Three-dimensional multi-source stray current interference characteristic analysis and identification method based on wavelet analysis

Abstract

The invention relates to a three-dimensional multi-source stray current interference characteristic analysis and identification method based on wavelet analysis. When a buried pipeline is subjected to electrical interference of different interference sources (such as high-voltage transmission line current, high-voltage direct-current grounding electrode grounding current, electrified railway and high-speed railway current, urban rail transit current and natural environment such as tidal interference current), the buried pipeline is subjected to electrical interference. And identifying and analyzing the pipe-to-ground potential and alternating current voltage fluctuation characteristics (amplitude characteristics and frequency characteristics) under stray current interference, judging the influence of interference sources on the safety and stability of the buried steel pipeline, solving the problems of analysis, identification and processing of multiple interference sources in the existing complex environment, improving the monitoring and treatment level of the interference sources of the buried steel pipeline, and improving the safety and reliability of the buried steel pipeline. Safe and reliable operation of the pipeline is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of corrosion protection for facilities such as buried steel pipelines, and in particular to a numerical analysis and processing method for identifying and analyzing stray current interference characteristics in buried steel pipelines under interference from different interference sources. Background Art

[0002] With the acceleration of urbanization, electrified and high-speed railways, urban rail transit (such as subways and trams), and high-voltage power projects (such as transmission lines) are increasingly intersecting with buried pipelines. This dense, three-dimensional layout results in increasingly frequent exposure to stray currents in buried pipelines. The intensity of these currents fluctuates over time, complicating the identification of corrosion risks for buried pipelines. The interference characteristics of different interference sources are typically identified based on frequency, time, and amplitude characteristics. Frequency characteristics are considered the primary parameter for distinguishing interference sources, and different interference sources exhibit significant differences in interference frequency. Time characteristics, on the other hand, provide a more intuitive representation of the temporal distribution of pipe-to-ground potential and AC voltage under stray current interference. Amplitude reflects the intensity of interference from different interference sources on buried pipelines.

[0003] In actual operating conditions, due to the significant differences in interference characteristics from different interference sources, analyzing the ground potential fluctuation characteristics of buried pipelines under stray current interference and conducting risk assessments present significant challenges. Currently, several main methods exist for analyzing ground potential fluctuation characteristics of buried pipelines under stray current interference. One method involves local amplification, which manually identifies interference characteristics by capturing potential data over a period of time. This method requires careful observation and is highly subjective, leading to significant errors. Another method uses Fourier transforms to analyze the fluctuation characteristics of potential data. While this method can yield clearer frequency characteristics, it also loses time-domain information. Although wavelet analysis is also widely used in stray current interference analysis, researchers have focused more on capturing frequency-domain information. Less attention has been paid to time-domain information.

[0004] Therefore, the present invention proposes a three-dimensional multi-source stray current interference feature analysis and identification method based on frequency-time-amplitude wavelet analysis. Summary of the Invention

[0005] In order to overcome the shortcomings of the existing technology, the purpose of the present invention is to provide a three-dimensional multi-source stray current interference feature analysis and identification method based on wavelet analysis. When buried steel pipelines are affected by electrical interference from different interference sources, such as high-voltage transmission line current, electrified railway and high-speed railway current, urban rail transit current, high-voltage DC grounding electrode current, and natural environment such as tidal interference current, the stray current interference characteristics and the buried pipeline ground potential fluctuation characteristics are analyzed, especially the impact of interference sources on the safety and stability of buried pipelines.

[0006] The technical solution adopted by the present invention to solve its technical problem is: A three-dimensional multi-source stray current interference feature analysis and identification method based on wavelet analysis is established to analyze the pipeline stray current interference feature under different interference sources, combining the interference source characteristics and the pipeline ground potential and AC voltage fluctuation characteristics. The three dimensions are frequency, time, and amplitude. Specifically, the following steps are included: Step S1. Collect data on the buried pipeline near various interference sources, such as high-voltage transmission line engineering currents, high-voltage DC grounding electrode grounding currents, electrified railway and high-speed railway currents, urban rail transit currents, and natural environment interference currents such as tidal interference currents. Data collection is carried out using the test piece power-off method, and the uDL2 with storage function and continuous recording is used to record data; the collected data includes the buried pipeline power-off potential and AC voltage; the collection process is continuous and lasts for no less than 24 hours; Step S2. Preprocessing the data collected in step S1; deleting the data recorded simultaneously with the power-off potential in the AC voltage; wherein the data recorded simultaneously with the power-off potential is data with a value of 0 in the AC voltage data; Step S3. Statistical analysis of interference characteristics of different interference sources on buried pipelines; the interference characteristics are performed in the time domain; specifically, the pipe-to-ground potential and the amplitude of the AC voltage, including the maximum, minimum, and average values; Step S4. Use wavelet analysis to extract and analyze the characteristics of the collected pipeline off-line potential and AC voltage. This characteristic is obtained in the frequency domain, specifically the interference frequency and interference amplitude of the pipeline off-line potential and AC voltage. It also includes time domain information (specifically, the acquisition time).

[0007] Specifically, a three-dimensional time-frequency graph is drawn with the acquisition time as the X-axis, the interference frequency as the Y-axis, and the amplitude as the Z-axis. The XZ data can show the overall trend of the data over time and determine the interference intensity; the XY data can identify the trend of the interference frequency over time; and the YZ data can determine the main components of the stray current interference frequency and identify different interference sources. The basis function of wavelet analysis is the Morlet function, which is an attenuated wavelet basis function with compact support characteristics. The sampling frequency of wavelet analysis is set, and its specific characteristic is that it is the reciprocal of the time interval of data acquisition. Step S5: Based on the time domain and frequency domain characteristics of pipeline interference, an interference identification technology is formed to accurately determine the type and intensity of interference to the pipeline.

[0008] Beneficial effects: The present invention provides a three-dimensional multi-source stray current interference feature analysis and identification method based on frequency-time-amplitude wavelet analysis, which solves the problem of analysis, identification and processing of different interference sources in existing complex environments. In actual projects, buried steel pipelines are susceptible to electrical interference from different interference sources, such as high-voltage transmission line currents, electrified railway and high-speed railway currents, urban rail transit currents, high-voltage DC grounding electrode currents, and natural environments such as tidal interference currents. The stray current flow law is analyzed by amplitude feature statistical analysis and wavelet analysis-based frequency feature analysis to identify the type and intensity of interference to the pipeline, determine the impact of interference sources on the safety and stability of buried steel pipelines, improve the level of monitoring and management of buried pipelines, and ensure the safe and reliable operation of pipelines. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 Graphs showing high-voltage transmission line engineering data in an embodiment of the present invention; (a) 24-hour monitoring data, (b) three-dimensional time-frequency graphs using wavelet analysis; Figure 2 This is a diagram of interference data for electrified railways and high-speed railways in an embodiment of the present invention; (a) 24-hour monitoring data, (b) three-dimensional time-frequency diagram of wavelet analysis; Figure 3 This is a diagram of urban rail transit interference data in an embodiment of the present invention; wherein, (a) 24-hour monitoring data, (b) three-dimensional time-frequency diagram of wavelet analysis; Figure 4 Graphs showing the interference data of the high-voltage DC grounding electrode into the ground current in an embodiment of the present invention; (a) 24-hour monitoring data, (b) three-dimensional time-frequency graph of wavelet analysis; Figure 5 Graphs of tidal disturbance data in an embodiment of the present invention; (a) 24-hour monitoring data, (b) three-dimensional time-frequency graph of wavelet analysis. DETAILED DESCRIPTION

[0010] The present invention will now be described in further detail with reference to the accompanying drawings. Example

[0011] A three-dimensional multi-source stray current interference feature analysis and identification method based on wavelet analysis, the steps are as follows: S1. Collect the off-line potential and AC voltage data of the buried pipeline using the test strip off-line method. The measurement should be conducted for at least 24 hours. The uDL2's on / off cycle is set to 15s / 3s, with a sampling interval of 3s or 1s. In addition, a 150ms delay is used for off-line potential data collection.

[0012] S2. Preprocess the pipeline-to-ground potential and AC voltage data collected using the above method. Delete the pipeline AC voltage data collected simultaneously with the test piece's power-off potential to avoid calculation errors caused by this data.

[0013] S3. Perform interference signature analysis based on the collected pipeline off-line potential and AC voltage data. Calculate the time-domain characteristics of the data interference signature. Specifically, the amplitudes of the pipeline off-line potential and AC voltage, including maximum, minimum, and average values, are included. See Table 1. The amplitude characteristics of the pipeline off-line potential and AC voltage can be used to determine the status of the pipeline's cathodic protection and the intensity of the interference.

[0014] Table 1

[0015] S4. Furthermore, frequency domain feature analysis is performed on the data measured and recorded in the above steps. Continuous wavelet transform technology is used to convert the digital signal from the time domain to the frequency domain. The Morlet wavelet is selected as the basis function for wavelet analysis. The sampling frequency is set to be the reciprocal of the sampling interval of the pipeline off-line potential or AC voltage.

[0016] The conversion process uses time as the X-axis, frequency as the Y-axis, and amplitude as the Z-axis to achieve data visualization. The extracted features include information in the time domain and frequency domain.

[0017] Among them, the time-frequency diagram of high-voltage transmission line project is shown in Figure 1 The X-axis in the figure represents time characteristics. The fluctuations in the pipeline AC voltage are relatively more dramatic during the day than at night. The overall pattern is convex at both ends and concave in the middle. The Y-axis represents frequency characteristics. Under the interference of high-voltage power projects, the fluctuation frequency of the pipeline AC voltage ranges from 0 to 450 MHz, with the frequency with the largest amplitude at 434.1 MHz. There are also interference components at other frequencies. However, the frequency with the largest amplitude is generally of greater concern, as it is the primary source of interference. The Z-axis represents amplitude characteristics. The response strength varies at different frequencies and changes continuously over time, with a maximum value of 1.016.

[0018] The time-frequency diagram of interference of electrified railway and high-speed railway is shown in Figure 2. The X-axis is the time characteristic, with violent fluctuations during the day and gentle fluctuations at night. This is consistent with the operating conditions of the electrified railway. The Y-axis is the frequency characteristic. The fluctuation frequency range of the pipeline AC voltage under mixed interference is 0~450mHz, and the frequency with the largest amplitude is 405.1mHz. In addition, there are interference components with interference frequencies of 101.3mHz and 202.5mHz. The exponential increase in the interference frequency may be related to the number of trains passing at the current moment. The Z-axis is the amplitude characteristic. The response intensity of different frequencies is different and changes continuously over time, with a maximum of 0.25.

[0019] from Figure 1 、 Figure 2 It can be seen that the interference from electrified railways and high-speed railways hardly fluctuates at night, while high-voltage transmission line projects fluctuate significantly at night. This is closely related to the operating conditions of the two interference sources.

[0020] The time-frequency diagram of urban rail transit interference is shown in Figure 3 The X-axis represents the time characteristic, with sharp fluctuations during the day and gentle fluctuations at night. This is consistent with the operating conditions of urban rail transit. The Y-axis represents the frequency characteristic. The fluctuation frequency of the pipe-to-ground potential under rail transit interference ranges from 0 to 35 MHz, with the maximum amplitude at 3.34 MHz. The Z-axis represents the amplitude characteristic. The response strength varies at different frequencies and changes continuously over time, with a maximum of 0.27.

[0021] from Figure 1 、 Figure 3 It can be seen that the frequency range of interference from electrified railways and high-speed railways is larger, and the frequency with the largest amplitude is in the high-frequency region. However, the frequency range of interference from rail transit is relatively smaller, and the frequency with the largest amplitude is in the low-frequency region.

[0022] The time-frequency diagram of the high-voltage DC grounding electrode ground current interference is shown in Figure 4 The X-axis represents the time characteristic. The fluctuation amplitude is smaller when the feed current increases, and larger when the feed current decreases or even reaches zero. The Y-axis represents the frequency characteristic. The fluctuation frequency of the pipe-to-ground potential under the interference of the unbalanced grounding current ranges from 0 to 45 MHz, with the maximum amplitude at 35.26 MHz. The Z-axis represents the amplitude characteristic. The response strength varies at different frequencies and changes continuously over time, with a maximum of 0.13.

[0023] The time-frequency diagram of tidal current interference is shown in Figure 5 The X-axis represents time, with the time-frequency image showing a wavy shape. The Y-axis represents frequency, with the fluctuation frequency of the pipe ground potential under tidal interference ranging from 0 to 30 MHz, with the maximum amplitude at 24.21 MHz. The Z-axis represents amplitude, with the response strength varying at different frequencies and changing over time, with a maximum amplitude of 0.02.

[0024] The frequency domain information is extracted, see Table 2.

[0025] Table 2

[0026] Frequency domain information specifically refers to the frequency with the maximum amplitude in the spectrum image. This frequency is the primary characteristic of stray current interference from different sources affecting the pipeline and can be used to identify the interference source. The frequency domain characteristics shown in Table 2 show that the fluctuation frequency of the pipeline AC voltage due to interference from high-voltage transmission line projects is 434.1 MHz, corresponding to a period of 2.30 seconds. The fluctuation frequency of the pipeline AC voltage due to interference from electrified railways and high-speed railways is 405.1 MHz, corresponding to a period of 2.47 seconds. The fluctuation frequency of the power-off potential due to interference from urban rail transit is 3.34 MHz, corresponding to a period of 299.40 seconds. The fluctuation frequency of the power-off potential due to interference from high-voltage DC grounding electrodes is 35.26 MHz, corresponding to a period of 28.36 seconds. The fluctuation frequency of the power-off potential due to tidal interference is 25.21 MHz, corresponding to a period of 39.67 seconds.

[0027] S5. The above process can synchronously identify the stray current interference of buried steel pipelines to distinguish the interference source and determine the interference type and interference intensity.

[0028] With the above-described preferred embodiments of the present invention as a guide, and with reference to the above description, relevant personnel are fully capable of making various changes and modifications without departing from the technical scope of this invention. The technical scope of this invention is not limited to the contents of the specification and must be determined according to the scope of the claims.

Claims

1. A three-dimensional multi-source stray current interference feature analysis and identification method based on wavelet analysis, characterized in that: When buried pipelines are subject to electrical interference from different interference sources, an analytical relationship between the pipeline stray current interference characteristics is established by combining the interference source characteristics and the pipeline ground potential and AC voltage fluctuation characteristics; the interference sources include but are not limited to high-voltage transmission line currents, high-voltage DC grounding electrode ground currents, electrified railway and high-speed railway currents, urban rail transit currents, and natural environment interference currents such as tidal interference currents.

2. The method for analyzing and identifying three-dimensional multi-source stray current interference characteristics based on wavelet analysis according to claim 1, characterized in that: The specific steps are as follows: Step S1. Collect data on the buried pipeline near different interference sources; the collected data are the power-off potential and AC voltage of the buried pipeline; Step S2. Preprocess the data collected in step S1 and delete the data recorded simultaneously with the power-off potential in the AC voltage; Step S3. Statistics on interference characteristics of different interference sources on buried pipelines; The interference characteristics are measured in the time domain; specifically, the amplitude of the pipe-to-ground potential and the AC voltage, including the maximum, minimum, and average values; Step S4. Use wavelet analysis to extract and analyze the characteristics of the collected pipeline off-line potential and AC voltage, converting the digital signals from the time domain to the frequency domain. This frequency domain characterization includes the interference frequency and amplitude of the pipeline off-line potential and AC voltage, as well as time domain information—acquisition time. Step S5: Based on the time domain and frequency domain characteristics of pipeline interference, an interference identification technology is formed to accurately determine the type and intensity of interference to the pipeline.

3. The method for analyzing and identifying three-dimensional multi-source stray current interference characteristics based on wavelet analysis according to claim 2, characterized in that: In step S1, data collection is performed using the test piece power-off method, and the uDL2 with storage function and continuous recording is used to record data; the collection process is performed continuously and for no less than 24 hours.

4. The method for analyzing and identifying three-dimensional multi-source stray current interference characteristics based on wavelet analysis according to claim 2, characterized in that: In step S2, the data recorded simultaneously with the power-off potential is data having a value of 0 in the AC voltage data.

5. The method for analyzing and identifying three-dimensional multi-source stray current interference characteristics based on wavelet analysis according to claim 2, characterized in that: The conversion of digital signals from the time domain to the frequency domain is to draw a three-dimensional time-frequency diagram with the acquisition time as the X-axis, the interference frequency as the Y-axis, and the amplitude as the Z-axis; the XZ data can display the trend of the overall data changing over time and judge the interference intensity; the XY data can identify the trend of the interference frequency changing over time; the YZ data can determine the main components of the stray current interference frequency and identify different interference sources.

6. The method for analyzing and identifying three-dimensional multi-source stray current interference characteristics based on wavelet analysis according to claim 2, characterized in that: In the step S4, the basis function of the wavelet analysis is selected as the attenuated wavelet basis function Morlet function with compact support characteristics; the sampling frequency of the wavelet analysis is set, which is the reciprocal of the time interval of data collection.

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