Vibration signal coordinate offset correction method, system, equipment and medium

Abstract

The invention discloses a vibration signal coordinate offset correction method, system and device and a medium, and relates to the field of vibration signal acquisition, and the method comprises the steps: employing a sensor to obtain an original vibration signal; when the length of the original vibration signal is smaller than or equal to a set threshold value, determining a local mean point corresponding to each extreme point in the original vibration signal, and obtaining a final local mean curve based on the local mean points; when the length of the original vibration signal is greater than a set threshold value, dividing the original vibration signal to obtain a plurality of original vibration sub-signals, determining a local mean point corresponding to each extreme point in any original vibration sub-signal, and obtaining an initial local mean curve of the original vibration sub-signals based on the local mean points; obtaining a final local mean curve based on the initial local mean curve of each original vibration sub-signal; and correcting the coordinate offset of the original vibration signal according to the final local mean value curve of the original vibration signal. According to the invention, the accuracy of vibration signal acquisition is improved.

Description

Technical Field

[0001] The present application relates to the field of vibration signal acquisition, and particularly to a method, system, device and medium for correcting coordinate offset of vibration signals. Background Art

[0002] The phenomenon of coordinate offset during vibration signal acquisition poses a significant challenge to the accuracy and reliability of data. Therefore, it is particularly important to conduct in-depth research on it before data processing and analysis. Coordinate offset, also known as zero drift, refers to the phenomenon that the output value of a measuring instrument or sensor changes slowly relative to its coordinates when there is no input signal or the input signal is zero. During the vibration signal acquisition process, this offset may cause changes in the statistical characteristic values of the data, such as the change in the root mean square value, and even distort the spectrum analysis. The causes of coordinate offset are complex and diverse, including device aging, temperature changes, power supply voltage fluctuations, electromagnetic interference, and environmental factors such as humidity and vibration changes. Especially in application scenarios that require long-term stable measurement, such as precision weighing and sensor monitoring, the negative impact of coordinate offset is particularly significant. A large coordinate offset will mask weak signals, resulting in distorted measurement results and even ineffective measurement.

[0003] To address the coordinate offset problem in vibration signal acquisition, a series of effective suppression measures need to be taken. These measures can include selecting high-stability components, performing temperature compensation, using high-performance power regulators, taking effective shielding and grounding measures to reduce electromagnetic interference, and adopting a reasonable mechanical structure design to improve the anti-vibration and anti-shock capabilities of the instrument. In addition, regularly calibrating the zero point of the instrument, adopting appropriate digital filtering algorithms, and establishing a mathematical model of coordinate offset and compensating it are also important means to improve measurement accuracy and reliability.

[0004] Therefore, during the vibration signal acquisition process, in-depth analysis of the coordinate offset phenomenon and taking effective suppression measures are of great significance for improving the accuracy and reliability of measurement data. This not only helps to ensure the accuracy of data acquisition but also provides a reliable basis for subsequent data analysis and processing. With the continuous development of technology, new methods and technologies for suppressing coordinate offset will continue to emerge, providing more accurate and reliable solutions for vibration signal acquisition. Summary of the Invention

[0005] The purpose of the present application is to provide a method, system, device and medium for correcting coordinate offset of vibration signals. By selecting an appropriate method according to the length of the original vibration signal, the final local mean curve of the original vibration signal is obtained, and the coordinate offset of the original vibration signal is corrected by using the final local mean curve, so as to improve the accuracy of vibration signal acquisition.

[0006] To achieve the above object, the present application provides the following solutions:

[0007] In a first aspect, the present application provides a method for correcting coordinate offset of vibration signals, including:

[0008] Obtaining an original vibration signal using a sensor;

[0009] When the length of the original vibration signal is less than or equal to a set threshold, determining local mean points corresponding to each extreme point in the original vibration signal, and obtaining a final local mean curve of the original vibration signal based on the local mean points;

[0010] When the length of the original vibration signal is greater than the set threshold, dividing the original vibration signal to obtain a plurality of original vibration sub-signals, determining local mean points corresponding to each extreme point in any one of the original vibration sub-signals, and obtaining an initial local mean curve of the original vibration sub-signal based on the local mean points; obtaining a final local mean curve of the original vibration signal based on the initial local mean curves of each original vibration sub-signal;

[0011] Correcting the coordinate offset of the original vibration signal according to the final local mean curve of the original vibration signal.

[0012] In a second aspect, the present application provides a system for correcting coordinate offset of vibration signals, including:

[0013] An original vibration signal acquisition module for obtaining an original vibration signal using a sensor;

[0014] A final local mean curve acquisition module for, when the length of the original vibration signal is less than or equal to a set threshold, determining local mean points corresponding to each extreme point in the original vibration signal, and obtaining a final local mean curve of the original vibration signal based on the local mean points; when the length of the original vibration signal is greater than the set threshold, dividing the original vibration signal to obtain a plurality of original vibration sub-signals, determining local mean points corresponding to each extreme point in any one of the original vibration sub-signals, and obtaining an initial local mean curve of the original vibration sub-signal based on the local mean points; obtaining a final local mean curve of the original vibration signal based on the initial local mean curves of each original vibration sub-signal;

[0015] A correction module for correcting the coordinate offset of the original vibration signal according to the final local mean curve of the original vibration signal.

[0016] In a third aspect, the present application provides a computer device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the above method for correcting coordinate offset of vibration signals.

[0017] In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the above-mentioned vibration signal coordinate offset correction method is implemented.

[0018] According to the specific embodiments provided by the present application, the present application has the following technical effects:

[0019] The present application provides a vibration signal coordinate offset correction method, system, device and medium. By selecting a suitable processing method according to the length of the original vibration signal, the accuracy of vibration signal processing is improved. For the original vibration signal with a length less than the set threshold, the offset trend of the original vibration signal is reflected by the final local mean curve. According to the final local mean curve in the original vibration signal, the low-frequency drift of the original vibration signal is removed, making the collected vibration signal more accurate. For the original vibration signal with a length greater than or equal to the set threshold, the original vibration signal is segmented, which not only reduces the difficulty of vibration signal processing, improves the efficiency of vibration signal processing, but also improves the accuracy of vibration signal processing, making the collected vibration signal more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0021] Figure 1 Schematic diagram of constructing the local mean curve in the local feature scale decomposition algorithm in an embodiment of the present application;

[0022] Figure 2 Application environment diagram of a vibration signal coordinate offset correction method in an embodiment of the present application;

[0023] Figure 3 Flow chart of a vibration signal coordinate offset correction method provided in an embodiment of the present application;

[0024] Figure 4 Schematic diagram of constructing the local mean curve of the m-th vibration signal to be processed in a vibration signal coordinate offset correction method provided in an embodiment of the present application;

[0025] Figure 5 Functional module diagram of a vibration signal coordinate offset correction system provided in another embodiment of the present application;

[0026] Figure 6Schematic diagram of the original vibration signals of the first to third channels collected by the LC0161 sensor in a vibration signal coordinate offset correction method provided by an embodiment of the present application;

[0027] Figure 7 Schematic diagram of approximating the signal segment within three adjacent extreme points in the local mean curve as a triangle in a vibration signal coordinate offset correction method provided by an embodiment of the present application;

[0028] Figure 8 Schematic diagram of the local mean points obtained by a vibration signal coordinate offset correction method provided by an embodiment of the present application and the LCD algorithm respectively;

[0029] Figure 9 Schematic diagram of the decomposition result of the original vibration signal of the first channel by the LCD algorithm provided by an embodiment of the present application;

[0030] Figure 10 Schematic diagram of the correction result of the original vibration signal of the first channel by the LCD algorithm provided by an embodiment of the present application;

[0031] Figure 11 Schematic diagram of the secondary correction result of the original vibration signal of the first channel by the LCD algorithm provided by an embodiment of the present application;

[0032] Figure 12 Schematic diagram of the original vibration signal collected from the first channel in a vibration signal coordinate offset correction method provided by an embodiment of the present application;

[0033] Figure 13 Schematic diagram of the extreme points of the original vibration signal collected from the first channel in a vibration signal coordinate offset correction method provided by an embodiment of the present application;

[0034] Figure 14 Schematic diagram of the local mean points of the original vibration signal collected from the first channel in a vibration signal coordinate offset correction method provided by an embodiment of the present application;

[0035] Figure 15 Schematic diagram of the local mean curve of the original vibration signal collected from the first channel in a vibration signal coordinate offset correction method provided by an embodiment of the present application;

[0036] Figure 16 Schematic diagram of the coordinate offset trend of the original vibration signal collected from the first channel in a vibration signal coordinate offset correction method provided by an embodiment of the present application;

[0037] Figure 17Schematic diagram of comparison between the correction result of the first-channel original vibration signal in a vibration signal coordinate offset correction method provided by an embodiment of the present application and the correction result of the LCD algorithm for the first-channel original vibration signal;

[0038] Figure 18 Schematic diagram of comparison between the correction result of the second-channel original vibration signal in a vibration signal coordinate offset correction method provided by an embodiment of the present application and the correction result of the LCD algorithm for the second-channel original vibration signal;

[0039] Figure 19 Schematic diagram of comparison between the correction result of the third-channel original vibration signal in a vibration signal coordinate offset correction method provided by an embodiment of the present application and the correction result of the LCD algorithm for the third-channel original vibration signal;

[0040] Figure 20 Schematic diagram of splicing different continuous local mean curves in a vibration signal coordinate offset correction method provided by an embodiment of the present application;

[0041] Figure 21 Schematic diagram of partial local mean curves in a vibration signal coordinate offset correction method provided by an embodiment of the present application;

[0042] Figure 22 Schematic diagram of the vibration signal corrected by the staggered weighted average method in a vibration signal coordinate offset correction method provided by an embodiment of the present application. Detailed implementation manners

[0043] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0044] To make the purpose, features, and advantages of the present application more obvious and understandable, the present application will be further described in detail below in conjunction with the accompanying drawings and specific implementation manners.

[0045] The principle of the Local Characteristic-scale Decomposition (LCD) algorithm comes from the conclusion that single-component signals are "locally symmetric about zero mean", and the construction method of the local mean curve is a major breakthrough. After clarifying the construction method of the local mean curve, the remaining steps are similar to methods such as the Empirical Mode Decomposition (EMD), that is, through repeated iterations, "the local mean curve is continuously separated from the original signal until the signal becomes an intrinsic scale component. As Figure 1 shown, where, A1 represents B1 represents C1 represents k is the serial number of the extreme point, τ k is the time point of the k-th extreme point, τ k+1 is the time point of the (k + 1)-th extreme point, τ k+2 is the time point of the (k + 2)-th extreme point, is the local mean point at the k-th extreme point, is the local mean point at the (k + 1)-th extreme point, is the local mean point at the (k + 2)-th extreme point, is the intermediate variable at the time point of the k-th extreme point, is the intermediate variable at the time point of the (k + 1)-th extreme point, is the intermediate variable at the time point of the (k + 2)-th extreme point, is the signal value at the k-th extreme point, is the signal value at the (k + 1)-th extreme point, is the signal value at the (k + 2)-th extreme point. The construction method of the local mean curve of the LCD algorithm is as follows:

[0046] Step 101, connect any two similar extreme points to form a line segment, and find the k+1 corresponding to the time point of

[0047] Step 102, from and obtain the local mean point: where, a ∈ (0, 1) is a constant, and a typical value is 0.5.

[0048] Step 103, divide any real signal x(t) into several intervals according to the time points of each extreme point, and perform a linear transformation on x(t) in each interval (between any two adjacent extreme points).

[0049]

[0050] where x(t) is an arbitrary real signal, t is the time point in the arbitrary real signal, and H k (c) represents the local mean curve of the interval where the k-th extreme point of the signal is located, c is any time point among adjacent extreme points, and x c is the signal value at the said arbitrary time point.

[0051] Step 104: Connect H k (c) in sequence to obtain the local mean curve. For any real signal x(t), continuously subtract the local mean curve from the signal, and the Intrinsic Scale Component (ISC) component can be obtained.

[0052] The vibration signal coordinate offset correction method provided by the embodiments of the present application can be applied to an application environment as Figure 2 shown. Among them, the terminal 202 communicates with the server 204 through the network. The data storage system can store the data that the server 204 needs to process. The data storage system can be set up separately, integrated on the server 204, or placed on the cloud or other servers. The terminal 202 can send the original vibration signal to the server 204, and the server 204 obtains the final local mean curve of the original vibration signal based on the original vibration signal; corrects the coordinate offset of the original vibration signal according to the final local mean curve of the original vibration signal. The server 204 can feedback the corrected vibration signal to the terminal 202.

[0053] Among them, the terminal 202 can be, but is not limited to, various desktop computers, laptop computers, smart phones, tablet computers, Internet of Things devices, and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, etc. The portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc. The server 204 can be implemented by an independent server or a server cluster composed of multiple servers, and can also be a cloud server.

[0054] In an exemplary embodiment, as Figure 3 shown, a vibration signal coordinate offset correction method is provided. This method is executed by a computer device, and can be specifically executed by a computer device such as a terminal or a server alone, or jointly executed by a terminal and a server. In the embodiments of the present application, taking this method applied to Figure 2 the server 204 in it as an example for illustration, it includes the following steps 301 to step 303. Among them:

[0055] Step 301, acquire the original vibration signal using a sensor. The original vibration signal includes multiple time points and the signal values corresponding to each time point. The original vibration signal Sig is acquired using a sensor, in the form of (t, X), where 1 ≤ t ≤ num represents the time points in the original vibration signal, and X is the signal value corresponding to each time point. The method for acquiring the original vibration signal using a sensor is to collect the vibration signal using the built-in IC piezoelectric vibration sensor in LC0161. When the sampling frequency is 500 Hz, the time at t = 1 is 1 / 500 s.

[0056] Step 302, when the length of the original vibration signal is less than or equal to the set threshold, determine the local mean points corresponding to each extreme point in the original vibration signal, and obtain the final local mean curve of the original vibration signal based on the local mean points.

[0057] Step 303, when the length of the original vibration signal is greater than the set threshold, divide the original vibration signal to obtain multiple original vibration sub-signals, determine the local mean points corresponding to each extreme point in any one of the original vibration sub-signals, and obtain the initial local mean curve of the original vibration sub-signal based on the local mean points; based on the initial local mean curves of each original vibration sub-signal, obtain the final local mean curve of the original vibration signal.

[0058] Step 304, correct the coordinate offset of the original vibration signal according to the final local mean curve of the original vibration signal.

[0059] In another exemplary embodiment of the present application, in step 302, determining the local mean points corresponding to each extreme point in the original vibration signal and obtaining the final local mean curve of the original vibration signal based on the local mean points specifically includes the following steps 401 to 404.

[0060] Step 401, for the m-th iteration, determine the extreme points in the m-th vibration signal to be processed; m ≥ 1; the first vibration signal to be processed is the original vibration signal.

[0061] Step 402, based on each extreme point in the m-th vibration signal to be processed and the m-th vibration signal to be processed, determine the local mean points corresponding to each extreme point in the m-th vibration signal to be processed.

[0062] Step 403, based on the local mean points corresponding to each extreme point in the m-th vibration signal to be processed, determine the local mean curve of the m-th vibration signal to be processed.

[0063] Step 404: Determine whether the difference between the signal value of the local mean curve of the m-th vibration signal to be processed at any time point and the signal value of the local mean curve of the (m - 1)-th vibration signal to be processed at the same time point is less than a set threshold. If not, use the local mean curve of the m-th vibration signal to be processed as the (m + 1)-th vibration signal to be processed, and perform the (m + 1)-th iteration. If so, use the local mean curve of the m-th vibration signal to be processed as the final local mean curve of the original vibration signal. The 0-th vibration signal to be processed is 0.

[0064] Alternatively, in step 404, determine whether the number of extreme points in the m-th vibration signal to be processed is greater than 3. If not, use the local mean curve of the m-th vibration signal to be processed as the (m + 1)-th vibration signal to be processed, and perform the (m + 1)-th iteration. If so, use the local mean curve of the m-th vibration signal to be processed as the final local mean curve of the original vibration signal. The 0-th vibration signal to be processed is 0.

[0065] In another exemplary embodiment of the present application, in step 401, for the m-th iteration of the original vibration signal, after determining the extreme points in the m-th vibration signal to be processed, it further includes: performing mirror extension on the m-th vibration signal to be processed. The mirror extension of the present application is symmetric extension, and can also be periodic mirror extension. Performing mirror extension on the vibration signal maintains the continuity and smoothness of the signal and reduces boundary effects.

[0066] In another exemplary embodiment of the present application, step 402 includes the following steps 501 to 503.

[0067] Step 501: For the k-th extreme point in the m-th vibration signal to be processed, based on the time point of the k-th extreme point and the time point of the (k - 1)-th extreme point, determine a first time point, and based on the first time point and the m-th vibration signal to be processed, determine a first signal value; 1 ≤ k ≤ K; K is the number of extreme points in the m-th vibration signal to be processed; the 0-th extreme point is determined by the initial time point of the m-th vibration signal to be processed and the signal value at the initial time point.

[0068] Step 502: Based on the time point of the k-th extreme point and the time point of the (k + 1)-th extreme point, determine a second time point, and based on the second time point and the m-th vibration signal to be processed, determine a second signal value; the (K + 1)-th extreme point is determined by the end time point of the m-th vibration signal to be processed and the signal value at the end time point.

[0069] Step 503: Based on the first time point, the first signal value, the second time point, the second signal value, and the time point of the k-th extreme point, determine the local mean point corresponding to the k-th extreme point in the m-th vibration signal to be processed.

[0070] In another exemplary embodiment of the present application, as Figure 4 shown, for the k-th extreme point in the m-th vibration signal to be processed Based on the time point τ of the k-th extreme point k and the time point τ of the (k - 1)-th extreme point k-1 Determine the first time point t D . Wherein, t D =(τ k-1 +τ k ) / 2. If t D is not an integer, the interpolation method is used to obtain the signal value on the m-th vibration signal to be processed Where (t a , X a ) and (t b , X b ) are two known points adjacent to (t D , X D ) on the m-th vibration signal to be processed, and D(t D , X D ) is the first signal point.

[0071] Based on the time point τ of the k-th extreme point k The time point τ of the (k + 1)-th extreme point k+1 Determine the second time point t E . Wherein, t E =(τ k +τ k+1 ) / 2. If t E is not an integer, the interpolation method is used to obtain the signal value X on the m-th vibration signal to be processed E , and E(t E , X E ) is the second signal point. Compared with the LCD algorithm that seeks solutions from outside three extreme points, the present application focuses on studying the internal signal change trend of the three extreme points. Compared with the LCD algorithm, the present application adjusts the construction method of the local mean curve, uses the median perpendicular intersection estimation method to obtain the local mean point, which is more in line with the local characteristics of the signal and makes the obtained local mean curve more accurate.

[0072] Step 503 calculates the local mean point corresponding to the k-th extreme point in the m-th vibration signal to be processed using the following formula: Where k is the serial number of the extreme point, τ k is the time point of the k-th extreme point, is the local mean point corresponding to the k-th extreme point, X D is the first signal value, X E is the second signal value, and t Dis the first time point, t E is the second time point.

[0073] For each local mean point corresponding to an extreme point, a local mean curve of the m-th vibration signal to be processed is obtained by cubic spline interpolation. The specific method is as follows: Interpolation is performed on each local mean point corresponding to an extreme point within the range 1 to λ, that is, the values at all time points other than the time points corresponding to the extreme points are filled in.

[0074] In another exemplary embodiment of the present application, step 404 uses the following formula to determine whether the difference between the signal value of the local mean curve of the m-th vibration signal to be processed at any time point and the signal value of the local mean curve of the (m - 1)-th vibration signal to be processed at the same time point is less than a set threshold:

[0075]

[0076] where t is the time point, end is the end time point of the m-th vibration signal to be processed, h m (t) is the signal value of the local mean curve of the m-th vibration signal to be processed at time point t, h m-1 (t) is the signal value of the local mean curve of the (m - 1)-th vibration signal to be processed at time point t, and SD is the set threshold.

[0077] Among them, the difference between the signal value of the local mean curve of the m-th vibration signal to be processed at any time point and the signal value of the local mean curve of the (m - 1)-th vibration signal to be processed at the same time point is the normalized mean square error. The set threshold is 0.1. And the vibration signal to be processed with a value less than the set threshold is used as the coordinate offset trend term of the original vibration signal.

[0078] In another exemplary embodiment of the present application, step 303 specifically includes: dividing the original vibration signal to obtain a plurality of original vibration sub-signals, determining the local mean point corresponding to each extreme point in any one of the original vibration sub-signals, and obtaining an initial local mean curve of the original vibration sub-signal based on the local mean points; obtaining a final local mean curve of the original vibration signal based on the initial local mean curves of each original vibration sub-signal, specifically including:

[0079] The original vibration signal is divided into a plurality of original vibration sub-signals by using a sliding window with a set step size.

[0080] For any one of the original vibration sub-signals, determine the extreme points in the original vibration sub-signal.

[0081] Based on each extreme point in the original vibration sub-signal, determine the local mean point corresponding to each extreme point.

[0082] Based on the local mean points corresponding to each extreme point, determine the initial local mean curve of the original vibration sub-signal.

[0083] Based on the initial local mean curves of each original vibration sub-signal, obtain the final local mean curve of the original vibration signal.

[0084] In another exemplary embodiment of the present application, the original vibration signal Sig is divided into multiple original vibration sub-signals by using a sliding window with a set step size. The multiple original vibration sub-signals include the first original vibration sub-signal to the Nth original vibration sub-signal; N≥1. The set step size is less than the length of the sliding window. Set the length of the sliding window as λ, and the set step size is The signal processed each time is represented by sn (i) The superscript i≤num - λ is the starting point flag bit, representing that the processing starts from t = i in the original vibration signal Sig. First, let i = 1.

[0085] Based on the initial local mean curves of each original vibration sub-signal, obtaining the final local mean curve of the original vibration signal specifically includes:

[0086] For the zth iteration, extract the signal values in the zth reference curve as the zth reference array; z≥1; the first reference curve is the initial local mean curve of the first original vibration sub-signal.

[0087] Perform a staggered weighted average on the signal values in the zth reference array and the signal values in the initial local mean curve of the (z + 1)th original vibration sub-signal to obtain the signal values corresponding to each time point in the first z + 1 initial local mean curves.

[0088] Based on the signal values corresponding to each time point in the first z + 1 initial local mean curves, obtain the (z + 1)th reference curve.

[0089] Judge whether z + 1 is greater than or equal to N. If not, perform the (z + 1)th iteration; if so, use the (z + 1)th reference curve as the final local mean curve of the original vibration signal.

[0090] When the set step size is equal to the length of the sliding window, in the present application, when the original vibration signal is divided to obtain the initial local mean curves of each original vibration sub-signal, and the initial local mean curves of each original vibration sub-signal are spliced to obtain the final local mean curve of the original vibration signal, at the splicing point, that is, at both ends of the initial local mean curve of the original vibration sub-signal, a large number of end effects will be generated, making the final local mean curve smooth. Therefore, in the present application, the set step size is less than the length of the sliding window, and the method of staggered weighted average is used to eliminate the end effects, making the final local mean curve smooth. The method of staggered weighted average is specifically as follows:

[0091] Extract the last λ signal values from the reference curve as the reference array. where end is the end time point of the original vibration sub-signal, and λ is the length of the sliding window, is the reference array, is the reference curve.

[0092] Use the reference array and the initial local mean curve h of the original vibration sub-signal starting from the i-th time point (i) to perform misaligned weighted averaging. The method of misaligned weighted averaging is as follows: The signal value corresponding to the central time point of (i) is weighted-averaged with the signal value corresponding to the first time point of h The signal value corresponding to the central time point + 1 of (i) is weighted-averaged with the signal value corresponding to the second time point of h At this time, i > 1.

[0093]

[0094] where avg[s] is the signal value corresponding to the s-th time point after misaligned weighted averaging in h (i) , mid is the central time point of , s is the sequence number of the time point in h (i) , and is also the offset of the central time point mid, is the weight of the signal value corresponding to the mid + s - 1-th time point in δ,k w (i) is the weight of the signal value corresponding to the s-th time point in h

[0095] The reference curve The signal value after misaligned weighted averaging is:

[0096]

[0097] At the same time, add the signal values in the second half of h (i) that have not been subjected to misaligned weighted averaging to the end of the reference curve :

[0098]

[0099] In this way, after each misaligned weighted averaging process, the length of the reference curve will increase Until the signal values in the original vibration signal are processed or The remaining part of the trend term h (last) Is filled in as the residual Finally, the original vibration signal is corrected Where Represents the floor function. For example: the sliding window λ is 1000, and the set step size of the sliding window is 500. When i = 1, the initial local mean curve of the first original vibration sub-signal corresponds to the time points from 1 to 1000, that is, 1 to 1000. When i = 501, the initial local mean curve of the second original vibration sub-signal is h (501) Corresponding to the time points from 501 to 1500. When i = 1001, the final initial mean curve of the third original vibration sub-signal is h (1001) Corresponding to the time points from 1001 to 2000.

[0100] For the first iteration, extract the last λ signal values from the first reference curve as the first reference array. Let Where h (1) Is the initial local mean curve of the first original vibration sub-signal, Is the first reference curve. Where end is the end time point of the first original vibration sub-signal, Is the first reference array.

[0101] The first reference array And the initial local mean curve h of the second original vibration sub-signal (501) Perform misaligned weighted averaging, With h (501) For the overlapping time points from 501 to 1000, the signal values corresponding to the overlapping time points are processed by misaligned weighted averaging. Specifically, the signal value corresponding to the 501st time point in Is weighted averaged with the signal value corresponding to the 501st time point in h (501) The signal value corresponding to the 502nd in Is weighted averaged with the signal value corresponding to the 502nd time point in h (501) Until After all the signal values corresponding to the time points from the 501st to the 1000th in are weighted averaged, the weighted average signal values for the time points from the 501st to the 1000th are obtained.

[0102] Add the signal values corresponding to the time points from the 1001st to the 1500th in the second half of h (501) To After that, the signal values corresponding to the 1st time point to the 1500th time point in the first 2 initial local mean curves are obtained, and a second reference curve is obtained based on the signal values corresponding to the 1st time point to the 1500th time point. Based on the signal values corresponding to each time point in to obtain a second reference array the signal values corresponding to the 1001st time point to the 1500th time point in (1001) are subjected to misaligned weighted averaging processing with the signal values corresponding to the 1001st time point to the 1500th time point in the first half of the initial local mean curve h of the 3rd original vibration sub-signal, and iterated successively until the signal values in the original vibration signal are processed completely.

[0103] Based on the same inventive concept, as Figure 5 shown, an embodiment of the present application further provides a vibration signal coordinate offset correction system. The vibration signal coordinate offset correction system includes:

[0104] An original vibration signal acquisition module 501, configured to acquire an original vibration signal by using a sensor.

[0105] A final local mean curve acquisition module 502, configured to, when the length of the original vibration signal is less than or equal to a set threshold, determine local mean points corresponding to each extreme point in the original vibration signal, and obtain a final local mean curve of the original vibration signal based on the local mean points. When the length of the original vibration signal is greater than the set threshold, divide the original vibration signal to obtain a plurality of original vibration sub-signals, determine local mean points corresponding to each extreme point in any one of the original vibration sub-signals, and obtain an initial local mean curve of the original vibration sub-signal based on the local mean points; and obtain a final local mean curve of the original vibration signal based on the initial local mean curves of each original vibration sub-signal.

[0106] A correction module 503, configured to correct the coordinate offset of the original vibration signal according to the final local mean curve of the original vibration signal.

[0107] In an exemplary embodiment, the method of the present application is verified by experiments.

[0108] 1. Signal source: The signal collected by the built-in IC piezoelectric vibration sensor in LC0161 is a vibration signal. This sensor works based on the piezoelectric effect and can convert mechanical vibration into an electrical signal. Specifically, when the vibration sensor senses external mechanical vibration, the piezoelectric elements inside it will generate a corresponding potential difference, which is related to the amplitude of the vibration. The sensor converts this potential difference into an electrical signal output, and then it can be processed by a signal conditioning circuit for amplification, filtering, etc., and finally obtain a vibration signal that can be used for analysis and processing.

[0109] As Figure 6 shown, for the original vibration signals collected by the first to third channels, in the graphical representation of the original vibration signals, the abscissa represents time, indicating the change of the original vibration signal over time, that is, the change of the signal value over time, and its scale is determined by the sampling frequency, typically 500 Hz. The ordinate represents the amplitude or intensity of the vibration, which can reflect the strength and frequency characteristics of the vibration.

[0110] The LC0161 sensor has the advantages of low impedance output, strong anti-interference ability, and low noise, and is especially suitable for long cable transmission and multi-point measurement. However, after being processed into a desktop device, due to the influence of temperature changes, power supply voltage fluctuations, electromagnetic interference, and environmental factor changes, obvious coordinate offset phenomena will be observed in its output results, which has a significant impact on the further processing of data.

[0111] 2. Differences between the LCD algorithm and the method of the present application for finding local mean points.

[0112] 2.1 Theoretical explanation: The LCD algorithm seeks local mean points outside the three extreme points. In contrast, the present application focuses on studying the signal change trend inside the three extreme points. The signal segment within the three adjacent extreme points shown in Figure 4 can be approximately regarded as the triangle shown in Figure 7 . Among them, D is the first signal point, E is the second signal point, and O is the local mean point. However, when the local characteristics of the vibration signal are as shown in Figure 8 , the method of using a linear method to find the local mean point O' in the LCD algorithm does not consider the inflection point characteristics on the right side of the extreme value. Compared with the present application, the present application adjusts the construction method of the local mean curve and uses the median perpendicular intersection estimation method to obtain the local mean point, which is more in line with the local characteristics of the signal.

[0113] 2.2 Numerical example: To verify the effectiveness of the method of the present application for finding local mean points, the method of the present application for finding local mean points is compared with the LCD algorithm.

[0114] 2.2.1 Coordinate correction of vibration signals using the LCD algorithm: Select the original vibration signals from the first channel to the ninth channel for LCD decomposition (the number of channels is generally a multiple of 3). Among them, the decomposition result of the original vibration signal of the first channel is as Figure 9 shown. To suppress the coordinate offset phenomenon, the residual component is removed from the original vibration signal for the first correction, and the correction result is as Figure 10 shown. Since there are also some low-frequency components in the last ISC component, the result of the first correction is further decomposed and the residual component is removed to obtain the secondary correction result of the original vibration signal of the first channel, as Figure 11 shown. It can be seen that the LCD algorithm also has the ability to correct coordinate offsets, but the number of corrections is uncertain.

[0115] 2.2.2 Example 2 uses the present application to correct the coordinate offset of the vibration signal

[0116] Taking the original vibration signal collected by the first channel as an example for correction, the original vibration signal at this time is less than or equal to the set threshold. The specific steps of the present application are as follows:

[0117] Step 1: Obtain the original vibration signal sn of the first channel, in the form of (t, X). t = 1 to end represents the index points of time, and X is the corresponding signal value. The method for obtaining the original vibration signal data is to collect vibration signals using the built-in IC piezoelectric vibration sensor in LC0161. When the sampling frequency is 500 Hz, the time at t = 1 is 1 / 500 s, as follows Figure 12 shown.

[0118] Step 2: Take the original vibration signal as the signal to be processed, and determine the extreme points of the original vibration signal sn, as Figure 13 shown.

[0119] Step 3: Determine the local mean points corresponding to each extreme point in the original vibration signal. The local mean points of some original vibration signals are as Figure 14 shown.

[0120] Step 4: Use cubic spline interpolation to obtain the local mean curve, as Figure 15 shown.

[0121] Step 5: When the local mean curve meets the set conditions, take the local mean curve at this time as the coordinate offset trend term of the vibration signal, as Figure 16 shown, otherwise continue to repeat Steps 3 to 5. Correct the vibration signal based on the coordinate offset trend term of the vibration signal.

[0122] Compare the correction results of the present application for the original vibration signals from the first channel to the ninth channel with the correction results of the LCD algorithm. Among them, as Figure 17 、Figure 18 and Figure 19 As shown in and

[0123] , by comparing the correction results of the original vibration signals of the first to third channels in this application with those of the LCD algorithm, it can be obtained that the correction results of this application are closer to the collected original vibration signals than those of the LCD algorithm.

[0123] 2.2.3 Example 3 The misalignment weighted average method is used to remove the endpoint effects of multiple sliding windows.

[0124] In Figure 12 it can be seen that although the overall coordinate offset trend term conforms to the Figure 14 sn signal offset trend in

[0125] the original vibration signal of the first channel is collected. The length of this vibration signal is greater than the set threshold, and it is a relatively long vibration signal. Taking λ = 1000 and the set step size of 1000 as an example for processing, now h (1) 、h (1001) 、h (2001) 、h (3001) 、h (4001) are listed in Figure 20 . It can be seen that when there is a large amount of data, there are a large number of endpoint effects in the direct splicing effect. When the set step size is 500 and taking h (1) 、h (501) as an example for processing, as Figure 21 shown. It can be seen that the endpoint effect of the coordinate offset trend term is the most obvious when approaching the endpoints. Therefore, the misalignment weighted average is used to correct it. The correction results are as follows Figure 22 shown. It can be seen that the right end of h (1) and the left end of h (501) have removed the endpoint effects and formed new elements are retained, and there are still endpoint effects at the right end of which will be removed in the next iteration using h (1001) .

[0126] In an exemplary embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, the above-mentioned vibration signal coordinate offset correction method is implemented.

[0127] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the above-mentioned vibration signal coordinate offset correction method is implemented.

[0128] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data that have been authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with relevant regulations.

[0129] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in this specification.

[0130] Specific examples are used in this article to elaborate on the principles and implementation manners of this application. The description of the above embodiments is only used to help understand the method and its core idea of this application; at the same time, for those of ordinary skill in the art, according to the idea of this application, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to this application.

Claims

1. A method for correcting coordinate offset of vibration signals, characterized in that, The method includes: Acquiring an original vibration signal by using a sensor; When the length of the original vibration signal is less than or equal to a set threshold, determining local mean points corresponding to each extreme point in the original vibration signal, and obtaining a final local mean curve of the original vibration signal based on the local mean points; When the length of the original vibration signal is greater than the set threshold, dividing the original vibration signal to obtain a plurality of original vibration sub-signals, determining local mean points corresponding to each extreme point in any one of the original vibration sub-signals, and obtaining an initial local mean curve of the original vibration sub-signal based on the local mean points; and obtaining a final local mean curve of the original vibration signal based on the initial local mean curves of each original vibration sub-signal; Correcting the coordinate offset of the original vibration signal according to the final local mean curve of the original vibration signal.

2. The vibration signal coordinate offset correction method according to claim 1, wherein The original vibration signal includes a plurality of time points and signal values corresponding to each time point; Determining local mean points corresponding to each extreme point in the original vibration signal, and obtaining a final local mean curve of the original vibration signal based on the local mean points, specifically including: For the m-th iteration, determining extreme points in the m-th vibration signal to be processed; m≥1; the first vibration signal to be processed is the original vibration signal; Based on each extreme point in the m-th vibration signal to be processed and the m-th vibration signal to be processed, determining local mean points corresponding to each extreme point in the m-th vibration signal to be processed; Based on the local mean points corresponding to each extreme point in the m-th vibration signal to be processed, determining a local mean curve of the m-th vibration signal to be processed; Judging whether the difference between the signal value of the local mean curve of the m-th vibration signal to be processed at any time point and the signal value of the local mean curve of the (m - 1)-th vibration signal to be processed at the time point is less than a set threshold; if not, taking the local mean curve of the m-th vibration signal to be processed as the (m + 1)-th vibration signal to be processed, and performing the (m + 1)-th iteration; if so, taking the local mean curve of the m-th vibration signal to be processed as the final local mean curve of the original vibration signal; the 0-th vibration signal to be processed is 0.

3. The vibration signal coordinate offset correction method according to claim 2, wherein Based on each extreme point in the m-th vibration signal to be processed and the m-th vibration signal to be processed, determining local mean points corresponding to each extreme point in the m-th vibration signal to be processed, specifically including: For the k-th extreme point in the m-th vibration signal to be processed, determining a first time point based on the time point of the k-th extreme point and the time point of the (k - 1)-th extreme point, and determining a first signal value based on the first time point and the m-th vibration signal to be processed; 1≤k≤K; K is the number of extreme points in the m-th vibration signal to be processed; the 0-th extreme point is determined by the initial time point of the m-th vibration signal to be processed and the signal value at the initial time point; Determine a second time point based on the time point of the k-th extreme point and the time point of the k+1-th extreme point, and determine a second signal value based on the second time point and the m-th vibration signal to be processed; the k+1-th extreme point is determined by the end time point of the m-th vibration signal to be processed and the signal value at the end time point; Determine the local mean point corresponding to the k-th extreme point in the m-th vibration signal to be processed based on the first time point, the first signal value, the second time point, the second signal value, and the time point of the k-th extreme point.

4. The vibration signal coordinate offset correction method according to claim 3, characterized in that Calculate the local mean point corresponding to the k-th extreme point in the m-th vibration signal to be processed using the following formula: Among them, k is the serial number of the extreme point, and τ k is the time point of the k-th extreme point, is the local mean point corresponding to the k-th extreme point, X D is the first signal value, X E is the second signal value, t D is the first time point, t E is the second time point.

5. The vibration signal coordinate offset correction method according to claim 2, characterized in that Use the following formula to determine whether the difference between the signal value of the local mean curve of the m-th vibration signal to be processed at any time point and the signal value of the local mean curve of the m-1-th vibration signal to be processed at the time point is less than a set threshold: where t is the time point, end is the end time point of the m-th vibration signal to be processed, and h m (t) is the signal value of the local mean curve of the m-th vibration signal to be processed at the time point t, and h m-1 (t) is the signal value of the local mean curve of the (m - 1)-th vibration signal to be processed at the time point t, and SD is the set threshold.

6. The vibration signal coordinate offset correction method according to claim 1, characterized in that Divide the original vibration signal to obtain a plurality of original vibration sub-signals, determine the local mean point corresponding to each extreme point in any original vibration sub-signal, and obtain the initial local mean curve of the original vibration sub-signal based on the local mean points; based on the initial local mean curves of each original vibration sub-signal, obtain the final local mean curve of the original vibration signal, specifically including: Divide the original vibration signal into a plurality of original vibration sub-signals using a sliding window with a set step size; For any original vibration sub-signal, determine the extreme points in the original vibration sub-signal; Based on each extreme point in the original vibration sub-signal, determine the local mean point corresponding to each extreme point; Based on the local mean points corresponding to each extreme point, determine the initial local mean curve of the original vibration sub-signal; Based on the initial local mean curves of each original vibration sub-signal, obtain the final local mean curve of the original vibration signal.

7. The vibration signal coordinate offset correction method according to claim 1, characterized in that The original vibration signal includes a plurality of time points and the signal value corresponding to each time point; the plurality of original vibration sub-signals include the first original vibration sub-signal to the N-th original vibration sub-signal; N≥1; the set step size is less than the length of the sliding window; Based on the initial local mean curves of each original vibration sub-signal, obtain the final local mean curve of the original vibration signal, specifically including: For the z-th iteration, extract the signal values in the z-th reference curve as the z-th reference array; z≥1; the first reference curve is the initial local mean curve of the first original vibration sub-signal; Perform a staggered weighted average on the signal values in the z-th reference array and the signal values in the initial local mean curve of the z+1-th original vibration sub-signal to obtain the signal value corresponding to each time point in the first z+1 initial local mean curves; Based on the signal values corresponding to each time point in the first z+1 initial local mean curves, obtain the z+1-th reference curve; Determine whether z+1 is greater than or equal to N. If not, perform the (z+1)-th iteration; if so, use the z+1-th reference curve as the final local mean curve of the original vibration signal.

8. A vibration signal coordinate offset correction system, characterized in that, Apply the vibration signal coordinate offset correction method according to any one of claims 1-7, the system includes: An original vibration signal acquisition module, configured to acquire an original vibration signal by using a sensor; A final local mean curve acquisition module, configured to, when the length of the original vibration signal is less than or equal to a set threshold, determine local mean points corresponding to each extreme point in the original vibration signal, and obtain a final local mean curve of the original vibration signal based on the local mean points; when the length of the original vibration signal is greater than the set threshold, divide the original vibration signal to obtain a plurality of original vibration sub-signals, determine local mean points corresponding to each extreme point in any one of the original vibration sub-signals, and obtain an initial local mean curve of the original vibration sub-signal based on the local mean points; and obtain a final local mean curve of the original vibration signal based on the initial local mean curves of each original vibration sub-signal; A correction module, configured to correct the coordinate offset of the original vibration signal according to the final local mean curve of the original vibration signal.

9. A computer device, comprising: A memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the computer program to implement the vibration signal coordinate offset correction method according to any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the vibration signal coordinate offset correction method according to any one of claims 1-7.

Images