defect nondestructive testing method based on a broadband impedance spectrum. The method comprises the following steps: step 1, signal output and acquisition; the method comprises the steps that a broadband impedance spectrum tester is used for outputting a broadband sine wave voltage signal, frequency domain measurement data are collected, and the frequency domain measurement data are impedance data of a cable under different frequencies; 2, carrying out time-frequency conversion; converting the frequency domain measurement data into time domain data through inverse Fourier transform, generating a time-amplitude curve, and analyzing the electrical characteristics of the cable; 3, establishing a defect identification model; analyzing the electrical characteristics of the cable at different frequencies by using the transmission line model, and evaluating the state of the cable; step 4, defect positioning and evaluation; and 5, displaying and analyzing a result.

The invention belongs to the technical field of power equipment state monitoring, and discloses a cable branch box operation state intelligent evaluation system based on multi-sensor fusion, which comprises a state acquisition module used for acquiring a partial discharge signal, a voltage fluctuation signal, a terminal temperature signal and a terminal contact resistance signal of a cable branch box in an operation process, constructing a multi-source operation state parameter set of the cable branch box through time synchronization and physical quantity normalization processing; the mutual coupling analysis module is used for performing transient correlation deduction on the partial discharge signal and the corresponding voltage fluctuation signal based on the multi-source operation state parameter set to obtain a partial discharge-voltage coupling amount; when the partial discharge-voltage coupling amount exceeds a preset partial discharge-voltage coupling amount threshold value, determining that partial discharge abnormity caused by insulation degradation exists in the cable branch box; comprehensive and accurate evaluation of the operation state of the cable branch box is realized, and reliable support is provided for safe operation and maintenance of equipment.

The invention provides a mutual inductor loop resistance dynamic compensation correction method and device, and relates to the technical field of circuit testing, and the method comprises the steps: constructing a structural feature tensor and an environmental interference tensor according to the structural parameter information and environmental parameters of a primary winding and a secondary winding; training a dynamic compensation model based on the structural feature tensor, the environmental interference tensor and historical loop resistance test data; injecting a set direct current into the primary winding, obtaining an initial voltage signal sequence at two ends of the primary winding, and constructing a test state tensor in combination with the current loop current and the real-time environment parameters; inputting the test state tensor into the dynamic compensation model, and outputting a non-target resistance compensation value at the current moment; and based on the non-target resistance compensation value, correcting an initial loop resistance value obtained by calculating the initial voltage signal sequence to obtain a compensation resistance value of the target mutual inductor loop. According to the invention, the accuracy of mutual inductance loop resistance testing can be improved.

The invention discloses an on-line qualitative detection method for partial discharge of power equipment, which comprises a detection system and detection steps, and also comprises the following steps: the detection system comprises a high-frequency partial discharge detector for detecting a high-frequency current transformer; the ultrahigh frequency detection system is used for detecting electromagnetic wave radiation which is generated by partial discharge and has extremely short duration time; the ultrasonic detection system is used for detecting sound waves and ultrasonic signals generated along with energy release when partial discharge occurs; a transient ground voltage method detection system is used for live-line detection of equipment such as a medium-voltage switch cabinet. According to the online qualitative detection method for the partial discharge of the power equipment, different detected equipment and different detection methods are adopted to perform online detection on the partial discharge of the equipment, so that the early partial discharge phenomenon of the power equipment can be found in time, the long-term discharge monitoring data of the power equipment can be stored, and the overall detection effect is improved.

The invention provides an intelligent battery sorting method integrating impedance characteristics and deep learning. The method comprises the following steps: acquiring battery impedance data through an electrochemical workstation, drawing an electrochemical impedance spectroscopy (EIS), and extracting impedance characteristics of a medium-frequency region; a 25-dimensional impedance coupling feature space is innovatively constructed, a dual-network differentiated feature selection strategy (IC-GRU) is adopted, a main network selects 12 features with the highest correlation, a boundary expert network selects 10 features with the highest correlation and additionally constructs 5 boundary sensitive features, and finally, the main network selects 12 features with the highest correlation. And establishing an impedance coupling sensing gating circulation unit network to realize accurate prediction of the state of health (SOH). And performing four-stage sorting on the SOH result predicted by the IC-GRU through a random forest algorithm (RF). According to the method, more accurate SOH prediction is realized through deep learning guided by a physical mechanism, the battery pack health state sorting precision and consistency are improved, and an intelligent solution is provided for new energy automobile battery life management.

The invention provides a grid-connected inverter impedance detection method based on an L-shaped filter, and belongs to the technical field of grid-connected inverter impedance detection. A multi-frequency-point disturbance signal is injected into a preset grid-connected inverter working point, time domain data of inverter side current and common coupling point voltage are collected, fast Fourier transform analysis is carried out on the collected data, amplitude and phase information corresponding to each injection frequency point is extracted, and a frequency domain feature vector matrix is established; and establishing a frequency compensation matrix model to compensate and correct high-frequency band measurement data based on a frequency characteristic attenuation vector, calculating to obtain optimal estimated values of power grid impedance and grid-connected inverter output impedance, performing error analysis and precision verification on an impedance detection result, and outputting a verified impedance parameter value. The technical problem of insufficient power grid impedance detection precision caused by high-frequency band attenuation of the L-shaped filter is solved.

The invention relates to a photovoltaic monocrystalline silicon material resistivity uniformity evaluation method, and belongs to the technical field of photovoltaic material detection. The method comprises the following steps: evaluating all-form resistivity and doping uniformity of a photovoltaic single crystal silicon rod, a single crystal silicon wafer and a single crystal silicon square wafer; carrying out standardized point distribution on the monocrystalline silicon wafer by using a concentric circular ring and a small circle, and calculating in-plane uniformity by using a triple integral derivation equation; the monocrystalline silicon square pieces are distributed in the form of grid small squares, and in-plane uniformity is calculated by means of a triple integral derivation equation; and for the axial direction of the silicon rod, the uniformity is quantified by utilizing range and variance models through the resistivity of the head, middle and tail wafers. Meanwhile, a continuous grid is generated through interpolation, and a 3D color mapping curved surface diagram with plane projection is drawn to visually present distribution. According to axial and in-plane uniformity results, silicon wafers are classified and graded, the doping uniformity of monocrystalline silicon is accurately reflected, and a support is provided for quality control, process optimization and silicon wafer sorting of photovoltaic monocrystalline silicon.

The invention relates to the technical field of resistance test equipment, in particular to a portable loop resistance tester, which comprises a test and acquisition module used for acquiring current and voltage signal data of a tested product, analyzing a loop contact state and calculating a loop resistance value and impedance characteristic parameters; the control and output module is used for performing high-precision constant-current output and self-adaptive adjustment; the interaction and printing module is used for receiving a user operation instruction and displaying current and voltage signal data and a resistance value of a tested product, and meanwhile, printing is performed through a built-in thermal printer according to the user instruction; the power supply module is used for stably supplying power to equipment; and the intelligent diagnosis module is in butt joint with the cloud case library, automatically diagnoses related defect types influencing the loop resistance test, and generates a health assessment report. Therefore, the problems of small current output, insufficient sampling precision, single operation mode and the like in the prior art are solved.

The invention relates to the technical field of power cable fault detection and positioning, in particular to a middle and high voltage cable insulation defect live detection and positioning method, which comprises the following steps: step 1, injecting a composite detection signal into a cable conductor through a signal injection device; 2, arranging signal acquisition devices at a plurality of preset point positions of the cable; step 3, carrying out adaptive processing on the acquired response signal; step 4, extracting insulation defect features from the response signals after adaptive processing; step 5, based on the extracted insulation defect features, classifying defect types by using a pattern recognition algorithm, and calculating defect positions based on a signal propagation time difference principle; and 6, outputting a defect identification and positioning result to a monitoring system, verifying, and if the deviation between the positioning result and historical data exceeds a threshold value, re-executing the steps 1 to 5. By combining a multi-point synchronous measurement technology and a precise space-time analysis method, the position where the defect occurs can be positioned more accurately.

The invention relates to the technical field of electric vehicle charging, in particular to a charging gun short-circuit fault detection method, and aims to solve the problems that in the prior art, charging gun short-circuit fault detection mainly depends on two technical paths of current threshold triggering and single parameter monitoring, when it is detected that the current exceeds a preset value, a circuit is cut off, detection hysteresis exists, and the detection time is shortened. And pre-judgment cannot be carried out before short circuit occurs, so that the equipment is damaged before the protection action is executed. According to the method, the digital twinning pre-diagnosis model is constructed by fusing multiple physical quantity data, early warning and graded protection of the short-circuit fault of the charging gun are realized by combining multi-dimensional feature fusion and a dynamic risk assessment mechanism, and the method has the advantages of improving the detection timeliness, reducing the misjudgment and missed judgment rate and enhancing the environmental adaptability.

The invention belongs to the field of power transmission line parameter measurement, and discloses a live-line testing device and method for mutual inductance line parameters and zero-sequence impedance parameters. The device comprises a double-circuit line simulation module, a pilot frequency excitation module, a power frequency simulation module, a synchronous acquisition module and a signal processing module. The isolation transformer simulates a double-circuit line, the pilot-frequency power supply provides pilot-frequency excitation signals, the measurement unit realizes synchronous acquisition, and the signal processing module performs anti-interference and amplification processing. The method comprises the steps of line simulation wiring, synchronous time synchronization, pilot frequency signal acquisition, parameter calculation and error verification, and pilot frequency parameters are converted into power frequency parameters by using a frequency conversion formula. According to the invention, power frequency interference can be effectively suppressed in a charged environment, high-precision measurement of zero-sequence impedance and mutual inductance parameters of a mutual inductance line is realized by using pilot frequency excitation and Beidou synchronization technologies, the measurement error is remarkably reduced, the safety and reliability are remarkably improved, and powerful technical support is provided for safe and stable operation of a power system.

The invention belongs to the technical field of quality detection, and discloses an electrical automation quality detection method and system. The method comprises the steps of collecting original voltage and current signals of a PCC point of a power grid and performing FFT to obtain a background harmonic frequency set and a background harmonic amplitude set; generating an initial frequency grid based on a preset target frequency band, and generating a sparse frequency grid in combination with the background harmonic waves; calculating the estimated signal-to-noise ratio of each candidate frequency, performing ascending sorting to obtain an injection sequence, injecting sinusoidal signals, collecting PCC point voltage response and total current, and calculating a frequency impedance data pair; performing rational function fitting based on the frequency impedance data to obtain a broadband impedance curve; analyzing the curve, extracting quality characteristic parameters, and performing quality judgment according to the parameters; according to the method, the technical problem that the grid-connected stability quality of a single new energy converter cannot be quickly and automatically qualified in a production line offline detection scene in the prior art is effectively solved.

The invention specifically relates to a standardized fuse fault monitoring and diagnosis system, and relates to the technical field of power system protection equipment monitoring. A signal processing and impedance spectrum calculation module; an intelligent diagnosis and state evaluation module; and a benchmark management and personalized tracking module. According to the invention, controllable micro test signals are actively injected to obtain frequency domain impedance fingerprints, and accurate capture of microscopic degradation is realized; non-intrusive coupling and signal injection are adopted, the topology of a main loop does not need to be changed, the inherent protection characteristic of the fuse is guaranteed, and power frequency interference can be penetrated; the recognition amount of budding faults such as contact oxidation and melt corrosion is improved in advance, and power failure accidents caused by fault expansion are avoided.

The invention relates to the technical field of mobile energy storage charging piles, and discloses a fault detection method and system for a mobile energy storage charging pile, and the method comprises the steps: collecting a voltage and current original sequence during an operation period, and executing the Kalman filtering to obtain a smooth electrical parameter; adaptively adjusting a process noise covariance matrix by using numerical dispersion to obtain a stable internal resistance value sequence; extracting a fluctuation trend and matching a working condition mode to filter periodic disturbance to obtain a pure internal resistance offset sequence; extracting a health degradation rate slope, establishing a dynamic health reference range by using kernel density estimation, and judging an abnormal migration event according to the dynamic health reference range; the offset severity is calculated through severity probability weighted fusion, the fault early warning level is obtained, and an event trigger counter reset mechanism is driven to judge the overall health state. The method can solve the problem of low fault detection accuracy in the prior art.

The invention discloses a high-precision transformer fault detection method and system, relates to the technical field of transformer detection, is used for solving the problems of insensitive fault characterization and delayed diagnosis under a light load condition, and judges whether to enter a load judgment mechanism or not by acquiring input side access voltage information and counting low-load accumulated duration. When entering a load discrimination mechanism, detecting the start-stop behavior of a load branch and the temperature rise trend of a winding, calculating a light load index, identifying a light load state, carrying out region division on an iron core, collecting magnetic flux density data, and calculating iron loss balance characteristics aiming at iron loss deviation which is easy to occur under a light load condition; the insulation degradation coefficient is calculated by fusing the oil temperature peak value and the dielectric loss factor, and the abnormal index is generated with the iron loss balance characteristic, so that the early warning of the early hidden fault of the transformer can be realized in a light load scene in which the traditional temperature rise and current indexes are insensitive, and the operation reliability and maintenance efficiency of the transformer in a power distribution system are improved.

The invention relates to the technical field of electrical equipment insulation performance detection, in particular to an insulating oil dielectric loss test system based on temperature compensation, which comprises a temperature acquisition module for acquiring insulating oil temperature data and environment temperature data; the dielectric loss measurement module measures a dielectric loss value and a dielectric loss angle through a self-adaptive anti-interference algorithm, and synchronously records voltage and frequency; the intelligent compensation module matches temperature characteristic parameters for different temperature intervals, and compensates a dielectric loss detection value through a segmented temperature compensation model; the state analysis module judges the aging degree and state of the insulating oil according to the compensated dielectric loss value and acid value, generates a multi-stage early warning signal and a diagnosis report by combining the breakdown voltage and the moisture content, and dynamically adjusts the test frequency according to the oil sample type and the operating age limit; and the cloud management platform stores historical data and compensation parameters, establishes a performance degradation model, analyzes a dielectric loss trend and generates maintenance suggestions. Therefore, the problems of insufficient test precision, poor environmental adaptability and the like in the prior art are solved.

A calibration unit comprises a first port which is arranged for being connected to a measurement device; a calibration module comprising at least three different calibration standards for calibrating the measurement device; and a switching module configured to connect the first port with one of the at least three different calibration standards of the calibration module. A daisy chain port is arranged for being connected to a further calibration unit, to an external power meter, or to a device-under-test, DUT. The first port is connectable to the daisy chain port. An internal power meter is arranged within a housing of the calibration unit. The first port is connectable to the internal power meter; or an internal impedance tuner. The first port is connectable to the internal impedance tuner.

A system comprises a signal generator circuit configured to generate a modulated radio frequency (RF) signal based on a predefined waveform. An output signal path is connected to the signal generator circuit and is connectable to a device under test. A first signal path is connected to the signal generator circuit so as to receive a reference signal corresponding to the modulated RF signal. A second signal path is connectable to the device under test so as to receive a measurement signal from the device under test. A analysis signal path is connected to the first and second signal paths for merging the reference signal and the measurement signal into an analysis signal. A signal analysis circuit is configured to separate the reference signal from the measurement signal for analyzing the analysis signal based on the predefined waveform.

The invention relates to the technical field of motor fault diagnosis, and discloses a multi-degree-of-freedom resonant excitation motor dynamic vibration test system and a test method, the system injects a specific harmonic current into a motor through closed-loop control and calculation and a high-bandwidth harmonic injection driver, so that the actual vibration of the tested motor tracks a preset target vibration profile in real time. In the testing process, the cross-spectral density of multi-point vibration signals is analyzed, and a transmission path and a collection area of vibration energy in a motor structure are calculated; and meanwhile, the electromagnetic impedance and the mechanical impedance of the motor are identified and decoupled on line by superposing a broadband disturbance signal in the driving current. In combination with energy flow analysis and an impedance decoupling result, the method can accurately position a vibration abnormal position, clearly causes whether a fault source is from mechanical structure characteristic change or electromagnetic part performance change from a physical level, and realizes deep and accurate diagnosis of the dynamic characteristics of the motor.