A discrete frequency spectrum correction method and device for mechanical equipment rotating speed measurement

Abstract

The application provides a discrete spectrum correction method and device for mechanical equipment rotating speed measurement, and belongs to the technical field of measurement. The method comprises the following steps: obtaining a vibration signal of a mechanical equipment with rotating structure; performing fast Fourier transform on the vibration signal after cutting and windowing to obtain a discrete spectrum corresponding to the cut vibration signal; obtaining a half-peak width of a spectrum peak where a main frequency is located; taking corresponding frequencies and amplitudes of spectrum lines within twice the half-peak width as fitting data; and calculating, according to the fitting data and a preset fitting curve, a parameter value closest to the fitting curve and the fitting data in the least square sense, wherein the parameter comprises a fitted center frequency of the spectrum peak, so as to correct the discrete spectrum. The application can fully utilize information contained in other spectrum lines except peak spectrum lines in the main lobe, and realize more accurate correction of the discrete spectrum.

Description

Technical Field

[0001] This invention belongs to the field of measurement technology, specifically relating to a discrete spectrum correction method and device for measuring the rotational speed of mechanical equipment. Background Technology

[0002] Rotating structures are widely found in various types of mechanical equipment, such as steam turbines, generators, electric motors, and water pumps. These devices all contain rotating structures directly related to their core functions. The motion state of these rotating structures can reflect the working state of the mechanical equipment. Therefore, accurately measuring the rotational speed of these rotating structures is crucial, as it can be used to monitor the operating status of the mechanical equipment and indirectly measure various key technical parameters.

[0003] During the operation of mechanical equipment, due to the slight deviation between the center of gravity and the center of rotation of the rotating structure, and the influence of other moving parts reciprocating under the influence of the rotating structure, the rotating structure generates corresponding vibration signals, which are then propagated to the surface of the mechanical equipment. The energy of these vibration signals is mainly distributed at multiple frequency points near or at the same frequency as the rotating structure or its harmonics. Therefore, by analyzing the frequency components of the vibration signals on the surface of the mechanical equipment, the rotational speed of its internal rotating structure can be indirectly measured.

[0004] Generally, the method for measuring the frequency components of a vibration signal is as follows: First, the vibration signal is acquired by a vibration sensor placed on the surface of the mechanical equipment. This signal is then truncated and windowed to obtain a fixed-length vibration signal. Next, a Fast Fourier Transform (FFT) is performed on this signal to obtain its corresponding discrete spectrum. Finally, the highest amplitude peak in the discrete spectrum is extracted, and its frequency is converted into the rotational speed of the mechanical equipment. However, since the spectrum obtained by the FFT is discrete in the frequency domain, directly reading the peak frequency will only yield an integer multiple of the spectral resolution, which may lead to significant measurement errors.

[0005] The technique for correcting the discreteness of the spectrum in the above measurement methods to obtain more accurate spectral parameters is called "discrete spectrum correction technique." Using discrete spectrum correction technique to analyze vibration signals can more accurately determine the peak frequency of the spectrum, thereby improving the measurement accuracy of the rotational speed of rotating structures in mechanical equipment.

[0006] Currently, there are several commonly used methods in discrete frequency correction techniques. Duan Huming's review of discrete frequency correction methods summarizes the following seven methods for correcting single-frequency component signals: energy method, ratio method, phase difference method, golden section method, correction method to eliminate the influence of negative frequencies, small deviation correction method, and triangle method. These methods are suitable for single-frequency component signals, and the vibration signals generated by rotating structures on the surface of mechanical equipment are usually single-frequency signals; therefore, these methods can be used for discrete frequency correction of vibration signals. The specific discrete frequency correction technique chosen depends on the characteristics of the target signal.

[0007] The specific implementation of these discrete spectrum correction methods will be introduced below using the triangle method as an example.

[0008] Let L be the discrete spectrum obtained by FFT of the original signal, where the amplitude of the i-th spectral line is L(i) and the corresponding frequency is f. i Let the spectral line with the largest amplitude be the k-th spectral line, and let the center frequency of the uncorrected peak of the k-th spectral line be f. k The center frequency of the corrected spectral peak is In the calculation process, 2m+1 spectral lines from km to k+m are used for calculation, where m is a positive integer and both km and k+m are within the spectrum range.

[0009] The amplitudes of 2m+1 spectral lines on either side of the k-th spectral line are taken as the processing objects of the correction algorithm, where L(ki) is the amplitude of the i-th spectral line to the left of the k-th spectral line, and L(k+i) is the amplitude of the i-th spectral line to the right of the k-th spectral line, i≤m. First, the correction amount of the k-th spectral line is obtained by the following formula. Then, the corrected center frequency of the k-th spectral line can be obtained according to the following formula.

[0010] Similarly, the ratio rule directly uses the spectral line with the largest amplitude (i.e., the k-th spectral line) and its two adjacent spectral lines, a total of three spectral lines, for correction. That is, taking m=1, the corresponding correction amount is... Where v is the ratio of the window spectral functions of the two spectral lines near the main lobe peak with a difference of 1 after normalization, and the corresponding frequency correction formula is:

[0011] The aforementioned mainstream discrete spectrum correction techniques for single-frequency component signals each have their own applicable scenarios and limitations. The energy method and ratio method require that the window function used in the truncation and windowing process be symmetrical, and that the signal's spectral peaks themselves possess symmetry. This makes these methods unsuitable for situations where the signal's spectral peaks or window functions are asymmetrical. The ratio method and triangle method only utilize spectral lines within a fixed range around the spectral line with the maximum amplitude, ignoring the information contained in other spectral lines. Therefore, they lack adaptability to spectral signals with different peak widths, and the results are highly dependent on the parameter selection. Summary of the Invention

[0012] The purpose of this invention is to overcome the shortcomings of existing mainstream discrete spectrum correction techniques for single-frequency component signals, and to propose a discrete spectrum correction method and device for measuring the rotational speed of mechanical equipment. This invention is applicable to both traditional methods and special cases with asymmetrical spectral peaks; it can fully utilize the information contained in spectral lines other than the peak line within the main lobe to achieve more accurate correction of the discrete spectrum.

[0013] A first aspect of this invention provides a discrete spectrum correction method for measuring the rotational speed of mechanical equipment, comprising:

[0014] Acquire vibration signals from mechanical equipment with rotating structures;

[0015] After truncating and windowing the vibration signal, a fast Fourier transform is performed to obtain the discrete spectrum corresponding to the truncated vibration signal.

[0016] Obtain the half-peak width of the spectral peak where the main frequency is located in the discrete spectrum, and use the corresponding frequency and amplitude of the spectral line within twice the half-peak width as the fitting data;

[0017] Based on the fitted data and the preset fitted curve, calculate the parameter value that is closest to the fitted curve and the fitted data in the least squares sense, wherein the parameter includes the center frequency of the fitted spectrum peak, so as to correct the discrete spectrum.

[0018] In one specific embodiment of the present invention, before truncating and windowing the vibration signal, the method further includes:

[0019] The vibration signal is filtered and amplified.

[0020] In one specific embodiment of the present invention, the method further includes:

[0021] The length of the truncated vibration signal is greater than or equal to 60 / Δf seconds, where Δf is the frequency resolution of the discrete spectrum.

[0022] In a specific embodiment of the present invention, the method for obtaining the spectral peak where the dominant frequency is located in the discrete spectrum is as follows:

[0023] Using a peak extraction algorithm, select the spectral peak data with the highest amplitude (h) from the discrete spectrum, where h is a positive integer;

[0024] The corresponding frequencies of the selected h spectral peaks are determined as follows: if there is a positive integer multiple relationship of less than 5 among the corresponding frequencies of the h spectral peaks, then the spectral peak corresponding to the fundamental frequency among the h spectral peaks is selected as the spectral peak where the main frequency is located; otherwise, the spectral peak with the highest amplitude among the h spectral peaks is selected as the spectral peak where the main frequency is located.

[0025] In a specific embodiment of the present invention, obtaining the half-peak width of the spectral peak where the dominant frequency is located in the discrete spectrum, and using the corresponding frequencies and amplitudes of spectral lines within twice the half-peak width as fitting data, includes:

[0026] Let the spectral line with the largest amplitude in the spectral peak where the dominant frequency is located be the k-th spectral line, and find the smallest positive integer k. - To satisfy the condition that there exists to the left of the kth spectral line Find the smallest positive integer k + To satisfy the condition that there exists to the right of the kth spectral line Among them, L(kk) - ) is the kth - The amplitude of each spectral line, L(k+k + ) is the k+kth + The amplitude of each spectral line, where L(k) is the amplitude of the k-th spectral line;

[0027] Then the (k-2k)th peak in the spectrum where the main frequency is located - up to the (k+2k)th + The corresponding frequency and amplitude of each spectral line are the fitted data.

[0028] In one specific embodiment of the present invention, the calculation of the parameter value that most closely approximates the fitted curve and the fitted data in the least squares sense adopts any one of the LM algorithm, the Dogleg algorithm, and the trust region algorithm.

[0029] In one specific embodiment of the present invention, the LM algorithm includes:

[0030] 1) Set the initial iteration count n = 0; determine the function F(x,a), independent variable x, and fitting object for the fitted curve. The initial value of the damping factor is λ0, and the growth rate is v, where the fitting parameters are a = (μ, h, d). T, where μ represents the center frequency of the spectral peak, h represents the amplitude of the spectral peak, and d represents the peak width of the spectral peak; the independent variable x is the corresponding frequency of the spectral line in the fitting data, and the fitting object is the corresponding amplitude of the spectral line in the fitting data;

[0031] let the initial value of the fitting parameter a0=(μ0, h0, d0) T , wherein the initial value μ0 of the center frequency of the spectral peak takes the corresponding frequency of the k-th spectral line, the initial value h0 of the amplitude of the spectral peak takes the amplitude of the k-th spectral line, and the initial value d0 of the peak width of the spectral peak takes the width of the spectral peak where the main frequency is located;

[0032] 2) Calculate the predicted value y of the n-th iteration n =F(x,a n ), where a n is the parameter value of the n-th iteration;

[0033] 3) Calculate the loss function of the n-th iteration

[0034] 4) Calculate the correction term where J is the Jacobian matrix of the loss function with respect to each parameter, λ n is the value of the damping factor in the n-th iteration, and I is the identity matrix;

[0035] 5) Calculate the parameter value a of the (n+1)-th iteration n+1 =a n -h LM ;

[0036] 6) Calculate the predicted value y of the (n+1)-th iteration n+1 =F(x,a n+1 ), then calculate the loss function of the (n+1)-th iteration

[0037] 7) Determination: if ||h LM ||2<min is satisfied, the iteration is completed, and the parameter value a of the n-th iteration n is used as the final fitting parameter value, and μ of the n-th iteration in a n n is the center frequency of the spectral peak obtained by fitting; otherwise, proceed to step 8);

[0038] wherein min is a preset threshold;

[0039] 8) Determination: if S n+1 >S n is satisfied, update the damping coefficient λ of the (n+1)-th iteration n+1 =λ n ·ν; otherwise, update λ n+1 =λ​n / ν;

[0040] 9) Let n = n + 1, then return to step 4).

[0041] A second aspect of the present invention provides a discrete spectrum correction device for measuring the rotational speed of mechanical equipment, comprising:

[0042] The signal acquisition module is used to acquire vibration signals from mechanical equipment with a rotating structure.

[0043] The discrete spectrum acquisition module is used to truncate and window the vibration signal and then perform a fast Fourier transform to obtain the discrete spectrum corresponding to the truncated vibration signal.

[0044] The fitting data extraction module is used to obtain the half-peak width of the spectral peak where the main frequency is located in the discrete spectrum, and to use the corresponding frequency and amplitude of the spectral line within twice the half-peak width as fitting data.

[0045] The correction module is used to calculate, in the least squares sense, the parameter value that makes the fitted curve and the fitted data closest to each other based on the fitted data and the preset fitted curve, wherein the parameter includes the center frequency of the fitted spectral peak, so as to correct the discrete spectrum.

[0046] A third aspect of the present invention provides an electronic device comprising:

[0047] At least one processor; and a memory communicatively connected to said at least one processor;

[0048] The memory stores instructions that can be executed by the at least one processor, the instructions being configured to perform the aforementioned discrete spectrum correction method for measuring the rotational speed of mechanical equipment.

[0049] A fourth aspect of the present invention provides a computer-readable storage medium storing computer instructions for causing the computer to execute the aforementioned discrete spectrum correction method for measuring the rotational speed of mechanical equipment.

[0050] The features and beneficial effects of this invention are as follows:

[0051] 1) Current common correction techniques are based on the symmetry of the signal's spectral peaks, using spectral lines within a fixed range near the highest spectral line in the peak to correct the parameters of the discrete spectrum. This makes existing techniques unsuitable for special cases where the signal's spectral peaks are asymmetrical, and also unable to adaptively adjust the data range used for correction according to the signal's characteristics. In contrast, this invention can be used for arbitrary spectral peak shapes and can adaptively change the range of data used according to the specific conditions of the signal, thereby utilizing the information hidden in the spectrum to correct the parameters of the discrete spectrum to a greater extent.

[0052] 2) The discrete spectrum correction of this invention is achieved through a fitting method. The function used for fitting can be selected or learned based on the actual problem or historical signals, making this invention adaptable to different vibration signal speed measurement problems. In addition, the fitting method can use data over a large range as the basis for spectrum correction, is relatively insensitive to noise in the signal, and can adaptively change the range of data used according to the characteristics of the signal to achieve better discrete spectrum correction results.

[0053] 3) This invention can be used to solve the problem of measuring the rotational speed of rotating structures in mechanical equipment, achieving adaptive high-precision rotational speed measurement for different mechanical equipment and vibration signals. Furthermore, this invention can also be used in scenarios other than measuring the rotational speed of rotating structures in mechanical equipment, demonstrating excellent versatility. Attached Figure Description

[0054] Figure 1 This invention provides a discrete spectrum correction method for measuring the rotational speed of mechanical equipment. Detailed Implementation

[0055] This invention proposes a discrete spectrum correction method and device for measuring the rotational speed of mechanical equipment, which is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0056] A first aspect of this invention provides a discrete spectrum correction method for measuring the rotational speed of mechanical equipment, comprising:

[0057] Acquire vibration signals from mechanical equipment with rotating structures;

[0058] After truncating and windowing the vibration signal, a fast Fourier transform is performed to obtain the discrete spectrum corresponding to the truncated vibration signal.

[0059] Obtain the half-peak width of the spectral peak where the main frequency is located in the discrete spectrum, and use the corresponding frequency and amplitude of the spectral line within twice the half-peak width as the fitting data;

[0060] Based on the fitted data and the preset fitted curve, calculate the parameter value that is closest to the fitted curve and the fitted data in the least squares sense, wherein the parameter includes the center frequency of the fitted spectrum peak, so as to correct the discrete spectrum.

[0061] In a specific embodiment of the present invention, the discrete spectrum correction method for measuring the rotational speed of mechanical equipment has the following overall process: Figure 1 As shown, it includes:

[0062] 1) Obtain vibration signals from mechanical equipment with rotating structures.

[0063] In this embodiment, vibration sensors deployed on the surface of a rotating mechanical device are used to collect raw vibration signals. The selection and specific placement of the vibration sensors on the surface of the mechanical device need to be determined based on the specific structure of the mechanical device. Generally speaking, the vibration sensors should be placed as close as possible to the vibration source, i.e., the rotating structure. The sampling frequency of the signal should be at least 10 times the upper limit of the target rotational speed.

[0064] In one specific embodiment of the present invention, the mechanical device uses a rotor platform, and the vibration sensor uses an accelerometer to measure the vibration signal in the form of acceleration. Since in actual mechanical devices, the rotating structure is often hidden inside the device and cannot be directly measured, in this embodiment of the present invention, the vibration sensor is arranged on the base of the rotor platform and on the disk driven by the rotor platform to approximate the real situation as closely as possible.

[0065] 2) Filter and amplify the vibration signal obtained in step 1) so that the vibration signal obtained in step 1) meets the requirements of digital signal acquisition.

[0066] In this embodiment, the filtering section uses a bandpass filter to retain the frequency components within the target rotational speed range, eliminating DC components and high-frequency noise. The amplification section requires the amplification factor to match the maximum input range of the digital acquisition card.

[0067] In one specific embodiment of the present invention, the filtering section uses a bandpass filter built with analog circuitry, and the amplification section uses an amplifier circuit that is compatible with the sensor and a digital acquisition circuit.

[0068] 3) The vibration signal processed in step 2) is truncated and windowed.

[0069] In this embodiment, the length of the signal truncation is directly related to the resolution of the resulting discrete spectrum. Assuming the required frequency resolution of the discrete spectrum is ΔfRPM, the length of the signal truncation should be at least 60 / Δf seconds. The truncation position can be randomly selected unless otherwise specified. Windowing is used to suppress the impact of spectral leakage caused by truncation on the signal spectrum. Common windowing methods include rectangular windows, Hamming windows, and Hanning windows.

[0070] In one specific embodiment of the present invention, the required spectral resolution is 30 RPM. Therefore, the signal is truncated to a length of 2 seconds for further analysis. In this embodiment, the Hamming window, which has strong versatility, is used as the windowing function.

[0071] 4) Perform a Fast Fourier Transform (FFT) on the vibration signal after truncation and windowing in step 3) to obtain the discrete spectrum corresponding to the truncation vibration signal, and select the spectral peak where the main frequency is located from the discrete spectrum.

[0072] Typically, the discrete spectrum of a vibration signal generated by a rotating structure consists of multiple frequency components with large spacing, corresponding to multiple spectral peaks spaced at certain distances. The vibration signal usually mainly contains components with the same frequency as or harmonics of the rotating structure, and the dominant frequency is not necessarily the frequency corresponding to the highest spectral peak.

[0073] Therefore, this embodiment uses a peak extraction algorithm to select the highest amplitude spectral peak data from the discrete spectrum, where h is a positive integer and can be arbitrarily selected according to the actual situation. In a specific embodiment of the present invention, the value of h is 3. Then, it is checked whether there is a multiple relationship between the corresponding frequencies of the selected h spectral peaks. To avoid overfitting, if there is a positive integer multiple relationship of less than 5 between the corresponding frequencies of the selected h spectral peaks, then the spectral peak corresponding to the fundamental frequency among the h spectral peaks is selected as the spectral peak where the main frequency is located; otherwise, the spectral peak with the highest amplitude among the h spectral peaks is directly selected as the spectral peak where the main frequency is located.

[0074] 5) Based on the spectrum peak where the main frequency is obtained in step 4), the half-peak width of the spectrum peak is obtained by searching one by one on both sides of the peak frequency of the spectrum peak where the main frequency is located. Then, the corresponding frequencies and amplitudes of the spectral lines within twice the half-peak width are used as fitting data.

[0075] In this embodiment, the spectral line with the largest amplitude in the spectral peak where the main frequency is located is denoted as the k-th spectral line, and the smallest positive integer k is searched. - To satisfy the condition that there exists to the left of the kth spectral line Find the smallest positive integer k + To satisfy the condition that there exists to the right of the kth spectral line This embodiment does not require k. - and k +They are equal. Where L(kk) - ) is the kth _ The amplitude of each spectral line, L(k+k + ) is the k+kth + Let L(k) be the amplitude of the k-th spectral line. Then, the (k-2k)-th spectral line is the peak containing the dominant frequency. - up to the (k+2k)th + The corresponding frequency and amplitude of each spectral line are the fitted data.

[0076] 6) Based on the fitted data obtained in step 5), the Levenberg-Marquardt algorithm (hereinafter referred to as the LM algorithm) is used to calculate the parameter value that is closest to the preset fitted curve and the fitted data in the least squares sense, wherein the parameter includes the center frequency of the peak of the fitted spectrum, so as to correct the discrete spectrum.

[0077] In this embodiment, the curve used for fitting can be freely selected based on the characteristics of the signal and the window function. In a specific embodiment of the present invention, the convolution of the Gaussian function Norm(x) and the corresponding spectral function Sinc(x) of the rectangular window function is used for fitting. Since the position, height, and width of the spectral peak of the fitting object are uncertain, this embodiment uses three parameters μ, h, and d to describe the center position, height, and width of the peak, respectively, where μ represents the center frequency of the spectral peak, h represents the amplitude of the spectral peak, and d represents the width of the spectral peak. Specifically, it can be expressed as follows: In practical applications, parameters can be added or removed according to the actual situation. For example, additional parameters can be used to describe the asymmetry of peaks in cases of spectral peak asymmetry. For ease of description, let the fitting curve function be F(x,a), where a=(μ,h,d). T .

[0078] In one specific embodiment of the present invention, the LM algorithm is used to fit the parameter values, and the specific process is as follows:

[0079] 6-1) Let the initial number of iterations n = 0; determine the function F(x,a), independent variable x, and fitting object of the fitted curve. The initial values ​​of the damping factor λ0 and the growth rate v, where the independent variable x is the corresponding frequency of the spectral line in the fitted data obtained in step 5), and the fitted object To fit the corresponding amplitude of the spectral lines in the data, the initial value of the damping factor λ0 and the growth rate v can be adjusted according to the actual situation. In this embodiment, λ0 = 0.001 and v = 3 are set.

[0080] Let the initial values ​​of the fitting parameters be a0 = (μ0, h0, d0). T, wherein the initial value μ0 of the central frequency of the spectral peak is taken as the corresponding frequency of the k-th spectral line, the initial value h0 of the amplitude of the spectral peak is taken as the amplitude of the k-th spectral line, and the initial value d0 of the peak width of the spectral peak is taken as the width of the spectral peak where the main frequency is located. In a specific embodiment of the present invention, the function of the selected fitting curve is a Lorentzian peak.

[0081] 6-2) calculating the predicted value y of the n-th iteration n =F(x,a n ), wherein a n is the parameter value of the n-th iteration.

[0082] 6-3) calculating the loss function (sum of squared deviations) of the n-th iteration

[0083] 6-4) calculating the correction term wherein J is the Jacobian matrix of the loss function with respect to each parameter, λ n is the value of the damping factor in the n-th iteration, and I is an identity matrix.

[0084] 6-5) calculating the parameter value a of the (n+1)-th iteration n+1 =a n -h LM ;

[0085] 6-6) calculating the predicted value y of the (n+1)-th iteration n+1 =F(x,a n+1 ), then calculating the loss function of the (n+1)-th iteration

[0086] 6-7) determining: if ||h LM ||2<min is satisfied, the iteration is completed, and the parameter value a of the n-th iteration n is used as the final fitting parameter value, and μ of the n-th iteration in a n n is the central frequency of the spectral peak obtained by fitting; otherwise, the process goes to step 6-8).

[0087] wherein, min is a preset threshold that can be selected freely, and in a specific embodiment of the present invention, the value is 0.001.

[0088] 6-8) determining: if S n+1 >S n is satisfied, update the damping coefficient λ of the (n+1)-th iteration n+1 =λ n ·v to increase the damping coefficient; otherwise, update λ n+1 =λ n / v to decrease the damping coefficient.

[0089] ​6-9) Let n = n+1, and then return to step 6-4) for the next iteration.

[0090] In this embodiment, the parameter μ in the parameter list returned by the LM algorithm represents the center frequency of the fitted spectrum peak. Converting this frequency into the required rotational speed unit outputs the rotational speed of the truncated signal, which is then used to estimate the rotational speed of rotating structures in mechanical equipment.

[0091] Furthermore, in the process of fitting data using the peak curve function, this embodiment can also select various optimization algorithms, including the LM algorithm, the dogleg algorithm, and the trust region algorithm, for solving the problem.

[0092] In a specific embodiment of the present invention, the rotational speed measurement values ​​obtained before and after discrete spectrum correction are shown in Table 1. It can be found that the standard deviation of the residual of the measurement data after correction is reduced to about 40% of that before correction, indicating that the discrete spectrum correction method of the present invention has a significant improvement on the rotational speed measurement task.

[0093] Table 1. Rotational speed measurement values ​​obtained before and after discrete spectrum correction in a specific embodiment of the present invention.

[0094]

[0095] To achieve the above embodiments, a second aspect of the present invention provides a discrete spectrum correction device for measuring the rotational speed of mechanical equipment, comprising:

[0096] The signal acquisition module is used to acquire vibration signals from mechanical equipment with a rotating structure.

[0097] The discrete spectrum acquisition module is used to truncate and window the vibration signal and then perform a fast Fourier transform to obtain the discrete spectrum corresponding to the truncated vibration signal.

[0098] The fitting data extraction module is used to obtain the half-peak width of the spectral peak where the main frequency is located in the discrete spectrum, and to use the corresponding frequency and amplitude of the spectral line within twice the half-peak width as fitting data.

[0099] The correction module is used to calculate, in the least squares sense, the parameter value that makes the fitted curve and the fitted data closest to each other based on the fitted data and the preset fitted curve, wherein the parameter includes the center frequency of the fitted spectral peak, so as to correct the discrete spectrum.

[0100] It should be noted that the foregoing explanation of an embodiment of a discrete spectrum correction method for measuring the rotational speed of mechanical equipment also applies to a discrete spectrum correction device for measuring the rotational speed of mechanical equipment in this embodiment, and will not be repeated here. According to an embodiment of the present invention, a discrete spectrum correction device for measuring the rotational speed of mechanical equipment acquires the vibration signal of a mechanical equipment with a rotating structure; after truncating and windowing the vibration signal, a fast Fourier transform is performed to obtain the discrete spectrum corresponding to the truncated vibration signal; the half-peak width of the spectral peak where the main frequency is located in the discrete spectrum is obtained; the corresponding frequencies and amplitudes of spectral lines within twice the half-peak width are used as fitting data; based on the fitting data and a preset fitting curve, the parameter value that most closely approximates the fitting curve and the fitting data in the least squares sense is calculated, wherein the parameter includes the center frequency of the fitted spectral peak, to achieve correction of the discrete spectrum. This allows for full utilization of the information contained in other spectral lines besides the peak spectral line within the main lobe, achieving more accurate correction of the discrete spectrum.

[0101] To implement the above embodiments, a third aspect of the present invention provides an electronic device, comprising:

[0102] At least one processor; and a memory communicatively connected to said at least one processor;

[0103] The memory stores instructions that can be executed by the at least one processor, the instructions being configured to perform the aforementioned discrete spectrum correction method for measuring the rotational speed of mechanical equipment.

[0104] To implement the above embodiments, a fourth aspect of the present invention provides a computer-readable storage medium storing computer instructions for causing the computer to execute the above-described discrete spectrum correction method for measuring the rotational speed of mechanical equipment.

[0105] It should be noted that the computer-readable medium described in this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0106] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device. The aforementioned computer-readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to perform a discrete spectrum correction method for measuring the rotational speed of mechanical equipment according to the above embodiments.

[0107] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0108] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0109] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0110] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the function involved, as will be understood by those skilled in the art to which embodiments of this application pertain.

[0111] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which programs can be printed, because programs can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0112] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0113] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0114] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0115] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A discrete spectrum correction method for measuring the rotational speed of mechanical equipment, characterized in that, include: Acquire vibration signals from mechanical equipment with rotating structures; After truncating and windowing the vibration signal, a fast Fourier transform is performed to obtain the discrete spectrum corresponding to the truncated vibration signal. Obtain the half-peak width (WHM) of the spectral peak containing the dominant frequency in the discrete spectrum, and use the corresponding frequencies and amplitudes of spectral lines within twice the WHM as fitting data; wherein, the spectral line with the largest amplitude in the spectral peak containing the dominant frequency is denoted as the k-th spectral line, and the smallest positive integer is found. To meet the requirements in the There is a spectral line on the left side Find the smallest positive integer. To meet the requirements in the There is a right side of the spectral line ,in, For the first The amplitude of each spectral line, For the first The amplitude of the spectral line, L(k) is the amplitude of the th spectral line. The amplitude of the spectral line indicates the peak of the spectrum containing the dominant frequency. To the The corresponding frequencies and amplitudes of the spectral lines are the fitted data; Based on the fitted data and the preset fitted curve, calculate the parameter value that is closest to the fitted curve and the fitted data in the least squares sense, wherein the parameter includes the center frequency of the fitted spectrum peak, so as to correct the discrete spectrum.

2. The method according to claim 1, characterized in that, Before truncating and windowing the vibration signal, the method further includes: The vibration signal is filtered and amplified.

3. The method according to claim 1, characterized in that, The method further includes: The length of the vibration signal truncation is greater than or equal to seconds, of which, The frequency resolution of the discrete spectrum.

4. The method according to claim 1, characterized in that, The method for obtaining the spectral peak containing the dominant frequency in the discrete spectrum is as follows: Using a peak extraction algorithm, select the spectral peak data with the highest amplitude (h) from the discrete spectrum, where h is a positive integer; The corresponding frequencies of the selected h spectral peaks are determined as follows: if there is a positive integer multiple relationship of less than 5 among the corresponding frequencies of the h spectral peaks, then the spectral peak corresponding to the fundamental frequency among the h spectral peaks is selected as the spectral peak where the main frequency is located; otherwise, the spectral peak with the highest amplitude among the h spectral peaks is selected as the spectral peak where the main frequency is located.

5. The method according to claim 1, characterized in that, The calculation of the parameter values ​​that make the fitted curve and the fitted data closest in the least squares sense is performed using any one of the LM algorithm, the Dogleg algorithm, and the trust region algorithm.

6. The method according to claim 5, characterized in that, The LM algorithm includes: 1) Let the initial number of iterations be... The function that determines the fitted curve. Independent variable Fitting object Initial value of damping factor and growth rate Among them, the fitting parameters , Indicates the center frequency of the spectral peak. Indicates the amplitude of the spectral peak. Indicates the peak width of the spectral peak; independent variable To fit the corresponding frequencies of spectral lines in the data, the fitting object The corresponding amplitude of the spectral line in the fitted data; Let the initial values ​​of the fitting parameters be... The initial value of the center frequency of the spectral peak. Take the initial value of the amplitude of the spectral peak corresponding to the k-th spectral line. Take the amplitude of the k-th spectral line and the initial value of the peak width of the spectral peak. Take the peak width of the spectrum where the main frequency is located; 2) Calculate the predicted value for the nth iteration. ,in The parameter value for the nth iteration; 3) Calculate the loss function for the nth iteration. ; 4) Calculate the correction term ,in Let Jacobian matrix be the loss function with respect to each parameter. Let n be the value of the damping factor in the nth iteration. It is the identity matrix; 5) Calculate the parameter values ​​for the (n+1)th iteration. = ; 6) Calculate the predicted value for the (n+1)th iteration. Then calculate the loss function for the (n+1)th iteration. ; 7) Judgment: If satisfied The iteration is complete, and the parameter values ​​for the nth iteration are output. These are the final fitted parameter values. The Middle That is, the center frequency of the peak obtained from the fitted spectrum; otherwise, proceed to step 8). Where min is a preset threshold; 8) Judgment: If satisfied > Then update the damping coefficient in the (n+1)th iteration. Otherwise, update. ; 9) Order Then return to step 4).

7. A discrete spectrum correction device for measuring the rotational speed of mechanical equipment, characterized in that, include: The signal acquisition module is used to acquire vibration signals from mechanical equipment with a rotating structure. The discrete spectrum acquisition module is used to truncate and window the vibration signal and then perform a fast Fourier transform to obtain the discrete spectrum corresponding to the truncated vibration signal. The fitting data extraction module is used to obtain the half-peak width of the spectral peak where the dominant frequency is located in the discrete spectrum, and to use the corresponding frequencies and amplitudes of spectral lines within twice the half-peak width as fitting data; wherein, the spectral line with the largest amplitude in the spectral peak where the dominant frequency is located is denoted as the k-th spectral line, and the smallest positive integer is found. To meet the requirements in the There is a spectral line on the left side Find the smallest positive integer. To meet the requirements in the There is a right side of the spectral line ,in, For the first The amplitude of each spectral line, For the first The amplitude of the spectral line, L(k) is the amplitude of the th spectral line. The amplitude of the spectral line indicates the peak of the spectrum containing the dominant frequency. To the The corresponding frequencies and amplitudes of the spectral lines are the fitted data; The correction module is used to calculate, in the least squares sense, the parameter value that makes the fitted curve and the fitted data closest to each other based on the fitted data and the preset fitted curve, wherein the parameter includes the center frequency of the fitted spectral peak, so as to correct the discrete spectrum.

8. An electronic device, characterized in that, include: At least one processor; And, a memory communicatively connected to the at least one processor; The memory stores instructions executable by the at least one processor, the instructions being configured to perform the method described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to perform the method according to any one of claims 1-6.

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