An anti-interference pipeline angle deviation detection method and device

Abstract

The application provides an anti-interference pipeline angle deviation detection method and device, and belongs to the technical field of underground pipeline detection. The method comprises the following steps: acquiring electromagnetic field X, Y and Z axis induction signals and corresponding sampling time information; extracting axis amplitude and phase parameters based on signal sequences, calculating amplitude correlation coefficient, phase correlation factor and amplitude stability evaluation parameters; obtaining an initial angle deviation reference value through XY axis amplitude parameters, correcting the amplitude correlation coefficient and weighting and fusing the stability parameters to obtain a final angle deviation reference value; obtaining a precise phase angle difference by combining XY axis phase parameters and the phase correlation factor; calculating the confidence degree based on the Z axis amplitude parameters to determine the effectiveness, and if the effectiveness is valid, the direction is determined according to the quadrant division rule, and if the effectiveness is invalid, the above process is repeated. The method integrates the three-axis signal characteristics, anti-interference is realized through multiple rounds of correction and effectiveness verification, the directional ambiguity is solved, and the detection accuracy and stability are improved.

Description

Technical Field

[0001] This invention relates to the field of underground pipeline detection technology, and more specifically to an interference-resistant pipeline angle deviation detection method and equipment. Background Technology

[0002] In fields such as municipal construction, resource exploration, and pipeline maintenance, accurate location and tracking of underground pipelines are crucial. Pipeline detectors are key equipment for achieving this goal. Their core principle involves a transmitter applying a specific frequency AC signal to the underground pipeline. This signal propagates within the pipeline, generating a secondary electromagnetic field. A receiver on the ground then captures this electromagnetic field signal through its built-in orthogonal induction coils (such as those along the X, Y, and Z axes). In existing technologies, receivers typically extract amplitude and phase information from the induced signal using time-frequency conversion algorithms such as Fast Fourier Transform. They then calculate the amplitude ratio of the horizontal induced signal and use the arctangent function to estimate the horizontal angular deviation between the receiver and the pipeline, thus enabling pipeline tracking.

[0003] However, the aforementioned existing technologies have significant drawbacks. First, in the signal parameter extraction stage, traditional time-frequency analysis methods suffer from slow response speed, limited computational accuracy, and large inter-frame fluctuations in the results, leading to insufficient accuracy and stability in the amplitude and phase baseline data provided for subsequent calculations. Second, relying solely on the amplitude ratio of the horizontal signal for angle determination introduces insurmountable ambiguity: it cannot distinguish whether the receiver is located on the left or right side of the pipeline, nor can it determine whether the calculated angle deviation is less than or greater than 90°, severely impacting the intuitiveness and accuracy of the positioning results. Furthermore, when facing complex on-site electromagnetic interference, existing technologies lack effective anti-interference and fault-tolerance mechanisms, making it difficult to guarantee the reliability of the detection results. Summary of the Invention

[0004] This invention provides an anti-interference pipeline angle deviation detection method and device to solve the problems of low accuracy and poor stability of signal parameter extraction, ambiguity in angle deviation judgment, and weak anti-interference ability in complex electromagnetic environments in the prior art.

[0005] To achieve the above objectives, one embodiment of the present invention provides an anti-interference pipeline angle deviation detection method, comprising the following steps: Step S1: Acquire the induced signals of each axis of the electromagnetic field and the corresponding sampling time information; Step S2: Based on the induced signal sequence, extract the amplitude parameters and phase parameters of the induced signals of each axis, and calculate the amplitude correlation coefficient and phase correlation factor based on the amplitude parameters and phase parameters of multiple axes; calculate the amplitude stability evaluation parameters based on the induced signals of each axis and the corresponding sampling time information; Step S3: Based on the amplitude parameters of the X-axis and Y-axis, obtain the initial amplitude stability evaluation parameters through arctangent calculation. Angle deviation reference value is obtained, and the initial angle deviation reference value is initially corrected based on the amplitude correlation coefficient; a second correction factor is calculated based on the signal amplitude stability evaluation parameter, and the initially corrected angle deviation reference value is weighted and fused to obtain the final angle deviation reference value; Step S4: Based on the phase parameters of the X-axis and Y-axis, the precise phase angle difference is obtained in combination with the phase correlation factor; Step S5: Based on the amplitude parameter of the Z-axis signal, the confidence level of the precise phase angle difference is calculated to determine the effectiveness of the precise phase angle difference, and when the precise phase angle difference is effective, the pipeline angle deviation is oriented in combination with the quadrant division rule.

[0006] Optionally, the calculation of the precise phase angle difference includes: obtaining the initial phase angle difference through difference calculation based on the phase parameters of the X-axis and Y-axis; determining the environmental interference level of the current signal based on the amplitude stability evaluation parameters, and selecting the corresponding target strategy from a plurality of preset compensation strategies according to the environmental interference level to generate dynamic compensation weights; and using the phase correlation factor and the dynamic compensation weights to perform weighted compensation on the initial phase angle difference to obtain the precise phase angle difference.

[0007] Optionally, the calculation of the amplitude correlation coefficient includes: calculating a first ratio of the Z-axis amplitude parameter to the X-axis amplitude parameter and a second ratio of the Z-axis amplitude parameter to the Y-axis amplitude parameter based on the amplitude parameters of the sensing signals of each axis; normalizing the first ratio and the second ratio, and using the weighted average of the two as the amplitude correlation coefficient.

[0008] Optionally, the calculation of the phase correlation factor includes: calculating the first phase difference between the Z-axis phase parameter and the X-axis phase parameter, and the second phase difference between the Z-axis phase parameter and the Y-axis phase parameter, based on the phase parameters of the sensing signals of each axis; normalizing the first phase difference and the second phase difference, and using the weighted average of the two as the phase correlation factor.

[0009] Optionally, the calculation of the amplitude stability evaluation parameters includes: selecting amplitude data corresponding to a preset number of continuous sampling points based on the continuous sampling amplitude parameters and sampling time information corresponding to the sensing signals of each axis; calculating the dispersion index of the selected amplitude data; and obtaining the amplitude stability evaluation parameters after normalizing the dispersion index.

[0010] Optionally, the confidence level calculation includes: calculating the arithmetic mean of the amplitude parameters of the X-axis and Y-axis sensing signals as the amplitude reference value; calculating the ratio of the amplitude parameter of the Z-axis sensing signal to the amplitude reference value as the original confidence level coefficient; calculating the absolute difference between the amplitude parameters of the X-axis and Y-axis, and combining it with the amplitude reference value to obtain the deviation correction amount; multiplying the original confidence level coefficient with the deviation correction amount to obtain the confidence level correction value, and normalizing it to obtain the confidence level of the precise phase angle difference.

[0011] Optionally, step S5 further includes: comparing the confidence level of the calculated precise phase angle difference with the effective confidence threshold; if the confidence level is greater than or equal to the effective confidence threshold, the precise phase angle difference is determined to be valid; if the confidence level is less than the effective confidence threshold, the precise phase angle difference is determined to be invalid.

[0012] Optionally, the quadrant division rule includes four quadrants, and the orientation of the pipeline angle deviation includes: determining the quadrant in which the precise phase angle difference is located according to the quadrant division rule; if the precise phase angle difference is in the first quadrant or the fourth quadrant, determining that the final angle deviation reference value is less than 90° and the receiver is located on the left side of the pipeline extension direction; if the precise phase angle difference is in the second quadrant or the third quadrant, determining that the final angle deviation reference value is greater than 90° and the receiver is located on the right side of the pipeline extension direction.

[0013] Optionally, step S5 further includes: if the precise phase angle difference is invalid, then repeat steps S1 to S5 to obtain the precise phase angle difference again and calculate its confidence level until the precise phase angle difference is determined to be valid.

[0014] On the other hand, a pipeline angle deviation detection device is also provided, which is equipped with the above-mentioned pipeline angle deviation detection method, including a transmitter and a receiver; the transmitter is used to inject an excitation signal of a preset frequency into the underground pipeline to excite the underground pipeline to generate an electromagnetic field; the receiver is equipped with an orthogonal multi-axis sensing component, which is used to collect the sensing signals of the X-axis, Y-axis and Z-axis corresponding to the electromagnetic field, and simultaneously record the sampling time information corresponding to the sensing signals of each axis.

[0015] The present invention provides an anti-interference pipeline angle deviation detection method and device, which extracts the amplitude and phase parameters of the sensing signals of each axis with high precision and synchronously, and constructs amplitude correlation coefficient, phase correlation factor and signal stability evaluation parameters based on the correlation between multi-axis parameters. Then, it performs multi-level correction and weighted fusion on the initial angle deviation benchmark value. At the same time, it uses the phase angle difference quadrant judgment mechanism to eliminate directional ambiguity, and introduces a confidence-based validity judgment and fault tolerance processing mechanism. Finally, it achieves high-precision, omnidirectional unambiguous and high-reliability anti-interference detection of pipeline angle deviation, effectively improving the accuracy and robustness of pipeline positioning in complex environments. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0017] Figure 1 This is a schematic diagram of the pipeline angle deviation detection method provided in an embodiment of the present invention;

[0018] Figure 2 This is a schematic diagram of the three axes provided in an embodiment of the present invention;

[0019] Figure 3 This is a flowchart of the precise phase angle difference calculation provided in the embodiments of the present invention. Detailed Implementation

[0020] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the scope of the present invention.

[0021] It should be noted that the acquisition, transmission, storage, use, and processing of data in the technical solution of this application all comply with the relevant provisions of national laws and regulations. In the embodiments of this application, certain existing industry solutions such as software, components, and models may be mentioned. These should be considered exemplary, intended only to illustrate the feasibility of implementing the technical solution of this application, and do not imply that the applicant has already used or necessarily used such solutions.

[0022] With the increasing demands for high precision and adaptability to complex environments in underground pipeline detection, existing pipeline angle detection technologies suffer from problems such as low signal parameter extraction accuracy and large inter-frame fluctuations, reliance solely on amplitude ratio leading to directional ambiguity in angle judgment, and insufficient reliability in complex environments due to the lack of effective anti-interference mechanisms. Therefore, it is crucial to develop a pipeline angle deviation detection scheme that can achieve high-precision parameter extraction, omnidirectional unambiguous angle judgment, and strong anti-interference capabilities.

[0023] To address this issue, this invention proposes an anti-interference pipeline angle deviation detection method and device. It constructs a high-precision parameter extraction process based on synchronous acquisition of multi-axis induction signals and least-squares sine fitting. The method calculates amplitude correlation coefficients and phase correlation factors based on the correlation between multi-axis amplitude and phase parameters, and uses signal stability evaluation parameters to perform multi-level correction and weighted fusion of the initial angle deviation benchmark value. Simultaneously, it eliminates directional ambiguity through a phase angle difference quadrant judgment mechanism, and combines confidence assessment and fault-tolerant processing strategies to form a complete anti-interference detection system from signal acquisition, parameter extraction, deviation calculation to intelligent decision-making. This significantly improves the accuracy of pipeline angle detection, the accuracy of omnidirectional judgment, and the overall reliability in complex environments.

[0024] The following is combined Figures 1-3 This invention is described in detail.

[0025] like Figure 1 and Figure 2 As shown, this embodiment of the invention provides an anti-interference pipeline angle deviation detection method, including the following steps: Step S1: Acquire the induced signals of each axis of the electromagnetic field and the corresponding sampling time information; Step S2: Based on the induced signal sequence, extract the amplitude parameters and phase parameters of the induced signals of each axis, and calculate the amplitude correlation coefficient and phase correlation factor based on the amplitude parameters and phase parameters of multiple axes; calculate the amplitude stability evaluation parameters based on the induced signals of each axis and the corresponding sampling time information; Step S3: Based on the amplitude parameters of the X-axis and Y-axis, obtain the initial angle deviation basis through arctangent operation. The initial angle deviation reference value is obtained by first calculating the reference value and then performing an initial correction based on the amplitude correlation coefficient; the second correction factor is calculated based on the signal amplitude stability evaluation parameter, and the initially corrected angle deviation reference value is weighted and fused to obtain the final angle deviation reference value; Step S4: Based on the phase parameters of the X-axis and Y-axis, the precise phase angle difference is obtained by combining the phase correlation factor; Step S5: Based on the amplitude parameter of the Z-axis signal, the confidence level of the precise phase angle difference is calculated to determine the effectiveness of the precise phase angle difference, and when the precise phase angle difference is effective, the pipeline angle deviation is oriented by combining the quadrant division rule.

[0026] The induced electromagnetic field signals for each axis are obtained by the receiver after sensing the electromagnetic field generated by the underground pipeline under excitation. This allows for the complete capture of electromagnetic field distribution characteristics from different spatial dimensions. Sampling time information records the acquisition time of each set of induced signals, providing a time reference for signal temporal variation analysis. Amplitude parameters characterize signal strength, while phase parameters reflect the phase state of signal propagation; both are the core foundation for describing signal characteristics. The amplitude correlation coefficient quantifies the degree of correlation between the amplitudes of signals on different axes, the phase correlation factor characterizes the cooperative relationship of the phases of multi-axis signals, and the amplitude stability evaluation parameter measures the stability of the signal amplitude in the temporal dimension.

[0027] Specifically, the formulas for calculating the amplitude parameter and the phase parameter are as follows:

[0028]

[0029]

[0030] in, Represents the amplitude parameter. Represents the phase parameter. and These are the amplitude components of the induced signal on two orthogonal components, respectively.

[0031] Specifically, the formula for calculating the initial angle deviation reference value is as follows:

[0032]

[0033] in, This represents the initial angle deviation reference value. The amplitude parameter representing the X-axis sensing signal. The amplitude parameter represents the Y-axis sensing signal.

[0034] Specifically, the formula for calculating the initial phase angle difference is:

[0035]

[0036] in, Represents the initial phase angle difference. The phase parameter representing the X-axis sensing signal. The phase parameter represents the Y-axis sensing signal.

[0037] Specifically, the initial angle deviation benchmark value is initially obtained through the arctangent operation of the X-axis and Y-axis amplitude parameters. The initial correction utilizes the multi-axis amplitude correlation characteristics to calibrate the initial calculation error. The second correction factor is constructed in conjunction with the signal amplitude stationarity characteristics. Weighted fusion integrates the initial correction results and stability correction terms by reasonably allocating weights, ultimately improving the accuracy of the angle deviation benchmark value. The initial phase angle difference is the direct difference between the two-axis phase parameters. Compensation calibration uses the multi-axis phase synergy relationship to correct interference errors, making the accurate phase angle difference more closely match the actual phase relative relationship. The confidence quantification measures the reliability of the accurate phase angle difference, and the validity determination is used to judge whether it meets the requirements of orientation analysis. The quadrant division rule establishes a classification standard based on the phase angle difference value range, thereby clarifying the directional attribute of the angle deviation and resolving the ambiguity problem of angle deviation judgment.

[0038] The pipeline angle deviation detection method provided in this invention calculates the signal amplitude and phase through orthogonal component quantization, constructs a multi-round correction mechanism by combining multi-axis correlation parameters, and sets up a reliability validity judgment and quadrant division rule. This not only improves the accuracy and stability of signal parameter extraction in complex electromagnetic environments, but also strengthens the anti-interference ability of the method. At the same time, it effectively solves the ambiguity problem of pipeline angle deviation judgment and achieves accurate orientation of pipeline angle deviation.

[0039] like Figure 3 As shown, preferably, the calculation of the precise phase angle difference includes: obtaining the initial phase angle difference through difference calculation based on the phase parameters of the X-axis and Y-axis; determining the environmental interference level of the current signal based on the amplitude stability evaluation parameters, and selecting the corresponding target strategy from multiple preset compensation strategies according to the environmental interference level to generate dynamic compensation weights; and using the phase correlation factor and dynamic compensation weights to perform weighted compensation on the initial phase angle difference to obtain the precise phase angle difference.

[0040] The environmental interference level is a grading standard based on the normalized value range of the amplitude stability evaluation parameter, used to accurately define the interference intensity of the current electromagnetic environment: when the amplitude stability evaluation parameter is in the range of 0 to 0.3, it is judged as a low interference level, at which time the signal amplitude fluctuation is small and the interference effect is weak; when it is in the range of 0.3 to 0.7, it is judged as a medium interference level, the signal has a moderate degree of fluctuation, and the interference has a certain impact on the parameter calculation; when it is in the range of 0.7 to 1.0, it is judged as a high interference level, the signal amplitude fluctuation is violent, and the interference effect is significant.

[0041] Specifically, the compensation strategy is a phase correction scheme preset for different interference levels. Each level corresponds to a specific target strategy: low interference level matches a weak compensation strategy, the core of which is to maintain the basic characteristics of the initial phase angle difference and only offset slight interference through small weight adjustments, with the dynamic compensation weight value ranging from 0.8 to 1.0; medium interference level matches a medium compensation strategy, which needs to balance phase accuracy and correction strength, and neutralizes the interference effect through moderate weight adjustments, with the dynamic compensation weight value ranging from 0.5 to 0.8; high interference level matches a strong compensation strategy, which focuses on enhancing the interference cancellation effect and corrects the interfered phase data through larger weight adjustments, with the dynamic compensation weight value ranging from 0.2 to 0.5.

[0042] Specifically, the dynamic compensation weight is an adjustment parameter extracted from the corresponding compensation strategy based on the environmental interference level. Its value is negatively correlated with the interference intensity; the stronger the interference, the smaller the weight, ensuring that the compensation strength is accurately matched to the interference level. The formula for calculating the precise phase angle difference is:

[0043]

[0044] in, Represents precise phase angle difference, Represents the initial phase angle difference. Represents the phase correlation factor. This represents the dynamic compensation weight.

[0045] Suppose that in a certain detection scenario, the initial phase angle difference between the X-axis and Y-axis phase parameters is 30° after difference calculation, and the amplitude stability evaluation parameter is calculated to be 0.45. According to the classification criteria, this is determined to be a medium interference level, corresponding to a medium compensation strategy and a dynamic compensation weight of 0.65. Simultaneously, the phase correlation factor is calculated to be 0.92 using multi-axis phase parameters. Substituting the above parameters into the formula... =30°×(0.92×0.65), and the final calculated precise phase angle difference is 17.94°, which realizes the targeted correction of the initial phase angle difference under the interference environment and effectively offsets the interference error caused by signal fluctuation.

[0046] The preferred embodiment of the present invention achieves targeted correction for different electromagnetic environments by quantifying the interference level and adapting a dedicated compensation strategy. This allows the phase angle difference calculation to retain the true signal characteristics while effectively offsetting the interference effect, significantly improving the reliability of the accurate phase angle difference and providing a more stable phase basis for subsequent angle deviation orientation.

[0047] Preferably, the calculation of the amplitude correlation coefficient includes: calculating a first ratio of the Z-axis amplitude parameter to the X-axis amplitude parameter and a second ratio of the Z-axis amplitude parameter to the Y-axis amplitude parameter based on the amplitude parameters of the sensing signals of each axis; normalizing the first ratio and the second ratio, and using the weighted average of the two as the amplitude correlation coefficient.

[0048] Further preferably, the calculation of the phase correlation factor includes: calculating the first phase difference between the Z-axis phase parameter and the X-axis phase parameter, and the second phase difference between the Z-axis phase parameter and the Y-axis phase parameter, based on the phase parameters of the sensing signals of each axis; normalizing the first phase difference and the second phase difference, and using the weighted average of the two as the phase correlation factor.

[0049] Specifically, the formula for calculating the amplitude correlation coefficient is as follows:

[0050]

[0051] in Represents the amplitude correlation coefficient. This is the first ratio of the Z-axis to the X-axis amplitude parameters. This represents the second ratio of the Z-axis to the Y-axis amplitude parameters, where N() represents the normalization process. α and β are preset weights, and α+β=1. The weights are preset based on the signal reliability of the XY axis in the detection scenario.

[0052] Specifically, the formula for calculating the phase correlation factor is as follows:

[0053]

[0054] in, Represents the phase correlation factor. The first phase difference between the Z-axis and X-axis phase parameters. Let N represent the second phase difference between the Z-axis and Y-axis phase parameters, and N() represent normalization. The purpose of normalization is to eliminate the dimensional differences between the first ratio and the second ratio, and between the first phase difference and the second phase difference, so that they have an equal basis for weighted calculation. The weighted mean calculation method can allocate weights according to the importance of the XY-axis signals, make full use of the spatial distribution characteristics of the electromagnetic field, and make the calculation of amplitude correlation and phase coordination more in line with the actual detection environment. This provides accurate parameter support for subsequent angle deviation correction and phase angle difference compensation, and enhances the anti-interference performance of the method.

[0055] Specifically, normalization refers to the normalization of linear mapping based on a preset physical reasonable range. The normalization formula for the amplitude ratio is: normalized value = actual ratio / upper limit of reasonable range; the normalization formula for the phase difference is: normalized value = positive phase difference / upper limit of reasonable range. Its core purpose is to eliminate the difference in dimensions, while maintaining the original ratio of the two values ​​through a unified mapping rule.

[0056] Suppose in a certain detection scenario, the amplitude of the X-axis sensing signal is 5V, the Y-axis is 6V, and the Z-axis is 4V. The calculated first ratio of the Z-axis amplitude to the X-axis amplitude is 0.8, and the second ratio of the Z-axis amplitude to the Y-axis amplitude is approximately 0.6667. Normalization is performed on both: the preset physical reasonable range for the amplitude ratio is [0,2]. Therefore, the normalized first ratio is 0.8 / 2 = 0.4, and the normalized second ratio is 0.6667 / 2 ≈ 0.3333. The ratio remains unchanged after normalization. The preset weights are α = 0.5 and β = 0.5. Substituting these values ​​into the formula... The amplitude correlation coefficient was calculated to be approximately 0.3667. Simultaneously, with the X-axis phase at 30°, the Y-axis at 45°, and the Z-axis at 35°, the first phase difference between the Z-axis and the X-axis was calculated to be 5°, and the second phase difference between the Z-axis and the Y-axis was -10°. The preset physical reasonable range for the phase difference was [0, 12°]. After normalization to convert the negative phase difference into a positive characteristic value, it was also calculated using weighted averages of α=0.5 and β=0.5, resulting in a phase correlation factor of approximately 0.625. Both parameters integrate the characteristics of the three-axis signals, effectively reducing the interference effect of single-axis signal fluctuations.

[0057] The preferred embodiment of this invention integrates the amplitude ratio and phase difference characteristics of the three-axis signals, and obtains the amplitude correlation coefficient and phase correlation factor through normalization and weighted mean calculation. This effectively reduces the interference caused by the fluctuation of a single-axis signal, and makes full use of the spatial distribution characteristics of the electromagnetic field. It provides accurate and reliable parameter support for subsequent angle deviation correction and phase angle difference compensation, significantly enhances the anti-interference performance of the method in complex electromagnetic environments, and improves the overall accuracy and stability of pipeline angle deviation detection.

[0058] Preferably, the calculation of the amplitude stability evaluation parameter includes: selecting amplitude data corresponding to a preset number of continuous sampling points based on the continuous sampling amplitude parameters and sampling time information corresponding to the sensing signals of each axis; calculating the dispersion index of the selected amplitude data; and obtaining the amplitude stability evaluation parameter after normalizing the dispersion index.

[0059] The amplitude data corresponding to the preset number of continuous sampling points is a segment of time-series data extracted from the continuous sampling data of the sensing signals of each axis. The purpose of selecting this data segment is to ensure the continuity and representativeness of the samples and avoid the deviation in stability judgment caused by isolated data. The dispersion index is the core parameter for quantifying the degree of fluctuation of the amplitude data. The greater the data fluctuation, the higher the value of the dispersion index, which intuitively reflects the degree of influence of environmental interference on the signal. Normalization processing is used to eliminate the dimensional differences of amplitude data under different detection scenarios, so that the amplitude stability evaluation parameters form a unified value range, which facilitates the establishment of an accurate correspondence with the environmental interference level in the future.

[0060] Specifically, the dispersion index is calculated using the standard deviation, and the formula is:

[0061]

[0062] in, This represents the dispersion index, where n represents the number of continuous sampling points selected. This represents the amplitude data of the i-th sampling point. This represents the arithmetic mean of the amplitude data from the n sampling points in the set, with the denominator using n. 1 represents the degree of freedom correction, which improves the accuracy of dispersion calculation under small sample data and better reflects the statistical characteristics of sampled data in actual detection.

[0063] The calculation method provided in this embodiment of the invention can accurately capture the stability characteristics of signal amplitude through fluctuation quantification analysis of time series data, providing a reliable basis for the selection of subsequent dynamic compensation strategies, thereby improving the method's adaptability and anti-interference performance in complex electromagnetic environments.

[0064] Preferably, the confidence level calculation includes: calculating the arithmetic mean of the amplitude parameters of the X-axis and Y-axis sensing signals as the amplitude reference value; calculating the ratio of the amplitude parameter of the Z-axis sensing signal to the amplitude reference value as the original confidence level coefficient; calculating the absolute difference between the amplitude parameters of the X-axis and Y-axis, and combining it with the amplitude reference value to obtain the deviation correction amount; multiplying the original confidence level coefficient with the deviation correction amount to obtain the confidence level correction value, and normalizing it to obtain the confidence level of the precise phase angle difference.

[0065] The amplitude reference value is obtained by arithmetically averaging the amplitude parameters of the X-axis and Y-axis sensed signals. Its core function is to integrate the amplitude strength of the two axes, weaken the interference of single-axis amplitude fluctuations on subsequent calculations, and form a stable reference benchmark. The original confidence coefficient is obtained by the ratio of the Z-axis sensed signal amplitude parameter to the amplitude reference value. It is used to initially measure the degree of matching between the Z-axis amplitude and the overall XY-axis amplitude levels. The higher the matching degree, the closer the coefficient is to the ideal state. The deviation correction amount is calculated based on the absolute difference between the X-axis and Y-axis amplitude parameters. First, the ratio of the absolute difference to the amplitude reference value reflects the degree of inconsistency between the two axis amplitudes. Then, a correction parameter is formed by reverse adjustment to offset the error caused by this inconsistency in the confidence calculation. Finally, the confidence score is obtained by fusing the original confidence coefficient and the deviation correction amount, and then normalizing the result to a fixed value range to ensure a unified standard for comparison with the effective confidence threshold.

[0066] The preferred embodiment of this invention integrates the amplitude information of three-axis sensing signals, weakens the interference of single-axis fluctuations by using the amplitude reference value, calibrates the amplitude difference between the two axes by the deviation correction amount, and obtains the confidence level through multi-step fusion and normalization, which accurately reflects the reliability of the precise phase angle difference, provides a scientific quantitative basis for the determination of the validity of the phase angle difference, and at the same time enhances the anti-interference capability in complex electromagnetic environments, and improves the accuracy and overall reliability of pipeline angle deviation detection.

[0067] Preferably, step S5 further includes: comparing the confidence level of the calculated precise phase angle difference with the effective confidence threshold; if the confidence level is greater than or equal to the effective confidence threshold, the precise phase angle difference is determined to be valid; if the confidence level is less than the effective confidence threshold, the precise phase angle difference is determined to be invalid.

[0068] More preferably, step S5 further includes: if the precise phase angle difference is invalid, then repeat steps S1 to S5 to obtain the precise phase angle difference again and calculate its confidence level until the precise phase angle difference is determined to be valid.

[0069] The confidence threshold is a quantitative standard calibrated based on extensive experimental data from various electromagnetic environments. Its value is tailored to the signal reliability requirements of common pipeline inspection scenarios, providing a unified and scientific reference for determining the validity of accurate phase angle differences. Validity is determined by directly comparing the confidence level with this effective threshold: when the confidence level reaches or exceeds the effective threshold, it indicates that the accurate phase angle difference is minimally affected by interference and its reliability meets directional requirements, thus it is deemed valid; when the confidence level is below the effective threshold, it indicates that the phase angle difference may have significant errors due to signal interference, thus it is deemed invalid.

[0070] By repeating steps S1 to S5, the sensing signals of each axis are reacquired, and relevant parameters and confidence levels are calculated until a valid and accurate phase angle difference is obtained. This avoids invalid data from entering subsequent orientation stages and causing judgment errors, and also avoids one-time errors caused by instantaneous strong interference by reacquiring signals, ensuring the continuity of the detection process and the reliability of the results.

[0071] Suppose that in a pipeline inspection scenario, the experimentally calibrated effective confidence threshold is 0.7. During the initial inspection, the amplitude baseline value is calculated using the X-axis and Y-axis amplitude parameters. Combined with the Z-axis amplitude parameter and the absolute difference between the two axes, the confidence level for the precise phase angle difference is finally obtained as 0.65. This value is lower than the effective threshold of 0.7, and the precise phase angle difference is deemed invalid. At this point, a closed-loop optimization mechanism is triggered, repeating the entire process of signal acquisition, parameter calculation, and confidence level verification. The re-acquired signal is less affected by transient interference, and the recalculated confidence level is 0.82, higher than the effective threshold. Therefore, the precise phase angle difference is deemed valid, and the subsequent angle deviation orientation stage is entered. This approach avoids judgment errors caused by invalid data and ensures the reliability of the inspection results.

[0072] In a preferred embodiment of the present invention, a reliability screening standard for accurate phase angle difference is established by using a confidence level effective threshold. Combined with a closed-loop optimization mechanism for invalid results, this avoids judgment errors caused by invalid data that has been interfered with entering the orientation process. Furthermore, it corrects the impact of instantaneous interference by repeatedly collecting data. The two work together to enhance the method's adaptability to complex electromagnetic environments and significantly improve the accuracy of pipeline angle deviation orientation and the reliability of detection results.

[0073] Preferably, the quadrant division rule includes four quadrants, and the orientation of pipeline angle deviation includes: determining the quadrant in which the precise phase angle difference is located according to the quadrant division rule; if the precise phase angle difference is in the first quadrant or the fourth quadrant, determining that the final angle deviation reference value is less than 90° and the receiver is located on the left side of the pipeline extension direction; if the precise phase angle difference is in the second quadrant or the third quadrant, determining that the final angle deviation reference value is greater than 90° and the receiver is located on the right side of the pipeline extension direction.

[0074] The quadrant division rule is clearly defined based on the precise phase angle difference range: the first quadrant is 0°≤ <90°, the second quadrant is 90°≤ <180°, the third quadrant is 180°≤ <270°, the fourth quadrant is 270°≤ <360°. This division standard aligns with the orthogonal distribution characteristics of electromagnetic fields, providing a clear angular basis for orientation determination. The core of the orientation logic utilizes the correlation between the quadrant distribution of phase angle difference and the spatial positions of the receiver and pipeline: when the precise phase angle difference is in the first or fourth quadrant, it indicates that the XY axis phase coordination characteristics conform to the electromagnetic field distribution law where the receiver is located to the left of the pipeline extension direction, and the angle deviation does not exceed 90°; when it is in the second or third quadrant, it corresponds to the right position and an angle deviation greater than 90°. This rule, by quantifying the correspondence between angle range and spatial position, completely solves the ambiguity problem of pipeline angle deviation judgment. At the same time, relying on a clear quadrant division standard, the orientation results are intuitive and accurate, providing clear guidance for pipeline positioning in actual detection.

[0075] Suppose that in a certain detection scenario, the accurate phase angle difference after validity determination is 60°. According to the quadrant division rules, 60° is in the first quadrant (0°≤Δφ<90°). Therefore, it is determined that the pipeline angle deviation is less than 90° and the receiver is located to the left of the pipeline extension direction. If in another detection scenario, the accurate phase angle difference is 150°, which is in the second quadrant (90°≤Δφ<180°). Therefore, it is determined that the pipeline angle deviation is greater than 90° and the receiver is located to the right of the pipeline extension direction. Through the clear quadrant and spatial position correspondence, orientation determination can be quickly completed.

[0076] This invention also provides a pipeline angle deviation detection device, configured with the above-mentioned pipeline angle deviation detection method, including a transmitter and a receiver; the transmitter is used to inject an excitation signal of a preset frequency into the underground pipeline to excite the underground pipeline to generate an electromagnetic field; the receiver is equipped with an orthogonal multi-axis sensing component, used to collect the sensing signals of the electromagnetic field on the X-axis, Y-axis and Z-axis, and synchronously record the sampling time information corresponding to the sensing signals of each axis.

[0077] The transmitter injects a preset frequency excitation signal, which is an alternating current signal. This frequency is optimized for the electromagnetic response characteristics of the pipeline, efficiently exciting the underground pipeline to generate a stable and moderately strong electromagnetic field. This provides a clear detection source for subsequent signal acquisition, avoiding signal distortion caused by weak excitation signals or frequency mismatch. The receiver's orthogonal multi-axis sensing component adopts a structure with mutually perpendicular X, Y, and Z axes. The three sensing axes comprehensively cover the spatial distribution dimensions of the electromagnetic field, simultaneously capturing electromagnetic signal components in different directions, eliminating spatial blind spots in signal acquisition, and ensuring that the three-axis signals can fully reflect the spatial characteristics of the electromagnetic field. The synchronously recorded sampling time information provides a precise time reference for the calculation of subsequent amplitude stability evaluation parameters and other time-series data-dependent calculations, ensuring the temporal consistency of parameter calculations. Through the collaborative work of the transmitter and receiver, the equipment provides stable hardware support for the aforementioned detection method, realizing full-process adaptation from electromagnetic field excitation and multi-dimensional signal acquisition to time-series data recording. This ensures that the anti-interference performance and accurate orientation effect of the detection method are fully implemented in practical applications, meeting the pipeline angle deviation detection requirements in complex field environments.

[0078] In summary, the anti-interference pipeline angle deviation detection method and device provided by this invention deeply integrates the amplitude and phase characteristics of X, Y, and Z axis sensing signals, constructs core parameters such as amplitude correlation coefficient and phase correlation factor, and combines a multi-round correction mechanism with a dynamic compensation strategy that adapts to environmental interference levels. This effectively weakens the interference effects of single-axis signal fluctuations and complex electromagnetic environments. By quantifying the degree of signal fluctuation through amplitude stability analysis and establishing a "screening-correction" closed loop for reliability judgment and closed-loop optimization, the high reliability of the precise phase angle difference used for orientation is ensured, avoiding judgment deviations caused by invalid data. With the help of clear quadrant division rules, the ambiguity problem of pipeline angle deviation judgment is completely solved, and the precise correspondence between the angle size and the receiver's spatial position relative to the pipeline is achieved. The supporting equipment, through optimized excitation signal frequency and orthogonal multi-axis sensing component design, achieves efficient electromagnetic field excitation, full-dimensional signal acquisition, and precise synchronization of time-series data, providing adaptable hardware support for the full-process implementation of the detection method. The invention forms a complete technical chain from signal acquisition, parameter calculation, interference cancellation, data verification to precise orientation, which significantly improves the accuracy and stability of pipeline angle deviation detection, effectively adapts to the detection needs of complex field environments, ensures the practicality and reliability of detection results, and provides an efficient and accurate technical solution for actual pipeline positioning operations.

[0079] The above description is merely a preferred embodiment of the technical solution of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for detecting pipeline angle deviation with anti-interference capabilities, characterized in that, Includes the following steps: Step S1: Obtain the induced signals of each axis of the electromagnetic field, and the corresponding sampling time information; Step S2: Based on the sensing signal sequence, extract the amplitude and phase parameters of the sensing signals of each axis, and calculate the amplitude correlation coefficient and phase correlation factor based on the amplitude and phase parameters of the multi-axis; calculate the amplitude stability evaluation parameters based on the sensing signals of each axis and the corresponding sampling time information. Step S3: Based on the amplitude parameters of the X-axis and Y-axis, the initial angle deviation reference value is obtained through arctangent operation, and the initial angle deviation reference value is initially corrected based on the amplitude correlation coefficient; the second correction factor is calculated based on the signal amplitude stability evaluation parameter, and the initially corrected angle deviation reference value is weighted and fused to obtain the final angle deviation reference value. Step S4: Based on the phase parameters of the X-axis and Y-axis, and combined with the phase correlation factor, obtain the accurate phase angle difference; Step S5: Based on the amplitude parameters of the Z-axis signal, calculate the confidence level of the precise phase angle difference to determine the validity of the precise phase angle difference. When the precise phase angle difference is valid, combine the quadrant division rules to orient the pipeline angle deviation.

2. The pipeline angle deviation detection method according to claim 1, characterized in that, The calculation of the precise phase angle difference includes: Based on the phase parameters of the X and Y axes, the initial phase angle difference is obtained through difference calculation; The environmental interference level of the current signal is determined based on the amplitude stability evaluation parameters, and a corresponding target strategy is selected from multiple preset compensation strategies according to the environmental interference level to generate dynamic compensation weights. The initial phase angle difference is weighted and compensated using the phase correlation factor and dynamic compensation weight to obtain the accurate phase angle difference.

3. The pipeline angle deviation detection method according to claim 1, characterized in that, The calculation of the amplitude correlation coefficient includes: Based on the amplitude parameters of the sensing signals of each axis, the first ratio of the Z-axis amplitude parameter to the X-axis amplitude parameter and the second ratio of the Z-axis amplitude parameter to the Y-axis amplitude parameter are calculated respectively. The first ratio and the second ratio are normalized, and their weighted average is used as the amplitude correlation coefficient.

4. The pipeline angle deviation detection method according to claim 1, characterized in that, The calculation of the phase correlation factor includes: Based on the phase parameters of the sensing signals of each axis, the first phase difference between the Z-axis phase parameter and the X-axis phase parameter, and the second phase difference between the Z-axis phase parameter and the Y-axis phase parameter are calculated respectively. The first phase difference and the second phase difference are normalized, and their weighted average is used as the phase correlation factor.

5. The pipeline angle deviation detection method according to claim 1, characterized in that, The calculation of the amplitude stability evaluation parameters includes: selecting amplitude data corresponding to a preset number of continuous sampling points based on the continuous sampling amplitude parameters and sampling time information corresponding to the sensing signals of each axis; calculating the dispersion index of the selected amplitude data; and obtaining the amplitude stability evaluation parameters after normalizing the dispersion index.

6. The pipeline angle deviation detection method according to claim 1, characterized in that, The calculation of the confidence level includes: Calculate the arithmetic mean of the amplitude parameters of the X-axis and Y-axis sensed signals, and use it as the amplitude reference value; Calculate the ratio of the Z-axis induction signal amplitude parameter to the amplitude reference value, and use it as the original confidence coefficient; Calculate the absolute difference between the amplitude parameters of the X-axis and Y-axis, and combine it with the amplitude reference value to obtain the deviation correction amount; The original confidence coefficient is multiplied by the deviation correction amount to obtain the confidence correction value, which is then normalized to obtain the confidence level of the precise phase angle difference.

7. The pipeline angle deviation detection method according to claim 1, characterized in that, Step S5 further includes: comparing the confidence level of the calculated precise phase angle difference with the effective confidence threshold; if the confidence level is greater than or equal to the effective confidence threshold, the precise phase angle difference is determined to be valid; if the confidence level is less than the effective confidence threshold, the precise phase angle difference is determined to be invalid.

8. The pipeline angle deviation detection method according to claim 1, characterized in that, The quadrant division rule includes four quadrants, and the orientation of pipeline angle deviation includes: Determine the quadrant in which the precise phase angle difference is located based on the quadrant division rules; If the precise phase angle difference is in the first or fourth quadrant, the final angle deviation benchmark value is determined to be a pipeline angle deviation of less than 90°, and the receiver is located on the left side of the pipeline extension direction. If the precise phase angle difference is in the second or third quadrant, the final angle deviation benchmark value is determined to be a pipeline angle deviation greater than 90°, and the receiver is located on the right side of the pipeline extension direction.

9. The pipeline angle deviation detection method according to claim 7, characterized in that, Step S5 further includes: if the precise phase angle difference is invalid, then repeat steps S1 to S5 to obtain the precise phase angle difference again and calculate its confidence level until the precise phase angle difference is determined to be valid.

10. A pipeline angle deviation detection device, configured with the pipeline angle deviation detection method as described in any one of claims 1-9, characterized in that, It includes a transmitter and a receiver; the transmitter is used to inject an excitation signal of a preset frequency into the underground pipeline to excite the underground pipeline to generate an electromagnetic field; the receiver is equipped with an orthogonal multi-axis sensing component, which is used to collect the sensing signals of the electromagnetic field on the X-axis, Y-axis and Z-axis, and simultaneously record the sampling time information corresponding to the sensing signals of each axis.

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