Dynamic cable fastening state monitoring method based on optical fiber sensing

Abstract

The invention relates to a dynamic cable fastening state monitoring method based on optical fiber sensing, and belongs to the technical field of submarine dynamic cable monitoring. The method comprises the following steps: selecting a plurality of fastening points on a dynamic cable according to the structure of the dynamic cable, and acquiring DAS monitoring data of the fastening points; constructing a fastening point detection value time sequence through a principal component analysis method according to the fastening point DAS monitoring data; acquiring an environment wind speed value and an environment wind speed value occurrence moment, and establishing an environment time sequence through sorting according to the environment wind speed value and the environment wind speed value occurrence moment; constructing a fastening point real-time detection sequence according to the environment time sequence and the fastening point detection value time sequence, and updating the fastening point real-time detection sequence according to the occurrence moment of the environment wind speed value; according to the fastening point real-time detection sequence, the anchoring state of the fastening point is obtained through fastening point abnormity judgment, and the abnormal state of the submarine cable fastening point under the complex submarine working condition is judged by analyzing the correlation of multi-moment and multi-position data.

Description

Technical Field

[0001] The invention belongs to the technical field of submarine dynamic cable monitoring, and in particular relates to a dynamic cable fastening state monitoring method based on optical fiber sensing. Background Art

[0002] A typical offshore floating wind power system generally consists of wind turbines, floating platforms, mooring devices and cables. Among them, the dynamic cable is suspended under the floating platform in a certain line shape and connected to the seabed equipment to provide power, data and signals for the seabed equipment. The operating risk of wind power dynamic cables is much higher than that of static submarine cables fixed on pile foundations or laid on the seabed. In particular, the tightening state of the submarine cable will be affected by environmental loads such as ocean currents and waves, which may cause damage to the submarine cable and seriously affect the stable operation of the power grid system. Among them, the top position of the connection between the dynamic cable and the floating platform, the connection with the seabed anchor chain and the mud entry point are subject to tensile loads caused by the large deadweight, and are also subject to repeated bending loads caused by harsh working conditions and large-scale floating body movements. These are the parts where the tightening state changes most obviously before and after abnormalities.

[0003] At present, the safety monitoring of submarine cables is mainly achieved by using distributed monitoring technology. Commonly used equipment includes distributed fiber acoustic sensors (DAS), which detect the phase difference between the two vibration signals before and after, and further analyze the strain change rate and vibration center frequency when the submarine cable vibrates. The changes in vibration data of dynamic cables during normal operation on the seabed are mostly related to environmental factors such as wind speed and ocean current velocity. Once the anchoring state is abnormal, it will change the shape of the submarine cable in the seawater. At this time, the vibration data detected by the equipment under the same environmental conditions will be different. However, due to the marine environment, wind force, mounts, wiring methods, etc. of the dynamic cable in the seawater, they will affect the vibration of the submarine cable, and each reason may lead to different abnormal conditions. At the same time, the vibration data of the submarine cable may change greatly over time.

[0004] Therefore, there is an urgent need for a dynamic cable tightening status monitoring method based on optical fiber sensing to solve the above problems. Summary of the invention

[0005] In order to solve the above problems existing in the prior art, the present invention proposes a dynamic cable tightening status monitoring method based on optical fiber sensing to solve the technical problems existing in the prior art of the multi-factor influence of vibration events and dynamic changes of vibration data of the dynamic cable of a floating wind turbine during operation.

[0006] The purpose of the present invention can be achieved through the following technical solutions: A method for monitoring dynamic cable tightening status based on optical fiber sensing, comprising: Select multiple fastening points on the dynamic cable according to the dynamic cable structure, and obtain DAS monitoring data of the fastening points, wherein the DAS monitoring data of the fastening points includes a strain change rate of the fastening points and a center frequency of the fastening points; Constructing a time series of fastening point detection values ​​by principal component analysis based on the fastening point DAS monitoring data; Acquire the ambient wind speed value and the time when the ambient wind speed value occurs, and establish an ambient time series by sorting the ambient wind speed value and the time when the ambient wind speed value occurs; Constructing a fastening point real-time detection sequence according to the environmental time sequence and the fastening point detection value time sequence, and updating the fastening point real-time detection sequence according to the occurrence time of the environmental wind speed value; The anchoring state of the fastening point is obtained by judging the fastening point abnormality according to the fastening point real-time detection sequence.

[0007] Preferably, constructing a time series of fastening point detection values ​​by principal component analysis based on the fastening point DAS monitoring data comprises: The SF matrix is ​​constructed according to the DAS monitoring data of the fastening point, and the mathematical expression of the SF matrix is: , in, is the strain change rate of each fastening point per hour, is the center frequency of each fastening point per hour, and n is the number of detection values ​​of each fastening point; According to the SF matrix, the dimension is reduced by principal component analysis and the mean is taken to establish a time series of fastening point detection values.

[0008] Preferably, the step of obtaining the ambient wind speed value and the time when the ambient wind speed value occurs, and establishing an ambient time series by sorting the ambient wind speed value and the time when the ambient wind speed value occurs comprises: Obtaining the ambient wind speed value and the time when the ambient wind speed value occurs through a wind speed measurement system, wherein the ambient wind speed value is a dynamic cable laying ambient wind speed value obtained in hours; From the initial time t s At the beginning, the occurrence time of each wind speed level from level M to level N is obtained in units of hours. The last moment after obtaining N-M+1 data is regarded as the current deadline t e ; The corresponding environmental wind speed value occurrence time is sorted in ascending order according to the environmental wind speed value Construct environmental time series.

[0009] Preferably, the constructing a fastening point real-time detection sequence according to the environmental time series and the fastening point detection value time series, and updating the fastening point real-time detection sequence according to the occurrence time of the environmental wind speed value comprises: Extracting the dynamic cable fastening point detection value at the corresponding moment of the environmental time series according to the fastening point detection value time series to form a fastening point real-time detection sequence; From e+1 Starting from the moment, the current environmental wind speed value is counted once every hour. If the current environmental wind speed level W is within the range of the set [M, N], the time value corresponding to the W-level wind speed in the environmental time series is updated, and then the dynamic cable fastening point detection value at the moment corresponding to the W-level wind speed is extracted from the fastening point detection value time series, and the corresponding data of the fastening point real-time detection sequence is replaced.

[0010] Preferably, obtaining the anchoring state of the fastening point by judging the fastening point abnormality according to the fastening point real-time detection sequence includes: According to the real-time detection sequence of the fastening point, the anchoring state of the same fastening point at different times is obtained by judging the correlation between the preceding and following sequences; The anchoring states of different fastening points at the same time are obtained according to the fastening point real-time detection sequence and the correlation coefficient outlier judgment condition.

[0011] Preferably, the determining the anchoring state of the same fastening point at different times by correlation between the preceding and following sequences according to the fastening point real-time detection sequence comprises: Obtain the real-time detection sequence of a certain fastening point L group under the normal state of the submarine cable; According to the L group of fastening point real-time detection sequences, the Spearman correlation coefficient is used to calculate the before and after sequence correlation coefficient and the first fastening point state threshold; Obtaining the anchoring state of the same fastening point at different times by comparing the correlation coefficient of the preceding and following sequences with the first fastening point state threshold; For any fastening point, when the correlation coefficient of the preceding and following sequences is less than the first fastening point state threshold, that is, the rth group of real-time detection sequence C p,r and the r-1th group of real-time detection sequence C p,(r-1) If the correlation is poor, it is judged that the anchoring state of this point is abnormal.

[0012] Preferably, obtaining the anchoring states of different fastening points at the same time according to the fastening point real-time detection sequence by using a correlation coefficient outlier judgment condition comprises: Obtain g groups of real-time detection sequences of each fastening point under normal conditions; Calculate the Spearman correlation coefficient between each pair of fastening points; For each combination of multiple sets of correlation coefficient data sets, the clustering cluster data sets and cluster centers are obtained by improved clustering, wherein the improved clustering includes: obtaining the initial cluster center by iterative optimization through a differential evolution algorithm, wherein the differential evolution algorithm uses the sum of squared errors as a fitness function; calculating the Euclidean distance between each data point in the data set and the initial cluster center; and updating the cluster center by a probability formula until a preset number of iterations is reached; A second fastening point state threshold is obtained by calculating the maximum distance between each data set and its cluster center, wherein the second fastening point state threshold is a judgment threshold of abnormal fastening point states of each combination at the same time; The anchoring states of different fastening points at the same time are obtained according to the second fastening point state threshold through the correlation coefficient outlier judgment condition.

[0013] Preferably, the correlation coefficient outlier judgment condition includes: When the Euclidean distance between the data sets in different combined clusters and the corresponding cluster center is greater than the corresponding second fastening point state threshold, the correlation coefficient is outlier; when the Euclidean distance between the data sets in different combined clusters and the corresponding cluster center is less than the corresponding second fastening point state threshold, the correlation coefficient is not outlier; When the correlation coefficients of two combinations are outliers at a certain moment, it means that the anchoring at the repeated position in the two combinations is abnormal; when the correlation coefficients of three combinations are outliers at a certain moment, the two combinations with the largest ratio of the Euclidean distance between the cluster data set and the corresponding cluster center and the corresponding second fastening point state threshold are taken, indicating that the anchoring at the repeated position in these two combinations is abnormal.

[0014] An electronic device comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the dynamic cable tightening state monitoring method based on optical fiber sensing is implemented.

[0015] A storage medium containing computer executable instructions, wherein the computer executable instructions are used to perform the above-mentioned dynamic cable tightening state monitoring method based on optical fiber sensing when executed by a computer processor.

[0016] The beneficial effects of the present invention are: (1) Through the comprehensive application of fiber optic sensing monitoring and data analysis methods, the real-time monitoring data of the cable fastening points detected by the fiber optic sensing equipment are processed for submarine cables with complex working conditions in marine environments. By analyzing the correlation of multi-time and multi-location data, the fixed-point vibration detection is performed using the serial correlation coefficient. This overcomes the multi-factor influence of vibration events during the operation of the floating wind turbine dynamic cable and the dynamic changes of vibration data. The cable fastening status in the suspended state can be judged, and the abnormal state of the cable fastening point under complex seabed working conditions can be judged, solving the problem of fastening status monitoring of dynamic submarine cables during online operation.

[0017] (2) The initial cluster center is obtained by iterative optimization through the differential evolution algorithm, which solves the blindness of the traditional clustering algorithm in randomly selecting the initial cluster center. The cluster center is updated through the probability formula, which can better iterate the center point to obtain better clustering performance, thereby better obtaining the clustering cluster data sets and cluster centers of multiple groups of correlation coefficient data sets in each combination through improved clustering. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0019] Figure 1 A schematic flow chart of a method for monitoring a dynamic cable tightening state based on optical fiber sensing according to the present invention; Figure 2 is a schematic diagram of dynamic cable laying according to an embodiment of the present invention; Figure 3 It is a diagram showing the correlation coefficients of 50 combinations of C1 and C2. DETAILED DESCRIPTION

[0020] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation methods, structures, features and effects of the present invention are described in detail below in conjunction with the accompanying drawings and preferred embodiments.

[0021] See also Figure 1 , a dynamic cable tightening state monitoring method based on optical fiber sensing, comprising: S1: selecting multiple fastening points on the dynamic cable according to the dynamic cable structure, and obtaining DAS monitoring data of the fastening points, wherein the DAS monitoring data of the fastening points includes the strain change rate of the fastening points and the center frequency of the fastening points; S2: constructing a time series of fastening point detection values ​​by principal component analysis based on the fastening point DAS monitoring data; S3: Acquire the ambient wind speed value and the time when the ambient wind speed value occurs, and establish an ambient time series by sorting the ambient wind speed value and the time when the ambient wind speed value occurs; S4: constructing a fastening point real-time detection sequence according to the environmental time sequence and the fastening point detection value time sequence, and updating the fastening point real-time detection sequence according to the occurrence time of the environmental wind speed value; S5: Obtaining the anchoring state of the fastening point by judging the fastening point abnormality according to the fastening point real-time detection sequence.

[0022] In this embodiment, the steps of selecting multiple fastening points on the dynamic cable according to the dynamic cable structure and obtaining DAS monitoring data of the fastening points are specifically implemented by the following steps: S101: selecting three fastening points on the dynamic cable according to the dynamic cable structure, wherein the three fastening points are respectively a dynamic cable hanging point, a dynamic cable anchor chain point and a dynamic cable mud entry point; S102: Acquiring DAS monitoring data of the fastening points through a DAS device, namely, the strain change rate and center frequency of the three fastening points on the dynamic cable; It should be noted that the number of the fastening points may be other numbers.

[0023] In this embodiment, the construction of the fastening point detection value time series by principal component analysis based on the fastening point DAS monitoring data is specifically implemented by the following steps: S201: constructing a SF matrix according to the fastening point DAS monitoring data, the mathematical expression of the SF matrix is: , in, is the strain change rate of each fastening point per hour, is the center frequency of each fastening point in unit hour, and n is the number of detection values ​​of each fastening point.

[0024] S202: reducing the dimension of the SF matrix by principal component analysis and taking the mean to establish a time series of fastening point detection values; S202-1: Establishing the original sequence of detection values ​​of each fastening point ; Specifically, the original sequence of detection values ​​of the dynamic cable suspension point is: , the original sequence of detection values ​​of the dynamic cable anchor chain point is The original sequence of detection values ​​of the dynamic cable entering mud point is: .

[0025] S202-2: Dimension reduction processing of the SF matrix by principal component analysis to obtain a dimension reduction detection value of the fastening point ; S202-3: Obtain the corresponding element of a certain fastening point detection value sequence at the current moment by taking the average value according to the fastening point dimension reduction detection value, then the original sequence of the certain fastening point detection value at the current moment The j-th fastening point detection value element is , based on the original sequence of a fastening point detection value, a fastening point detection value is added every hour pj , which is the time series of the fastening point detection value.

[0026] Specifically, in this embodiment, taking 100 data detected by the DAS device at each fastening point every hour as an example, the fastening point strain change rate is , the center frequency of the fastening point is , the original sequence of detection values ​​of a fastening point The jth element in , one fastening point detection value a is added every hour pj .

[0027] In this embodiment, the obtaining of the ambient wind speed value and the time when the ambient wind speed value occurs, and establishing the ambient time series by sorting the ambient wind speed value and the time when the ambient wind speed value occurs are specifically implemented by the following steps: S301: Acquire the ambient wind speed value and the time when the ambient wind speed value occurs through a wind speed measurement system, wherein the ambient wind speed value is a dynamic cable laying ambient wind speed value acquired in hours.

[0028] S302: From the initial time t s At the beginning, the occurrence time of each wind speed level from level M to level N is obtained in units of hours. The last moment after obtaining N-M+1 data is regarded as the current deadline t e ; S303: sorting the corresponding environmental wind speed value occurrence time in ascending order according to the environmental wind speed value Constitute the environmental time series E.

[0029] Specifically, in this embodiment, starting from the initial moment, the occurrence time of each level of wind from level 1 to level 10 is obtained in units of hours. The last moment after obtaining 10 data is regarded as the current cutoff time, and the corresponding environmental wind speed value occurrence time is sorted in ascending order according to the environmental wind speed value to form an environmental time series. .

[0030] In this embodiment, the construction of the fastening point real-time detection sequence according to the environmental time sequence and the fastening point detection value time sequence, and updating the fastening point real-time detection sequence according to the occurrence time of the environmental wind speed value are specifically implemented by the following steps: S401: Extract the dynamic cable fastening point detection value at the corresponding moment of the environmental time series according to the fastening point detection value time series to form a fastening point real-time detection sequence, which includes a hanging point real-time detection sequence C1, an anchor chain point real-time detection sequence C2, and a mud entry point real-time detection sequence C3.

[0031] S402: From t e +1, the current environmental wind speed value is counted once every hour. If the current environmental wind speed level W is within the range of the set [M, N], the time value corresponding to the W-level wind speed in the environmental time series E is updated, and then the dynamic cable fastening point detection value at the time corresponding to the W-level wind speed is extracted from the fastening point detection value time series, and the corresponding data of the fastening point real-time detection sequence is replaced.

[0032] Specifically, in order to eliminate the influence of environmental factors on the measurement data, the dynamic cable fastening point detection values ​​at the time when the fixed wind speed level occurs are selected to form the fastening point real-time detection sequence C p And determine whether to update the fastening point real-time detection sequence in units of hours, so that the fastening point real-time detection sequence is continuously updated with time changes, that is, the sequence after the rth update is C p,r .

[0033] In this embodiment, the fastening point anchoring state is obtained by fastening point abnormality judgment according to the fastening point real-time detection sequence, specifically by the following steps: S501: determining the anchoring state of the same fastening point at different times by judging the correlation between the preceding and following sequences according to the fastening point real-time detection sequence; S501-1: Acquire a real-time detection sequence of a certain fastening point L of the submarine cable in a normal state; Specifically, when the submarine cable is in normal operation, L groups of fastening point real-time detection sequences are taken for a certain fastening point according to the above steps S1-S4.

[0034] S501-2: Calculating the before-after sequence correlation coefficient and the first fastening point state threshold value according to the L group of fastening point real-time detection sequences by using the Spearman correlation coefficient; S501-21: Real-time detection sequence C according to the rth group of fastening points p,r and the r-1th group of real-time detection sequence C p,(r-1) , the correlation coefficient of the before and after series is calculated by Spearman correlation coefficient; Specifically, the mathematical expression of the Spearman correlation coefficient is: , Among them, ρ is the Spearman correlation coefficient, n is the number of samples, R(x i ) is the actual observed value of the ith data point of variable x, R(y i ) is the actual observed value of the ith data point of variable y, is the average observed value of all data points of variable x, is the average observed value of all data points of variable y.

[0035] It should be noted that the variable x is the rth group of real-time detection sequence C of the fastening point. p,r , the variable y is the r-1th group of real-time detection sequence C of the fastening point p,(r-1) .

[0036] The rth group of real-time detection sequence C p,r and the r-1th group of real-time detection sequence C p,(r-1)The ascending order of the m data in each is used as the rank value. When the values ​​of two data are equal, the average of the numerical ranks is calculated as the rank number of the two data. The simplified mathematical expression of the Spearman correlation coefficient is: , Among them, r s is the simplified Spearman correlation coefficient, d is the real-time detection sequence C of the rth group p,r and the r-1th group of real-time detection sequence C p,(r-1) The corresponding data level difference.

[0037] It should be noted that the rth group of real-time detection sequence C of the calculation of the fastening point p,r and the r-1th group of real-time detection sequence C p,(r-1) The simplified Spearman correlation coefficient is used as the before-after serial correlation coefficient.

[0038] S501-22: Obtain a first fastening point state threshold by calculating the mean of the L-1 group correlation coefficients and the standard deviation of the L-1 group correlation coefficients. The first fastening point state threshold is a judgment threshold for abnormal states of the same fastening point at different times. The mathematical expression of the first fastening point state threshold is: , in, is the mean of the correlation coefficient of the L-1 group, is the standard deviation of the correlation coefficient of the L-1 group, is the first fastening point status threshold.

[0039] In this embodiment, the threshold for judging the anchoring state of the same fastening point at different times is estimated as follows: when the submarine cable is in normal operation, 50 sets of fastening point real-time detection sequences are taken for a certain fastening point, and the sequence numbers of the 10 data in the rth group of real-time detection sequences and the r-1th group of real-time detection sequences, which are sorted in ascending order, are used as the level values, and are substituted into the mathematical expression of the simplified Spearman correlation coefficient, that is, , The first fastening point state threshold is obtained by calculating the L-1 group correlation coefficient mean and the L-1 group correlation coefficient standard deviation.

[0040] S501-3: Obtain the anchoring state of the same fastening point at different times by comparing the correlation coefficient of the preceding and following sequences with the first fastening point state threshold.

[0041] Specifically, for any fastening point, when the correlation coefficient of the preceding and following sequences is less than the first fastening point state threshold, that is, the rth group of real-time detection sequence C p,r and the r-1th group of real-time detection sequence C p,(r-1) If the correlation is poor, it is judged that the anchoring state of this point is abnormal.

[0042] S502: Obtain the anchoring states of different fastening points at the same time according to the fastening point real-time detection sequence and the correlation coefficient outlier judgment condition.

[0043] S502-1: Obtaining a real-time detection sequence of g groups of each fastening point in a normal state; Specifically, when the submarine cable is in normal operation, according to the above steps S1-S4, g groups of fastening point real-time detection sequences are taken for each of the three fastening points.

[0044] S502-2: Calculate the Spearman correlation coefficient of each pairwise combination between two fastening points; Specifically, the Spearman correlation coefficients of the three combinations of the three fastening point detection values, C1 and C2, C1 and C3, and C2 and C3, are calculated respectively.

[0045] S502-3: obtaining clustering data sets and cluster centers by improved clustering for each combination of multiple sets of correlation coefficient data sets; The step of improving clustering comprises: The initial cluster center is obtained by iterative optimization using a differential evolution algorithm, wherein the differential evolution algorithm uses the sum of squared errors as a fitness function; Calculate the Euclidean distance between each data point in the data set and the initial cluster center; The cluster center is updated by a probability formula until the preset number of iterations is reached. The probability formula is: , Among them, Z is the updated cluster center, d i (x) is the Euclidean distance between the current data point and the initial cluster center.

[0046] The cluster data sets formed by the g group correlation coefficients of each combination are , , , where x gi (i=1,2,3) is the combination number, i.e., the g-group real-time detection sequence of the fastening points under the i-th combination, y gi are the corresponding Spearman correlation coefficient values, and the cluster centers are , , .

[0047] In this embodiment, 50 sets of real-time detection sequences are taken for each of the three fastening points, that is, g is 50. In other embodiments, other numbers of sets may be taken for each of the three fastening points according to actual detection needs.

[0048] S502-4: Calculating a second fastening point status threshold value based on the maximum distance between each data set and its cluster center, where the second fastening point status threshold value is a judgment threshold value for abnormal fastening point status of each combination at the same moment; The mathematical expression of the second fastening point state threshold is: , , , Among them, D i is the distance between each data set and its cluster center, D max,i is the maximum distance between each data set and its cluster center, is the second fastening point state threshold, and i is three fastening points.

[0049] S502-5: Obtain the anchoring states of different fastening points at the same time according to the second fastening point state threshold and the correlation coefficient outlier judgment condition.

[0050] K groups of vibration data corresponding to the fastening points under the monitoring state are selected, and the correlation coefficient data of the corresponding combination and the Euclidean distance with the cluster center are calculated. By judging whether the Euclidean distance between the data set within the cluster and the corresponding cluster center is greater than the corresponding second fastening point state threshold, the anchoring state of different fastening points at the same time is obtained.

[0051] Specifically, the Spearman correlation coefficients of the three combinations of the three fastening point detection values ​​C1 and C2, C1 and C3, and C2 and C3 are calculated respectively, and the k groups of correlation coefficients of each combination constitute the cluster data set , , , according to the cluster data set With their respective cluster centers Euclidean distance , whether it is greater than the corresponding second fastening point state threshold is used to determine whether there is a correlation coefficient outlier.

[0052] In this embodiment, Figure 3 The figure shows the correlation coefficients of 50 groups of C1 and C2 combinations.

[0053] The correlation coefficient outlier judgment condition includes: when the Euclidean distance between the data sets in different combination clusters and the corresponding cluster center is greater than the corresponding second fastening point state threshold, the correlation coefficient is outlier; when the Euclidean distance between the data sets in different combination clusters and the corresponding cluster center is less than the corresponding second fastening point state threshold, the correlation coefficient is not outlier.

[0054] When the correlation coefficients of two combinations are outliers at a certain moment, it means that the anchoring at the repeated position in the two combinations is abnormal; when the correlation coefficients of three combinations are outliers at a certain moment, the ratio of the Euclidean distance between the cluster data set and the corresponding cluster center in the three combinations to the corresponding second fastening point state threshold is taken. The two largest combinations indicate abnormal anchoring at the repeat position in both combinations.

[0055] The computer storage medium of the embodiment of the present invention may adopt any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device.

[0056] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0057] The program code included on the computer readable medium can be transmitted with any appropriate medium, including but not limited to wireless, electric wire, optical cable, RF, etc., or any suitable combination of the above. The computer program code for performing the operation of the present invention can be written in one or more programming languages ​​or their combinations, and the programming language includes object-oriented programming languages-such as Java, Smalltalk, C++, and also includes conventional procedural programming languages-such as "C" language or similar programming languages. The program code can be executed completely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on the remote computer, or completely on the remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0058] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention without departing from the content of the technical solution of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A method for monitoring dynamic cable tightening status based on optical fiber sensing, characterized in that: include: Select multiple fastening points on the dynamic cable according to the dynamic cable structure, and obtain DAS monitoring data of the fastening points, wherein the DAS monitoring data of the fastening points includes a strain change rate of the fastening points and a center frequency of the fastening points; Constructing a time series of fastening point detection values ​​by principal component analysis based on the fastening point DAS monitoring data; Acquire the ambient wind speed value and the time when the ambient wind speed value occurs, and establish an ambient time series by sorting the ambient wind speed value and the time when the ambient wind speed value occurs; Constructing a fastening point real-time detection sequence according to the environmental time sequence and the fastening point detection value time sequence, and updating the fastening point real-time detection sequence according to the occurrence time of the environmental wind speed value; The anchoring state of the fastening point is obtained by judging the fastening point abnormality according to the fastening point real-time detection sequence.

2. The method for monitoring the dynamic cable tightening state based on optical fiber sensing according to claim 1, characterized in that: The constructing of a time series of fastening point detection values ​​by principal component analysis according to the fastening point DAS monitoring data comprises: The SF matrix is ​​constructed according to the DAS monitoring data of the fastening point, and the mathematical expression of the SF matrix is: ， in, is the strain change rate of each fastening point per hour, is the center frequency of each fastening point in a unit hour, and n is the number of detection values ​​of each fastening point; According to the SF matrix, the dimension is reduced by principal component analysis and the mean is taken to establish a time series of fastening point detection values.

3. The method for monitoring the dynamic cable tightening state based on optical fiber sensing according to claim 1, characterized in that: The obtaining of the ambient wind speed value and the time when the ambient wind speed value occurs, and establishing the ambient time series by sorting the ambient wind speed value and the time when the ambient wind speed value occurs comprises: Obtaining the ambient wind speed value and the time when the ambient wind speed value occurs through a wind speed measurement system, wherein the ambient wind speed value is a dynamic cable laying ambient wind speed value obtained in hours; From the initial time t s At the beginning, the occurrence time of each wind speed level from level M to level N is obtained in units of hours. The last moment after obtaining N-M+1 data is regarded as the current deadline t e ; The corresponding environmental wind speed value occurrence time is sorted in ascending order according to the environmental wind speed value Construct environmental time series.

4. The method for monitoring the dynamic cable tightening state based on optical fiber sensing according to claim 1, characterized in that: The step of constructing a fastening point real-time detection sequence according to the environmental time sequence and the fastening point detection value time sequence, and updating the fastening point real-time detection sequence according to the occurrence time of the environmental wind speed value comprises: Extracting the dynamic cable fastening point detection value at the corresponding moment of the environmental time series according to the fastening point detection value time series to form a fastening point real-time detection sequence; From e+1 Starting from the moment, the current environmental wind speed value is counted once every hour. If the current environmental wind speed level W is within the range of the set [M, N], the time value corresponding to the W-level wind speed in the environmental time series is updated, and then the dynamic cable fastening point detection value at the moment corresponding to the W-level wind speed is extracted from the fastening point detection value time series, and the corresponding data of the fastening point real-time detection sequence is replaced.

5. The method for monitoring the dynamic cable tightening state based on optical fiber sensing according to claim 1, characterized in that: The method of obtaining the anchoring state of the fastening point by judging the fastening point abnormality according to the fastening point real-time detection sequence includes: According to the real-time detection sequence of the fastening point, the anchoring state of the same fastening point at different times is obtained by judging the correlation between the preceding and following sequences; The anchoring states of different fastening points at the same time are obtained according to the fastening point real-time detection sequence and the correlation coefficient outlier judgment condition.

6. The method for monitoring the dynamic cable tightening state based on optical fiber sensing according to claim 5, characterized in that: The method of determining the anchoring state of the same fastening point at different times by judging the correlation between the preceding and following sequences according to the fastening point real-time detection sequence includes: Obtain the real-time detection sequence of a certain fastening point L group under the normal state of the submarine cable; According to the L group of fastening point real-time detection sequences, the Spearman correlation coefficient is used to calculate the before and after sequence correlation coefficient and the first fastening point state threshold; Obtaining the anchoring state of the same fastening point at different times by comparing the correlation coefficient of the preceding and following sequences with the first fastening point state threshold; For any fastening point, when the correlation coefficient of the preceding and following sequences is less than the first fastening point state threshold, that is, the rth group of real-time detection sequence C p,r and the r-1th group of real-time detection sequence C p,(r-1) If the correlation is poor, it is judged that the anchoring state of this point is abnormal.

7. The method for monitoring the dynamic cable tightening state based on optical fiber sensing according to claim 5, characterized in that: The method of obtaining the anchoring states of different fastening points at the same time according to the fastening point real-time detection sequence by using the correlation coefficient outlier judgment condition includes: Obtain g groups of real-time detection sequences of each fastening point under normal conditions; Calculate the Spearman correlation coefficient between each pair of fastening points; For each combination of multiple sets of correlation coefficient data sets, the clustering cluster data sets and cluster centers are obtained by improved clustering, wherein the improved clustering includes: obtaining the initial cluster center by iterative optimization through a differential evolution algorithm, wherein the differential evolution algorithm uses the sum of squared errors as a fitness function; calculating the Euclidean distance between each data point in the data set and the initial cluster center; and updating the cluster center by a probability formula until a preset number of iterations is reached; A second fastening point state threshold is obtained by calculating the maximum distance between each data set and its cluster center, wherein the second fastening point state threshold is a judgment threshold of abnormal fastening point states of each combination at the same time; The anchoring states of different fastening points at the same time are obtained according to the second fastening point state threshold through the correlation coefficient outlier judgment condition.

8. The method for monitoring the dynamic cable tightening state based on optical fiber sensing according to claim 7, characterized in that: The correlation coefficient outlier judgment condition includes: When the Euclidean distance between the data sets in different combined clusters and the corresponding cluster center is greater than the corresponding second fastening point state threshold, the correlation coefficient is outlier; when the Euclidean distance between the data sets in different combined clusters and the corresponding cluster center is less than the corresponding second fastening point state threshold, the correlation coefficient is not outlier; When the correlation coefficients of two combinations are outliers at a certain moment, it means that the anchoring at the repeated position in the two combinations is abnormal; when the correlation coefficients of three combinations are outliers at a certain moment, the two combinations with the largest ratio of the Euclidean distance between the cluster data set and the corresponding cluster center and the corresponding second fastening point state threshold are taken, indicating that the anchoring at the repeated position in these two combinations is abnormal.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the dynamic cable tightening state monitoring method based on optical fiber sensing as described in any one of claims 1 to 8 is implemented.

10. A storage medium containing computer executable instructions, characterized in that: When the computer executable instructions are executed by a computer processor, they are used to perform the dynamic cable tightening state monitoring method based on optical fiber sensing as described in any one of claims 1-8.

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