Method and device for compiling random vibration fatigue load spectrum of high-speed motor train unit structure

Abstract

The invention provides a compilation method and device for a random vibration fatigue load spectrum of a high-speed motor train unit structure, and relates to the technical field of locomotives and vehicles. The method comprises the following steps: collecting a vibration acceleration signal and a stress signal, and preprocessing the vibration acceleration signal and the stress signal; obtaining a principal component load and a trend load according to the preprocessed vibration acceleration signal, determining a judgment threshold according to the principal component load, and extracting a plurality of signal components according to the judgment threshold; superposing the plurality of signal components and the trend load to obtain a high-precision acceleration time domain signal, and performing extrapolation reconstruction according to the high-precision acceleration time domain signal, the preprocessed stress signal and preset working condition information to obtain a multi-working condition acceleration vibration load time domain spectrum; and a high-precision full-life acceleration vibration load spectrum is obtained. The device executes the method. According to the method and the device provided by the embodiment of the invention, the high-speed motor train unit structure random vibration load spectrum with higher precision can be obtained.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of rolling stock technology, in particular to a method and device for compiling a random vibration fatigue load spectrum of a high-speed EMU structure. BACKGROUND

[0002] Key components of high-speed EMUs (including but not limited to traction transformers, traction converters, gearboxes, and suspension structures) are subjected to complex multi-source coupled vibration loads during operation. These loads have significant non-stationary characteristics, and their dynamic characteristics are mainly affected by three factors:

[0003] Operating conditions: including train speed (especially 400 km / h and above super high-speed conditions), track conditions (track irregularities, curve radii, slope angles, etc.).

[0004] Environmental factors: temperature gradient changes, humidity fluctuations, and lateral wind loads.

[0005] Structural coupling effects: dynamic interaction between the car body, bogie, and components.

[0006] However, the existing load spectrum compilation techniques have the following problems:

[0007] Insufficient data reliability: existing load spectrum compilation methods mainly rely on limited historical data or simulation results, and lack of measured vibration databases at speeds of 400 km / h and above. The data collection means is single, only stress or acceleration single-mode sensing is used, which is difficult to fully characterize the actual load conditions. In addition, the existing sample size is insufficient, which cannot effectively cover the extreme conditions under super high-speed operation, resulting in significant deviation in fatigue life assessment.

[0008] Insufficient accuracy of extrapolation methods: traditional load spectrum extrapolation methods (such as linear extrapolation or simple statistical models) cannot accurately capture the nonlinear characteristics of vibration loads. Threshold selection depends on subjective experience (such as fixed percentile method), lacks objective criteria, and leads to distortion of extreme load reconstruction. In addition, commonly used statistical models such as Weibull distribution have poor adaptability to non-stationary loads, making it difficult to meet the accuracy requirements of life cycle load prediction.

[0009] Poor engineering applicability: existing methods are time-consuming (single-condition analysis takes several hours), and lack effective multi-source data fusion algorithms, resulting in limited load spectrum accuracy. The prediction error is large for the entire life cycle, and it cannot provide reliable fatigue life assessment basis for key components of high-speed EMUs. SUMMARY

[0010] To solve the problems in the prior art, the embodiments of the present application provide a method and device for compiling a random vibration fatigue load spectrum of a high-speed EMU structure, which can at least partially solve the problems in the prior art.

[0011] In one aspect, the application provides a high-speed train structure random vibration fatigue load spectrum compiling method, comprising:

[0012] Synchronously collecting vibration acceleration signals and stress signals of the high-speed train, and preprocessing the vibration acceleration signals and the stress signals;

[0013] Obtaining principal component loads and trend loads according to the preprocessed vibration acceleration signals, determining a judgment threshold according to the principal component loads, and extracting a plurality of signal components according to the judgment threshold;

[0014] Superimposing the plurality of signal components and the trend loads to obtain high-precision acceleration time-domain signals, and extrapolating and reconstructing according to the high-precision acceleration time-domain signals, the preprocessed stress signals and preset working condition information to obtain multi-working condition acceleration vibration load time-domain spectra;

[0015] Obtaining a high-precision full-life acceleration vibration load spectrum according to the multi-working condition acceleration vibration load time-domain spectra.

[0016] The preprocessing of the vibration acceleration signals and the stress signals comprises:

[0017] Band-pass filtering the vibration acceleration signals and the stress signals.

[0018] The obtaining of the principal component loads and the trend loads according to the preprocessed vibration acceleration signals comprises:

[0019] Empirical mode decomposition is performed on the preprocessed vibration acceleration signals, and feature analysis is performed on the features obtained by the decomposition to obtain the principal component loads and the trend loads.

[0020] The judgment threshold comprises a principal frequency threshold, an energy proportion threshold and a correlation coefficient threshold; correspondingly, the extracting of the plurality of signal components according to the judgment threshold comprises:

[0021] The signal components satisfying at least two types of threshold conditions among the principal frequency threshold, the energy proportion threshold and the correlation coefficient threshold are taken as the extracted plurality of signal components.

[0022] The judgment threshold further comprises a kurtosis threshold; correspondingly, the high-speed train structure random vibration fatigue load spectrum compiling method further comprises:

[0023] Kurtosis judgment is performed on each signal component not satisfying the at least two types of threshold conditions using the kurtosis threshold;

[0024] The signal component satisfying the kurtosis threshold condition is taken as the extracted plurality of signal components.

[0025] The high-precision full-life acceleration vibration load spectrum is obtained according to the multi-working-condition acceleration vibration load time-domain spectrum, and the method comprises the following steps:

[0026] The multi-working-condition acceleration vibration load time-domain spectrum is used as an excitation signal to act on a single-degree-of-freedom system with different natural frequencies.

[0027] The stress response of the single-degree-of-freedom system is solved by using Duhamel integral, and the fatigue damage spectrum is calculated according to the stress response of the single-degree-of-freedom system and by using a rain flow counting method.

[0028] The high-precision full-life acceleration vibration load spectrum equivalent to the fatigue damage spectrum is obtained by calculating the equivalent vibration load spectrum of the fatigue damage spectrum.

[0029] In one aspect, the application provides a high-speed EMU structure random vibration fatigue load spectrum compiling device, which comprises:

[0030] A collection unit is configured to synchronously collect vibration acceleration signals and stress signals of the high-speed EMU and to pre-process the vibration acceleration signals and the stress signals.

[0031] An extraction unit is configured to obtain principal component loads and trend loads according to the pre-processed vibration acceleration signals, to determine a judgment threshold according to the principal component loads, and to extract a plurality of signal components according to the judgment threshold.

[0032] A reconstruction unit is configured to superimpose the plurality of signal components and the trend loads to obtain high-precision acceleration time-domain signals, to perform extrapolation reconstruction according to the high-precision acceleration time-domain signals, the pre-processed stress signals and preset working condition information, and to obtain a multi-working-condition acceleration vibration load time-domain spectrum.

[0033] An obtaining unit is configured to obtain a high-precision full-life acceleration vibration load spectrum according to the multi-working-condition acceleration vibration load time-domain spectrum.

[0034] In still another aspect, the application provides a computer device, which comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, and the processor implements the following method when executing the computer program.

[0035] The vibration acceleration signals and the stress signals of the high-speed EMU are synchronously collected, and the vibration acceleration signals and the stress signals are pre-processed.

[0036] The principal component loads and the trend loads are obtained according to the pre-processed vibration acceleration signals, the judgment threshold is determined according to the principal component loads, and the plurality of signal components are extracted according to the judgment threshold.

[0037] Superimpose the plurality of signal components with the trend load to obtain a high-precision acceleration time-domain signal, and extrapolate and reconstruct according to the high-precision acceleration time-domain signal, the preprocessed stress signal and preset working condition information to obtain a multi-working-condition acceleration vibration load time-domain spectrum.

[0038] According to the multi-working-condition acceleration vibration load time-domain spectrum, a high-precision full-life acceleration vibration load spectrum is obtained.

[0039] The embodiment of the present application provides a computer readable storage medium, comprising:

[0040] The computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the following method:

[0041] Synchronously collect vibration acceleration signals and stress signals of a high-speed motor train unit, and pre-process the vibration acceleration signals and the stress signals;

[0042] According to the pre-processed vibration acceleration signals, main component loads and trend loads are obtained, a judgment threshold is determined according to the main component loads, and a plurality of signal components are extracted according to the judgment threshold;

[0043] Superimpose the plurality of signal components with the trend load to obtain a high-precision acceleration time-domain signal, and extrapolate and reconstruct according to the high-precision acceleration time-domain signal, the preprocessed stress signal and preset working condition information to obtain a multi-working-condition acceleration vibration load time-domain spectrum;

[0044] According to the multi-working-condition acceleration vibration load time-domain spectrum, a high-precision full-life acceleration vibration load spectrum is obtained.

[0045] The embodiment of the present application further provides a computer program product, comprising a computer program, and the computer program is executed by a processor to implement the following method:

[0046] Synchronously collect vibration acceleration signals and stress signals of a high-speed motor train unit, and pre-process the vibration acceleration signals and the stress signals;

[0047] According to the pre-processed vibration acceleration signals, main component loads and trend loads are obtained, a judgment threshold is determined according to the main component loads, and a plurality of signal components are extracted according to the judgment threshold;

[0048] Superimpose the plurality of signal components with the trend load to obtain a high-precision acceleration time-domain signal, and extrapolate and reconstruct according to the high-precision acceleration time-domain signal, the preprocessed stress signal and preset working condition information to obtain a multi-working-condition acceleration vibration load time-domain spectrum;

[0049] According to the multi-working-condition acceleration vibration load time-domain spectrum, a high-precision full-life acceleration vibration load spectrum is obtained.

[0050] The method and apparatus for compiling random vibration fatigue load spectrum of high-speed train structure provided in this invention synchronously acquires vibration acceleration signals and stress signals of high-speed train, preprocesses the vibration acceleration signals and stress signals; obtains principal component loads and trend loads based on the preprocessed vibration acceleration signals, determines a judgment threshold based on the principal component loads, and extracts multiple signal components based on the judgment thresholds; superimposes the multiple signal components with the trend loads to obtain a high-precision acceleration time-domain signal; extrapolates and reconstructs based on the high-precision acceleration time-domain signal, the preprocessed stress signal, and preset working condition information to obtain a multi-working-condition acceleration vibration load time-domain spectrum; and obtains a high-precision full-life acceleration vibration load spectrum based on the multi-working-condition acceleration vibration load time-domain spectrum, which can obtain a higher-precision random vibration load spectrum of high-speed train structure and improve engineering applicability. Attached Figure Description

[0051] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0052] Figure 1 This is a flowchart illustrating a method for compiling a random vibration fatigue load spectrum for a high-speed train structure, provided in an embodiment of the present invention.

[0053] Figure 2 This is a flowchart illustrating a method for compiling a random vibration fatigue load spectrum for a high-speed train structure, provided in another embodiment of the present invention.

[0054] Figure 3 This is a schematic diagram illustrating the adaptive threshold filtering and filtering information provided in an embodiment of the present invention.

[0055] Figure 4 This is a schematic diagram illustrating the fatigue damage spectrum (FDS) provided in an embodiment of the present invention.

[0056] Figure 5 This is a schematic diagram of the structure of a high-speed train structure random vibration fatigue load spectrum compilation device provided in an embodiment of the present invention.

[0057] Figure 6 This is a schematic diagram of the physical structure of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0058] For the purposes, technical solutions and advantages of the embodiments of the present application to be clearer, the embodiments of the present application are further described in detail below with reference to the drawings. Herein, the illustrative embodiments of the present application and their descriptions are used to explain the present application, but are not as limitations of the present application. It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other in any manner without conflict.

[0059] Figure 1 is a flowchart of a method for compiling a random vibration fatigue load spectrum of a high-speed EMU structure according to an embodiment of the present application, as shown in Figure 1 the method for compiling a random vibration fatigue load spectrum of a high-speed EMU structure according to an embodiment of the present application includes:

[0060] Step S1: synchronously collecting vibration acceleration signals and stress signals of a high-speed EMU, and pre-processing the vibration acceleration signals and the stress signals.

[0061] Step S2: obtaining principal component loads and trend loads according to the pre-processed vibration acceleration signals, determining a judgment threshold according to the principal component loads, and extracting a plurality of signal components according to the judgment threshold.

[0062] Step S3: superimposing the plurality of signal components and the trend loads to obtain high-precision acceleration time-domain signals, and performing extrapolation reconstruction according to the high-precision acceleration time-domain signals, the pre-processed stress signals and preset working condition information to obtain multi-working condition acceleration vibration load time-domain spectra.

[0063] Step S4: obtaining a high-precision full-life acceleration vibration load spectrum according to the multi-working condition acceleration vibration load time-domain spectra.

[0064] In the above step S1, the device synchronously collects vibration acceleration signals and stress signals of a high-speed EMU, and pre-processes the vibration acceleration signals and the stress signals. The device can be a computer device for executing the method. The acquisition, storage, use, processing and the like of data in the technical solution of the present application all conform to relevant provisions. Sensor arrangement can be performed in advance, as follows:

[0065] Three-axis acceleration sensors (for collecting random vibration loads) and strain gauges (for measuring stress responses) are arranged at key components (such as traction transformers, traction converters, gearboxes and motors) of the EMU and at suspensions and thin-walled structures.

[0066] The vibration acceleration signals and the stress signals are synchronously collected by using a whole vehicle comprehensive test system, and the sampling frequency is set to 10 kHz to ensure the real-time performance and accuracy of the data.

[0067] The pre-processing of the vibration acceleration signals and the stress signals includes:

[0068] The vibration acceleration signal and the stress signal are subjected to band-pass filtering processing. The original data are subjected to band-pass filtering processing to remove high-frequency noise and low-frequency drift, so as to ensure the effectiveness and reliability of the data.

[0069] In the step S2, the device obtains principal component load and trend load according to the preprocessed vibration acceleration signal, determines a judgment threshold according to the principal component load, and extracts a plurality of signal components according to the judgment threshold. The obtaining of the principal component load and the trend load according to the preprocessed vibration acceleration signal comprises:

[0070] The preprocessed vibration acceleration signal is subjected to empirical mode decomposition, and the features obtained by the decomposition are subjected to feature analysis to obtain the principal component load and the trend load. As shown in the figure, the empirical mode decomposition is EEMD decomposition. The principal component load reflects the main characteristics of the vibration signal, and the trend load reflects the long-term trend of the signal. Figure 2

[0071] The determination of the judgment threshold according to the principal component load is described as follows:

[0072] Based on the obtained principal component load, the optimal threshold of the vibration signal in multiple dimensions is calculated and comprehensively judged. By calculating and counting the principal frequency, energy proportion and correlation coefficient between the vibration signal and the original signal of the principal component load, the judgment threshold information is formed.

[0073] For the principal frequency threshold, the 10th percentile of the principal frequency of all vibration signals is taken as the lower limit of the low-frequency threshold, and the 90th percentile of the principal frequency of all vibration signals is taken as the upper limit of the high-frequency threshold (not more than 80% of the Nyquist frequency of the original signal).

[0074] For the energy proportion threshold, the energy (sum of squares of component amplitudes) of each vibration signal and the average energy are calculated, and the 20% of the average energy is taken as the lower limit threshold (at least 0.5% of the energy is reserved).

[0075] For the correlation coefficient threshold, the correlation coefficient of each vibration signal and the original signal is calculated, and the median and standard deviation of all correlation coefficients are calculated, and the lower limit threshold is the median minus 1.5 times the standard deviation.

[0076] The judgment threshold comprises the principal frequency threshold, the energy proportion threshold and the correlation coefficient threshold; correspondingly, the extraction of the plurality of signal components according to the judgment threshold comprises:

[0077] The signal components satisfying at least two types of threshold conditions among the principal frequency threshold, the energy proportion threshold and the correlation coefficient threshold are taken as the plurality of signal components extracted. Referring to the above example, the signal component satisfying the principal frequency threshold condition is the signal component between the lower limit threshold and the upper limit threshold corresponding to the principal frequency.

[0078] ​Signal components that meet the energy percentage threshold condition are those whose energy percentage is greater than the lower limit of the threshold corresponding to the energy percentage.

[0079] Signal components that meet the correlation coefficient threshold condition are those whose threshold is greater than the lower limit of the threshold corresponding to the correlation coefficient.

[0080] The judgment threshold also includes a kurtosis threshold; correspondingly, the method for compiling the random vibration fatigue load spectrum of high-speed train structures also includes:

[0081] Each signal component that does not meet at least two types of threshold conditions is subjected to kurtosis determination using a kurtosis threshold;

[0082] Signal components that meet the kurtosis threshold condition are extracted as multiple signal components. Referring to the example above, kurtosis judgment is performed separately for all signals that do not meet the above judgment threshold condition. First, the kurtosis (fourth-order statistic) of each signal is calculated, and the 75th percentile of all kurtosis is taken as the lower limit threshold. If the kurtosis detection is passed, it is retained to ensure that the impulse information in the original signal is preserved.

[0083] like Figure 3 As shown, this automatic threshold calculation and filtering process can be implemented without manual parameter setting and is effective for different types of vibration / impact signals. Simultaneously, it retains key transient features through kurtosis detection and effectively filters out irrelevant components through multi-dimensional joint judgment.

[0084] In step S3 above, the device superimposes multiple signal components with the trend load to obtain a high-precision acceleration time-domain signal. Based on the high-precision acceleration time-domain signal, the preprocessed stress signal, and preset working condition information, extrapolation reconstruction is performed to obtain the multi-working-condition acceleration vibration load time-domain spectrum. The selected signal components and the decomposed trend load are then linearly superimposed to obtain a high-precision acceleration time-domain signal suitable for subsequent extrapolation reconstruction.

[0085] Taking the station entry operation of a certain type of EMU as an example, the collected frequency domain stress data is input into the simulation extrapolation model, and the acceleration is simulated and extrapolated using the Monte Carlo simulation method to generate corresponding time domain and frequency domain information. The obtained extrapolated acceleration spectrum is compared with the original stress spectrum by the response frequency to ensure the reliability and accuracy of the results.

[0086] In step S4 above, the device obtains a high-precision full-life acceleration vibration load spectrum based on the time-domain spectrum of multi-condition acceleration vibration load. The process of obtaining the high-precision full-life acceleration vibration load spectrum based on the time-domain spectrum of multi-condition acceleration vibration load includes:

[0087] The time-domain spectrum of multi-condition acceleration vibration load is used as the excitation signal and applied to a single-degree-of-freedom system with different natural frequencies.

[0088] The stress response of the single degree of freedom system is solved by Duhamel integral, and the fatigue damage spectrum is calculated according to the stress response of the single degree of freedom system and by using a rainflow counting method;

[0089] The equivalent vibration load spectrum is calculated according to the fatigue damage spectrum, and a high-precision full-life acceleration vibration load spectrum equivalent to the fatigue damage spectrum is obtained.

[0090] For the multi-condition acceleration vibration load time-domain spectrum (i.e. non-stationary load) obtained by extrapolation reconstruction, a series of single degree of freedom (SDOF) systems with fixed damping ratio and different natural frequencies are constructed to replace the actual auxiliary mounting seat. For a single degree of freedom system at a certain natural frequency, the relative displacement response time-domain solution of the non-stationary load acting on the SDOF system can be solved by Duhamel integral, and the stress response time-domain solution can be obtained by the material elastic modulus. The damage value caused by the stress response at the certain natural frequency is calculated by combining the rainflow counting method. By changing the natural frequency, the damage value varying with the natural frequency is obtained, forming a fatigue damage spectrum with the frequency as the horizontal coordinate and the damage value as the vertical coordinate, as shown in Figure 4 .

[0091] Equivalent vibration load spectrum calculation: theoretically, both stationary load and non-stationary load have fatigue damage spectrum. Therefore, according to the equal damage principle, the equivalent stationary vibration load spectrum causing the same fatigue damage as the non-stationary load can be deduced to replace the original non-stationary load, so as to obtain an acceleration vibration load spectrum with the same damage ability to the auxiliary mounting seat as the original non-stationary load.

[0092] The high-speed EMU structure random vibration fatigue load spectrum preparation method provided by the embodiment of the application has the following specific technical improvement directions:

[0093] Multi-source data fusion: synchronous acquisition of vibration acceleration and stress response data, which makes up for the limitations of single sensor data and improves the accuracy and reliability of the load spectrum.

[0094] Data preprocessing optimization: EEMD modal decomposition technology is used to replace the traditional filtering method to more accurately separate the main components and trend components of the signal and improve the data accuracy.

[0095] Optimized extrapolation method: based on statistical threshold screening and generalized Pareto distribution (GPD) extreme value extrapolation, the extreme value load reconstruction accuracy is improved to ensure the applicability of the full-life cycle load spectrum.

[0096] Frequency domain analysis method improvement: the vibration load spectrum preparation method based on the fatigue damage spectrum is used, the stress response of the non-stationary load is calculated by the single degree of freedom (SDOF) model and Duhamel integral, and the high-precision frequency spectrum is generated by combining the rainflow counting method, so as to optimize the calculation efficiency.

[0097] Improve data collection and processing efficiency: Introduce automatic data collection and real-time processing technology to meet the demand of large-scale test of high-speed EMUs and improve overall analysis efficiency.

[0098] The prior art has key defects such as insufficient multi-source data fusion, limited extrapolation method accuracy, and imperfect time-frequency conversion method in high-speed EMU load spectrum compilation, and the present application innovatively uses multi-sensor synchronous acquisition, EEMD modal decomposition, threshold screening and extrapolation reconstruction based on generalized Pareto distribution, and fatigue damage spectrum generation method combining single degree of freedom model and Duhamel integral, to construct a complete load spectrum compilation technology system, significantly improving the accuracy and efficiency of fatigue life assessment of key components of EMUs with speed grade of 400km / h and above.

[0099] The high-speed EMU structure random vibration fatigue load spectrum compilation method provided by the embodiments of the present application has the following beneficial technical effects:

[0100] Multi-source data fusion: The present application collects vibration acceleration and stress response data simultaneously, making up for the limitations of single sensor data collection, and significantly improving the accuracy and reliability of the load spectrum.

[0101] Innovative algorithm combination: The present application combines empirical mode decomposition (EEMD), threshold screening and vibration load spectrum based on fatigue damage spectrum, and extrapolation reconstruction, forming a complete load spectrum compilation method, and significantly improving the engineering applicability of the load spectrum.

[0102] Accurate threshold calculation: Using statistical principles, the data modal is analyzed and judged from the aspects of main frequency range, correlation coefficient, and energy proportion, to accurately extract the principal component load and realize multiple data cleaning.

[0103] Efficiency and economy: The present application optimizes threshold selection and extrapolation algorithm, reduces test cycle and cost, and provides high reliability input for fatigue life assessment of key components of EMUs.

[0104] The high-speed motor train unit structure random vibration fatigue load spectrum compiling method provided by the embodiment of the application comprises the following steps: synchronously collecting vibration acceleration signals and stress signals of a high-speed motor train unit, and preprocessing the vibration acceleration signals and the stress signals; obtaining principal component loads and trend loads according to the preprocessed vibration acceleration signals, determining a judgment threshold according to the principal component loads, and extracting a plurality of signal components according to the judgment threshold; superimposing the plurality of signal components and the trend loads to obtain high-precision acceleration time-domain signals, and performing extrapolation reconstruction according to the high-precision acceleration time-domain signals, the preprocessed stress signals and preset working condition information to obtain multi-working condition acceleration vibration load time-domain spectra; and obtaining high-precision full-life acceleration vibration load spectra according to the multi-working condition acceleration vibration load time-domain spectra, which can obtain a high-precision high-speed motor train unit structure random vibration load spectrum and improve engineering applicability.

[0105] Further, the preprocessing of the vibration acceleration signals and the stress signals comprises:

[0106] The vibration acceleration signals and the stress signals are subjected to band-pass filtering processing. Refer to the above embodiment for details.

[0107] Further, the obtaining of the principal component loads and the trend loads according to the preprocessed vibration acceleration signals comprises:

[0108] The preprocessed vibration acceleration signals are subjected to empirical mode decomposition, and the features obtained by the decomposition are subjected to feature analysis to obtain the principal component loads and the trend loads. Refer to the above embodiment for details.

[0109] Further, the judgment threshold comprises a principal frequency threshold, an energy proportion threshold and a correlation coefficient threshold; correspondingly, the extracting of the plurality of signal components according to the judgment threshold comprises:

[0110] The signal components satisfying at least two types of threshold conditions among the principal frequency threshold, the energy proportion threshold and the correlation coefficient threshold are taken as the plurality of extracted signal components. Refer to the above embodiment for details.

[0111] Further, the judgment threshold further comprises a kurtosis threshold; correspondingly, the high-speed motor train unit structure random vibration fatigue load spectrum compiling method further comprises:

[0112] Each signal component not satisfying the at least two types of threshold conditions is subjected to kurtosis judgment using the kurtosis threshold. Refer to the above embodiment for details.

[0113] The signal component satisfying the kurtosis threshold condition is taken as the plurality of extracted signal components. Refer to the above embodiment for details.

[0114] Further, the high-precision full-life acceleration vibration load spectrum according to the multi-working-condition acceleration vibration load time-domain spectrum comprises:

[0115] The multi-working-condition acceleration vibration load time-domain spectrum is used as an excitation signal to act on a single-degree-of-freedom system with different natural frequencies; refer to the above embodiment description, which will not be repeated here.

[0116] The stress response of the single-degree-of-freedom system is solved by Duhamel integral, and the fatigue damage spectrum is calculated according to the stress response of the single-degree-of-freedom system and by using rain flow counting method; refer to the above embodiment description, which will not be repeated here.

[0117] The fatigue damage spectrum is calculated to obtain a high-precision full-life acceleration vibration load spectrum equivalent to the fatigue damage spectrum; refer to the above embodiment description, which will not be repeated here.

[0118] Figure 5 is a structural schematic diagram of a high-speed EMU structure random vibration fatigue load spectrum compiling device provided by an embodiment of the present application, as shown in Figure 5 The high-speed EMU structure random vibration fatigue load spectrum compiling device provided by the embodiment of the present application comprises a collecting unit 501, an extracting unit 502, a reconstructing unit 503 and an obtaining unit 504, wherein:

[0119] The collecting unit 501 is configured to synchronously collect vibration acceleration signals and stress signals of the high-speed EMU and to pre-process the vibration acceleration signals and the stress signals; the extracting unit 502 is configured to obtain principal component loads and trend loads according to the pre-processed vibration acceleration signals, to determine a judgment threshold according to the principal component loads, and to extract a plurality of signal components according to the judgment threshold; the reconstructing unit 503 is configured to superimpose the plurality of signal components and the trend loads to obtain a high-precision acceleration time-domain signal, to extrapolate and reconstruct according to the high-precision acceleration time-domain signal, the pre-processed stress signals and preset working condition information to obtain a multi-working-condition acceleration vibration load time-domain spectrum; and the obtaining unit 504 is configured to obtain a high-precision full-life acceleration vibration load spectrum according to the multi-working-condition acceleration vibration load time-domain spectrum.

[0120] Specifically, the acquisition unit 501 in the device is configured to synchronously acquire vibration acceleration signals and stress signals of the high-speed motor train unit, and pre-process the vibration acceleration signals and the stress signals; the extraction unit 502 is configured to acquire principal component loads and trend loads according to the pre-processed vibration acceleration signals, determine a judgment threshold according to the principal component loads, and extract a plurality of signal components according to the judgment threshold; the reconstruction unit 503 is configured to superimpose the plurality of signal components and the trend loads to obtain high-precision acceleration time-domain signals, and perform extrapolation reconstruction according to the high-precision acceleration time-domain signals, the pre-processed stress signals and preset working condition information to obtain multi-working-condition acceleration vibration load time-domain spectra; and the acquisition unit 504 is configured to acquire high-precision full-life acceleration vibration load spectra according to the multi-working-condition acceleration vibration load time-domain spectra.

[0121] The device for compiling a high-speed motor train unit structure random vibration fatigue load spectrum provided by the embodiment of the application synchronously acquires vibration acceleration signals and stress signals of the high-speed motor train unit, and pre-processes the vibration acceleration signals and the stress signals; acquires principal component loads and trend loads according to the pre-processed vibration acceleration signals, determines a judgment threshold according to the principal component loads, and extracts a plurality of signal components according to the judgment threshold; superimposes the plurality of signal components and the trend loads to obtain high-precision acceleration time-domain signals, and performs extrapolation reconstruction according to the high-precision acceleration time-domain signals, the pre-processed stress signals and preset working condition information to obtain multi-working-condition acceleration vibration load time-domain spectra; and acquires high-precision full-life acceleration vibration load spectra according to the multi-working-condition acceleration vibration load time-domain spectra, so that a high-precision high-speed motor train unit structure random vibration load spectrum can be acquired, and engineering applicability is improved.

[0122] Further, the acquisition unit 501 is specifically configured to:

[0123] The vibration acceleration signals and the stress signals are subjected to band-pass filtering.

[0124] Further, the extraction unit 502 is specifically configured to:

[0125] The pre-processed vibration acceleration signals are subjected to empirical mode decomposition, and the features obtained by the decomposition are subjected to feature analysis to obtain the principal component loads and the trend loads.

[0126] Further, the judgment threshold includes a principal frequency threshold, an energy proportion threshold and a correlation coefficient threshold; correspondingly, the extraction unit 502 is specifically configured to:

[0127] The signal components satisfying at least two types of threshold conditions among the principal frequency threshold, the energy proportion threshold and the correlation coefficient threshold are taken as the plurality of signal components extracted.

[0128] Further, the judgment threshold further comprises a kurtosis threshold; correspondingly, the high-speed train structure random vibration fatigue load spectrum compiling device further is used for:

[0129] Each signal component not satisfying at least two threshold conditions is subjected to kurtosis judgment using the kurtosis threshold respectively;

[0130] The signal component satisfying the kurtosis threshold condition is taken as the extracted signal component.

[0131] Further, the acquisition unit 504 is specifically used for:

[0132] The multi-condition acceleration vibration load time domain spectrum is taken as an excitation signal, and is applied to a single degree of freedom system with different natural frequencies;

[0133] The stress response of the single degree of freedom system is solved by Duhamel integral, and the fatigue damage spectrum is calculated according to the stress response of the single degree of freedom system and by using the rain flow counting method;

[0134] The fatigue damage spectrum is subjected to equivalent vibration load spectrum calculation, and the high-precision full-life acceleration vibration load spectrum equivalent to the fatigue damage spectrum is obtained.

[0135] The embodiment of the high-speed train structure random vibration fatigue load spectrum compiling device provided by the embodiment of the present application can be specifically used for executing the processing flow of each method embodiment described above, and the functions thereof will not be repeated here, and the detailed description of the method embodiments described above can be referred to.

[0136] Figure 6 The computer device entity structure schematic diagram provided by the embodiment of the present application is shown as follows, Figure 6 The computer device comprises a memory 601, a processor 602, and a computer program stored in the memory 601 and capable of running on the processor 602, and the processor 602 implements the following method when executing the computer program:

[0137] The vibration acceleration signal and the stress signal of the high-speed train are synchronously collected, and the vibration acceleration signal and the stress signal are preprocessed;

[0138] The principal component load and the trend load are obtained according to the preprocessed vibration acceleration signal, the judgment threshold is determined according to the principal component load, and the plurality of signal components are extracted according to the judgment threshold;

[0139] The plurality of signal components and the trend load are superimposed to obtain a high-precision acceleration time domain signal, and the multi-condition acceleration vibration load time domain spectrum is obtained by extrapolation reconstruction according to the high-precision acceleration time domain signal, the preprocessed stress signal and the preset working condition information;

[0140] According to the multi-working-condition acceleration vibration load time domain spectrum, a high-precision full-life acceleration vibration load spectrum is acquired.

[0141] The embodiment discloses a computer program product, which comprises a computer program, and the computer program realizes the following method when executed by a processor.

[0142] Synchronously collect vibration acceleration signals and stress signals of a high-speed motor train unit, and pretreat the vibration acceleration signals and the stress signals;

[0143] According to the pretreated vibration acceleration signals, a principal component load and a trend load are acquired, a judgment threshold is determined according to the principal component load, and a plurality of signal components are extracted according to the judgment threshold;

[0144] The plurality of signal components and the trend load are superposed to obtain a high-precision acceleration time domain signal, and the high-precision acceleration time domain signal, the pretreated stress signals and preset working condition information are used for extrapolation reconstruction to obtain a multi-working-condition acceleration vibration load time domain spectrum;

[0145] According to the multi-working-condition acceleration vibration load time domain spectrum, a high-precision full-life acceleration vibration load spectrum is acquired.

[0146] The embodiment provides a computer readable storage medium, which stores a computer program, and the computer program realizes the following method when executed by a processor.

[0147] Synchronously collect vibration acceleration signals and stress signals of a high-speed motor train unit, and pretreat the vibration acceleration signals and the stress signals;

[0148] According to the pretreated vibration acceleration signals, a principal component load and a trend load are acquired, a judgment threshold is determined according to the principal component load, and a plurality of signal components are extracted according to the judgment threshold;

[0149] The plurality of signal components and the trend load are superposed to obtain a high-precision acceleration time domain signal, and the high-precision acceleration time domain signal, the pretreated stress signals and preset working condition information are used for extrapolation reconstruction to obtain a multi-working-condition acceleration vibration load time domain spectrum;

[0150] According to the multi-working-condition acceleration vibration load time domain spectrum, a high-precision full-life acceleration vibration load spectrum is acquired.

[0151] Compared with the technical solution in the prior art, the high-speed motor train unit structure random vibration fatigue load spectrum compiling method provided by the embodiment of the present application can simultaneously collect vibration acceleration signals and stress signals of the high-speed motor train unit, pretreat the vibration acceleration signals and the stress signals, obtain principal component loads and trend loads according to the pretreated vibration acceleration signals, determine a judgment threshold according to the principal component loads, and extract a plurality of signal components according to the judgment threshold, superimpose the plurality of signal components and the trend loads to obtain high-precision acceleration time-domain signals, and perform extrapolation reconstruction according to the high-precision acceleration time-domain signals, the pretreated stress signals and preset working condition information to obtain multi-working condition acceleration vibration load time-domain spectra, and obtain high-precision full-life acceleration vibration load spectra, so that a high-precision high-speed motor train unit structure random vibration load spectrum can be obtained, and engineering applicability is improved.

[0152] Those skilled in the art will understand that the embodiments of the present application can be provided as methods, systems or computer program products. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0153] The present application is described with reference to flowcharts and / or block diagrams of the method, device (system) and computer program product according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device that implements the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 an apparatus that carries out the functions specified in one or more blocks or flows.

[0154] These computer program instructions can also be stored in a computer-readable memory that can direct the computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including instruction apparatus that implements the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 an apparatus that carries out the functions specified in one or more blocks or flows.

[0155] These computer program instructions can also be loaded into a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 Figure 1

[0156] In the description of the present specification, the description of the terms "one embodiment", "one specific embodiment", "some embodiments", "for example", "exemplary", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0157] The above-described specific embodiments further illustrate the purpose, technical solutions and beneficial effects of the present application. It should be understood that the above-described embodiments are only specific embodiments of the present application and are not intended to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.​​

Claims

1. A method for compiling a high-speed train structure random vibration fatigue load spectrum, characterized in that, The method comprises the following steps: synchronously collecting vibration acceleration signals and stress signals of a high-speed train, and preprocessing the vibration acceleration signals and the stress signals; obtaining principal component loads and trend loads from the preprocessed vibration acceleration signals, determining a judgment threshold according to the principal component loads, and extracting a plurality of signal components according to the judgment threshold; superimposing the plurality of signal components and the trend loads to obtain high-precision acceleration time-domain signals, and performing extrapolation reconstruction according to the high-precision acceleration time-domain signals, the preprocessed stress signals and preset working condition information to obtain multi-working condition acceleration vibration load time-domain spectra; obtaining high-precision full-life acceleration vibration load spectra according to the multi-working condition acceleration vibration load time-domain spectra.

2. The method for compiling a high-speed train structure random vibration fatigue load spectrum according to claim 1, characterized in that, The preprocessing of the vibration acceleration signals and the stress signals comprises: band-pass filtering the vibration acceleration signals and the stress signals.

3. The method for compiling a high-speed train structure random vibration fatigue load spectrum according to claim 1, characterized in that, The obtaining of the principal component loads and the trend loads from the preprocessed vibration acceleration signals comprises: performing empirical mode decomposition on the preprocessed vibration acceleration signals, and performing feature analysis on features obtained by the decomposition to obtain the principal component loads and the trend loads.

4. The method for compiling a high-speed train structure random vibration fatigue load spectrum according to claim 1, characterized in that, The judgment threshold comprises a principal frequency threshold, an energy proportion threshold and a correlation coefficient threshold; correspondingly, the extracting of the plurality of signal components according to the judgment threshold comprises: taking signal components satisfying at least two types of threshold conditions among the principal frequency threshold, the energy proportion threshold and the correlation coefficient threshold as the plurality of extracted signal components.

5. The method for compiling a high-speed train structure random vibration fatigue load spectrum according to claim 4, characterized in that, The judgment threshold further comprises a kurtosis threshold; correspondingly, the method further comprises: performing kurtosis judgment on each signal component not satisfying the at least two types of threshold conditions by using the kurtosis threshold; taking signal components satisfying the kurtosis threshold condition as the plurality of extracted signal components.

6. The method of claim 1 to 5, wherein, The obtaining of the high-precision full-life acceleration vibration load spectra according to the multi-working condition acceleration vibration load time-domain spectra comprises: taking the multi-working condition acceleration vibration load time-domain spectra as excitation signals, and applying the excitation signals to single-degree-of-freedom systems with different natural frequencies; solving stress responses of the single-degree-of-freedom systems by Duhamel integral, and calculating fatigue damage spectra according to the stress responses of the single-degree-of-freedom systems and by using a rain flow counting method; performing equivalent vibration load spectrum calculation on the fatigue damage spectra to obtain high-precision full-life acceleration vibration load spectra equivalent to the fatigue damage spectra.

7. A high-speed train structure random vibration fatigue load spectrum compiling device, characterized in that, The method comprises the following steps: collecting vibration acceleration signals and stress signals of a high-speed train, and preprocessing the vibration acceleration signals and the stress signals; obtaining principal component loads and trend loads from the preprocessed vibration acceleration signals, determining a judgment threshold according to the principal component loads, and extracting a plurality of signal components according to the judgment threshold; superimposing the plurality of signal components and the trend loads to obtain high-precision acceleration time-domain signals, and performing extrapolation reconstruction according to the high-precision acceleration time-domain signals, the preprocessed stress signals and preset working condition information to obtain multi-working condition acceleration vibration load time-domain spectra; obtaining high-precision full-life acceleration vibration load spectra according to the multi-working condition acceleration vibration load time-domain spectra.

8. A computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor executes the computer program to implement the method of any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is executed by the processor to implement the method in any one of claims 1 to 6.

10. A computer program product, characterised in that, The computer program product comprises a computer program, and the computer program is executed by the processor to implement the method in any one of claims 1 to 6.

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