A method for calculating and processing amplitude spectrum and a method for diagnosing equipment faults

Abstract

The present invention discloses an amplitude spectrum calculation and processing method and an equipment fault diagnosis method, the processing method comprising: collecting a vibration time domain signal or a current time domain signal of an equipment; converting the collected time domain signal into a frequency domain signal; calculating the amplitude of the frequency domain signal to obtain initial amplitude spectrum data; searching for k amplitude maximum value points in the initial amplitude spectrum data; recalculating the spectrum value of each amplitude maximum value point in the following manner: searching for spectrum leakage points on both sides of the currently traversed amplitude maximum value point, and determining the number d of spectrum leakage points on the left side of the amplitude maximum value point 1 and the number of spectrum leakage points on the right side d 2 ; Calculate the new amplitude at the maximum point of the amplitude as #imgabs0# where m i is the index number of the current traversed amplitude maximum point in the initial amplitude spectrum data set; the amplitude of the amplitude maximum point is replaced by the new amplitude. The present invention effectively solves the spectrum leakage problem of extreme points in the spectrum and greatly improves the accuracy of amplitude spectrum calculation.

Description

Technical Field

[0001] The present invention relates to the field of frequency domain analysis, and particularly to a method for calculating and processing an amplitude spectrum and a method for diagnosing equipment faults. Background Art

[0002] Converting a signal to the frequency domain through a fast Fourier transform (FFT) for spectrum analysis is a commonly used means for vibration analysis of mechanical equipment and current analysis of power equipment. Among them, amplitude spectrum analysis is the most commonly used basic analysis method in spectrum analysis. However, the fast Fourier transform (FFT) of discrete data often causes spectrum leakage near the extreme points, resulting in large errors in the amplitudes of the relevant frequencies in the spectrum. Therefore, how to reduce the calculation error of the amplitude is very important for the accuracy of spectrum analysis.

[0003] The disclosure of the above background art content is only used to assist in understanding the inventive concept and technical solution of the present invention. It does not necessarily belong to the prior art of this patent application, nor does it necessarily provide technical guidance. Without clear evidence that the above content was publicly available before the filing date of this patent application, the above background art should not be used to evaluate the novelty and inventiveness of this application. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for calculating and processing an amplitude spectrum that improves calculation accuracy, which can effectively reduce the interference and influence of spectrum leakage near the extreme points and their vicinity in the spectrum on the calculation result of the amplitude spectrum.

[0005] To achieve the above purpose, the technical solution adopted by the present invention is as follows:

[0006] A method for calculating and processing an amplitude spectrum includes the following steps:

[0007] Collect the vibration time-domain signal or current time-domain signal of the equipment, the number of sampling points is n, n is an integer power of 2, and the collected time-domain signal set is denoted as X = {x1, x2, x3,..., x n};

[0008] Convert the collected time-domain signal into a frequency-domain signal;

[0009] Calculate the amplitude of the frequency-domain signal to obtain initial amplitude spectrum data, and the initial amplitude spectrum data set is denoted as Y = {y1, y2, y3,..., y n / 2};

[0010] Find k amplitude maximum points in the initial amplitude spectrum data and sort them according to the position index to obtain a position index set denoted as M = {m1, m2,..., m k}, m k < n / 2, where m kis the subscript number of the kth amplitude maximum point in the initial amplitude spectrum data set Y;

[0011] Traverse k amplitude maximum points, and recalculate the spectrum value of each amplitude maximum point in the following way: find the spectrum leakage points on both sides of the current amplitude maximum point, determine the number of spectrum leakage points d1 on the left side of the amplitude maximum point and the number of spectrum leakage points d2 on the right side of the amplitude maximum point; calculate the new amplitude as Among them, am is the new amplitude at the maximum point of the amplitude, m i is the subscript number of the current traversed amplitude maximum point in the initial amplitude spectrum data set Y; the amplitude of the amplitude maximum point is replaced by the new amplitude am;

[0012] After the k amplitude maximum points are traversed, the amplitude spectrum data after adjusting the amplitude is output.

[0013] Furthermore, the search for the current maximum amplitude point traversed is The steps of finding the spectrum leakage point on the left side include:

[0014] Calculate the distance between it and the adjacent amplitude maximum point on the left:

[0015]

[0016] According to the preset classification rule, the number d1 of left spectrum leakage points corresponding to the calculation result of Δm is determined.

[0017] Furthermore, the search for the current maximum amplitude point traversed is The steps to find the right spectrum leakage point include:

[0018] Calculate the distance between it and the adjacent amplitude maximum point on the right:

[0019]

[0020] According to the preset classification rule, the number d2 of right spectrum leakage points corresponding to the calculation result of Δm is determined.

[0021] Furthermore, the preset classification rule is to establish a mapping relationship between the distance to the adjacent amplitude maximum value point and the number of spectrum leakage points. The larger the distance is or the larger the interval it belongs to, the larger the number of spectrum leakage points is.

[0022] Furthermore, the number d of spectrum leakage points corresponding to the calculation result of Δm is determined by the following formula:

[0023]

[0024] Further, the number k of amplitude maximum points to be found in the initial amplitude spectrum data is manually specified, or k is the total number of amplitude maximum points in the initial amplitude spectrum data.

[0025] Furthermore, the collected time domain signal is converted into a frequency domain signal using a fast Fourier transform algorithm.

[0026] Furthermore, while the amplitude of the amplitude maximum point is replaced by the new amplitude am, the amplitudes of the spectrum leakage points on the left and right sides of the amplitude maximum point are replaced by 0.

[0027] According to another aspect of the present invention, a mechanical equipment fault diagnosis method is provided, which collects the vibration time domain signal of the mechanical equipment to be diagnosed, and uses the amplitude spectrum calculation and processing method as described above to obtain the vibration velocity amplitude spectrum data after adjusting the amplitude;

[0028] Check whether the 0.5X, 1X, 2X or 3X harmonic amplitude is abnormal to determine whether the mechanical equipment has a shaft system failure.

[0029] According to another aspect of the present invention, a method for diagnosing faults of electric power equipment is provided, which collects a current time domain signal of the electric power equipment to be diagnosed, and uses the amplitude spectrum calculation and processing method as described above to obtain amplitude spectrum data of the current signal after adjusting the amplitude;

[0030] Check whether the amplitude of the power frequency and / or its harmonics is abnormal to determine whether the power equipment has a fault.

[0031] The beneficial effects brought by the technical solution provided by the present invention are as follows:

[0032] a. The new amplitude at each amplitude maximum point is recalculated by determining the number of spectrum leakage points on the left and right sides of the amplitude maximum point, which effectively reduces the interference and influence of spectrum leakage at the extreme point in the spectrum and its vicinity on the amplitude spectrum calculation results, and improves the calculation accuracy of the amplitude spectrum.

[0033] b. It only needs to adjust the amplitude of the extreme value points of interest, which requires little calculation and has almost no impact on performance;

[0034] c. The calculated amplitude spectrum can be used for fault diagnosis of both mechanical equipment and electrical equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0036] Figure 1 A schematic flow chart of a method for calculating and processing an amplitude spectrum provided by an exemplary embodiment of the present invention;

[0037] Figure 2 A schematic diagram of an amplitude spectrum before amplitude correction processing provided for an exemplary embodiment of the present invention;

[0038] Figure 3 for Figure 2 Schematic diagram of the amplitude spectrum after the amplitude correction processing of the amplitude spectrum in FIG.

[0039] Figure 4 An exemplary embodiment of the present invention provides a method for utilizing Figure 1 The schematic diagram of the flow chart of the amplitude spectrum calculation processing method for diagnosing mechanical equipment failures;

[0040] Figure 5 An exemplary embodiment of the present invention provides a method for utilizing Figure 1 The figure shows a flow chart of the amplitude spectrum calculation and processing method for diagnosing power equipment faults. DETAILED DESCRIPTION

[0041] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme 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 only 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 should fall within the scope of protection of the present invention.

[0042] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, device, product or equipment that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or equipment.

[0043] Fault diagnosis of mechanical and electrical equipment by analyzing the amplitude spectrum is a common method for equipment fault diagnosis. The amplitude spectrum is the amplitude data of the frequency-domain signal obtained by performing a fast Fourier transform (FFT) on the time-domain signal. Then, by calculating the amplitudes at each frequency point, the amplitude / frequency data can be obtained, and the reference amplitude at the relevant frequency can be searched and compared to determine whether the equipment has a fault. However, after the discrete time-domain data is transformed into the frequency-domain signal by the fast Fourier transform (FFT), spectral leakage often occurs. When the spectral leakage is severe, it may even seriously affect the numerical judgment.

[0044] In an embodiment of the present invention, a method for calculating and processing the amplitude spectrum is provided. As Figure 1 shown, the method for calculating and processing the amplitude spectrum includes the following steps:

[0045] Collect the vibration time-domain signal or current time-domain signal of the equipment. The number of sampling points is n, where n is an integer power of 2. The collected time-domain signal set is denoted as X = {x1, x2, x3,..., x n};

[0046] Use the fast Fourier transform algorithm to transform the collected time-domain signal into a frequency-domain signal;

[0047] Calculate the amplitude of the frequency-domain signal to obtain the initial amplitude spectrum data. The initial amplitude spectrum data set is denoted as Y = {y1, y2, y3,..., y n / 2};

[0048] Find k amplitude maximum points in the initial amplitude spectrum data and sort them according to the position index to obtain the position index set denoted as M = {m1, m2,…, m k}, where m k < n / 2, and m k is the subscript number of the k-th amplitude maximum point in the initial amplitude spectrum data set Y;

[0049] Traverse the k amplitude maximum points, and recalculate the spectrum value for each amplitude maximum point in the following way: Find the spectral leakage points on both sides of the currently traversed amplitude maximum point, and determine the number d1 of spectral leakage points on the left side and the number d2 of spectral leakage points on the right side of this amplitude maximum point; Calculate the new amplitude as where am is the new amplitude at this amplitude maximum point, and m iis the subscript number of the currently traversed amplitude maximum point in the initial amplitude spectrum data set Y; the amplitude of the amplitude maximum point is replaced with the new amplitude am; at the same time, the amplitudes of the spectrum leakage points on the left and right sides of the amplitude maximum point are replaced with 0 (or amplitudes close to 0, such as 0.1, 0.2, 0.3 or any value less than 0.5); in one embodiment, for example, the calculation results of d1 and d2 are 2 and 4 respectively, then the amplitudes of the two adjacent points on the left and the four adjacent points on the right of the amplitude maximum point are replaced with 0.

[0050] After the k amplitude maximum points are traversed, the amplitude spectrum data after adjusting the amplitude is output.

[0051] In a specific embodiment, the step of searching for the current maximum amplitude point is The steps of finding the spectrum leakage point on the left side include:

[0052] Calculate the distance between it and the adjacent amplitude maximum point on the left:

[0053]

[0054] According to the preset classification rule, the number d1 of left spectrum leakage points corresponding to the calculation result of Δm is determined.

[0055] Find the current maximum amplitude point traversed The steps for finding the spectrum leakage point on the right side of the spectrum are the same as finding the current amplitude maximum point traversed The steps of finding the spectrum leakage point on the left side include:

[0056] Calculate the distance between it and the adjacent amplitude maximum point on the right:

[0057]

[0058] According to the preset classification rule, the number d2 of right spectrum leakage points corresponding to the calculation result of Δm is determined.

[0059] The preset classification rule is to establish a mapping relationship between the distance to the adjacent amplitude maximum point and the number of spectrum leakage points. The larger the distance or the larger the interval to which it belongs, the larger the number of spectrum leakage points. For example, the number of spectrum leakage points d corresponding to the calculation result of Δm is determined by the following formula:

[0060] The present invention is not limited to this mapping relationship, but can specifically divide the interval segments of Δm and the number of leakage points associated with each interval segment according to actual conditions.

[0061] The number k of amplitude maximum points to be searched in the initial amplitude spectrum data is manually specified, or k is the total number of amplitude maximum points in the initial amplitude spectrum data. The former only needs to select the k amplitude maximum points of greatest concern / relative concern, and recalculate the new amplitude am for them. The calculation amount of amplitude adjustment is small, the processing efficiency is high, and the performance requirements can be better met; the latter adjusts the amplitude of all amplitude maximum points. Although the processing efficiency is slightly sacrificed compared to the former, the accuracy of the amplitude spectrum calculation result after adjustment reaches the upper limit.

[0062] The following specific embodiment is used as an illustration:

[0063] The time domain signal is sampled with 8192 sampling points and a sampling rate of f s =16384, the signal generation formula is as follows:

[0064]

[0065] After transforming the signal data into frequency domain signal by FFT, the amplitude is calculated and the amplitudes of the five maximum points are 13.06, 15, 5, 3.85, and 4 respectively. The amplitude spectrum is shown in Figure 2 As shown in the above signal generation formula, the five theoretical maximum points should be 20, 15, 5, 6, and 4. Figure 2 It can be determined that the actual amplitude at a frequency of 25Hz is 13.06, which has serious spectrum leakage compared to the theoretical amplitude of 20; similarly, the actual amplitude at a frequency of 125Hz is 3.85, which has serious spectrum leakage compared to the theoretical amplitude of 6. If the amplitude is not corrected, the amplitude at 25Hz is lower than the amplitude at 50Hz (the value is 15), and the amplitude at 125Hz is lower than the amplitude at 100Hz (the value is 5), which will seriously affect the accuracy of the analysis results, that is, affect the diagnosis of equipment failures.

[0066] The processing method of the embodiment of the present invention is used to correct the amplitudes of the two spectrum leakages mentioned above, using the formula The amplitude loss caused by spectrum leakage is compensated, and the amplitudes of the 5 corrected / adjusted maximum points are 19.7, 15, 5, 5.9, and 4 respectively. In a further embodiment, the amplitudes of the d1 points adjacent to the left of the 25Hz point and the d2 points adjacent to the right are replaced with 0, and similarly, the amplitudes of the leakage points on both sides of 125Hz are replaced with 0. The amplitude spectrum is shown in FIG. Figure 3As shown, it can be seen that the new amplitude with severe spectrum leakage after adjustment is very close to the true value, and the amplitude of the extreme point without spectrum leakage is also not affected. Therefore, the present invention has a very good application effect and can avoid wrong judgment caused by amplitude calculation error. Since spectrum leakage is caused by FFT algorithm, the calculation and processing method in the present invention is also applicable to all analysis methods that perform frequency domain analysis by FFT, such as energy spectrum, power spectrum, etc.

[0067] In one embodiment of the present invention, a mechanical equipment fault diagnosis method is provided, such as Figure 4 As shown, the vibration time domain signal of the mechanical equipment to be diagnosed is collected, and the amplitude spectrum calculation and processing method as described above is used to obtain the vibration velocity amplitude spectrum data after adjusting the amplitude;

[0068] Check whether the 0.5X, 1X, 2X or 3X harmonic amplitude is abnormal to determine whether the mechanical equipment has a shaft system failure.

[0069] In one embodiment of the present invention, a method for diagnosing faults of electric power equipment is provided. Figure 5 As shown, the current time domain signal of the power equipment to be diagnosed is collected, and the amplitude spectrum data of the current signal after adjusting the amplitude is obtained by using the amplitude spectrum calculation and processing method as described above;

[0070] Check whether the amplitude of the power frequency and / or its harmonics is abnormal to determine whether the power equipment has a fault.

[0071] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0072] The above is only a specific implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for calculating and processing an amplitude spectrum, characterized in that: The following steps are involved: The vibration time domain signal or current time domain signal of the equipment is collected. The number of sampling points is n, where n is a power of 2 integer. The collected time domain signal set is recorded as X = {x1, x2, x3, ..., x n }; Convert the collected time domain signal into a frequency domain signal; Calculate the amplitude of the frequency domain signal to obtain initial amplitude spectrum data, and the initial amplitude spectrum data set is recorded as Y = {y1, y2, y3, ..., y n / 2 }; Find k amplitude maximum points in the initial amplitude spectrum data, and sort them according to the position index to obtain a position index set denoted as M = {m1, m2, …, m k}, m k < n / 2, where m k is the subscript number of the k-th amplitude maximum point in the initial amplitude spectrum data set Y; Traverse k amplitude maximum points, and recalculate the spectrum value of each amplitude maximum point in the following way: find the spectrum leakage points on both sides of the current amplitude maximum point, determine the number of spectrum leakage points d1 on the left side of the amplitude maximum point and the number of spectrum leakage points d2 on the right side of the amplitude maximum point; calculate the new amplitude as Among them, am is the new amplitude at the maximum point of the amplitude, m i is the subscript number of the current traversed amplitude maximum point in the initial amplitude spectrum data set Y; the amplitude of the amplitude maximum point is replaced by the new amplitude am; After the k amplitude maximum points are traversed, the amplitude spectrum data after adjusting the amplitude is output.

2. The amplitude spectrum calculation method according to claim 1, characterized in that: The search for the current traversed amplitude maximum point The steps of finding the spectrum leakage point on the left side include: Calculate the distance between it and the adjacent amplitude maximum point on the left: According to the preset classification rule, the number d1 of left spectrum leakage points corresponding to the calculation result of Δm is determined.

3. The amplitude spectrum calculation method according to claim 1, characterized in that: The search for the current traversed amplitude maximum point The steps to find the right spectrum leakage point include: Calculate the distance between it and the adjacent amplitude maximum point on the right: According to the preset classification rule, the number d2 of right spectrum leakage points corresponding to the calculation result of Δm is determined.

4. The amplitude spectrum calculation processing method according to claim 2 or 3, characterized in that: The preset classification rule is to establish a mapping relationship between the distance to the adjacent amplitude maximum value point and the number of spectrum leakage points. The larger the distance is or the larger the interval it belongs to, the larger the number of spectrum leakage points is.

5. The amplitude spectrum calculation method according to claim 2 or 3, characterized in that: The number of spectrum leakage points d corresponding to the calculation result of Δm is determined by the following formula:

6. The amplitude spectrum calculation method according to claim 1, characterized in that: The number k of amplitude maximum points to be found in the initial amplitude spectrum data is manually specified, or k is the total number of amplitude maximum points in the initial amplitude spectrum data.

7. The amplitude spectrum calculation method according to claim 1, characterized in that: The collected time domain signal is converted into frequency domain signal using the fast Fourier transform algorithm.

8. The amplitude spectrum calculation and processing method according to any one of claims 1, 2, 3, 6, and 7, characterized in that: While the amplitude of the amplitude maximum point is replaced by the new amplitude am, the amplitudes of the spectrum leakage points on the left and right sides of the amplitude maximum point are replaced by 0.

9. A mechanical equipment fault diagnosis method, characterized in that: Collecting the vibration time domain signal of the mechanical equipment to be diagnosed, and obtaining the vibration velocity amplitude spectrum data after adjusting the amplitude thereof by using the amplitude spectrum calculation and processing method described in any one of claims 1 to 8; Check whether the 0.5X, 1X, 2X or 3X harmonic amplitude is abnormal to determine whether the mechanical equipment has a shaft system failure.

10. A method for diagnosing faults in electric power equipment, characterized in that: Collecting a current time domain signal of the power equipment to be diagnosed, and obtaining amplitude spectrum data of the current signal after adjusting the amplitude using the amplitude spectrum calculation and processing method according to any one of claims 1 to 8; Check whether the amplitude of the power frequency and / or its harmonics is abnormal to determine whether the power equipment has a fault.

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