Method and system for automatically intercepting high-frequency signal in constant-speed operation section of mechanical equipment

Abstract

The invention discloses a method and a system for automatically intercepting a high-frequency signal in a constant-speed operation section of mechanical equipment. The method comprises the following steps: acquiring signal data of the mechanical equipment; determining the size and the step length of a first sliding window processing window; performing sliding window processing on the original signal, calculating the variance of each window signal, and performing data compression to obtain a first signal; visually judging whether signals in different operation states in the first signals are in the same order of magnitude or not; determining the window size and step length of second-time window sliding processing; performing sliding window processing on the compressed first signal, calculating the variance of each window signal, and performing data compression to obtain a second signal; determining a threshold magnitude order of data distinguishing of the operation section and the non-operation section; finding out a starting point and an ending point of the operation section, and restoring to original signals to obtain operation section signals; calculating a central point of an operation section, calculating constant-speed operation time according to an actual working condition, and restoring to an original signal; and error analysis is carried out through a starting point and end point signal interception mode and a midpoint signal interception mode.

Description

Background Art

[0002] The health monitoring and maintenance of mechanical equipment are of great significance for extending equipment life, reducing maintenance costs, improving production efficiency and economic benefits, ensuring safe production, and promoting technological application and innovation. The traditional health monitoring methods mainly include post-monitoring, regular maintenance, manual inspection, and historical fault-based methods. These methods not only cannot reflect the operating status of the equipment in real time, but also regular monitoring and maintenance will lead to inefficiency and economic losses. In recent years, with the advent of the big data era, data-based analysis and model prediction have achieved rapid development. Through the current, vibration and other related signals in the operation of the equipment, automated equipment management, predictive maintenance and intelligent diagnosis can be achieved. The premise for achieving these goals is to accurately extract effective information from the data. Vibration signals, current signals and other high-frequency signals can extract key information such as the operating status, fault warning, and health status of mechanical equipment, which is the key to the monitoring and maintenance of mechanical equipment. However, in the signal acquisition process, the acquisition signal length includes non-operating segment signals, acceleration and deceleration segment signals, and uniform speed segment signals. Among them, the non-operating segment signals mainly contain noise signals, and the acceleration and deceleration segment signals are unstable. In the acquired signals, the time domain and frequency domain characteristics of the uniform speed segment signals are more stable, which can better reflect the operating status of the equipment. Therefore, the process of monitoring the equipment based on the signal requires intercepting the uniform speed running segment in the collected signal.

[0003] The traditional data capture method is to convert data text information into image information, manually divide the data according to the division experience of professionals, and select the uniform speed segment signal in a section of the collected signal. In some occasions where the operating position information and speed information of mechanical equipment can be collected, the start and end times of the uniform speed running segment can be calculated based on the time synchronization of various signals, through the position information or speed information, to complete the capture of the collected signal. At the same time, the vibration signal of the uniform speed running segment can also be captured based on a combination of smoothing filtering and finding the zero crossing point.

[0004] At present, in some fields with small data volume and low data accuracy requirements, manual interception can be selected. However, this method is not suitable for automated analysis and processing of large-scale data. It will greatly reduce the analysis efficiency and increase the cost. Although the combination of position information or speed information and acquisition signal can accurately complete data segmentation in principle, in actual acquisition, due to clock drift, trigger mechanism, sampling frequency, sensor delay, it is difficult to maintain a high degree of synchronization between position information or speed information and acquisition signal in time, and there is a problem of data point loss. At the same time, it is difficult to collect position information or speed information in the operating conditions of some mechanical equipment, and the method has poor universality. The method based on smoothing filtering and finding zero crossing points is mainly aimed at vibration signal segmentation, but in the operation of mechanical equipment, there are not only vibration signals, but also current signals, force signals, etc. It is not yet known how it works for other signals. At the same time, by intercepting the time domain interval from the first zero crossing point to the last zero crossing point in the time domain of the acceleration data as a method for intercepting the vibration signal of the uniform speed running segment, it is difficult to accurately extract each uniform speed segment signal for the acquisition signal containing multiple segments of running information. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a method and system for automatically intercepting high-frequency signals of a mechanical equipment in a uniform speed operation section in view of the deficiencies in the above-mentioned prior art, so as to solve the technical problems of low efficiency, poor data synchronization and single signal type existing in the prior art.

[0006] The present invention adopts the following technical solutions:

[0007] A method for automatically intercepting high-frequency signals of a mechanical device in a uniform speed operation section, comprising the following steps:

[0008] S1. Obtain signal data of the entire process of mechanical equipment;

[0009] S2. Determine the size of the first sliding window processing window win 1 and stride 1 ;

[0010] S3, performing sliding window processing on the original signal, calculating the variance of each window signal, performing data compression, and obtaining a first signal;

[0011] S4. Perform visual judgment on the first signal to determine whether signals in different operating states in the first signal are in the same order of magnitude;

[0012] S5. Determine the second sliding window processing window size win 2 and stride 2 ;

[0013] S6, performing sliding window processing on the first signal, calculating the variance of each window signal, performing data compression, and obtaining a second signal;

[0014] S7, determining a threshold magnitude for distinguishing between running segment data and non-running segment data;

[0015] S8, finding the starting point start and the end point last of the running segment, and restoring the original signal to obtain the running segment signal;

[0016] S9. Calculate the center point mid of the running section and calculate the uniform speed running time t according to the actual working conditions. 1 , restore to the original signal and obtain the uniform speed running segment signal;

[0017] S10, performing error analysis on the signal interception method through the starting point and the end point and the signal interception method through the midpoint respectively.

[0018] Preferably, in step S1, a complete cycle signal during the operation of the mechanical equipment includes a non-operating segment signal, an acceleration / deceleration segment signal and a uniform speed segment signal.

[0019] Preferably, step S2 specifically includes:

[0020] S201, obtain the original signal sampling frequency f s ,Fourier transform of the original signal;

[0021] S202, according to the Fourier transform result, obtain the resonance frequency f max ;

[0022] S203, determine the window size win according to the resonance frequency and sampling theorem 1 and stride 1 .

[0023] Preferably, step S4 is specifically:

[0024] If they are in the same order of magnitude, continue to step S5; if they are not in the same order of magnitude, jump to step S6.

[0025] Preferably, step S5 is specifically:

[0026] S501, obtaining the first signal sampling frequency f s1 , Fourier transform the first signal;

[0027] S502, according to the Fourier transform result, obtain the resonance frequency f max1 ;

[0028] S503, determine the window size win according to the resonance frequency and sampling theorem 2 and stride 2 .

[0029] Preferably, in step S6, the variance of the first signal is calculated, and the running segment and stationary segment data are compressed again to compress the data to different orders of magnitude to obtain the second signal; the segmented order of magnitude of the data collected by the same mechanical equipment under the same working conditions remains basically consistent.

[0030] Preferably, in step S7, according to the second signal and the order of magnitude of the determined running state division threshold, the start and end points of the running segment signal are determined in the second signal, and restored to the original signal. End point value range

[0031] Preferably, in step S8, according to start and last, The value range of the midpoint of the uniform speed segment in the original signal According to the midpoint meaning Obtain the uniform speed running time length t according to the actual working conditions 1 , the range of uniform speed data is

[0032]

[0033] Preferably, in step S9, the error source in restoring the second signal to the original signal is analyzed as follows: a signal point in the second signal represents a signal point in the original signal. points; compare the error restored to the original signal through the starting point and end point with the error restored to the original signal through the midpoint, and choose the midpoint method to intercept the uniform speed segment signal in the original signal.

[0034] In a second aspect, an embodiment of the present invention provides a system for automatically intercepting high-frequency signals of a mechanical device in a uniform speed operation section, comprising:

[0035] Data module, obtains the signal data of the entire process of mechanical equipment; determines the size of the first sliding window processing window win 1 and stride 1 ;

[0036] The first processing module performs sliding window processing on the original signal, calculates the variance of each window signal, performs data compression, and obtains the first signal; performs visual judgment on the first signal to determine whether the signals in different operating states in the first signal are in the same order of magnitude;

[0037] The second processing module determines the second sliding window processing window size win 2 and stride 2 ; Perform sliding window processing on the first signal, calculate the variance of each window signal, perform data compression, and obtain the second signal;

[0038] The restoration module determines the threshold magnitude for distinguishing the running segment and the non-running segment data; finds the starting point start and the end point last of the running segment, and restores the original signal to obtain the running segment signal;

[0039] Output module, calculates the center point mid of the running section, and calculates the uniform speed running time t according to the actual working conditions 1 , restore to the original signal and obtain the uniform speed running segment signal; perform error analysis on the signal interception method through the starting point, end point and midpoint.

[0040] In a third aspect, a computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned method for automatically intercepting high-frequency signals of a uniform speed running segment of a mechanical device when executing the computer program.

[0041] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, including a computer program, which, when executed by a processor, implements the steps of the above-mentioned method for automatically intercepting high-frequency signals in a uniform speed operation segment of a mechanical device.

[0042] In a fifth aspect, a chip comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned method for automatically intercepting high-frequency signals in a uniform speed running section of a mechanical device when executing the computer program.

[0043] In a sixth aspect, an embodiment of the present invention provides an electronic device, including a computer program, which, when executed by the electronic device, implements the steps of the above-mentioned method for automatically intercepting high-frequency signals in a uniform speed operation segment of a mechanical device.

[0044] Compared with the prior art, the present invention has at least the following beneficial effects:

[0045] A method for automatically intercepting high-frequency signals of uniform speed running sections of mechanical equipment. The signals during the operation of mechanical equipment always contain different operating state information such as static, acceleration, deceleration, and uniform speed. The signals under uniform speed running state can better reflect the health status of mechanical equipment, but it is difficult to collect only uniform speed signals when using sensors for collection. Therefore, the present invention proposes an effective and reasonable method for extracting uniform speed running section signals of mechanical equipment. First, the equipment operation signals are collected by sensors in the mechanical equipment, and the signal variance is considered to find the uniform speed running state interception standard according to the signal amplitude characteristics under different operating states.

[0046] Furthermore, the resonant frequency of the signal is solved by Fourier transform, and the window size and moving step size in the sliding window processing are determined in combination with the sampling theorem. Determining the window length according to the resonant frequency can ensure that the complete waveform of the resonant frequency is captured in each time period, enhance the balance between frequency resolution and time resolution, reduce spectrum leakage, and improve the signal-to-noise ratio. At the same time, an appropriate window can prevent data distortion and feature loss caused by a window that is too large, and prevent the problem of unclear data feature extraction caused by a window that is too small.

[0047] Furthermore, we consider using sliding window processing to solve the variance of the data in each window, compress the data, extract the amplitude characteristics of the signal under different operating states, and obtain the first signal. Using amplitude as the basis for judging different operating states is more intuitive, simple and clear. Using sliding window processing can reduce the influence of noise in the signal and enhance the stability of the signal. Compared with the original signal, the degree of amplitude change in the first signal is more significant in the variance characteristics.

[0048] Furthermore, by analyzing the first signal obtained, it is observed whether the signal segmentation threshold under different operating conditions can be obtained. Generally, due to too many signals such as noise in the signal, it is difficult to obtain an ideal segmentation effect through a sliding window process. However, the first signal has completed signal compression to a certain extent and extracted some key features. The analysis of the first signal can provide an important reference for the optimization of the window size and step size parameters in the process of obtaining the second signal.

[0049] Further, the window size and step size of the second sliding window are determined. Compared with the original signal, the actual sampling frequency of the first signal is the ratio of the sampling frequency of the original signal to the step size of the first sliding window processing. If the window size and step size of the first sliding window processing are continued to be used, it may cause excessive data compression, thereby introducing a large restoration error when restoring the signal. To this end, re-optimizing the sliding window size and step size parameters for the first signal can effectively reduce the restoration error and reduce unnecessary sample loss.

[0050] Furthermore, by performing sliding window processing on the first signal and calculating the variance in each window, the second signal is obtained. Compared with the first signal, the amplitude change in the second signal is more significant, which will make the operating state classification standard clearer and the classification result more accurate. In the second signal, the magnitude difference between the static segment and the non-static segment is within 10 -2 above.

[0051] Further, the threshold order of magnitude for dividing the running segment and the non-running segment is determined. The threshold order of magnitude in different running states in the second signal is clearly distinguished, but the second signals obtained from different types of signals have order of magnitude differences. Therefore, the data division order of magnitude threshold is determined by combining the second signal generated after the actual signal transformation, so that the running state can be divided more accurately. In addition, using the order of magnitude as the threshold standard is more helpful to accurately determine the starting point and end point of the signal.

[0052] Furthermore, the starting point and end point of the running segment are found according to the second signal, and error analysis is performed. In the running segment, the difference between the acceleration segment, the deceleration segment and the uniform speed segment in the second signal is small. At the same time, due to the existence of smoothing, it is difficult to directly and accurately extract the uniform speed segment. By finding the starting point and end point of the running segment and further combining the actual running time to intercept the uniform speed segment signal, the interception result is more accurate.

[0053] Furthermore, according to the starting point and the end point of the running segment, the midpoint of the running segment is found. According to the symmetry of the running process, the acceleration and deceleration time are the same and easy to obtain, and the uniform running time length and the midpoint of the uniform running segment are calculated. Then, according to the uniform speed segment signal length, half of the uniform speed running time length is taken on both sides of the midpoint at the sampling frequency. Compared with the method of intercepting the uniform speed segment running signal through the starting point and the end point, the method of intercepting the uniform speed segment signal through the midpoint can reduce the error and ensure that the signal interception length of the uniform speed segment signal is equal under the same operating conditions.

[0054] Furthermore, by solving the variance of the amplitude under different operating conditions, threshold judgment and uniform speed running segment signal extraction are performed. Through the analysis of the solution process and example verification, it is proved that this method has good applicability in various types of signal processing work such as vibration signals and current signals. At the same time, for multiple uniform speed running segment signals contained in the same acquisition signal, this method can effectively extract each uniform speed segment, so it is suitable for complex operation signal analysis containing multiple uniform speed conditions.

[0055] In summary, the advantages of the present invention are:

[0056] 1. The present invention uses sliding window processing to solve the variance of the data in each window, compresses the data, and can extract the amplitude change characteristics of the signal under different operating states. Using the amplitude change characteristics as the basis for judging different operating states is more intuitive, simple and clear.

[0057] 2. The present invention determines the window size and step size in sliding window processing through Fourier transform and sampling theorem, which can reduce spectrum leakage and improve signal-to-noise ratio.

[0058] 3. The present invention can be applied to various signals such as vibration signals and current signals by solving the variance of amplitudes under different operating states, performing threshold judgment and uniform speed running segment signal extraction. At the same time, for operating conditions where multiple uniform speed running segment signals are contained in the same collected signal, multiple uniform speed running segment signals contained in the signal can be extracted separately at the same time.

[0059] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0061] Figure 1 It is a flow chart of the present invention;

[0062] Figure 2 This is the original vibration signal diagram of unidirectional motion in Example 1;

[0063] Figure 3 This is the first Fourier transform diagram of Example 1;

[0064] Figure 4 This is the result diagram of the first variance solution of Example 1;

[0065] Figure 5 This is the second Fourier transform diagram of Example 1;

[0066] Figure 6 This is the result diagram of the second variance solution of Example 1;

[0067] Figure 7 This is the result diagram of the automatic capture of the unidirectional motion vibration signal running segment in Example 1;

[0068] Figure 8 This is the result diagram of the automatic capture of the uniform speed running section of the unidirectional motion vibration signal in Example 1;

[0069] Fig. 9 This is the error analysis diagram of the data restoration result;

[0070] Fig.10 This is the result diagram of the automatic capture of the bidirectional motion vibration signal running segment of Example 2;

[0071] Fig.11 This is the result diagram of the automatic capture of the uniform speed running section of the bidirectional motion vibration signal in Example 2;

[0072] Fig.12This is the result diagram of the automatic capture of the bidirectional motion current signal operation section of Example 3;

[0073] Fig.13 This is the result diagram of the automatic capture of the uniform speed running section of the bidirectional motion current signal in Example 3;

[0074] Fig.14 A schematic diagram of a computer device provided by an embodiment of the present invention;

[0075] Fig.15 The block diagram is a chip provided according to an embodiment of the present invention. DETAILED DESCRIPTION

[0076] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0077] In the description of the present invention, it should be understood that the terms “include” and “comprises” indicate the presence of described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or collections thereof.

[0078] It should also be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0079] It should be further understood that the term "and / or" used in the present specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes these combinations. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in the present invention generally indicates that the associated objects are in an "or" relationship.

[0080] It should be understood that, although the terms first, second, third, etc. may be used to describe preset ranges, etc. in the embodiments of the present invention, these preset ranges should not be limited to these terms. These terms are only used to distinguish preset ranges from each other. For example, without departing from the scope of the embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0081] The word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0082] Various structural schematic diagrams of the embodiments disclosed in the present invention are shown in the accompanying drawings. These figures are not drawn to scale, and some details are magnified and some details may be omitted for the purpose of clear expression. The shapes of various regions and layers shown in the figures and the relative sizes and positional relationships therebetween are only exemplary, and may deviate in practice due to manufacturing tolerances or technical limitations, and those skilled in the art may additionally design regions / layers with different shapes, sizes, and relative positions according to actual needs.

[0083] The present invention provides a method for automatically intercepting high-frequency signals of uniform speed running sections of mechanical equipment. Based on the amplitude characteristics of the signals in different running sections, the signals are divided into different running states by calculating the variance through a sliding window function, and the standard for extracting uniform speed section signals is intuitive and clear. This method is applicable to a variety of signals such as vibration signals, current signals, and force signals. This method is not only widely applicable and efficient, but also can complete the interception of uniform speed section signals in the case where a collected signal contains multiple sections of uniform speed signals; for data collected under the same working conditions, only the window and step size of the sliding window in the first data division process need to be calculated, which significantly improves the calculation efficiency.

[0084] See also Figure 1 The present invention provides a method for automatically intercepting high-frequency signals of a mechanical device in a uniform speed operation section, comprising the following steps:

[0085] S1. Obtain signal data of the entire process of mechanical equipment;

[0086] A complete cycle signal during the operation of mechanical equipment includes non-operating segment signals, acceleration and deceleration segment signals, constant speed segment signals, and corresponding reverse signals.

[0087] The original signal is obtained through current, vibration and other sensors, which are installed on the screw nut, bearing seat and motor seat.

[0088] S2. Determine the size of the first sliding window processing window win 1 and stride 1 ;

[0089] Through sensor sampling frequency, Fourier transform and sampling theorem, the selection of window size in sliding window processing is made more reasonable and effective.

[0090] S201, obtain the original signal sampling frequency f s ,Fourier transform of the original signal;

[0091] S202, through Fourier transform Get the resonant frequency f max ;

[0092] S203, according to the resonance frequency and sampling theorem f>2f max , calculate the value range of win Determine the window size win 1 and stride 1 .

[0093] S3, performing sliding window processing on the original signal, calculating the variance of each window signal, and performing data compression of the running segment and the static segment data to obtain a first signal;

[0094] S4. Visually determine whether signals in different operating states in the first signal are in the same order of magnitude by performing a first signal visualization;

[0095] S401, if they are at the same order of magnitude, proceed to step S5;

[0096] S402: If they are not at the same order of magnitude, jump to step S6;

[0097] S5. Determine the second sliding window processing window size win 2 and stride 2 ;

[0098] S501, obtaining the first signal sampling frequency f s1 , Fourier transform the first signal;

[0099] S502, according to the Fourier transform result, obtain the resonance frequency f max1 ;

[0100] S503, determine the window size win according to the resonance frequency and sampling theorem 2 and stride 2 ;

[0101] S6, performing sliding window processing on the first signal, calculating the variance of each window signal, performing data compression, and obtaining a second signal;

[0102] According to the analysis of signal characteristics, any signal in the static segment and the non-static segment has a large difference in amplitude. The variance can directly reflect the change of data and can simply and clearly reflect the basis for data segment interception. However, due to the unevenness of the data, there are also some data segments with small amplitudes in the running segment. Therefore, the result of the variance solution may have a certain data intersection in the running segment and the static segment. Therefore, two variance calculations are required to compress the data of the running segment and the static segment to different orders of magnitude. The segmented order of magnitude of the data collected by the same mechanical equipment under the same working conditions is basically consistent, so a single operation process can ensure the automatic batch processing of the data collected by the same mechanical equipment under the same working conditions.

[0103] S7, determine the threshold magnitude for distinguishing the running segment and the non-running segment data; find the starting point start and the end point last of the running segment, and restore the original signal to obtain the running segment signal;

[0104] According to the second signal and the determined running state, the threshold value is divided into the order of magnitude, the start and end points of the running segment signal are determined in the second signal, and the original signal is restored. End point value range

[0105] S8. Calculate the center point mid of the running section and calculate the uniform speed running time t according to the actual working conditions. 1 , restore to the original signal;

[0106] According to the above start and last, The value range of the midpoint of the uniform speed segment in the original signal According to the midpoint meaning Obtain the uniform speed running time length t according to the actual working conditions 1 , the range of uniform speed segment data is as follows:

[0107]

[0108] S9. Error analysis through the starting point and end point signal interception method and the midpoint signal interception method.

[0109] The error source in restoring the second signal to the original signal is that a signal point in the second signal represents Comparing the error of restoring the original signal through the starting point and the end point with the error of restoring the original signal through the midpoint, choosing the midpoint method to intercept the uniform speed signal in the original signal can not only ensure the reduction of error, but also ensure that the intercepted signal length is the same under the same working conditions and the same speed.

[0110] It will be appreciated by those skilled in the art that various aspects of the present invention may be implemented as systems, methods or program products. Therefore, various aspects of the present invention may be specifically implemented in the following forms, namely: complete hardware implementation, complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software implementations, which may be collectively referred to herein as "circuits", "modules" or "platforms".

[0111] In one embodiment of the present invention, a system for automatically intercepting high-frequency signals of a mechanical device during a uniform speed operation segment is provided. The system can be used to implement the above-mentioned method for automatically intercepting high-frequency signals of a mechanical device during a uniform speed operation segment. Specifically, the system for automatically intercepting high-frequency signals of a mechanical device during a uniform speed operation segment includes a data module, a first processing module, a second processing module, a restoration module, and an output module.

[0112] Among them, the data module obtains the signal data of the entire process of the mechanical equipment; determines the size of the first sliding window processing window win 1 and stride 1 ;

[0113] The first processing module performs sliding window processing on the original signal, calculates the variance of each window signal, performs data compression, and obtains the first signal; performs visual judgment on the first signal to determine whether the signals in different operating states in the first signal are in the same order of magnitude;

[0114] The second processing module determines the second sliding window processing window size win 2 and stride 2 ; Perform sliding window processing on the first signal, calculate the variance of each window signal, perform data compression, and obtain the second signal;

[0115] The restoration module determines the threshold magnitude for distinguishing the running segment and the non-running segment data; finds the starting point start and the end point last of the running segment, and restores the original signal to obtain the running segment signal;

[0116] Output module, calculates the center point mid of the running section, and calculates the uniform speed running time t according to the actual working conditions 1 , restore to the original signal and obtain the uniform speed running segment signal; perform error analysis on the signal interception method through the starting point, end point and midpoint.

[0117] In one embodiment of the present invention, a terminal device is provided, which includes a processor and a memory, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or other general-purpose processors, graphics processing units (GPU), tensor processing units (TPU), digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions to implement the corresponding method flow or corresponding function; the processor described in the embodiment of the present invention can be used for the operation of the method for automatically intercepting high-frequency signals in the uniform speed operation section of mechanical equipment, including:

[0118] Obtain signal data of the entire process of mechanical equipment; determine the size of the first sliding window processing window win 1 and stride 1 ; Perform sliding window processing on the original signal, calculate the variance of each window signal, perform data compression, and obtain the first signal; visualize the first signal to determine whether the signals in different operating states in the first signal are at the same order of magnitude; determine the window size win for the second sliding window processing 2 and stride 2 ; Perform sliding window processing on the first signal, calculate the variance of each window signal, perform data compression, and obtain the second signal; determine the threshold magnitude for distinguishing the running segment and the non-running segment data; find the starting point start and the end point last of the running segment, restore the original signal to obtain the running segment signal; calculate the center point mid of the running segment, and calculate the uniform speed running time t according to the actual working conditions 1 , restore to the original signal and obtain the uniform speed running segment signal; perform error analysis on the signal interception method through the starting point, end point and midpoint.

[0119] See also Fig.14, the terminal device is a computer device, and the computer device 60 of this embodiment includes: a processor 61, a memory 62, and a computer program 63 stored in the memory 62 and executable on the processor 61. When the computer program 63 is executed by the processor 61, the method for automatically intercepting high-frequency signals of a mechanical device in a uniform speed operation section in the embodiment is implemented. To avoid repetition, it is not described one by one here. Alternatively, when the computer program 63 is executed by the processor 61, the functions of each model / unit in the system for automatically intercepting high-frequency signals of a mechanical device in a uniform speed operation section in the embodiment are implemented. To avoid repetition, it is not described one by one here.

[0120] The computer device 60 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The computer device 60 may include, but is not limited to, a processor 61 and a memory 62. Those skilled in the art will appreciate that Fig.14 This is only an example of the computer device 60 and does not constitute a limitation of the computer device 60. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the computer device may also include input and output devices, network access devices, buses, etc.

[0121] The processor 61 may be a central processing unit (CPU), or other general-purpose processors, graphics processing units (GPU), tensor processing units (TPU), digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0122] The memory 62 may be an internal storage unit of the computer device 60, such as a hard disk or memory of the computer device 60. The memory 62 may also be an external storage device of the computer device 60, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc., equipped on the computer device 60.

[0123] Furthermore, the memory 62 may include both an internal storage unit of the computer device 60 and an external storage device. The memory 62 is used to store computer programs and other programs and data required by the computer device. The memory 62 may also be used to temporarily store data that has been output or is to be output.

[0124] See also Fig.15 The terminal device 600 is an electronic device, and the electronic device is in the form of a general computing device. The components of the electronic device may include but are not limited to: at least one processing unit 610, at least one storage unit 620, a bus 630 connecting different platform components (including the storage unit 620 and the processing unit 610), a display unit 640, etc.

[0125] The storage unit stores program codes, which can be executed by the processing unit 610, so that the processing unit 610 performs the steps according to various exemplary embodiments of the present invention described in the above method section of this specification. For example, the processing unit 610 can perform the following steps: Figure 1 Follow the steps shown in .

[0126] The storage unit 620 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 6201 and / or a cache memory unit 6202 , and may further include a read-only memory unit (ROM) 6203 .

[0127] The storage unit 620 may also include a program / utility 6204 having a set (at least one) of program modules 6205, such program modules 6205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0128] Bus 630 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0129] The electronic device 600 may also communicate with one or more external devices 700 (e.g., keyboards, pointing devices, Bluetooth devices, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 600, and / or communicate with any device that enables the electronic device 600 to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface 650. Furthermore, the electronic device 600 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 660. The network adapter 660 may communicate with other modules of the electronic device 600 via a bus 630. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms, etc.

[0130] In one embodiment of the present invention, the present invention also provides a storage medium, specifically a computer-readable storage medium, which is a memory device in a terminal device for storing programs and data. It can be understood that the computer-readable storage medium here can include both the built-in storage medium in the terminal device and the extended storage medium supported by the terminal device. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space, and these instructions can be one or more computer programs. It should be noted that the computer-readable storage medium here can be a high-speed RAM memory, or a non-volatile memory (Non-Volatile Memory), such as at least one disk memory.

[0131] The processor may load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the method for automatically intercepting high-frequency signals of a mechanical device in a uniform speed operation section in the above embodiment; the processor may load and execute the following steps:

[0132] Obtain signal data of the entire process of mechanical equipment; determine the size of the first sliding window processing window win 1 and stride 1 ; Perform sliding window processing on the original signal, calculate the variance of each window signal, perform data compression, and obtain the first signal; perform visual judgment on the first signal to determine whether the signals in different operating states in the first signal are at the same order of magnitude; determine the window size win for the second sliding window processing 2and stride 2 ; Perform sliding window processing on the first signal, calculate the variance of each window signal, perform data compression, and obtain the second signal; determine the threshold magnitude for distinguishing the running segment and the non-running segment data; find the starting point start and the end point last of the running segment, restore the original signal to obtain the running segment signal; calculate the center point mid of the running segment, and calculate the uniform speed running time t according to the actual working conditions 1 , restore to the original signal and obtain the uniform speed running segment signal; perform error analysis on the signal interception method through the starting point, end point and midpoint.

[0133] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. The components of the embodiments of the present invention described and shown in the drawings here can usually be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0134] Example 1

[0135] A certain type of ball screw is selected to perform reciprocating motion on a mechanical equipment test bench, and a complete vibration signal is collected during the processes of static, acceleration, constant speed, deceleration, and static.

[0136] See also Figure 1 The present invention proposes a method for automatically intercepting a signal of a uniform speed running section of a mechanical device, and the specific steps include:

[0137] Step 1: Obtain the vibration signal of the ball screw during a complete motion process including static, acceleration, uniform speed, deceleration, and static motion;

[0138] Step 2: Determine the window size win for the first sliding window 1 and stride 1 ;

[0139] Including obtaining the sampling frequency f s The window size and step size in sliding window processing are obtained by combining Fourier transform and sampling theorem. Figure 2 As shown, through Get the frequency domain diagram of the original signal, such as Figure 3 As shown. According to the Fourier transform results, the resonance frequency f is obtained from the figuremax =195Hz.

[0140] Step 201: Obtain the original signal sampling frequency f s ,Fourier transform of the original signal;

[0141] Step 202: Obtain the resonance frequency f according to the Fourier transform result max ;

[0142] Step 203: Determine the window size win according to the resonance frequency and sampling theorem 1 and stride 1 ;

[0143] Determine the window size win 1 and stride 1 The calculation process is: based on the resonance frequency, combined with the sampling theorem f>2f max , calculate win 1 The value range of

[0144] Step 3: Perform sliding window processing on the original signal, calculate the variance of each window signal, perform data compression, and obtain the first signal;

[0145] The original signal is win 1 =120, stride 1 = 60 for sliding window processing, through Calculate the variance s of each window signal, perform data compression, and obtain the first signal, such as Figure 4 shown.

[0146] Step 4: Draw a graph to observe the first signal, and the data of different signal segments in the first signal are in the same order of magnitude;

[0147] The key to data extraction is to divide the data in different states into different orders of magnitude. The order of magnitude of the data in the running segment and the static segment is 10 -1 ~10 -3 The difference in magnitude is small and difficult to distinguish.

[0148] Step 5: Determine the window size win for the second sliding window 2 and stride 2 ;

[0149] Sampling frequency of the first signal The Fourier transform result of the first signal is as follows Figure 5 As shown, f is obtained from the figure max1 =12.3Hz, calculate win 2 The value range of Win2 =40, stride 2 = 20, and the second signal is obtained through sliding window processing as Figure 6 shown.

[0150] Step 501: Obtain the first signal sampling frequency Fourier transforming the first signal;

[0151] Step 502: Obtain the resonance frequency f according to the Fourier transform result max1 ;

[0152] Step 503: Determine the window size win according to the resonance frequency and sampling theorem 2 and stride 2 ;

[0153] Step 6: Perform sliding window processing on the first signal, calculate the variance of each window signal, perform data compression, and obtain the second signal;

[0154] The magnitude of the data in the second signal in different states is divided into the magnitude of the running segment signal in the second signal between 10 -2 The order of magnitude of static segment data is within 10 -4 above.

[0155] Step 7: Determine the threshold magnitude for distinguishing the running segment and the non-running segment data;

[0156] The magnitude of the data discrimination threshold is determined according to the second signal. In order to reduce the influence of errors, 10 -4 As the threshold for extracting the uniform speed segment of the data.

[0157] Step 8: Find the starting point start and the end point last of the running segment, and restore the original signal to obtain the running segment signal;

[0158] Find the starting point and end point of the running segment according to the above threshold, and restore it to the original signal. The value range of the starting point of the running segment of the original signal is End point value range The automatic interception results of the original vibration signal running segment are as follows Figure 7 The number of manually intercepted sampling points is less than that of automatically intercepted sampling points, which proves that this method is more accurate than the manual method.

[0159] Step 9: Calculate the center point mid of the running section and calculate the uniform speed running time t according to the actual working conditions 1 , restore to the original signal;

[0160] According to the above start and last, calculate The value range of the midpoint of the uniform speed segment in the original signal According to the midpoint meaning Obtain the uniform speed running time length t according to the actual working conditions 1 =37.5s, the range of uniform speed data The length of the uniform speed segment is 375000. The result of automatic interception of the uniform speed segment of the original vibration signal is as follows: Figure 8 shown.

[0161] Step 10: Error analysis through the starting point and end point signal interception methods and the midpoint signal interception method.

[0162] Analyze the error sources in restoring the second signal to the original signal. Fig. 9 It is shown that one signal point in the second signal represents 1200 points in the original signal. The error of intercepting the original signal by selecting the starting point and end point method is larger than that of intercepting the original signal by selecting the midpoint method. Selecting the midpoint method to intercept the uniform speed signal in the original signal can ensure that the error is controlled within 600 sampling points. Compared with the sampling frequency of 10000Hz, the error is within the allowable range. The above method can not only ensure the reduction of errors, but also ensure that the intercepted signal length is the same under the same working conditions and the same speed.

[0163] As an embodiment, the acceleration sensor is installed on the ball screw nut, the bearing seat, and the motor seat. The sampling frequency of the sensor is f s The speed is 10000Hz and the lead screw speed is 100r / min. Data collection starts when the test bench starts running. After clicking Start, the load adjustment process of the test bench is in a static state, loaded to a certain value, accelerated to the target speed in the positive direction, and after running at a constant speed for a period of time, it decelerates to zero before reaching the other end of the lead screw, and the load is released.

[0164] Example 2

[0165] As an embodiment, the acceleration sensor is installed on the lead screw nut, the bearing seat, and the motor seat. The sampling frequency of the sensor is 10000Hz and the speed is 100r / min. When the test bench starts running, data collection begins. After clicking start, the load adjustment process of the test bench is in a static state, loaded to a certain value, and accelerated to the target speed in the forward direction. After running at a constant speed for a period of time, it decelerates to zero before reaching the other end of the lead screw, releases the load, and repeats the above process in the reverse direction. Collect a complete vibration signal during the reciprocating motion process including static, accelerated, uniform speed, decelerated, static, reverse acceleration, reverse uniform speed, and reverse deceleration.

[0166] Based on the process of Example 1, the vibration signal of the ball screw workbench collected in the above example is intercepted. The above signal contains the forward and reverse running process, and the signal should contain the two-end running section and the uniform speed section. The result of automatic interception of the forward and reverse running section of the original vibration signal is as follows: Fig.10 As shown, the original vibration signal is automatically intercepted in the forward and reverse uniform speed running sections. Fig.11 It is verified that the present invention can extract multiple uniform speed signals contained in one acquisition signal.

[0167] Example 3

[0168] The current sensor is installed on the screw nut, bearing seat, and motor seat. The sampling frequency of the sensor is 10000Hz and the speed is 1100r / min. When the test bench starts running, data collection begins. After clicking start, the load adjustment process of the test bench is in a static state, loaded to a certain value, and accelerated to the target speed in the forward direction. After running at a constant speed for a period of time, it decelerates to zero before reaching the other end of the screw, releases the load, and repeats the above process in the reverse direction.

[0169] Based on the process of Example 1, the current signal in the above example is intercepted, and the result of automatic interception of the original current signal running section is as follows: Fig.12 As shown, the original current signal uniform speed segment automatic interception result is as follows Fig.13 The present invention is not only applicable to vibration signals and low-speed signals, but also can efficiently capture other signals such as current signals and signals collected under high-speed conditions.

[0170] Based on the process of Example 1, in addition to being used to intercept the uniform speed running segment signal of the ball screw, the method of the present invention can also be used to intercept the uniform speed running segment signal of mechanical equipment such as tool processing acquisition signals containing multiple repeated processes, bearing operation, traction machines, centrifuges, motors, etc.

[0171] In summary, the present invention proposes a method for automatically intercepting high-frequency signals of uniform-speed running sections of mechanical equipment, which can accurately complete the extraction of uniform-speed running section data of high-frequency signals such as vibration signals and current signals, and can also realize the extraction of multiple uniform-speed running section data in the same signal. The realization of automatic interception of high-frequency signals of uniform-speed running sections of mechanical equipment can improve the efficiency of data preprocessing, and efficiently complete the interception of different signals and multiple uniform-speed running section signals, which will greatly reduce the time cost in the data preprocessing stage.

[0172] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0173] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0174] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the present invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0175] In the embodiments provided by the present invention, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0176] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0177] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0178] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0179] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices, and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, 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 generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0180] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0181] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0182] The above contents are only for explaining the technical idea of ​​the present invention and cannot be used to limit the protection scope of the present invention. Any changes made on the basis of the technical solution in accordance with the technical idea proposed by the present invention shall fall within the protection scope of the claims of the present invention.

Claims

1. A method for automatically capturing high-frequency signals of a mechanical device in a uniform speed operation section, characterized in that: The following steps are involved: S1. Obtain signal data of the entire process of mechanical equipment; S2, determine the window size win1 and step length stride1 of the first sliding window processing; S3, performing sliding window processing on the original signal, calculating the variance of each window signal, performing data compression, and obtaining a first signal; S4. Perform visual judgment on the first signal to determine whether signals in different operating states in the first signal are in the same order of magnitude; S5, determine the window size win2 and step size stride2 of the second sliding window processing; S6, performing sliding window processing on the first signal, calculating the variance of each window signal, and obtaining a second signal through data compression; S7, determining a threshold magnitude for distinguishing between running segment data and non-running segment data; S8, finding the starting point start and the end point last of the running segment, and restoring the original signal to obtain the running segment signal; S9, calculate the center point mid of the running section, calculate the uniform speed running time t1 according to the actual working conditions, restore to the original signal, and obtain the uniform speed running section signal; S10, performing error analysis on the signal interception method through the starting point and the end point and the signal interception method through the midpoint respectively.

2. The method for automatically capturing high-frequency signals of a mechanical device in a uniform speed operation section according to claim 1 is characterized in that: In step S1, a complete cycle signal during the operation of the mechanical equipment includes a non-operating segment signal, an acceleration / deceleration segment signal, and a uniform speed segment signal.

3. The method for automatically capturing high-frequency signals of a mechanical device in a uniform speed operation section according to claim 1 is characterized in that: Step S2 is specifically as follows: S201, obtain the original signal sampling frequency f s ,Fourier transform of the original signal; S202, according to the Fourier transform result, obtain the resonance frequency f max ; S203. Determine the window size win1 and the step size stride1 according to the resonance frequency and the sampling theorem.

4. The method for automatically capturing high-frequency signals of a mechanical device in a uniform speed operation section according to claim 1 is characterized in that: Step S4 is specifically as follows: If they are in the same order of magnitude, continue to step S5; if they are not in the same order of magnitude, jump to step S6.

5. The method for automatically capturing high-frequency signals of a mechanical device in a uniform speed operation section according to claim 1 is characterized in that: Step S5 is specifically as follows: S501, obtaining the first signal sampling frequency f s1 , Fourier transform the first signal; S502, according to the Fourier transform result, obtain the resonance frequency f max1 ; S503: Determine the window size win2 and the step size stride2 according to the resonance frequency and the sampling theorem.

6. The method for automatically capturing high-frequency signals of a mechanical device in a uniform speed operation section according to claim 1 is characterized in that: In step S6, two variance calculations are performed, and the running segment and stationary segment data are compressed again to compress the data to different orders of magnitude; the segmented order of magnitude of the data collected by the same mechanical equipment under the same working conditions remains basically consistent.

7. The method for automatically capturing high-frequency signals of a mechanical device in a uniform speed operation section according to claim 1 is characterized in that: In step S7, according to the second signal and the order of magnitude of the determined running state division threshold, the start and end points of the running segment signal are determined in the second signal, and the original signal is restored. End point value range 8. The method for automatically capturing high-frequency signals of a mechanical device in a uniform speed operation section according to claim 1 is characterized in that: In step S8, according to start and last, The value range of the midpoint of the uniform speed segment in the original signal According to the midpoint meaning According to the actual working conditions, the uniform speed running time length t1 is obtained, and the range of uniform speed segment data is 9. The method for automatically capturing high-frequency signals of a mechanical device in a uniform speed operation section according to claim 1 is characterized in that: In step S9, the error source in restoring the second signal to the original signal is analyzed to be a signal point in the second signal representing the original signal. points; compare the error restored to the original signal through the starting point and end point with the error restored to the original signal through the midpoint, and choose the midpoint method to intercept the uniform speed segment signal in the original signal.

10. A system for automatically capturing high-frequency signals during uniform-speed operation of mechanical equipment, characterized in that: include: Data module, to obtain signal data of the entire process of mechanical equipment; Determine the window size win1 and step size stride1 for the first sliding window processing; The first processing module performs sliding window processing on the original signal, calculates the variance of each window signal, performs data compression, and obtains the first signal; and visualizes the first signal to determine whether the signals in different operating states in the first signal are in the same order of magnitude; The second processing module determines the window size win2 and the step size stride2 of the second sliding window processing; performs sliding window processing on the first signal, calculates the variance of each window signal, performs data compression, and obtains the second signal; A restoration module determines a threshold magnitude for distinguishing between running segment data and non-running segment data; Find the starting point start and the end point last of the running segment, and restore the original signal to obtain the running segment signal; The output module calculates the center point mid of the running section, calculates the uniform speed running time t1 according to the actual working conditions, restores the original signal, and obtains the uniform speed running section signal; the error analysis is performed on the signal interception method passing through the starting point and end point and the signal interception method passing through the midpoint respectively.

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