76 results about "Fourier analysis" patented technology

The invention relates to the technical field of ground resistance detection, in particular to a single-core cable ground resistance detection method capable of resisting strong power frequency interference. High-frequency signals are injected in a non-contact mode through a coupling type capacitor clamp, background voltage and current signals are collected firstly, and injection frequency far away from power frequency and harmonic waves is selected through Fourier analysis; cancelling background noise by adopting a normalized least mean square adaptive filter to generate an enhanced signal; the signal is down-converted to a base band through digital quadrature demodulation, a Kalman filter estimates the amplitude and the phase in real time, and the state and noise parameters are periodically calibrated through a compressed sensing algorithm; and finally, loop impedance is calculated according to the voltage and current amplitudes and the phase difference to obtain grounding resistance. The method has the advantages of being non-contact, high in safety, strong in anti-interference capability, high in measurement precision and the like, and is suitable for monitoring the grounding state of the cable in a complex electromagnetic environment.

The invention discloses a six-winding high-voltage variable-frequency speed regulation control method and system, and belongs to the technical field of high-voltage variable-frequency speed regulation, and the method comprises the steps: building an electric-thermal-magnetic coupled six-dimensional nonlinear system model through collecting the structural parameters, thermosensitive data and an initial state of a motor; establishing a frequency domain regulation and control matrix among the six windings in combination with the operation condition and the load type; predicting a future disturbance power trend by using a weighted short-time Fourier analysis method, dynamically correcting the reference current of each winding, and generating six groups of PWM control signals; when the performance of the winding is degraded, fault-tolerant topology reconstruction and driving task redistribution are executed; periodically reconstructing a control matrix through a thermoelectric feedback mechanism, and executing parameter adaptive optimization according to a current balance coefficient and hot redundancy distribution; according to the method, high-precision current coordination control, frequency domain energy decoupling and winding thermal load balancing can be realized, and the speed regulation response speed, the stability and the fault-tolerant capability of the system are remarkably improved.

This application relates to the field of electrical technologies, and provides a full even harmonic digital demodulation method based on full-phase analysis for a magnetic modulator. According to the full even harmonic digital demodulation method based on full-phase analysis for a magnetic modulator, standard voltage timing data output by the magnetic modulator is obtained when a DC calibration current with a set amplitude is fed into the magnetic modulator during calibration of the magnetic modulator; an output voltage sequence from full-phase Fourier analysis is established based on the standard voltage sequence data, and the output voltage sequence is preprocessed; comprehensive analysis is performed on the preprocessed output voltage sequence from full-phase Fourier analysis to obtain all standard even harmonic signals and current conversion coefficients.

The present invention discloses a gear meshing noise evaluation method based on a gear transmission error curve, specifically comprising the following steps: Step 1: Acquisition of tooth surface waviness based on the gear measurement center; Step 2: Synthesis of the gear full tooth surface waviness curve; Step 3: Calculation of gear transmission error based on the envelope; Step 4: Fourier analysis of the gear transmission error curve based on sine fitting; Step 5: Calculation of the order spectrum; Step 6: Analysis of abnormal orders. The gear transmission error curve can be decomposed into harmonic components of different frequencies through sine fitting Fourier analysis, with each harmonic corresponding to a specific order in the gear error. Abnormal orders can excite vibrations of specific frequencies. Identifying and eliminating abnormal orders is a key step in analyzing gear noise problems.

The invention relates to the technical field of power grid safety evaluation, in particular to a power system short-circuit parameter prediction method, system and device based on time-space relevance and a storage medium. A multi-dimensional state vector including a node voltage vector, a branch current vector, a short-circuit impedance matrix, spatial position information and a time feature vector is constructed, and a space-time correlation feature vector including a time-dimensional feature, a spatial-dimensional feature, a space-time coupling feature and a state feature is extracted. Wavelet transform, Fourier analysis and graph theory analysis are adopted to identify a parameter change rule and a propagation effect. A multi-level prediction model of a statistical prediction layer, a deep learning layer and a fusion layer is constructed, and comprehensive description of dynamic characteristics of short-circuit parameters is realized through spatio-temporal feature fusion. A staged training strategy is adopted, and comprises the steps of establishing a basic model through offline training, updating parameters in real time through online learning, and quantifying uncertainty through a probability prediction framework. And a prediction correction mechanism and a reliability evaluation system are established, and a complete prediction-evaluation-correction closed loop is formed.

The invention relates to the technical field of ship navigation behavior prediction, and discloses a ship navigation behavior prediction method and system based on interpretable artificial intelligence. Comprising the following steps: acquiring ship AIS historical data and historical marine environment data in a target sea area; based on a time scale and a space scale, fusing the ship AIS historical data and the historical marine environment data, and constructing a spatio-temporal data set; performing feature decoupling on a static variable and a time-varying variable of the spatio-temporal data set, and determining historical input data, known future input data and static input data; an interpretable space-time fusion neural network model is constructed based on a dynamic gating residual neural network, a space-time characteristic variable selection network, a Fourier analysis gating neural unit and an interpretable multi-head attention mechanism so as to accurately predict ship navigation behaviors such as a ship trajectory, an over-the-ground navigational speed and an over-the-ground course. And a navigation behavior influence factor weight visualization result is output, and the method has interpretability.

The invention discloses a colon adenoma identification method and device based on Mueller matrix polarization measurement and regularization, a storage medium and electronic equipment. The method comprises the following steps: acquiring a polarization image corresponding to a fresh medical sample containing colon adenoma and normal tissue through a light polarization system, and preprocessing the polarization image; fourier analysis is carried out on a detection signal in the light polarization system to obtain a Mueller matrix, and a Lu-Chipman polarization decomposition algorithm is used for carrying out polarization decomposition on the Mueller matrix to obtain three polarization decomposition parameters; obtaining polarization data of a plurality of channels based on the Mueller matrix, and constructing a sample set based on the polarization data; constructing a target function based on the projection function and the sample set, solving the target function to obtain an analytic solution of the optimal projection direction, and calculating a characteristic value based on the analytic solution of the optimal projection direction; and classifying the polarization images corresponding to the fresh medical samples of the colon adenoma and the normal tissue based on the feature values to obtain a classification result. The lesion recognition rate can be improved.

The invention relates to the technical field of geological disaster assessment, in particular to a seafloor landslide mass stability assessment method based on multi-source geophysical data, which comprises the following steps: S1, acquiring multi-beam sounding, side-scan sonar, seafloor seismograph and sediment columnar sample data, completing space-time registration, and performing equivalent density conversion on acoustic wave impedance and shear wave velocity to obtain an acoustic wave impedance and shear wave velocity; constructing a three-dimensional grid model; s2, based on the three-dimensional grid model, calculating a curvature mutation index by adopting sliding window Fourier analysis, calculating a pressure gradient in combination with pore water pressure data, and generating a characteristic parameter matrix composed of density, curvature and pressure gradient; and S3, based on the characteristic parameter matrix, calculating shear strain energy and gravitational potential energy superposition field intensity, and generating a landslide mass stability map taking the instability probability as an index. According to the invention, a visual three-dimensional landslide mass stability map is constructed, and high-precision identification and three-dimensional early warning of submarine landslide risks are realized.

The application provides a method and device for graph data processing, and relates to the technical field of artificial intelligence, and the method comprises: a method for graph data processing, which comprises the following steps: acquiring graph data, extracting the basic structure features of the graph data through a static topology path, adaptively screening the key neighbor features in the graph data based on an attention mechanism and in combination with the basic structure features through a dynamic path, establishing long-distance semantic association between nodes through topology-aware coding based on the basic structure features and the key neighbor features through a linear graph transformer with O ( n ) of linear complexity, and establishing long-distance semantic association between nodes through topology-aware coding; performing frequency domain projection on the node features to generate frequency domain features, explicitly extracting and enhancing the periodic discriminant components in the frequency domain features through a Fourier analysis network to generate graph neural network data. Thus, the graph representation learning capability of the graph neural network is effectively improved.

The present application relates to the technical field of image processing, and more particularly to a self-adaptive periodic background elimination method based on Fourier analysis, comprising the following steps: step one, image input; step two, horizontal and vertical frequency division; step three, respectively performing inverse color, enhancement and normalization preprocessing operations on the horizontal frequency graph and the vertical frequency graph; step four, performing Fourier transform on the image of step three, and performing Fourier transform on the horizontal frequency preprocessed graph and the vertical frequency preprocessed graph; step five, obtaining high-amplitude phase difference of the image of step four; step six, obtaining horizontal and vertical phases; step seven, high-response point elimination; step eight, inverse Fourier transform, performing inverse Fourier transform on the separated frequency response graph and phase response graph in step seven; and step nine, feature recognition; the algorithm of the present application can automatically identify the periodic grid background on the liquid crystal panel, automatically eliminate a number of frequency parts with the highest response in the horizontal and vertical directions, and the remaining non-periodic features after elimination are defects.

This invention discloses a specific harmonic cancellation pulse width modulation method suitable for digital power amplifiers. It involves fitting a periodic signal f(t) to obtain an approximate function g(t) and performing Fourier analysis to derive the Fourier coefficients b of the current. n Wherein, the Fourier coefficient b n With the switching angle sequence α q 'As a parameter; for the switching angle sequence α q 'Optimization is performed to obtain the optimized switching angle sequence α' q According to α q The corresponding circuit is controlled by pulse width modulation to output a voltage waveform with specific harmonics filtered out. This invention obtains a specific switching angle sequence by establishing and solving a system of nonlinear equations. The output voltage waveform with specific harmonics filtered out is then modulated based on this switching angle sequence. This method can generate the desired frequency domain component and eliminate unwanted harmonics. It is also applicable to the design of multiple H-bridge units. At the same switching frequency, this method can output higher-order harmonics than other modulation methods, thus reducing switching losses. Furthermore, its excellent harmonic suppression performance saves hardware costs.

[Problem] To provide a polishing end point detection device and method, and a CMP device capable of accurately detecting a polishing end point when polishing a workpiece having a thin film thickness. [Solution] A polishing end point detection device (70) is provided with: a measurement unit (71) that, during polishing of a workpiece (W), radiates measurement light onto the workpiece (W), disperses reflected light from the workpiece (W), and acquires a spectral waveform indicating the relationship between the wavelength and reflectance of the reflected light; the reflectivity is the ratio of the intensity of the reflected light to the reference intensity of each wavelength component obtained in advance; and a detection unit (72) that calculates the film thickness of the thermal oxide film by applying Fourier analysis to the spectral waveform. The reference intensity is calculated by bringing a sample workpiece having substantially the same reflectance characteristic as a substrate of a workpiece (W) into contact with a polishing pad (5) in a state where a CMP slurry is interposed between the polishing pad (5) and the sample workpiece, and irradiating the sample workpiece with measurement light through an observation window (80) of the polishing pad (5) by a measurement unit (71). And the reflected light from the sample workpiece is split.

The invention provides a chronic lumbago surface electromyogram discrimination method and system based on a Fourier analysis neural network and a storage medium, and the method comprises the steps: firstly obtaining a data set which comprises a plurality of surface electromyogram signals and corresponding real labels; preprocessing the surface electromyogram signal to obtain a preprocessed surface electromyogram signal; inputting the preprocessed surface electromyogram signals into a constructed neural network based on Fourier analysis to obtain a prediction label of each surface electromyogram signal; constructing a loss function according to the real label and the predicted label, and training the neural network based on Fourier analysis to obtain a trained neural network based on Fourier analysis; and inputting a surface electromyogram signal to be detected into the trained neural network based on Fourier analysis to obtain a corresponding prediction label. According to the method, the neural network based on Fourier analysis is constructed and trained, the potential periodic features with discrimination are extracted, automatic discrimination of the abnormal modes in the chronic lumbago surface electromyogram signals is achieved, and therefore discrimination with higher robustness, higher generalization and higher efficiency is achieved.

The invention discloses a method and a system for online monitoring harmonic signal abnormity of a high-voltage cable. The method comprises the following steps: respectively arranging harmonic sensors in grounding wire preset areas at two ends of a tested high-voltage cable; a harmonic signal output by the harmonic sensor is collected through a signal collection module based on a sampling interval, and the harmonic signal is transmitted to a data analysis processing module through a data transmission module; performing windowed Fourier analysis on the harmonic signal through the data analysis processing module to obtain harmonic current data in the harmonic signal; calculating a key quantitative index of the harmonic signal based on the harmonic current data; and analyzing the harmonic abnormal degree of the tested high-voltage cable based on the key quantitative index, and evaluating the deterioration degree of the tested high-voltage cable based on an analysis result. According to the invention, through on-line measurement, the harmonic signal detection result is analyzed in real time according to the on-site actual situation.

This invention discloses a system and method for psychotherapy that integrates virtual reality scenes, belonging to the interdisciplinary field of psychotherapy and virtual reality. It addresses the problems of fixed scenes, delayed adjustment, weak interactivity, and lack of cultural adaptability in traditional psychotherapy. The method includes using non-contact biosensors to capture facial blood oxygen fluctuations, combining this with a hemodynamic model to remove artifacts, and then quantifying these fluctuations into emotional energy values ​​based on an individual emotional sample set and an incremental learning algorithm to generate scene seeds containing parameters such as color temperature. A virtual physics engine is then driven to reconstruct elements such as light and shadow, and fluids, forming a physically-level dynamic scene. Inertial sensors capture user movements and convert them into virtual pressure gradients, constructing a coupled feedback loop between movement and scene. Psychological trends are predicted through hierarchical Fourier analysis of the seed sequence. This invention achieves real-time adaptation and proactive intervention between psychological states and virtual scenes, enhancing user immersion and cultural and emotional resonance, and improving the accuracy and effectiveness of psychotherapy.

The invention belongs to the technical field of electric quantity prediction, and provides a hierarchical decoupling-based modularized long-time sequence user electricity consumption prediction method, which comprises the following steps of S1, acquiring user electricity consumption data; s2, a modular time series prediction framework based on a'trend-local change-multi-scale period 'decoupling concept; s3, designing three efficient sub-modules; according to the invention, a modularized time series prediction framework of a'trend-local change-multi-scale period 'decoupling concept is constructed; designing a trend module fusing reversible normalization and a trend feature processor, a local change module introducing a local importance pooling mechanism, and a period module combining a Fourier analysis network and a frequency mapping network; the problems that a traditional time sequence prediction model is high in calculation complexity and insufficient in information extraction capacity in long sequence prediction are effectively solved, and in addition, due to introduction of the lightweight fusion network, the feature integration efficiency and the accuracy of a prediction result are further improved.

The invention discloses an MMC impedance prediction method and system of a flexible interconnection system, equipment, a medium and a product, and the method comprises the steps: injecting positive and negative sequence voltage disturbances with different voltage frequencies into a pre-constructed MMC simulation model of a network construction type flexible interconnection system under a plurality of different working condition variables; the method comprises the steps of obtaining output voltage and current time-domain signals of an MMC under disturbance of multiple different voltage frequencies, obtaining output voltage and current frequency-domain data through fast Fourier analysis, determining equivalent impedance of the MMC of the network-forming flexible interconnection system at each frequency according to the output voltage and current frequency-domain data, and determining the equivalent impedance of the MMC of the network-forming flexible interconnection system according to the equivalent impedance. And taking the equivalent impedance and the working condition variable corresponding to each frequency as mapping samples, constructing a training data set, and training the initial fuzzy neural network, thereby enabling the trained MMC equivalent impedance prediction model to output an equivalent impedance prediction value of the MMC at the current calculation moment. Therefore, the impedance characteristics of the network-forming type MMC can be accurately represented in a wide working range.

A quantum computing system includes a classical computer coupled in combination with a quantum computer, wherein the quantum computing system is configurable to execute program instructions to process input data to generate corresponding output data. The program instructions include one or more arithmetic functions to be executed using the quantum computer. The quantum computing system is configured to apply a transformation to transform the one or more arithmetic functions into a series of Fourier components that are executable using the quantum computer by using one or more quantum circuits utilizing rotation gates acting on qubits representing the Fourier components, and to process outputs from the one or more quantum circuits to generate results of the one or more arithmetic functions, wherein the results are used to generate the corresponding output data.

The invention provides a high-stability magnetic modulator excitation demodulation method without correcting a winding, and relates to the technical field of precise electromagnetic measurement and signal processing. A low-frequency current signal is equivalently injected into the magnetic modulator by adjusting the number-of-turns difference of excitation windings of two magnetic cores in the double-magnetic-core differential magnetic modulator and utilizing a microcontroller to control positive and negative duty ratio superposition low-frequency components of a square wave excitation source; by combining digital acquisition and Fourier analysis, a low-frequency voltage sequence and a second harmonic sequence are constructed, and a low-frequency proportionality coefficient and an actual direct-current proportionality coefficient are calculated, so that on-line calibration of a direct-current measured value is realized. Measurement errors caused by time and environment changes can be eliminated without additionally arranging a correction winding or a correction power supply, and the long-term measurement precision and stability of the magnetic modulator are remarkably improved.

The invention discloses a high-frequency suppression method, device, equipment, medium and product for a multi-terminal direct-current transmission system, and the method comprises the steps: constructing a time-delay-considered MMC high-frequency impedance model based on the multi-terminal direct-current transmission system; collecting a harmonic current signal of each converter station in the multi-terminal direct current delivery system in real time; performing Fourier analysis on the harmonic current signal of each converter station to obtain an oscillation amplitude and an oscillation frequency of the harmonic current signal of each converter station; taking the converter station with the maximum oscillation amplitude in the converter stations as a dominant converter station; and in combination with the MMC high-frequency impedance model, correcting the center frequency of an additional filter in a voltage feed-forward link by using the oscillation frequency of the dominant converter station. According to the embodiment of the invention, the high-frequency suppression effect can be improved.

This invention discloses a two-dimensional contour morphology representation method based on current-round Fourier transform, belonging to the field of geometric morphometrics. It solves the technical problems of contour rotation and misalignment caused by elliptical Fourier descriptors. The key point of its technical solution is to complete the reconstruction and normalization of contour shape through current-round Fourier descriptors, achieving contour shape description effect comparable to elliptical Fourier analysis and contour normalization (alignment) effect comparable to the Pu-style method. It can also avoid the graphic pseudo-rotation problem caused by standardization during the extraction of elliptical Fourier descriptors, without the need for prior standardization of contours using other methods, and quantitatively describes contour features based on current-round Fourier descriptors.

The invention discloses a bus bunching prediction method and system based on a time-aware network. The method comprises the following steps: preprocessing bus arrival data, fusing multi-source spatial-temporal characteristics, introducing time period codes, and processing abnormal and missing values; targeted denoising is performed on data with different characteristics based on Fourier analysis, so that the data quality is improved; a time perception neural network is established, local features and long-term dependence are captured through a CNN-LSTM architecture, a time decay factor mechanism is introduced, dynamic modeling of a time sequence information importance decay process is realized, and a long-term rule of data and short-term disturbance after time calibration are effectively integrated; and a dual attention mechanism of time dimension and feature dimension is fused, key features are extracted and integrated, and multi-step prediction of bus bunching is realized. According to the method, the non-linear relation and the space-time dynamic rule of the bus data can be fully captured, and the problem of unequal intervals in a bunching time sequence is effectively solved.

In some embodiments, a computer-implemented method of measuring heart rate analytics using raw photoplethysmography (PPG) data is provided. A computing system determines a plurality of frequency peaks in the raw PPG data using a Fourier analysis. The computing system determines a plurality of selected frequency peaks from the plurality of frequency peaks. For each selected frequency peak of the plurality of selected frequency peaks, the computing system creates filtered PPG data by applying a frequency of the selected frequency peak as a high-pass filter to the raw PPG data; detects diastole peaks and systole valleys in the filtered PPG data; and performs one or more pulse quality checks on the detected diastole peaks and systole valleys. The computing system uses diastole peaks and systole valleys associated with a lowest selected frequency peak that passed the pulse quality checks to determine a heart rate analytic measurement.

The invention discloses a voltage harmonic suppression method and device for offshore wind power through a hybrid commutation sending-out system, terminal equipment and a storage medium, and belongs to the field of offshore wind power, and the method comprises the steps: collecting a three-phase line voltage waveform of a diode uncontrolled rectification unit in the hybrid commutation sending-out system, carrying out the Fourier analysis, obtaining a line voltage fundamental component, and carrying out the voltage harmonic suppression of the three-phase line voltage waveform; the total harmonic distortion amount is calculated; whether the total harmonic distortion amount exceeds a preset threshold value or not is judged, if yes, the voltage at a PCC point in the hybrid commutation sending-out system is measured, and PCC voltage is obtained through measurement; and according to the PCC voltage, controlling an auxiliary converter in the hybrid commutation sending-out system to inject harmonic current into a diode uncontrolled rectification unit so as to eliminate the harmonic component of the PCC point voltage in the hybrid commutation sending-out system, and if not, maintaining the current operation state of the auxiliary converter unchanged. According to the invention, the problem of voltage harmonic waves existing in the hybrid commutation sending-out system in the prior art can be solved.

The present application relates to a distributed power rich area cable insulation partial aging online positioning method and system, the positioning method comprising: establishing a cable distributed parameter model; superimposing f 1±1kHz and f 2±1kHz near wideband signals, the system continuously collects outlet three-phase voltage and current during operation and obtains amplitude-frequency characteristics through Fourier analysis, and the amplitude-frequency characteristics are divided by the amplitude of each phase voltage and current at each frequency point to obtain the wideband impedance spectrum of each phase; the second series resonance frequency measured in the current operating state f 2 is substituted into the cable insulation partial aging distance formula to obtain the cable insulation partial aging distance. The positioning system comprises a first calculation module, a second calculation module and a positioning module; the first calculation module determines the mathematical model of the power station back-end cable and power grid system impedance; the second calculation module obtains the impedance formula of the mathematical model of the power station back-end cable and power grid system impedance after partial aging; and the positioning module determines the position of the partial aging defect of the measured cable. The present application can obtain accurate positioning of partial aging.

The invention provides a control method and device for a magnetic suspension bearing, a medium, a controller and a program product, and the method comprises the steps: collecting the displacement precision data of the magnetic suspension bearing when a magnetic suspension unit is shut down; fourier analysis is carried out on the collected displacement precision data to obtain a corresponding frequency spectrum; determining whether the rotor of the magnetic suspension bearing stops rotating or not according to the obtained frequency spectrum; and if it is determined that the rotor of the magnetic suspension bearing stops rotating, floating stopping operation is executed. According to the scheme provided by the invention, the rotor can stop floating in time after shutdown.

The application belongs to the technical field of laser radar, and discloses a laser radar system and a velocity measurement method based on an unequal-arm interferometer, which comprises a laser, a light splitting module, an optical amplification module, a transmitting light path, a receiving light path, a filtering module, an unequal-arm interferometer, two-way detection modules and a main control module; the main control module is used for controlling the system timing, collecting first to fourth electric signals for data processing, calculating a first phase according to the first and second electric signals, calculating a second phase according to the third and fourth electric signals, and finally obtaining the velocity information of the target according to the difference between the first and second phases. Compared with the prior art, the application utilizes the unequal-arm interferometer to make the echo signal delay self-interference, can obtain the Doppler shift information of the target, and thus obtains the velocity of the target. The scheme does not need to transmit double-pulse signals, does not need to perform coherent detection and Fourier analysis, or sweep the echo signal, and thus reduces the complexity of the system.

The present invention provides an evaluation method capable of objectively evaluating the average visual perception of a subject when looking through an eyeglass lens to be evaluated for a relatively long period of time, the time-dependent change in visual perception, and the visual perception when looking with both eyes, and provides a design method, and provides a calculation method for calculating the visual perception characteristics of a subject when looking at an object through a lens. The subject is made to induce brain activity by having the subject look through an eyeglass lens to be evaluated at a visual stimulus that induces a change in periodic brain activity, and the current change caused by the brain activity is recorded in the form of a change in a magnetic field (magnetic flux density) in a time-dependent manner by using a brain magnetic wave recorder; one or more of the amplitude, the dioptric value, and the frequency phase, the frequency being the inverse of the period of the periodic brain activity, is calculated by fast Fourier analysis of the waveform, and the eyeglass lens to be evaluated and the visual perception characteristics of the subject are evaluated based on the magnitude of the amplitude or dioptric value obtained above or based on the slowness / fastness of the phase obtained above.

The invention discloses a motor optimal efficiency control method based on minimum loss online search, which aims at the over-loss problem of a servo drive system, establishes a novel full frequency domain harmonic loss model through double Fourier analysis, and can effectively reduce torque ripples by combining a minimum loss fusion algorithm and a golden section online search algorithm. The control precision is improved, dynamic optimization of energy efficiency and minimization of system loss can be achieved under different working conditions, and the system control efficiency and the overall energy efficiency performance are remarkably improved.

The embodiment of the invention relates to the technical field of carriage crack detection, and provides a railway freight carriage crack detection method, device and system, and the method comprises the steps: applying an electric signal to any two points of a to-be-detected railway freight carriage through employing an AC signal source, and measuring the conductivity between any two points; based on the conductance between any two points, determining a first electric signal feature after the electric signal passes through the railway freight carriage, the first electric signal feature being an electric signal feature obtained after the electric signal passes through the railway freight carriage; fourier analysis is carried out on the first electric signal feature and an original electric signal feature of the electric signal, whether the railway freight carriage has a crack or not is determined according to an analysis result, and the original electric signal feature is the electric signal feature obtained when the alternating current signal source sends the electric signal. Therefore, accurate and efficient detection of the crack of the railway freight carriage is realized.