A method for identifying the natural vibration frequency of steel strings based on the golden section
The golden segmentation method quickly locks the count value range of the excitation signal sampling period to identify the natural vibration frequency of the steel string, solving the problems of slow recognition speed and low accuracy of the traditional swept excitation method, and achieving more efficient frequency identification.
Patent Information
- Application Number
- CN202411181155.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2024-08-27
- Publication Date
- 2024-12-31
- Estimated Expiration
- 2044-08-27
AI Technical Summary
The traditional swept-frequency excitation method requires scanning within a large frequency range when identifying the natural vibration frequency of the steel string, resulting in slow or inaccurate recognition speed, which may lead to excitation failure and unstable measurement results.
The golden segmentation method is used to quickly lock the range of the excitation signal sampling period count value by calculating the segmentation value, count the stable interval and calculate the natural vibration frequency to improve identification efficiency and accuracy.
The golden segmentation method quickly searches and locks the range of the excitation signal sampling period count value, effectively identifying the natural vibration frequency of the steel string, improving the recognition speed and stability, and avoiding the problem of slow or inaccurate recognition in traditional methods.
Smart Images
Figure CN118706253B_ABST
Abstract
Description
Technical Field
[0001] The invention belongs to the technical field of data recognition, and in particular relates to a method for identifying the natural vibration frequency of a steel string based on the golden section. Background Art
[0002] Steel string sensors are widely used in the field of geotechnical engineering safety monitoring. They are resonant sensors with taut metal strings as sensitive elements. When the length of the string is determined, the change in its natural vibration frequency can represent the size of the load on the string. Through the corresponding measurement circuit, an electrical signal with a certain relationship with the load can be obtained. When measuring, the measurement circuit generally outputs a series of continuous frequency signals to excite the coil of the steel string sensor. When the frequency of the output signal is close to the natural vibration frequency of the steel string, the steel string can quickly reach a resonant state and vibrate. After the steel string vibrates, the frequency of the induced potential generated in the coil is the natural vibration frequency of the steel string. Since the frequency of the excitation signal is easy to control with software, as long as the approximate range of the natural vibration frequency of the steel string is known, the excitation signal near this frequency can be used to excite it, so that the steel string can be quickly vibrated. The sampling cycle count value of the normally vibrated steel string sensor will continue to stabilize near a specific value, and then decay and disappear with time.
[0003] The traditional frequency sweeping excitation method is applicable to the case where the natural vibration frequency of the steel string is known. The natural vibration frequency range of the steel string of most steel string sensors is between 200 and 2500 Hz. If the natural vibration frequency of the steel string is unknown, the frequency sweeping excitation signal needs to be scanned in a relatively large frequency range. In this way, the time required for the frequency sweep will increase. If the natural vibration frequency recognition speed is slow or inaccurate, it will further lead to excitation failure or unstable precision measurement results for multiple consecutive times. Summary of the invention
[0004] The purpose of the present invention is to provide a method for identifying the natural vibration frequency of a steel string based on the golden section, which can effectively identify the natural vibration frequency of the steel string by quickly searching and locking the count value range of the sampling period of the excitation signal.
[0005] In order to achieve the above object, the technical solution adopted by the present invention is as follows:
[0006] The method for identifying the natural vibration frequency of a steel string based on the golden section includes the following steps:
[0007] S1, obtaining the excitation signal sampling period count value sequence R;
[0008] S2, calculate the minimum value a and the maximum value b in the sequence R;
[0009] S3, calculate the segmentation value c according to the golden section method;
[0010] S4, according to the segmentation value c, count the number of cycle count values on both sides of c in the sequence, and take the interval with more cycle count values as the stable interval;
[0011] S5, in the stable interval, determining the final stable interval of the count value;
[0012] S6, calculating the natural vibration frequency f of the values in the sequence R within the stable range.
[0013] Preferably, in S3, the segmentation value c is calculated using the following formula:
[0014] c=a+0.618*(ba)
[0015] Among them, the initial value of a is the minimum value in the sequence R, and after segmentation, it becomes the left endpoint value of the stable interval. The initial value of b is the maximum value in the sequence R, and after segmentation, it becomes the right endpoint value of the stable interval.
[0016] Preferably, in S4, the number of count values in the sequence R in the intervals [a, c] and [c, b] are counted as n1 and n2 respectively. When n1≥n2, the stable count value is determined to be in the interval [a, c], and b=c is set. The stable count value is in the interval [a, b], a is the left endpoint value of the stable interval, and b is the right endpoint value of the stable interval; when n1<n2, the stable count value is in the interval [c, b], and a=c is set. The stable count value is in the interval [a, b], a is the left endpoint value of the stable interval, and b is the right endpoint value of the stable interval.
[0017] Preferably, in S5, when ba≤Sv, the stable interval of the count value is determined to be [a-Sv, b+Sv], and when ba>Sv, S3-S4 are repeatedly executed until ba≤Sv, wherein a is the left endpoint value of the stable interval, b is the right endpoint value of the stable interval, and Sv is the maximum variation allowed for the sequence.
[0018] Preferably, in S6, the specific steps of calculating the natural vibration frequency f of the values in the sequence R within the stable range are as follows:
[0019] S601, calculating the mean value v of the sampling period count values of the values in the sequence R within the stable interval, the calculation formula is as follows:
[0020]
[0021] Among them, the sampling period count value sequence RY whose value in the statistical sequence R is within [a-Sv, b+Sv] is denoted as , j = 1, 2, 3...m, m is the length of the sequence RY;
[0022] S602, calculating the natural vibration frequency f of the values in the sequence R within the stable range, the calculation formula is as follows:
[0023]
[0024] Where v is the mean of the sampling period count values of the values in the sequence R within the stable interval.
[0025] The beneficial effects of the present invention are: the golden section method is used to quickly search and lock the counting value range of the sampling period of the excitation signal, effectively identify the stable section and calculate the natural vibration frequency of the steel string. BRIEF DESCRIPTION OF THE DRAWINGS
[0026] Figure 1 Flow chart of the method of the present invention.
[0027] Figure 2 This is a sample diagram of the count value of the excitation signal sampling period of the present invention.
[0028] Figure 3 This is a schematic diagram of the first golden section of the excitation signal sampling period count value of the present invention.
[0029] Figure 4 This is a schematic diagram of the second golden section of the excitation signal sampling period count value of the present invention.
[0030] Figure 5 This is a schematic diagram of the third golden section of the excitation signal sampling period count value of the present invention.
[0031] Figure 6 This is a schematic diagram of the fourth golden section of the excitation signal sampling period count value of the present invention.
[0032] Figure 7 This is a schematic diagram of the fifth golden section of the excitation signal sampling period count value of the present invention.
[0033] Figure 8 This is a schematic diagram of the sixth golden section of the excitation signal sampling period count value of the present invention.
[0034] Fig. 9 This is a schematic diagram of the seventh golden section of the excitation signal sampling period count value of the present invention.
[0035] Fig.10 It is a schematic diagram of the final stable interval of the count value of the excitation signal sampling period of the present invention. DETAILED DESCRIPTION
[0036] In order to make the purpose, technical solution and advantages of the present invention more clear, the technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the present invention.
[0037] like Figure 1As shown, the present invention discloses a method for identifying the natural vibration frequency of a steel string based on the golden section, comprising the following steps:
[0038] S1, obtain the excitation signal sampling period count value sequence, denoted as R.
[0039] Get the excitation signal sampling period count value sequence, denoted as R, then the i-th count value can be expressed as Ri, where: i is the sequence number, i=1, 2, 3...n; n is the sequence length, such as Figure 2 ,The change curve is plotted with the sampling cycle number as the horizontal coordinate and the count value R as the vertical coordinate. The count value sequence of 500 cycles is collected. There are obvious stable and attenuation segments.
[0040] S2, calculate the minimum value a and the maximum value b in the sequence R.
[0041] Calculate the minimum value a and the maximum value b in the sequence R, that is, a=min(R), b=max(R), such as Figure 2 The values of the positions marked by a and b.
[0042] S3, calculate the segmentation value c according to the golden section method.
[0043] Calculate the segmentation value c, the calculation formula is as follows:
[0044] c=a+0.618*(ba)
[0045] Among them, the initial value of a is the minimum value in the sequence R, and after segmentation, it becomes the left endpoint value of the stable interval. The initial value of b is the maximum value in the sequence R, and after segmentation, it becomes the right endpoint value of the stable interval.
[0046] S4, according to the segmentation value c, count the number of cycle count values on both sides of c in the sequence, and take the interval with more cycle count values as the stable interval.
[0047] The number of count values in the sequence R in the intervals [a, c] and [c, b] is counted as n1 and n2 respectively, that is, there are n1 count values greater than or equal to a and less than or equal to c, and there are n2 count values greater than or equal to c and less than or equal to b. When n1≥n2, the stable count value is determined to be in the interval [a, c], and b=c is set. The stable count value is in the interval [a, b], a is the left endpoint value of the stable interval, and b is the right endpoint value of the stable interval; when n1<n2, the stable count value is in the interval [c, b], and a=c is set. The stable count value is in the interval [a, b], a is the left endpoint value of the stable interval, and b is the right endpoint value of the stable interval.
[0048] S5, in the stable interval, determining a final stable interval of the count value.
[0049] When ba≤Sv, the final stable interval of the count value is determined to be [a-Sv, b+Sv];
[0050] When ba>Sv, repeat S3-S4 until ba≤Sv;
[0051] Among them, a is the left endpoint value of the stable interval, b is the right endpoint value of the stable interval, and Sv is the maximum allowable variation of the sequence.
[0052] Sv can be obtained by repeated experiments on similar steel strings, and can generally be taken as 1000. This experiment is a prior art and will not be described in detail here.
[0053] S6, calculating the natural vibration frequency f of the values in the sequence R within the stable range.
[0054] The specific steps for calculating the natural vibration frequency f of the sequence R within the stable range are as follows:
[0055] S601, calculating the mean value v of the sampling period count values of the values in the sequence R within the stable interval.
[0056] The calculation formula is:
[0057]
[0058] Among them, the sampling period count value sequence RY whose value in the statistical sequence R is within [a-Sv, b+Sv] is denoted as , j=1, 2, 3…m, m is the length of the sequence RY.
[0059] S602, calculating the natural vibration frequency f of the values in the sequence R within the stable range.
[0060]
[0061] Where v is the mean of the sampling period count values of the values in the sequence R within the stable interval.
[0062] The present invention is further verified and explained below in conjunction with specific embodiments.
[0063] like Figure 2 It is the sampling period count value sequence R of a steel string after excitation. The sequence length is 500. It is a variation curve drawn with the sampling period number as the horizontal axis and the count value R as the vertical axis.
[0064] like Figure 3 , marking the minimum value a in sequence R as 9612 and the maximum value b as 50185.
[0065] The segmentation value c calculated by the golden section method is 34686.
[0066] The number of count values in the interval [a, c] and [c, b] in the sequence R is counted as n1 and n2 respectively, that is, there are n1 count values greater than or equal to a and less than or equal to c, and there are n2 count values greater than or equal to c and less than or equal to b. When n1≥n2, it is determined that the stable count value is in the interval [a, c], and b=c; when n1<n2, the stable count value is in the interval [c, b], and a=c; if Figure 3 In the equation, n1=499, n2=1, n1>n2, so let b=c=34686.
[0067] Determine the maximum variation Sv of the count value stability interval allowed sequence to be 1000, such as Figure 3 In the first segmentation, ba=25074>1000, so S3-S4 is repeated, i.e., the second segmentation, such as Figure 4 , calculate the segmentation value c=25108, the number of count values in the interval [a, c] and [c, b] n1=497, n2=2, because n1>n2, so, let b=c=25108, and because ba=15496>1000, so, repeat S3-S4; if Figure 5-Figure 9 , and so on, after 7 divisions, ba=23380-22847=533<1000, and the final stable interval is determined to be [a-Sv, b+Sv], that is, [21847, 24380]. Fig.10 The number of sampling period count values in the calculation sequence R that are in the stable interval [21847, 24380] is 314, and its mean value v is 22980.65, and the natural vibration frequency f is calculated to be 7804.8.
Claims
1. A method for identifying the natural vibration frequency of a steel string based on the golden section, characterized in that: The following steps are involved: S1, obtaining the excitation signal sampling period count value sequence R; S2, calculate the minimum value a and the maximum value b in the sequence R; S3, calculate the segmentation value c according to the golden section method, the calculation formula is as follows: c=a+0.618*(ba) Among them, the initial value of a is the minimum value in the sequence R, and after segmentation, it becomes the left endpoint value of the stable interval; the initial value of b is the maximum value in the sequence R, and after segmentation, it becomes the right endpoint value of the stable interval; S4, according to the segmentation value c, count the number of cycle count values on both sides of c in the sequence, and take the interval with more cycle count values as the stable interval; The number of count values in the interval [a, c] and [c, b] in the sequence R is counted as n1 and n2 respectively. When n1≥n2, the stable count value is determined to be in the interval [a, c], and b=c is set. The stable count value is in the interval [a, b], a is the left endpoint value of the stable interval, and b is the right endpoint value of the stable interval; when n1<n2, the stable count value is in the interval [c, b], and a=c is set. The stable count value is in the interval [a, b], a is the left endpoint value of the stable interval, and b is the right endpoint value of the stable interval; S5, in the stable interval, determining the final stable interval of the count value; When ba≤Sv, the stable interval of the count value is determined to be [a-Sv, b+Sv]. When ba>Sv, S3-S4 are repeated until ba≤Sv, where a is the left endpoint value of the stable interval, b is the right endpoint value of the stable interval, and Sv is the maximum variation allowed for the sequence. S6, calculate the natural vibration frequency f of the values in the sequence R within the stable range, the specific steps are as follows: S601, calculating the mean value v of the sampling period count values of the values in the sequence R within the stable interval, the calculation formula is as follows: Among them, the sampling period count value sequence RY whose value in the statistical sequence R is within [a-Sv, b+Sv] is denoted as , j = 1, 2, 3...m, m is the length of the sequence RY; S602, calculating the natural vibration frequency f of the values in the sequence R within the stable range, the calculation formula is as follows: Where v is the mean of the sampling period count values of the values in the sequence R within the stable interval.