A method for monitoring the wear of sucker rod centralizer blocks based on optical detection

Abstract

This invention discloses a method for monitoring the wear of a sucker rod centralizer centralizer block based on optical detection, belonging to the field of centralizer wear monitoring technology. The method includes the following steps: real-time monitoring of the vibration spectrum and environmental data of the centralizer block; conducting wear tests to obtain vibration spectra and environmental data under different wear conditions, naming them test data; analyzing the baseline wear relationship between the wear depth of the centralizer block and the vibration spectrum based on the test data; analyzing the temperature and pressure influence of the environmental data of the FBG sensor on the vibration spectrum based on the test data; calibrating the real-time monitored vibration spectrum based on the temperature and pressure influence relationship, and calculating the real-time wear depth of the centralizer block based on the baseline wear relationship. This invention addresses the problems of existing centralizer wear monitoring technologies, which require stopping the machine to measure the centralizer block, leading to reduced sucker rod efficiency and the inability to perform real-time, non-stop, high-precision wear monitoring.

Description

Technical Field

[0001] This invention relates to the field of centralizer wear monitoring technology, specifically to a method for monitoring the wear of sucker rod centralizer centralizer blocks based on optical detection. Background Technology

[0002] Centralizer wear monitoring technology refers to an engineering technology system that uses sensing, signal processing and intelligent diagnosis to continuously or periodically detect, quantify and evaluate the wear degree of the centralizer blocks on the sucker rod centralizer, so as to ensure that the centralizer can operate stably and normally.

[0003] Existing centralizer wear monitoring technologies typically rely on measuring the thickness or weight of the centralizer block to infer wear, resulting in low accuracy and the inability to monitor online. Furthermore, these methods require stopping the sucker rod operation and removing the centralizer before testing, making real-time, non-stop wear monitoring impossible. In addition, the high temperature and pressure conditions within oil wells make online monitoring of centralizer block wear even more difficult and affect the final monitoring results. The influence of high temperature and pressure on the monitoring results must be eliminated during the monitoring process to obtain accurate wear readings. Existing centralizer wear monitoring technologies also suffer from the problems of requiring shutdown for centralizer block measurement, leading to reduced sucker rod efficiency and the inability to perform real-time, non-stop, high-precision wear monitoring. Summary of the Invention

[0004] This invention aims to at least partially solve one of the technical problems in the prior art. By installing optical fibers and FBG sensors on the inner side of the metal frame of the centralizer, along with temperature and pressure sensors, the vibration spectrum and environmental data of the centralizer block are monitored in real time. Wear tests are then conducted to obtain vibration spectrum and environmental data under different wear states, which are named test data. The wear reference peak and frequency reference range of the vibration spectrum in the test data are then extracted. Based on the wear reference peak, the reference wear relationship between the vibration spectrum and standard wear is analyzed. Then, based on the test data, temperature and pressure influence diagrams on standard wear are analyzed. Based on the temperature and pressure influence diagrams, environmental calibration parameters are used to calculate the wear depth. Finally, after calibrating the real-time monitored vibration spectrum based on the temperature and pressure influence relationship, the real-time wear depth of the centralizer block is calculated based on the reference wear relationship. This solves the problem that existing centralizer wear monitoring technologies still require stopping the machine to measure the centralizer block, which reduces the working efficiency of the sucker rod and cannot perform real-time, non-stop, high-precision wear monitoring.

[0005] To achieve the above objectives, this application provides a method for monitoring the wear of sucker rod centralizer centralizer blocks based on optical detection, comprising the following steps: An optical fiber and an FBG sensor are installed inside the metal frame of the centralizer, along with a temperature and pressure sensor, to monitor the vibration spectrum of the centralizer and environmental data in real time. Wear tests were conducted to obtain vibration spectra and environmental data under different wear conditions, which were named test data. The baseline wear relationship between the wear depth of the straightening block and the vibration spectrum was analyzed based on test data. Based on test data analysis, the relationship between the environmental data of the FBG sensor and the temperature and pressure effects on the vibration spectrum is analyzed. After calibrating the real-time monitored vibration spectrum based on the temperature and pressure influence relationship, the real-time wear depth of the straightening block is calculated based on the reference wear relationship.

[0006] Furthermore, optical fibers and FBG sensors are installed inside the metal frame of the centralizer, along with temperature and pressure sensors, to monitor the vibration spectrum of the centralizer and environmental data in real time, including the following sub-steps: An optical fiber is installed inside the metal frame of the stabilizer, and an FBG sensor is installed at the optical fiber at the same horizontal position as the stabilizer block, in the radial direction. A temperature and pressure sensor is installed at the same horizontal position as the FBG sensor inside the metal frame. The ambient temperature and pressure at the FBG sensor are monitored by the temperature and pressure sensor, and are collectively referred to as environmental data. The reflected wavelength of the FBG sensor is monitored in real time by a demodulator to obtain the time-domain waveform of the reflected wavelength. The fast Fourier transform is performed on the time-domain waveform to obtain the spectrum of the reflected wavelength, which is named the vibration spectrum.

[0007] Further, wear testing is conducted to obtain vibration spectra and environmental data under different wear conditions, including the following sub-steps: Randomly select the first number of uprighting blocks that have been put into use, name them sample blocks, measure the wear depth of the sample blocks, and name them standard wear; The sample block was installed on the stabilizer to obtain a test experimental group. There was a total of the first number of test experimental groups. The sample block was installed in the same position in different test experimental groups. The test groups were sorted and numbered in ascending order of standard wear, using the symbol S. n It is represented as follows, where n is a non-zero natural number and n is the index of S, where the standard wear of S1 is fixed at 0; To obtain the commonly used depth of the stabilizer, move the stabilizer block downwards to the commonly used depth, start the stabilizer, and record the detected vibration spectrum and environmental data, collectively referred to as wear test data. The depth of the centralizer was randomly changed, and the detected vibration spectrum and environmental data were recorded. These are collectively referred to as environmental experimental data. The wear test data and environmental test data are collectively referred to as test data, and S n The test data is labeled ST n ST n The wear test data and environmental test data in the sample are labeled as STM. n and STH n .

[0008] Furthermore, the baseline wear relationship between the wear depth of the straightening block and the vibration spectrum, based on test data analysis, includes the following sub-steps: Extract the wear reference peak and frequency reference range from the vibration spectrum in the test data; The relationship between the vibration spectrum and the standard wear was analyzed based on the wear reference peak.

[0009] Furthermore, extracting the wear reference peak and frequency reference range from the vibration spectrum in the test data includes the following sub-steps: For any STM n When analyzing the vibration spectrum in the STM0, it is named the wear spectrum to be analyzed. The wear spectrum to be analyzed is superimposed with the vibration spectrum in the STM0 to obtain an effective peak analysis diagram. The effective peak analysis diagram includes a reference peak and a peak to be analyzed. The reference peak belongs to the vibration spectrum in the STM0, and the peak to be analyzed belongs to the wear spectrum to be analyzed. The peaks to be analyzed are numbered from left to right using the symbol DF. m This means that, where m is a non-zero natural number and m is the index of DF, we search for a match with DF. m The nearest reference peak is labeled GF. m , obtain DF m With GF m The distance between them is denoted as FL. m ; Clustering algorithm for FL m Clustering was performed to obtain different peak difference clusters, and FL was divided into clusters. m The cluster with the smallest peak difference is named the invalid cluster, and the FLs in the invalid cluster are... m Corresponding DF m Remove the remaining DF m Name it as a valid reference peak; Obtain the two troughs adjacent to the valid reference peak and name them the first trough and the second trough, respectively. The first trough is to the left of the second trough. Obtain the frequencies of the first trough and the second trough and label them PA and PB, respectively. Name the range [PA,PB] as the frequency range. Frequency ranges that overlap are merged into a single frequency range. After merging, all frequency ranges are named a frequency reference range. DFs within the frequency reference range are then... m All were named wear reference peaks.

[0010] Furthermore, the baseline wear relationship between the vibration spectrum and standard wear, analyzed based on the wear reference peak, includes the following sub-steps: Extracting STM n The frequency and signal amplitude of each wear reference peak in the vibration spectrum are used to establish a two-dimensional coordinate system with frequency as the X-axis and signal amplitude as the Y-axis, named the amplitude distribution feature map. The signal amplitude is entered into the amplitude distribution feature map according to the corresponding frequency. Linear regression is performed on the amplitude distribution feature map to obtain the slope of the regression line, named the amplitude distribution parameter. A two-dimensional coordinate system is established with amplitude distribution parameters as the horizontal axis and standard wear as the vertical axis, named the Wear Analysis Chart. The standard wear is then analyzed using STM. n The amplitude distribution parameters corresponding to the vibration spectrum are entered into the wear analysis diagram. Regression analysis is performed on the wear analysis diagram, and the function obtained from the regression analysis is named the benchmark wear relationship.

[0011] Furthermore, the analysis of the influence of environmental data on the vibration spectrum of the FBG sensor based on test data includes the following sub-steps: Based on test data, we analyze the temperature and pressure effects on standard wear. The wear depth calculation environment calibration parameters are based on the temperature effect analysis diagram and the pressure effect analysis diagram.

[0012] Furthermore, the analysis of the temperature and pressure effects on standard wear based on test data includes the following sub-steps: STM n The ambient temperature and pressure remain constant during the STM process. n The ambient temperature and ambient pressure are named reference temperature and reference pressure, respectively, and are represented by the symbols TJ and PJ. STH n The ambient temperature and ambient pressure are denoted as TR. n and PR n Calculate TR n -TJ, marks the calculation result as TC. n Calculate PR n -PJ, marks the calculation result as PC. n ; S n The standard wear mark is BM nSTH is calculated based on the frequency reference range and the reference wear relationship. n The wear depth corresponding to the vibration spectrum in the image is denoted as WD. n Calculate BM n / WD n The calculation result is marked as ID. n ; TC n and PC n Using ID as the X-axis. n Establish two two-dimensional coordinate systems for the Y-axis, named the Temperature Influence Analysis Chart and the Pressure Influence Analysis Chart respectively, and assign ID... n According to TC n and PC n Enter the temperature effect analysis diagram and the pressure effect analysis diagram respectively.

[0013] Furthermore, the environmental calibration parameters for calculating wear depth based on the temperature and pressure influence analysis diagrams include the following sub-steps: Multinomial regression was performed on the temperature influence diagram and the pressure influence diagram respectively, and the resulting curves were named the temperature influence line and the pressure influence line respectively. Obtain the coordinate point on the temperature influence analysis diagram that is above the temperature influence line and furthest from the temperature influence line, and name it the upper limit point of pressure influence. Obtain the coordinate point on the temperature influence analysis diagram that is below the temperature influence line and furthest from the temperature influence line, and name it the lower limit point of pressure influence. Obtain the distances from the upper and lower limits of pressure influence points along the Y-axis to the temperature influence line, and label them as YU and YD, respectively. Suppose that in a certain monitoring, the ambient temperature is TestT and the ambient pressure is TestP. Obtain the Y-axis value of the coordinate point on the pressure influence line where X equals TestP-PJ, and mark it as PH. At the same time, mark the Y-axis values ​​at the left and right endpoints of the pressure influence line as CL and CR respectively. Mark the maximum value of CL and CR as CU and the minimum value as CD. Name the coordinate point on the temperature influence line where X equals TestT-TJ as the initial reference point, label the Y-axis value of the initial reference point as CY, calculate CY-YD and CY+YU, label the calculation results as FU and FD respectively, and name the coordinate points (TestT,FU) and (TestT,FD) as the real-time upper limit reference point and the real-time lower limit reference point respectively. calculate The calculation results are named as environmental calibration parameters.

[0014] Furthermore, after calibrating the real-time monitored vibration spectrum based on the temperature and pressure influence relationship, the calculation of the real-time wear depth of the straightening block based on the reference wear relationship includes the following sub-steps: The vibration spectrum, ambient temperature, and ambient pressure of the straightening block are monitored in real time and named as real-time spectrum, real-time temperature, and real-time pressure, respectively. The wear depth corresponding to the real-time spectrum is calculated based on the frequency reference range and the reference wear relationship, and named as real-time undetermined wear. At the same time, the real-time temperature is subtracted from the reference temperature and the real-time pressure is subtracted from the reference pressure. The calculation results are named as temperature difference and pressure difference, respectively. The temperature difference is considered as TestT, the pressure difference as TestP, and the environmental calibration parameters are calculated. The real-time undetermined wear is multiplied by the environmental calibration parameters to obtain the actual wear depth of the straightening block.

[0015] The beneficial effects of this invention are as follows: This invention installs optical fibers and FBG sensors on the inner side of the metal skeleton of the centralizer, along with temperature and pressure sensors, to monitor the vibration spectrum and environmental data of the centralizer block in real time. Wear tests are then conducted to obtain vibration spectra and environmental data under different wear conditions, which are named test data. The wear reference peaks and frequency reference ranges of the vibration spectrum in the test data are then extracted. Based on the wear reference peaks, the baseline wear relationship between the vibration spectrum and standard wear is analyzed. The advantage is that, compared to traditional vibration sensors, monitoring the vibration spectrum through optical fibers is less affected by external factors in oil wells, resulting in more accurate detection results. Simultaneously, the test preliminarily determines the correspondence between the vibration spectrum and wear depth, providing a data foundation for subsequent calculations. Furthermore, during the analysis, the wear reference peaks and corresponding frequency reference ranges caused by different wear depths are extracted to reduce the influence of other irrelevant peaks on the baseline wear relationship, thus improving the accuracy and effectiveness of centralizer wear monitoring. This invention analyzes the temperature and pressure effects of ambient temperature and pressure on standard wear based on test data. It then uses these effects as environmental calibration parameters to calculate wear depth. Finally, it calibrates the real-time monitored vibration spectrum based on the temperature-pressure relationship and calculates the real-time wear depth of the straightener block based on the baseline wear relationship. The advantage lies in the fact that ambient temperature and pressure significantly affect the vibration spectrum detected by optical fiber, requiring calibration. Furthermore, the interaction between ambient temperature and pressure comprehensively impacts the detection results. Therefore, the analysis process needs to consider both effects and calibrate the detection results, improving the accuracy and rationality of straightener wear monitoring. Attached Figure Description

[0016] Figure 1 This is a flowchart of the steps of the method of the present invention; Figure 2 This is a simplified schematic diagram of the effective peak analysis diagram of the present invention; Figure 3 This is a schematic diagram of the effective reference peak of the present invention; Figure 4 This is a schematic diagram of the temperature effect analysis of the present invention; Figure 5 This is a schematic diagram of the pressure effect analysis diagram of the present invention; Figure 6 This is a schematic diagram of the initial reference point, real-time upper limit reference point, and real-time lower limit reference point of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Example 1, please refer to Figure 1 As shown, this application provides a method for monitoring the wear of sucker rod centralizer centralizer blocks based on optical detection, including the following steps: Step S1 involves installing optical fibers and FBG sensors inside the metal frame of the centralizer, along with temperature and pressure sensors, to monitor the vibration spectrum of the centralizer and environmental data in real time. Step S1 includes the following sub-steps: Step S101: Install an optical fiber inside the metal frame of the stabilizer, and install an FBG sensor at the optical fiber at the same horizontal position as the stabilizer block of the stabilizer, in the radial direction. Step S102: Install a temperature and pressure sensor at the same horizontal position as the FBG sensor inside the metal frame. Monitor the ambient temperature and ambient pressure at the FBG sensor using the temperature and pressure sensor, which are collectively referred to as environmental data. Step S103: The reflected wavelength of the FBG sensor is monitored in real time by a demodulator to obtain the time-domain waveform of the reflected wavelength. The time-domain waveform is then subjected to a fast Fourier transform to obtain the spectrum of the reflected wavelength, which is named the vibration spectrum. In practice, the centralizer consists of a multi-layered structure. The metal frame is located at the innermost layer and is hollow. An optical fiber is installed close to the metal frame, running from top to bottom along the entire length of the centralizer. The optical fiber is evenly distributed along the axial direction on the inner wall of the metal frame and fixed with high-temperature resistant adhesive to ensure no bending or stress concentration. FBG sensors are engraved at the radial center of each centralizer block to ensure the accuracy and spatial consistency of vibration response acquisition. At the same horizontal position, a temperature and pressure sensor is installed at the same position as the FBG sensor. The FBG sensor is essentially a grating that reflects light of a specific wavelength, engraved in the fiber core. When the centralizer vibrates, causing the optical fiber to dynamically stretch, this reflected wavelength will experience a corresponding slight drift. By rapidly tracking this drift with a demodulator, the time-domain waveform of the vibration can be obtained. Then, a fast Fourier transform is performed to obtain the vibration spectrum. Since the time-domain waveform is obtained by direct monitoring, and the fast Fourier transform is a classic time-domain signal to frequency-domain signal conversion processing technique, and no special processing is performed in this embodiment, this embodiment will not provide a detailed description, but only gives the final processed vibration spectrum.

[0019] Step S2 involves conducting wear tests to obtain vibration spectra and environmental data under different wear conditions, which are then named test data. Step S2 includes the following sub-steps: Step S201: Randomly obtain the first number of uprighting blocks that have been put into use, name them as sample blocks, measure the wear depth of the sample blocks, and name them as standard wear; Step S202: Install the sample block on the stabilizer to obtain a set of test experimental groups. There are a first number of test experimental groups in total. The sample block is installed in the same position in different test experimental groups. Step S203: Sort and number the test groups according to the standard wear from smallest to largest, using the symbol S. n It is represented as follows, where n is a non-zero natural number and n is the index of S, where the standard wear of S1 is fixed at 0; In practice, the first quantity is determined by the tester, usually by the number of straightening blocks with wear depths that are approximately evenly distributed. Since the wear of the straightening blocks cannot be specifically defined, it is impossible to obtain straightening blocks with specific wear for reference. Therefore, straightening blocks already in use are directly selected for reference. The straightening blocks in use have different wear depths. The disadvantage is that the sample distribution of wear depth is not uniform. Compared with uniformly distributed sample blocks, the final analysis of the benchmark wear relationship and voltage stabilization effect relationship has a slight deviation. However, this deviation is small and can usually be ignored. At the same time, when selecting sample blocks, manual selection is required. Try to select wear depths with equal arithmetic progression as sample blocks. For example, in this embodiment, the wear depths of the selected sample blocks are 0mm, 1.33mm, 2.23mm, 3.16mm, 3.97mm, 4.86mm, 6.18mm and 7.24mm, thus obtaining 8 test experimental groups, corresponding to S1 to S8 in sequence.

[0020] Step S204: Obtain the common depth of the stabilizer, move the stabilizer block downward to the common depth, start the stabilizer, and record the detected vibration spectrum and environmental data, collectively referred to as wear test data; Step S205: Randomly change the depth of the centralizer and record the detected vibration spectrum and environmental data, collectively referred to as environmental experimental data. Step S206, the wear test data and environmental test data are collectively referred to as test data, and S... n The test data is labeled ST n ST n The wear test data and environmental test data in the sample are labeled as STM. n and STH n ; In practice, the commonly used depth of the stabilizer is 1600m. The stabilizer block is moved down to a depth of 1600m, and the stabilizer is started to detect wear test data. Since the ambient temperature and pressure in the oil well are related to the depth, the depth of the stabilizer can be randomly changed to detect different vibration spectra of the stabilizer block with the same wear depth under different ambient temperature and pressure conditions, i.e., environmental test data.

[0021] Step S3 involves analyzing the baseline wear relationship between the wear depth of the straightening block and the vibration spectrum based on the test data. Step S3 includes the following sub-steps: Step S301: Extract the wear reference peak and frequency reference range of the vibration spectrum from the test data; Step S301 includes the following sub-steps: Please see Figure 2 As shown, in step S3011, for any STMn When analyzing the vibration spectrum in STM0, it is named the wear spectrum to be analyzed. The wear spectrum to be analyzed is superimposed with the vibration spectrum in STM0 to obtain the effective peak analysis diagram. The effective peak analysis diagram includes the reference peak and the peak to be analyzed. The reference peak belongs to the vibration spectrum in STM0, and the peak to be analyzed belongs to the wear spectrum to be analyzed. Step S3012: Number the peaks to be analyzed in order from left to right, using the symbol DF. m This means that, where m is a non-zero natural number and m is the index of DF, we search for a match with DF. m The nearest reference peak is labeled GF. m , obtain DF m With GF m The distance between them is denoted as FL. m ; Please see Figure 3 As shown, in step S3013, the FL is clustered using a clustering algorithm. m Clustering was performed to obtain different peak difference clusters, and FL was divided into clusters. m The cluster with the smallest peak difference is named the invalid cluster, and the FLs in the invalid cluster are... m Corresponding DF m Remove the remaining DF m Name it as a valid reference peak; Step S3014: Obtain two troughs adjacent to the valid reference peak, and name them as the first trough and the second trough respectively. The first trough is to the left of the second trough. Obtain the frequencies of the first trough and the second trough, and label them as PA and PB respectively. Name the range [PA,PB] as the frequency range. Step S3015: Merge the frequency ranges that overlap into a single frequency range, and then name all the frequency ranges as frequency reference ranges. DFs within the frequency reference range are then... m All were named wear reference peaks; In practice, since not all characteristic peaks in the vibration spectrum are related to the wear of the straightening block, it is necessary to filter them to reduce the influence of other factors. The vibration spectrum in STM0 and STM... n The only difference between the vibration spectra in the two datasets is the wear depth. Therefore, if the characteristic peaks are caused by changes in wear depth, there will definitely be significant differences between the characteristic peaks. Similar characteristic peaks, however, are not related to wear depth and can be discarded. For example, the vibration spectrum in STM2 can be used as the wear spectrum to be analyzed, and the effective peak analysis diagram can be obtained by overlaying the spectra. Figure 2 As shown, the original vibration spectrum peaks are too dense, making it unsuitable for data examples in this embodiment. Figure 2 The data processing procedure in this embodiment is illustrated using only simplified diagrams. Figure 2 The solid line represents the baseline peak, and the dashed line represents the peak to be analyzed. Figure 2 It can be seen that there are some very similar characteristic peaks, while there are also some characteristic peaks with large differences. Since the frequency of characteristic peaks is not fixed but fluctuates, the distance between the baseline peak and the peak to be analyzed is obtained as a reference. For example, the distance FL1 between DF1 and GF1 is 8.42. Similarly, FL2, FL3, FL4, FL5 and FL6 are obtained as 9.58, 11.88, 38.48 and 8.33 respectively. Through clustering algorithm analysis, two peak difference clusters are obtained. The first peak difference cluster includes 8.42, 9.58, 11.88 and 8.33, and the second peak difference cluster includes 38.48. The FL values ​​in the first peak difference cluster are... m The minimum value is used to eliminate all peaks to be analyzed in the first peak difference cluster, leaving the remaining valid reference peaks as follows: Figure 3 As shown, a trough is the lowest point between two peaks. Figure 3 The two intersections of the effective reference peak and the X-axis, from left to right, represent the first and second troughs. PA and PB are obtained as 234Hz and 248Hz respectively, thus yielding a frequency range of [234Hz, 248Hz]. This frequency range is only obtained from a simplified schematic diagram in this embodiment; in actual analysis, numerous frequency ranges will be obtained. Similarly, the analysis can be performed on each STM group except for STM1. n The frequency range, for example, if there is another frequency range [244Hz, 262Hz] that intersects with [234Hz, 248Hz], then they are merged into the frequency range [234Hz, 262Hz], and finally different frequency reference ranges are obtained. The frequency reference range is the range of frequencies that the wear depth will affect. Analyzing only the wear reference peaks within the frequency reference range can minimize the interference of other factors.

[0022] Step S302: Analyze the reference wear relationship between the vibration spectrum and the standard wear based on the wear reference peak; Step S302 includes the following sub-steps: Step S3021, extract STM n The frequency and signal amplitude of each wear reference peak in the vibration spectrum are used to establish a two-dimensional coordinate system with frequency as the X-axis and signal amplitude as the Y-axis, named the amplitude distribution feature map. The signal amplitude is entered into the amplitude distribution feature map according to the corresponding frequency. Linear regression is performed on the amplitude distribution feature map to obtain the slope of the regression line, named the amplitude distribution parameter. Step S3022: Establish a two-dimensional coordinate system with amplitude distribution parameters as the horizontal axis and standard wear as the vertical axis, named "Wear Analysis Chart". Then, apply the standard wear data using STM... nThe amplitude distribution parameters corresponding to the vibration spectrum are entered into the wear analysis diagram. Regression analysis is performed on the wear analysis diagram, and the function obtained from the regression analysis is named the benchmark wear relationship. In practice, the amplitude distribution feature map, with frequency as the X-axis and signal amplitude as the Y-axis, reveals the distribution characteristics of the wear reference peak in a vibration spectrum. The slope of the calculated regression line is an index representing the distribution characteristics of the wear reference peak. Different wear depths have different distribution characteristics of the wear reference peak in the vibration spectrum, that is, they have different amplitude distribution parameters. By analyzing the functional relationship between wear depth and amplitude distribution parameters, the baseline wear relationship can be obtained. Since the processing procedure and principle are relatively simple, they will not be listed in detail in this embodiment. In this embodiment, the baseline wear relationship obtained is Y = 8730.3 × X + 3.1408, where Y is the standard wear and X is the amplitude distribution parameter.

[0023] Step S4 involves analyzing the temperature and pressure influence of the environmental data of the FBG sensor on the vibration spectrum based on the test data. Step S4 includes the following sub-steps: Step S401: Analyze the temperature and pressure effects of ambient temperature and pressure on standard wear based on the test data. Step S401 includes the following sub-steps: Step S4011, STM n The ambient temperature and pressure remain constant during the STM process. n The ambient temperature and ambient pressure are named reference temperature and reference pressure, respectively, and are represented by the symbols TJ and PJ. STH n The ambient temperature and ambient pressure are denoted as TR. n and PR n Calculate TR n -TJ, marks the calculation result as TC. n Calculate PR n -PJ, marks the calculation result as PC. n ; In practice, since the straightening blocks are all at the same depth during wear test data analysis, their ambient temperature and pressure are the same. Furthermore, the baseline wear relationship is obtained from the wear test data analysis. Therefore, the ambient temperature and pressure are used as the baseline temperature and pressure, resulting in baseline temperatures of 73℃ and baseline pressures of 16MPa. For example, STH1 contains a data point with an ambient temperature of 86℃ and an ambient pressure of 20.3MPa. From this, TC1 is calculated to be 86℃ - 73℃ = 13℃, and PC1 is calculated to be 20.3MPa - 16MPa = 4.3MPa. It should be noted that STH1 contains not just this one data point, but several data points; that is, each STH...n There are several vibration spectra and environmental data; similarly, all STH values ​​can be calculated. n TC for all environmental data n and PC n .

[0024] Step S4012, S n The standard wear mark is BM n STH is calculated based on the frequency reference range and the reference wear relationship. n The wear depth corresponding to the vibration spectrum in the image is denoted as WD. n Calculate BM n / WD n The calculation result is marked as ID. n ; Please see Figures 4 to 5 As shown, in step S4013, respectively using TC n and PC n Using ID as the X-axis. n Establish two two-dimensional coordinate systems for the Y-axis, named the Temperature Influence Analysis Chart and the Pressure Influence Analysis Chart respectively, and assign ID... n According to TC n and PC n Enter the temperature effect analysis diagram and the pressure effect analysis diagram respectively; In specific implementation, BM1 to BM8 are 0mm, 1.33mm, 2.23mm, 3.16mm, 3.97mm, 4.86mm, 6.18mm, and 7.24mm respectively. For example, after extracting the amplitude distribution parameters from the vibration spectrum of a certain data point in STH2 and substituting them into the reference wear relationship, WD2 is obtained as 1.68mm, and ID2 is calculated as 0.79. The calculation results are rounded to two decimal places, and the temperature influence analysis diagram and pressure influence analysis diagram are constructed as follows. Figure 4 and Figure 5 As shown.

[0025] Step S402: Based on the temperature influence analysis diagram and the pressure influence analysis diagram, environmental calibration parameters are used to calculate the wear depth. Step S402 includes the following sub-steps: Step S4021: Perform multinomial regression on the temperature influence analysis diagram and the pressure influence analysis diagram respectively, and name the curves obtained from the regression as the temperature influence line and the pressure influence line respectively. Step S4022: Obtain the coordinate point on the temperature influence analysis diagram that is above the temperature influence line and furthest from the temperature influence line, and name it the upper limit point of pressure influence; obtain the coordinate point on the temperature influence analysis diagram that is below the temperature influence line and furthest from the temperature influence line, and name it the lower limit point of pressure influence. In practice, temperature influence lines and pressure influence lines have been established. Figure 4 and Figure 5 The exhibition is shown in the middle, where, Figure 4 The curve in the figure is the temperature influence line. Figure 5 The curve in the figure is the pressure influence line, which is formed by... Figure 4 and Figure 5 It is evident that the temperature effect analysis plot has a higher degree of fit than the pressure effect analysis plot, i.e., ID. n The influence of ambient temperature on ID is greater than that of ambient pressure, and the influence of ambient temperature on ID is greater. n At the same time, environmental stress will simultaneously affect ID. n This leads to the dispersion of coordinate points in the temperature influence analysis diagram. The upper limit point and lower limit point of pressure influence correspond to the influence of the lowest and highest environmental pressures on the distribution of coordinate points in the temperature influence analysis diagram, respectively. The values ​​of YU and YD are 0.21 and 0.17, respectively.

[0026] Step S4023: Obtain the distances between the upper and lower limit points of pressure influence and the temperature influence line in the Y-axis direction, and label them as YU and YD, respectively; Step S4024: Assuming that in a certain monitoring, the ambient temperature is TestT and the ambient pressure is TestP, obtain the Y-axis value of the coordinate point on the pressure influence line where X equals TestP-PJ, and mark it as PH. At the same time, mark the Y-axis values ​​at the left and right endpoints of the pressure influence line as CL and CR respectively, mark the maximum value of CL and CR as CU, and the minimum value as CD. Please see Figure 6 As shown, in step S4025, the coordinate point on the temperature influence line where X equals TestT-TJ is named the initial reference point, the Y-axis value of the initial reference point is marked as CY, CY-YD and CY+YU are calculated, and the calculation results are marked as FU and FD respectively. The coordinate points (TestT,FU) and (TestT,FD) are named the real-time upper limit reference point and the real-time lower limit reference point respectively. Step S4026, Calculate The calculation results are named as environmental calibration parameters; In specific implementation, assuming that in a certain monitoring session, the ambient temperature is 79℃ and the ambient pressure is 18MPa, the Y-axis value of the coordinate point on the pressure influence line where X equals 18MPa - 16MPa = 2MPa is obtained, yielding PH of 0.79, CL of 0.56, and CR of 1.52, where CL < CR. Therefore, CU is 1.52 and CD is 0.56. The coordinate point on the temperature influence line where X equals 79℃ - 73℃ = 6℃ is named the initial reference point. The initial reference point, real-time upper limit reference point, and real-time lower limit reference point are then obtained as follows: Figure 6 As shown, from top to bottom, the real-time upper limit reference point, the initial reference point, and the real-time lower limit reference point are respectively: the initial reference point is (6, 1.15), the real-time upper limit reference point is (6, 0.98), and the real-time lower limit reference point is (6, 1.36), meaning FU is 1.36 and FD is 0.98. The real-time upper limit reference point corresponds to the coordinate point obtained when the environmental pressure is at its minimum under constant environmental temperature, while the real-time lower limit reference point corresponds to the coordinate point obtained when the environmental pressure is at its maximum under constant environmental temperature. These correspond to CU and CD in the pressure influence analysis diagram. The aim is to explore the effect of the current environmental pressure on ID. n To understand the influence of temperature, we can refer to the positional relationship between the coordinate point corresponding to TestP and CU and CD in the pressure influence analysis diagram. Assuming that the Y-axis of the coordinate point corresponding to the current ambient temperature and ambient pressure in the temperature influence analysis diagram is β, then there are relationships PH / CU=β / FU and PH / CD=β / FD. We can convert these to β=PH / CU×FU or PH / CD×FD. Calculating the average of these two values ​​gives us β, which is the environmental calibration parameter. In this embodiment, when the ambient temperature is 79℃ and the ambient pressure is 18MPa, the corresponding environmental calibration parameter is calculated to be [(0.79 / 1.52×1.36)+(0.79 / 0.56×0.98)] / 2=1.045. The calculation result is rounded to three decimal places.

[0027] Step S5 involves calibrating the real-time monitored vibration spectrum based on the temperature and pressure influence relationship, and then calculating the real-time wear depth of the straightening block based on the reference wear relationship. Step S5 includes the following sub-steps: Step S501: Monitor the vibration spectrum, ambient temperature and ambient pressure of the straightening block in real time, and name them as real-time spectrum, real-time temperature and real-time pressure respectively. Step S502: Calculate the wear depth corresponding to the real-time spectrum based on the frequency reference range and the reference wear relationship, and name it real-time undetermined wear. At the same time, calculate the real-time temperature minus the reference temperature and the real-time pressure minus the reference pressure, and name the calculation results as temperature difference and pressure difference, respectively. Step S503: Treat the temperature difference as TestT and the pressure difference as TestP, calculate the environmental calibration parameters, multiply the real-time undetermined wear by the environmental calibration parameters, and obtain the actual wear depth of the straightening block. In practice, for example, during a monitoring session, the real-time temperature was 79℃ and the real-time pressure was 18MPa. The real-time undetermined wear obtained from the real-time spectrum analysis was 3.86mm. The environmental calibration parameter corresponding to the real-time temperature of 79℃ and the real-time pressure of 18MPa was 1.045. Calculating 3.86mm × 1.045, the actual wear depth of the straightening block was found to be 4.0337mm.

[0028] Example 2: This application provides an electronic device, which may include a processor, a communication interface, a memory, and a communication bus. The processor, communication interface, and memory communicate with each other via the communication bus. The memory stores computer-readable instructions, and the processor can call these instructions. When the processor executes a computer-readable instruction, it performs steps such as those in the optical detection-based sucker rod centralizer wear monitoring method to achieve the following functions: real-time monitoring of the centralizer's vibration spectrum and environmental data; conducting wear tests to obtain vibration spectra and environmental data under different wear conditions, naming them test data; analyzing the baseline wear relationship between the centralizer's wear depth and the vibration spectrum based on the test data; analyzing the temperature and pressure influence of the environmental data of the FBG sensor on the vibration spectrum based on the test data; calibrating the real-time monitored vibration spectrum based on the temperature and pressure influence relationship, and then calculating the real-time wear depth of the centralizer based on the baseline wear relationship.

[0029] Furthermore, when the logical instructions in the aforementioned memory can be implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0030] Example 3: This application also provides a computer program product, which includes a computer program stored on a computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by the computer, the computer can execute the optical detection-based sucker rod centralizer centralizer wear monitoring method provided by the above methods. The method includes: real-time monitoring of the vibration spectrum and environmental data of the centralizer; performing wear tests to obtain vibration spectra and environmental data under different wear states, naming them test data; analyzing the reference wear relationship between the wear depth of the centralizer and the vibration spectrum based on the test data; analyzing the temperature and pressure influence relationship of the environmental data of the FBG sensor on the vibration spectrum based on the test data; calibrating the real-time monitored vibration spectrum based on the temperature and pressure influence relationship, and calculating the real-time wear depth of the centralizer based on the reference wear relationship.

[0031] Example 4: This application also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it performs the steps in the above-described method for monitoring the wear of the centralizer block of a sucker rod centralizer based on optical detection, to achieve the following functions: real-time monitoring of the vibration spectrum and environmental data of the centralizer block; conducting wear tests to obtain vibration spectra and environmental data under different wear states, naming them test data; analyzing the reference wear relationship between the wear depth of the centralizer block and the vibration spectrum based on the test data; analyzing the temperature and pressure influence relationship of the environmental data of the FBG sensor on the vibration spectrum based on the test data; calibrating the real-time monitored vibration spectrum based on the temperature and pressure influence relationship, and calculating the real-time wear depth of the centralizer block based on the reference wear relationship.

[0032] Based on the above description of the embodiments, the embodiments of the present invention can be provided as methods, systems, or computer program products. Based on this understanding, the above technical solutions, in essence or in terms of their contribution to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or certain parts of the embodiments.

[0033] In the embodiments provided in this application, it should be understood that the disclosed system or method can be implemented in other ways. The embodiments described above are merely illustrative. For example, the division of modules or units is only a logical functional division, and there may be other division methods in actual implementation. Furthermore, multiple modules or units may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be through some communication interfaces. The indirect coupling or communication connection between systems, modules, and units may be electrical, mechanical, or other forms.

[0034] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for monitoring wear of sucker rod centralizer centralizer blocks based on optical detection, characterized in that, Includes the following steps: An optical fiber and an FBG sensor are installed inside the metal frame of the centralizer, along with a temperature and pressure sensor, to monitor the vibration spectrum of the centralizer and environmental data in real time. Wear tests were conducted to obtain vibration spectra and environmental data under different wear conditions, which were named test data. The baseline wear relationship between the wear depth of the straightening block and the vibration spectrum was analyzed based on test data. Based on test data analysis, the relationship between the environmental data of the FBG sensor and the temperature and pressure effects on the vibration spectrum is analyzed. After calibrating the real-time monitored vibration spectrum based on the temperature and pressure influence relationship, the real-time wear depth of the straightening block is calculated based on the reference wear relationship.

2. The method for monitoring wear of sucker rod centralizer centralizer blocks based on optical detection according to claim 1, characterized in that, An optical fiber and an FBG sensor are installed inside the metal frame of the centralizer, along with a temperature and pressure sensor, to monitor the vibration spectrum of the centralizer and environmental data in real time. This includes the following sub-steps: An optical fiber is installed inside the metal frame of the stabilizer, and an FBG sensor is installed at the optical fiber at the same horizontal position as the stabilizer block, in the radial direction. A temperature and pressure sensor is installed at the same horizontal position as the FBG sensor inside the metal frame. The ambient temperature and pressure at the FBG sensor are monitored by the temperature and pressure sensor, and are collectively referred to as environmental data. The reflected wavelength of the FBG sensor is monitored in real time by a demodulator to obtain the time-domain waveform of the reflected wavelength. The fast Fourier transform is performed on the time-domain waveform to obtain the spectrum of the reflected wavelength, which is named the vibration spectrum.

3. The method for monitoring wear of sucker rod centralizer centralizer blocks based on optical detection according to claim 2, characterized in that, The wear test is conducted to obtain vibration spectra and environmental data under different wear conditions, including the following sub-steps: Randomly select the first number of uprighting blocks that have been put into use, name them sample blocks, measure the wear depth of the sample blocks, and name them standard wear; The sample block was installed on the straightener to obtain a test experimental group. There was a total of the first number of test experimental groups. The sample block was installed in the same position in different test experimental groups. The test groups are ranked in order of standard wear from small to large, and are denoted by the symbol S n where n is a non-zero natural number and n is the rank of S, where the standard wear of S1 is fixed at 0; To obtain the commonly used depth of the stabilizer, move the stabilizer block downwards to the commonly used depth, start the stabilizer, and record the detected vibration spectrum and environmental data, collectively referred to as wear test data. The depth of the centralizer was randomly changed, and the detected vibration spectrum and environmental data were recorded. These are collectively referred to as environmental experimental data. The wear test data and environmental test data are collectively referred to as test data, and S n The test data is labeled ST n ST n The wear test data and environmental test data in the sample are labeled as STM. n and STH n .

4. The method for monitoring wear of sucker rod centralizer centralizer blocks based on optical detection according to claim 3, characterized in that, The analysis of the reference wear relationship between the wear depth of the straightening block and the vibration spectrum based on test data includes the following sub-steps: Extract the wear reference peak and frequency reference range from the vibration spectrum in the test data; The relationship between the vibration spectrum and the standard wear was analyzed based on the wear reference peak.

5. The method for monitoring wear of sucker rod centralizer centralizer blocks based on optical detection according to claim 4, characterized in that, Extracting the wear reference peak and frequency reference range from the vibration spectrum in the test data includes the following sub-steps: When analyzing the vibration spectrum in any STM n , it is named as a wear spectrum to be analyzed, the wear spectrum to be analyzed is overlapped with the vibration spectrum in STM0, an effective peak analysis diagram is obtained, the effective peak analysis diagram includes a reference peak and a peak to be analyzed, the reference peak belongs to the vibration spectrum in STM0, and the peak to be analyzed belongs to the wear spectrum to be analyzed. The peaks to be analyzed are numbered in the order from left to right, and are denoted by symbols DF m , wherein m is a non-zero natural number and m is the serial number of DF m , the nearest reference peak to DF m is found and is denoted by GF m , the distance between DF m and GF m is obtained and is denoted by FL Clustering algorithm for FL m Clustering was performed to obtain different peak difference clusters, and FL was divided into clusters. m The cluster with the smallest peak difference is named the invalid cluster, and the FLs in the invalid cluster are... m Corresponding DF m Remove the remaining DF m Name it as a valid reference peak; Obtain the two troughs adjacent to the valid reference peak and name them the first trough and the second trough, respectively. The first trough is to the left of the second trough. Obtain the frequencies of the first trough and the second trough and label them PA and PB, respectively. Name the range [PA,PB] as the frequency range. The frequency ranges in which there is an intersection are merged into one frequency range, and after merging all the frequency ranges are named as frequency reference range, and the DFs that are in the frequency reference range are named as wear reference peaks. m All are named as wear reference peaks.

6. The method for monitoring wear of sucker rod centralizer centralizer blocks based on optical detection according to claim 5, characterized in that, The analysis of the reference wear relationship between the vibration spectrum and standard wear based on the wear reference peak includes the following sub-steps: Extracting the frequency of each wear reference peak in the vibration spectrum in STM n and the signal amplitude, establish a two-dimensional coordinate system with frequency as X-axis and signal amplitude as Y-axis, name it as amplitude distribution characteristic map, record the signal amplitude according to the corresponding frequency in the amplitude distribution characteristic map, perform linear regression on the amplitude distribution characteristic map, obtain the slope of the regression straight line, and name it as amplitude distribution parameter; A two-dimensional coordinate system is established with the amplitude distribution parameter as the horizontal axis and the standard wear as the vertical axis, named the wear analysis diagram. The standard wear is entered into the wear analysis diagram according to the amplitude distribution parameter corresponding to the vibration spectrum in STM n , and regression analysis is performed on the wear analysis diagram. The function obtained by the regression analysis is named the reference wear relationship.

7. The method for monitoring wear of sucker rod centralizer centralizer blocks based on optical detection according to claim 6, characterized in that, The analysis of the influence of environmental data on the vibration spectrum of the FBG sensor based on test data includes the following sub-steps: Based on test data, we analyze the temperature and pressure effects on standard wear. The wear depth calculation environment calibration parameters are based on the temperature effect analysis diagram and the pressure effect analysis diagram.

8. The method for monitoring wear of sucker rod centralizer centralizer blocks based on optical detection according to claim 7, characterized in that, The analysis of the temperature and pressure effects on standard wear based on test data includes the following sub-steps: STM n The ambient temperature and pressure remain constant during the STM process. n The ambient temperature and ambient pressure are named reference temperature and reference pressure, respectively, and are represented by the symbols TJ and PJ. STH n The ambient temperature and ambient pressure are denoted as TR. n and PR n Calculate TR n -TJ, marks the calculation result as TC. n Calculate PR n -PJ, marks the calculation result as PC. n ; S n tandard wear mark as BM n , based on the frequency reference range and the reference wear relationship, the vibration spectrum in STH n corresponds to the wear depth, marked as WD n , calculate BM n / WD n , the calculation result is marked as ID n ; TC n and PC n The X-axis is used as the reference point, and ID is used as the reference point. n Establish two two-dimensional coordinate systems for the Y-axis, named the Temperature Influence Analysis Diagram and the Pressure Influence Analysis Diagram respectively. (ID...) n According to TC n and PC n Enter the temperature effect analysis diagram and the pressure effect analysis diagram respectively.

9. The method for monitoring wear of sucker rod centralizer centralizer blocks based on optical detection according to claim 8, characterized in that, The environmental calibration parameters for calculating wear depth based on temperature and pressure effect analysis diagrams include the following sub-steps: Multinomial regression was performed on the temperature influence diagram and the pressure influence diagram respectively, and the resulting curves were named the temperature influence line and the pressure influence line respectively. Obtain the coordinate point on the temperature influence analysis diagram that is above the temperature influence line and furthest from the temperature influence line, and name it the upper limit point of pressure influence. Obtain the coordinate point on the temperature influence analysis diagram that is below the temperature influence line and furthest from the temperature influence line, and name it the lower limit point of pressure influence. Obtain the distances from the upper and lower limits of pressure influence points along the Y-axis to the temperature influence line, and label them as YU and YD, respectively. Suppose that in a certain monitoring, the ambient temperature is TestT and the ambient pressure is TestP. Obtain the Y-axis value of the coordinate point on the pressure influence line where X equals TestP-PJ, and mark it as PH. At the same time, mark the Y-axis values ​​at the left and right endpoints of the pressure influence line as CL and CR respectively. Mark the maximum value of CL and CR as CU and the minimum value as CD. Name the coordinate point on the temperature influence line where X equals TestT-TJ as the initial reference point, label the Y-axis value of the initial reference point as CY, calculate CY-YD and CY+YU, label the calculation results as FU and FD respectively, and name the coordinate points (TestT,FU) and (TestT,FD) as the real-time upper limit reference point and the real-time lower limit reference point respectively. calculate The calculation results are named as environmental calibration parameters.

10. The method for monitoring wear of sucker rod centralizer centralizer blocks based on optical detection according to claim 9, characterized in that, After calibrating the real-time monitored vibration spectrum based on the temperature and pressure influence relationship, the real-time wear depth of the straightening block is calculated based on the reference wear relationship, including the following sub-steps: The vibration spectrum, ambient temperature, and ambient pressure of the straightening block are monitored in real time and named as real-time spectrum, real-time temperature, and real-time pressure, respectively. The wear depth corresponding to the real-time spectrum is calculated based on the frequency reference range and the reference wear relationship, and named as real-time undetermined wear. At the same time, the real-time temperature is subtracted from the reference temperature and the real-time pressure is subtracted from the reference pressure. The calculation results are named as temperature difference and pressure difference, respectively. The temperature difference is considered as TestT, the pressure difference as TestP, and the environmental calibration parameters are calculated. The real-time undetermined wear is multiplied by the environmental calibration parameters to obtain the actual wear depth of the straightening block.

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