Method and system for digitizing hertzian signals for underground pipeline detection

Abstract

The present application relates to the technical field of underground pipeline detection, in particular to a Hertz signal digitization method and system for underground pipeline detection. A stable Hertz frequency digital detection excitation signal is generated by using the phase accumulation mechanism of DDS (direct digital synthesis) technology and digital interpolation translation; a controllable random jitter frequency division strategy is introduced to generate multiple sets of single frequency point voltage signals to reduce spectral aliasing and background noise; the response signal is sampled and filtered by a high-precision ADC and an adaptive FIR low-pass filter; the target underground pipeline is detected, analyzed and alarmed by combining wavelet sub-band frequency band energy normalization analysis and feature vector construction. The present application can digitize the 512 Hertz analog signal of traditional underground pipeline detection, greatly improving the sensitivity, anti-interference ability and signal processing accuracy of underground pipeline detection.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of underground pipeline detection, and in particular to a Hertz signal digitization method and system for underground pipeline detection. BACKGROUND

[0002] In the technical field of underground pipeline detection, conventional detection instruments usually use 512Hz Hertz frequency analog circuits for signal transmission and reception. Although such analog circuits are simple in structure and widely used, the Hertz analog signals generated by them are extremely susceptible to external electromagnetic interference in the actual detection process in complex underground pipeline environments. In complex or high-noise underground environments, the signals have poor stability, resulting in unstable detection results. Secondly, false signals or false responses often occur in analog circuits, making it difficult to distinguish pipeline signals from background noise and causing great difficulty in detection and judgment. At the same time, due to the easy aging or performance drift of components affected by factors such as temperature, the reliability of the system in long-term operation is greatly reduced. In addition, the structure of the analog circuit limits the signal processing accuracy, and it is unable to meet the demand for high-precision extraction of weak signals and high-dynamic-range signals.

[0003] In addition, the traditional analog circuit is difficult to integrate and run complex digital signal processing algorithms such as filtering, adaptive detection, or signal enhancement and feature extraction, which limits the intelligent and refined development of underground pipeline detection technology. At the same time, in terms of maintenance, the debugging and maintenance process of the analog system is complex and tedious, and it is highly dependent on technical personnel, with high maintenance costs. Therefore, it is necessary to develop a method for efficiently and accurately digitizing improved Hertz analog signals to solve the above problems. SUMMARY

[0004] The present application overcomes the shortcomings of the prior art and provides a Hertz signal digitization method and system for underground pipeline detection.

[0005] To achieve the above purpose, the technical solution adopted by the present application is as follows:

[0006] The present application provides a Hertz signal digitization method for underground pipeline detection, comprising the following steps:

[0007] S102: Using DDS technology, phase accumulation digital pipeline detection equipment parameters are determined for the expected detection conditions, a step-by-step phase gradient is generated, and digital interpolation translation of iterative rotation is performed on the step-by-step phase gradient based on the accumulation mapping rule of the 512 Hertz analog signal analog sine wave to obtain a digital detection excitation signal;

[0008] S104: Start the power supply boost IC tuning of the digital pipeline detection equipment to obtain the inherent oscillation frequency of the digital detection excitation signal, accumulate the periodic phase error of the inherent oscillation frequency, and apply controllable random jitter for digital frequency division to generate multiple groups of single-frequency point voltage signals;

[0009] S106: converting the multiple sets of single-frequency voltage signals into operation signals by the coil driving IC, driving the inductive transmitting coil, and using the inductive transmitting coil and the radio frequency antenna to radiate the digital detection excitation signal to the target underground pipeline in the form of single-frequency electromagnetic waves;

[0010] S108: using a high-precision ADC to digitize and collect a plurality of response discrete signals of the target underground pipeline, filtering out high-frequency noise items of the response discrete signals after mixing through an adaptive FIR low-pass filter, performing filter optimization of error code simulation analysis, and generating a digital response feedback signal of the target underground pipeline;

[0011] S110: calculating the frequency band energy power of the digital response feedback signal in different wavelet sub-bands and normalizing and organizing to form a hidden detection feature vector, performing detection analysis on the target underground pipeline based on the hidden detection feature vector, obtaining a detection result, and controlling the digital pipeline detection device to make an alarm according to the detection result.

[0012] Preferably, the S102 specifically comprises the following steps:

[0013] obtaining a detection planning record of the target underground pipeline, reading a detection object type of the target underground pipeline through the detection planning record, and obtaining expected detection working condition parameters of the digital pipeline detection device pre-evaluated and decided for the detection object type in the target underground pipeline;

[0014] introducing a DDS technology, obtaining a closed-loop clock period of the digital pipeline detection device, designing a phase accumulation strategy in the DDS technology according to the closed-loop clock period, and constructing a phase accumulator;

[0015] presetting a sampling frequency and an accumulation bit width suitable for the detection object according to the expected detection working condition parameters, calculating a frequency step control word in the DDS technology according to the sampling frequency and the accumulation bit width, using the frequency step control word to accumulate a phase in the phase accumulator once every closed-loop clock period, and generating a gradual phase gradient;

[0016] extracting a standard 512 Hz analog signal detected by the digital pipeline detection device through a memo log, analyzing quadrant symmetry of an intercept and a slope of a corresponding sinusoidal waveform of the standard 512 Hz analog signal, obtaining symmetry coincidence degrees of sub-waveform segments in a cross-quadrant field, and obtaining an accumulation mapping rule of the analog sinusoidal wave;

[0017] locating a cross-quadrant field where a sub-waveform segment corresponding to the minimum symmetry coincidence degree is located according to a high-bit gradient of the gradual phase gradient, obtaining a waveform blueprint accumulation address, rotating and iterating a low-bit vector of the gradual phase gradient at the waveform blueprint accumulation address, and performing a translation operation of digital interpolation according to the accumulation mapping rule, and obtaining the digital detection excitation signal.

[0018] Preferably, the standard Hertz analog signal detected by the digital pipeline detection device is extracted through the memo log, the quadrant symmetry of the intercept and slope of the corresponding sinusoidal waveform of the standard 512 Hertz analog signal is analyzed and recorded, the symmetry coincidence degree of the sub-waveform segment in the cross-quadrant field and the accumulation mapping rule of the analog sinusoidal wave are obtained, and the method specifically comprises the following steps:

[0019] The memo log of the digital pipeline detection device is obtained, and the standard 512 Hertz analog signal for finding the detection object type applied to the target underground pipeline in a preset time unit is obtained through the memo log;

[0020] The symmetry transformation of the waveform period of the standard 512 Hertz analog signal is performed on the quadrant coordinates by introducing the Hilbert-Huang transformation algorithm, the analog sinusoidal wave is obtained, and the equal-division quadrant field is constructed, and the analog sinusoidal wave is divided into N sub-waveform segments in the equal-division quadrant field;

[0021] Each sub-waveform segment is converted into a Spline waveform differential equation and a linear equation of the spline interpolation control point is solved by using the MATLAB digital software, and the intercept coefficient and the slope value of each Spline waveform differential equation are output;

[0022] In the solving process, a sub-waveform segment is locked from the bird's eye angle of a certain division quadrant field, at this time, the corresponding intercept coefficient and slope value of the sub-waveform segment are generated one by one according to the quadrant symmetry characteristics of the sinusoidal wave, and the cross-symmetry mapping record of each sub-waveform segment in the remaining quadrant field is obtained, the symmetry coincidence degree of the sub-waveform segment in the cross-quadrant field is obtained, and the accumulation mapping rule of the analog sinusoidal wave is constructed.

[0023] Preferably, the minimum symmetry coincidence degree corresponding sub-waveform segment is located in the cross-quadrant field according to the high-bit gradient positioning of the step-by-step phase gradient, the waveform blueprint accumulation address is obtained, the low-bit vector of the step-by-step phase gradient is rotated and iterated on the waveform blueprint accumulation address, and the translation operation of the digital interpolation is performed according to the accumulation mapping rule, and the digital detection excitation signal is obtained, and the method specifically comprises the following steps:

[0024] The gradient recorded in the phase high-bit interval is extracted from the step-by-step phase gradient, which is defined as a high-bit gradient parameter, and the vector recorded in the phase low-bit interval is obtained, which is defined as a low-bit vector parameter;

[0025] According to the high-bit gradient parameter, a symmetry coincidence degree threshold is preset, only the cross-quadrant field corresponding to the sub-waveform segment with the minimum symmetry coincidence degree below the symmetry coincidence degree threshold is extracted, and the cross-quadrant field is marked as the waveform blueprint accumulation address, and the low-bit vector parameter is iteratively rotated on the waveform blueprint accumulation address, so that the low-bit vector tends to the quadrant X axis, and the rotation angle of the waveform phase is continuously accumulated in the iterative rotation process, and the rotation angle quadrant coordinate is obtained.

[0026] Obtain the Y-axis component value and polar coordinate range contained in the low-order vector parameter. If the Y-axis component value approaches or equals 0 and the rotation angle quadrant coordinate reaches the polar coordinate range, then stop the rotation iteration operation of the low-order vector parameter and output the magnitude and iteration phase angle.

[0027] On the waveform blueprint accumulation address, the amplitude of the back-mapping and the phase angle of the iteration are processed by digital complementation of the intercept coefficient and slope value to obtain a series of adjacent and continuous waveform amplitude address codes. According to the accumulation mapping rule, the series of waveform amplitude address codes are subjected to sinusoidal quadrant symmetrical second-order interpolation to finally generate a sinusoidal digital waveform.

[0028] A digital-to-analog converter (DAC) is constructed to input the sinusoidal digital waveform into the DAC for smooth calibration and translation of the 512 Hz analog signal, thereby obtaining the digital detection excitation signal.

[0029] Preferably, step S104 specifically includes the following steps:

[0030] The power supply boost IC of the digital pipeline detection equipment is activated to obtain the origin oscillation frequency of the digital detection excitation signal. An oscillation stability evaluation model is constructed by weighing the changes in the past node circuits of the topology power supply boost IC.

[0031] The frequency stability of the originating oscillation frequency is obtained by evaluating the oscillation stability assessment model.

[0032] If the frequency stability is lower than the preset frequency stability, the boost control strategy of the power supply boost IC for the digital detection excitation signal is optimized until the frequency stability is highly parallel to the preset frequency stability. At this time, the inherent oscillation frequency of the optimized digital detection excitation signal is obtained.

[0033] The frequency division requirement of the digital detection excitation signal is obtained by detecting the planning record. Based on the frequency division requirement, the ideal frequency division ratio and ideal transmission period of the inherent oscillation frequency are preset. The phase accumulator is used to accumulate the fractional part of the inherent oscillation frequency according to the ideal frequency division ratio when one ideal transmission period is experienced, and the frequency phase accumulation value is generated.

[0034] If the frequency phase accumulation value is greater than 1, then a frequency division pulse is generated at this time, and the integer part of the ideal frequency division ratio is subtracted simultaneously to form a series of frequency division period error values ​​for achieving the ideal transmission period and the frequency division pulse layout diagram corresponding to the ideal transmission period.

[0035] An LFSR pseudo-random generation mechanism is introduced. Based on the ideal transmission period, a random jitter value within a constant range is constructed in the LFSR pseudo-random generation mechanism. The random jitter value is applied and injected into a series of frequency division period error values ​​to obtain a controllable jitter period error value for each frequency phase.

[0036] If the controllable jitter period error value is greater than the preset threshold, the frequency division pulse corresponding to the controllable jitter period error value is triggered in advance through the frequency division pulse layout diagram; otherwise, the standardized frequency division is maintained, and multiple sets of single-frequency voltage signals are finally generated.

[0037] Preferably, step S108 specifically includes the following steps:

[0038] The receiving coil of the digital pipeline detection equipment is combined with a high-precision ADC to digitally acquire the response samples of the digital detection excitation signal, thereby obtaining several discrete response signals of the target underground pipeline and the actual modulation frequency of the discrete response signals.

[0039] Based on big data, the working condition case of Hertz analog signal is obtained. According to the detection plan, the working condition case is extracted to obtain the local oscillator reference signal that conforms to the standard Hertz analog signal and is orthogonal and in the same frequency as the actual modulation frequency.

[0040] A DC demodulation domain is constructed, and each discrete response signal and the local oscillator reference signal are migrated to the DC demodulation domain for point-by-point coherent demodulation based on the signal spectrum to obtain multiple sets of mixing signal components;

[0041] An adaptive FIR low-pass filter with a cutoff frequency higher than the signal bandwidth, designed using the Hanning window function, is introduced. The adaptive FIR low-pass filter is used to filter each group of the mixed signal components to remove high-frequency noise terms and obtain the demodulated DC component value of the feedback response discrete signal after filtering.

[0042] Based on the decoding rules of digital pipeline detection equipment, a signal receiving and decoding simulation model is constructed. The demodulated DC component value is imported into the signal receiving and decoding simulation model for simulation, and the analog bit error rate after filtering the feedback response discrete signal is obtained.

[0043] If the simulated bit error rate is greater than the preset bit error rate threshold, the filtered feedback response discrete signal is defined as the first filtered signal, the current signal-to-noise ratio of the first filtered signal is obtained, and the filtered directional benchmark feedback response discrete signal that satisfies the detection planning record is obtained based on big data and defined as the second filtered signal, and the expected signal-to-noise ratio of the second filtered signal is obtained.

[0044] The deviation between the current signal-to-noise ratio and the desired signal-to-noise ratio is calculated to obtain the signal-to-noise ratio deviation value. Based on the signal-to-noise ratio deviation value, the filtering parameters of the adaptive FIR low-pass filter are reconfigured and double filtering is performed until the signal-to-noise ratio deviation value is eliminated, thereby generating the digital response feedback signal of the target underground pipeline.

[0045] Preferably, step S110 specifically includes the following steps:

[0046] The existing time-series dynamic characteristics and frequency fluctuation range of the digital response feedback signal are obtained, and the frequency fluctuation range is divided into wavelet sub-bands with different detail coefficient scales based on the existing time-series dynamic characteristics.

[0047] The wavelet transform algorithm is introduced to transfer the digital response feedback signal from the time domain to the frequency domain, and the dynamic change spectrum of the digital response feedback signal fluctuates over time is obtained.

[0048] Extract the spectral amplitude of each wavelet sub-band within the dynamic transition spectrum, construct a power periodicity map based on the spectral amplitude, calculate the power spectral density at each level of detail coefficients based on the power periodicity map, and sum the squares to obtain the band power energy value of each wavelet sub-band.

[0049] A preset reference frequency band power energy threshold is established, and the ratio of the power energy value of each frequency band to the reference frequency band power energy threshold is calculated to eliminate the individual frequency band differences in the digital response feedback signal and obtain multiple frequency band power energy ratios.

[0050] Using dynamic time sequence as the contextual clue trajectory, the frequency band power energy value of each wavelet sub-band is normalized and organized according to the frequency band power energy ratio to form the hidden detection feature vector of the digital response feedback signal.

[0051] Based on big data, the accurate detection feature vector of the target type is obtained, and the degree of matching between the hidden detection feature vector and the accurate detection feature vector is calculated. If the degree of matching is greater than the preset degree of matching, the digital response feedback signal is marked and output as the target detection signal result, and the digital pipeline detection equipment is controlled to issue an alarm.

[0052] A second aspect of the present invention provides a Hertz signal digitization system for underground pipeline detection, applicable to any of the Hertz signal digitization methods for underground pipeline detection described in the present invention, the system comprising:

[0053] Digital signal generation module: The digital signal generation module is equipped with DDS technology, which is used for phase accumulation and digital interpolation translation to generate a 512Hz digital detection excitation signal;

[0054] Signal transmission module: The digital signal transmission module includes a power supply boost IC unit, a digital frequency divider unit, a coil drive IC unit, and an inductor coil unit, which is responsible for transmitting a 512Hz digital detection excitation signal to the target underground pipeline;

[0055] Digital signal processing module: The digital signal processing module is equipped with high-precision ADC technology and adaptive FIR filter, which is used to digitally acquire several discrete response signals of the target underground pipeline and perform mixing and filtering to improve the signal-to-noise ratio;

[0056] Intelligent signal analysis module: The intelligent signal analysis module is responsible for calculating the frequency band energy power of the digital response feedback signal to detect and analyze the target underground pipeline;

[0057] Pipeline detection alarm module: The pipeline detection alarm module is used to control the digital pipeline detection equipment to issue an alarm based on the detection results.

[0058] This invention addresses the technical deficiencies in the prior art, and its beneficial technical effects are as follows:

[0059] By combining the phase accumulation mechanism of DDS (Direct Digital Synthesis) technology with digital interpolation translation algorithms, a stable Hertz frequency digital detection excitation signal can be generated with high precision and low distortion, improving the frequency controllability and phase continuity of the signal source. During the signal radiation stage, a controllable random jitter frequency division strategy is introduced to generate multiple sets of single-frequency voltage signals, effectively reducing spectral aliasing and background noise, and improving the penetration and positioning resolution of the detection signal for the target underground pipeline. High-precision ADC and adaptive FIR low-pass filters are used to sample and filter the response signal, significantly enhancing the ability to extract weak underground response signals and reducing interference from high-frequency noise. Furthermore, by combining wavelet sub-band frequency band energy normalization analysis and feature vector construction, high-dimensional expression and intelligent discrimination of underground pipeline features are achieved, improving the accuracy of target identification and the reliability of detection results. In summary, this invention digitally improves the 512Hz underground pipeline detection analog circuit, realizing end-to-end digital optimization from signal excitation to response analysis, effectively improving the sensitivity, anti-interference capability, and signal processing accuracy of underground pipeline detection. Attached Figure Description

[0060] To more clearly illustrate the technical solutions in the embodiments of the present 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 only some embodiments of the present invention. For those skilled in the art, other embodiments can be obtained from these drawings without creative effort.

[0061] Figure 1 A first method flowchart for Hertz signal digitization method used for underground pipeline detection is shown;

[0062] Figure 2 A flowchart of a second method for digitizing Hertzian signals for underground pipeline detection is shown.

[0063] Figure 3 A system framework diagram of a Hertz signal digitization method for underground pipeline detection is shown;

[0064] Figure 4The system hardware architecture diagram of the signal transmission module is shown. Detailed Implementation

[0065] To better understand the above-mentioned objectives, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0066] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and therefore the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0067] The first aspect of this invention provides a method for digitizing Hertzian signals for underground pipeline detection, such as... Figure 1 As shown, it includes the following steps:

[0068] S102: The desired detection conditions of the digital pipeline detection equipment using DDS technology are determined, and a progressive phase gradient is generated. Based on the accumulation mapping rule of the simulated sine wave of the 512 Hz analog signal, the progressive phase gradient is iteratively rotated and digitally interpolated to obtain the digital detection excitation signal.

[0069] S104: Start the power supply boost IC of the digital pipeline detection equipment to optimize and obtain the inherent oscillation frequency of the digital detection excitation signal, accumulate the periodic phase error of the inherent oscillation frequency and apply controllable random jitter to perform digital frequency division, and generate multiple sets of single-frequency voltage signals.

[0070] S106: The coil driver IC converts multiple single-frequency voltage signals into running signals to drive the inductor transmitting coil. The inductor transmitting coil and the radio frequency antenna are responsible for radiating the digital detection excitation signal to the target underground pipeline in the form of a single-frequency electromagnetic wave.

[0071] S108: Use a high-precision ADC to digitally acquire several discrete response signals of the target underground pipeline, filter out the high-frequency noise terms after mixing of the discrete response signals using an adaptive FIR low-pass filter, and perform filtering optimization through bit error simulation analysis to generate the digital response feedback signal of the target underground pipeline.

[0072] S110: Calculate the frequency band energy power of the digital response feedback signal in different wavelet sub-bands and normalize the organization to form a hidden detection feature vector. Based on the hidden detection feature vector, perform detection and analysis on the target underground pipeline to obtain the detection results. Control the digital pipeline detection equipment to issue an alarm based on the detection results.

[0073] It should be noted that during field exploration, this invention typically requires one RF antenna for basic transmission and reception in single-frequency applications using the 512Hz digital detection excitation signal. However, in multi-frequency applications such as ranging, geodesy, or depth measurement, which require multi-point detection and geometric calculations, at least three or more RF antennas are needed to maintain the transmission and reception of multiple signals at different frequencies (such as GPS L1+L2). This utilizes frequency differentials to eliminate ionospheric delay and improve the accuracy of digital signal pipeline space exploration.

[0074] Preferably, S102, as Figure 2 As shown, the specific steps include:

[0075] The detection planning record of the target underground pipeline is obtained. The detection object type of the target underground pipeline is read from the detection planning record. The expected detection working conditions of the digital pipeline detection equipment in the target underground pipeline are pre-evaluated and decided for the detection object type.

[0076] DDS technology is introduced to obtain the closed-loop clock period of digital pipeline detection equipment. Based on the closed-loop clock period, a phase accumulation strategy is designed in DDS technology to construct a phase accumulator.

[0077] Based on the desired detection conditions, the parameters are set to adapt to the sampling frequency and accumulation bit width of the detection object. The frequency step control word is calculated in DDS technology according to the sampling frequency and accumulation bit width. The phase is accumulated once in the phase accumulator after each closed-loop clock cycle using the frequency step control word to generate a gradual phase gradient.

[0078] The standard 512 Hz analog signal detected by the digital pipeline detection equipment is extracted by memo log. The quadrant symmetry of the intercept and slope of the corresponding sinusoidal waveform of the standard 512 Hz analog signal is analyzed and recorded. The symmetry overlap of the sub-waveform segments in the cross quadrant domain and the accumulation mapping rule of the analog sine wave are obtained.

[0079] Based on the high-order gradient of the progressive phase gradient, the cross quadrant region of the sub-waveform segment corresponding to the minimum symmetry overlap is located, and the waveform blueprint accumulation address is obtained. The low-order vector of the progressive phase gradient is rotated and iterated on the waveform blueprint accumulation address, and the digital interpolation translation operation is performed according to the accumulation mapping rule to obtain the digital detection excitation signal.

[0080] It should be noted that traditional digital pipeline detection equipment cannot accurately and directly generate digital signals that correspond to 512 Hz analog signals, and its frequency stability is less than 0.1 ppm. To address this, this method utilizes DDS technology on the digital pipeline detection equipment to generate a highly targeted and adaptable periodic waveform frequency that meets the specific needs of the equipment in searching for the target underground pipeline. Simultaneously, a phase accumulator is constructed using DDS technology to continuously accumulate the phase value of the periodic waveform frequency, thereby generating a linear digital phase sequence conforming to 512 Hz. This is equivalent to creating a digital phase ramp, enabling high-precision control of the digital waveform's progression. The frequency step control word determines the phase amplitude that should be accumulated each clock cycle of the digital pipeline detection equipment to sample and search for the target object, achieving direct control of the output waveform frequency. This converts traditional analog frequency to digital domain control, rapidly capturing frequency jumps or scanning behavior, and significantly improving the output stability and resolution of the 512 Hz digital signal. The periodic accumulation of the phase accumulator outputs a phase value that represents the timing node position of the 512Hz digital waveform of the target object within a sampling period. The progressive phase gradient shows the gradual cyclic trend of the digital waveform. The parameters are controlled according to the desired detection conditions, which effectively controls the output period of the digital waveform. This makes the 512Hz digital signal meet the requirements of the detection plan and better replace the 512Hz analog signal in the detection of the target underground pipeline.

[0081] It should be noted that DDS technology, or Direct Digital Frequency Synthesis, is used to synthesize and output high-precision and high-stability sine, square, or triangular waves without the need for circuit reconstruction. In this method, a sine waveform reference template generated from a standard Hertz analog signal is used as the 512Hz digital signal. Quadrant coordinates are employed to perform a symmetrical transformation and decomposition of the standard Hertz analog signal waveform, along with differential equation-based analysis of the intercept and slope symmetry. This constructs a waveform characteristic formulation rule that highly adheres to the traditional standardized Hertz analog signal, accurately identifying the target object type. This rule is the accumulation mapping rule for Hertz frequency domain sine waves, providing a highly reliable and trustworthy underlying logic for waveform reconstruction in the precise generation of 512Hz digital signals. Furthermore, this method analyzes the gradual phase gradient in the quadrant domain through rotational iteration, thereby achieving dynamic programmable adjustment and control of the sinusoidal waveform. This replaces the inefficient step of traditional DDS technology, which uses lookup tables to define the waveform amplitude. Finally, based on the constructed accumulation mapping rule, digital interpolation tracks the rotating phase vector planned by the phase accumulator for the 512Hz digital waveform, forming a more accurate 512Hz digital probe excitation signal and ensuring that the frequency stability of the digital signal is better than 0.1ppm. This method achieves a digital improvement on the traditional 512Hz analog signal, enhancing the frequency controllability and phase continuity of the signal source, thereby mitigating the susceptibility of analog signals to environmental noise interference and significantly reducing the emission rate of spurious signals.

[0082] Preferably, the step of extracting the standard Hertz analog signal detected by the digital pipeline detection device through the memo log, analyzing and recording the quadrant symmetry of the intercept and slope of the corresponding sine waveform of the standard 512 Hertz analog signal, and obtaining the symmetry overlap of sub-waveform segments in the cross-quadrant domain and the accumulation mapping rule of the analog sine wave specifically includes the following steps:

[0083] Obtain the memo log of the digital pipeline detection equipment, and obtain the standard 512 Hz analog signal of the digital pipeline detection equipment applying the target underground pipeline to find the type of object to be detected within a preset time unit from the memo log;

[0084] The Hilbert-Huang transform algorithm is introduced to perform a symmetrical transformation of the waveform period of the standard 512 Hz analog signal on the quadrant coordinates to obtain an analog sine wave. An equally divided quadrant domain is constructed, and the analog sine wave is divided into N sub-waveform segments in the equally divided quadrant domain.

[0085] Using MATLAB digital software, each sub-waveform segment is converted into a spline waveform differential equation and the linear equation of the spline interpolation control points is solved, outputting the intercept coefficient and slope value of each spline waveform differential equation;

[0086] During the solution process, a sub-waveform segment is locked from a bird's-eye view of a certain quadrant. At this time, according to the quadrant symmetry characteristics of the sine wave, the corresponding intercept coefficient and slope value are generated for each sub-waveform segment. The corresponding intercept coefficient and slope value are then generated and the sub-waveform segments in the other quadrants are cross-symmetrically mapped. The symmetry overlap of the sub-waveform segments in the cross quadrants is obtained, and the accumulation mapping rule of the simulated sine wave is constructed.

[0087] It should be noted that, for the construction of the accumulation mapping rule for the Hertz frequency domain signal sine wave, this method linearly segments the waveform of the standard Hertz analog signal on the quadrant coordinates, i.e., sub-waveform segments. The quadrant coordinates are divided into four equally divided quadrants (quadrant 1, quadrant 2, quadrant 3, and quadrant 4). The layout of the sub-waveform segments within the equally divided quadrants can explain the quadrant symmetry mechanism of the sine wave period. Sine waves usually have special four-quadrant symmetry characteristics, which makes each sine wave in each quadrant have a symmetric rule that can be followed with sine waves in other quadrants. For example, the second quadrant is the opposite of the first quadrant, or the third quadrant is the negative of the first quadrant, etc. This provides a tracing clue for the accurate reconstruction of the periodic waveform of digital signals. Therefore, based on this symmetry characteristic, this method transforms and solves each sub-waveform segment in the form of a Spline waveform differential equation. The intercept coefficient represents the intersection of the local sinusoidal waveform of the standard Hertz analog signal with the quadrant period time axis, clarifying the starting point of the amplitude of the sinusoidal waveform of the standard Hertz analog signal. The slope value represents the rate of change of the local derivative of the sinusoidal waveform data of the standard Hertz analog signal, revealing the rising or falling speed of the corresponding band of the sinusoidal waveform data. Combining the intercept coefficient and the slope value can reflect the symmetrical positive and negative half-cycles and instantaneous frequency changes of the sinusoidal waveform of the standard Hertz analog signal, making the subsequent mapping and reconstruction of the 512Hz sinusoidal digital waveform more detailed and improving the frequency period stability and waveform accuracy of the digital signal generation. Finally, based on the four-quadrant symmetry of the sine wave, the intercept coefficients and slope values ​​of the sub-waveform segments in each quadrant are cross-mapped and recorded to construct the accumulation mapping rule for the Hertz frequency domain sine wave signal. Using this accumulation mapping rule, the values ​​in the remaining quadrants can be obtained through the mapping of the digital signal phase, thus enabling the rapid establishment of the correct waveform of the 512Hz digital signal. This effectively reduces the periodic drift error phenomenon in traditional digital signal generation and improves the reliability of digital signal detection and transmission. Furthermore, due to the quadrant symmetry of the sine wave, this method only requires discrete writing of one-quarter of the quadrants (e.g., the first quadrant 0 to...). The waveform trend profiles of the remaining quadrants can be derived from the digitally sampled waveform data (64 or 256-point sinusoidal rotation vectors), which greatly reduces the amount of unnecessary digital waveform generation and processing, saves storage space, improves the transmission efficiency of digital signals, and has high economic benefits.

[0088] Preferably, the step of locating the cross quadrant region of the sub-waveform segment corresponding to the minimum symmetry overlap based on the high-order gradient of the progressive phase gradient, obtaining the waveform blueprint accumulation address, rotating and iterating the low-order vector of the progressive phase gradient on the waveform blueprint accumulation address, and performing digital interpolation translation operation according to the accumulation mapping rule to obtain the digital detection excitation signal specifically includes the following steps:

[0089] The gradient recorded in the high-order interval of the phase gradient is extracted from the stepwise phase gradient and defined as the high-order gradient parameter; and the vector recorded in the low-order interval of the phase is obtained and defined as the low-order vector parameter.

[0090] Based on the high-order gradient parameter, a symmetry overlap threshold is preset. Only the cross quadrant area corresponding to the sub-waveform segment with the minimum symmetry overlap below the symmetry overlap threshold is extracted and marked as the waveform blueprint accumulation address. The low-order vector parameter is iteratively rotated on the waveform blueprint accumulation address so that the low-order vector tends to the quadrant X-axis. During the iterative rotation process, the rotation angle of the waveform phase is continuously accumulated to obtain the quadrant coordinate of the rotation angle.

[0091] Obtain the Y-axis component value and polar coordinate range contained in the low-order vector parameter. If the Y-axis component value approaches or equals 0 and the rotation angle quadrant coordinate reaches the polar coordinate range, then stop the rotation iteration operation of the low-order vector parameter and output the magnitude and iteration phase angle.

[0092] On the waveform blueprint accumulation address, the amplitude of the back-mapping and the phase angle of the iteration are processed by digital complementation of the intercept coefficient and slope value to obtain a series of adjacent and continuous waveform amplitude address codes. According to the accumulation mapping rule, the series of waveform amplitude address codes are subjected to sinusoidal quadrant symmetrical second-order interpolation to finally generate a sinusoidal digital waveform.

[0093] A digital-to-analog converter (DAC) is constructed to input the sinusoidal digital waveform into the DAC for smooth calibration and translation of the 512 Hz analog signal, thereby obtaining the digital detection excitation signal.

[0094] It should be noted that by recording the high-order gradient parameters of the phase gradient step by step, the current phase's neighborhood can be located. The cross-quadrant neighborhood where the sub-waveform segment that does not exceed the symmetry overlap threshold and minimizes the symmetry overlap is located can be extracted. Thus, based on the high-order phase, the quadrant of the 512Hz digital signal's starting waveform searched for the appropriate detection object type can be determined. This cross-quadrant neighborhood is the waveform's starting region for generating the 512Hz digital signal, i.e., the waveform blueprint accumulation address. It is mainly used to accumulate and store the rotating phase data of the signal frequency, achieving the effect of high-order phase identification quadrant. In this way, the complete periodic waveform can be reconstructed without increasing the scale of waveform data processing, ensuring waveform continuity and accuracy. Next, the low-order vector parameters (x, y) are loaded onto the waveform template accumulation address for iterative rotation. Through iterative rotation of the low-order vector, the magnitude and iterative phase angle of the waveform data can be obtained. The magnitude reveals the oscilloscope line shape amplitude of the waveform vector in phase accumulation adapted to the type of probe, while the iterative phase angle characterizes the phase angle orientation of the waveform vector. This makes the symmetry reconstruction of the digital signal more coherent and smooth, avoiding waveform mapping redundancy and missing phenomena, and improving the fidelity and spatial penetration of the digital signal output. The direction judgment if the Y-axis component value infinitely approaches or equals 0 is to ensure that each rotation makes the y-component smaller (approaching 0), thereby converging to determine the rotation direction of the waveform data and improving the accuracy of magnitude imitation. The judgment that the rotation angle quadrant coordinates reach the polar coordinate region detects whether the waveform phase rotation angle converges to the vector polar angle, thus maintaining a high degree of reproduction of the phase angle radian change. Finally, the frequency of the digital detection excitation signal obtained by using the accumulation mapping rule digital complement and second-order interpolation is 512Hz, which can achieve a high degree of consistency with the frequency of traditional Hertz analog signals, thereby improving the detection arrival rate and penetration accuracy of digital pipeline detection equipment in the blind zone of the target underground pipeline space.

[0095] Preferably, step S104 specifically includes the following steps:

[0096] The power supply boost IC of the digital pipeline detection equipment is activated to obtain the origin oscillation frequency of the digital detection excitation signal. An oscillation stability evaluation model is constructed by weighing the changes in the past node circuits of the topology power supply boost IC.

[0097] The frequency stability of the originating oscillation frequency is obtained by evaluating the oscillation stability assessment model.

[0098] If the frequency stability is lower than the preset frequency stability, the boost control strategy of the power supply boost IC for the digital detection excitation signal is optimized until the frequency stability is highly parallel to the preset frequency stability. At this time, the inherent oscillation frequency of the optimized digital detection excitation signal is obtained.

[0099] The frequency division requirement of the digital detection excitation signal is obtained by detecting the planning record. Based on the frequency division requirement, the ideal frequency division ratio and ideal transmission period of the inherent oscillation frequency are preset. The phase accumulator is used to accumulate the fractional part of the inherent oscillation frequency according to the ideal frequency division ratio when one ideal transmission period is experienced, and the frequency phase accumulation value is generated.

[0100] If the frequency phase accumulation value is greater than 1, then a frequency division pulse is generated at this time, and the integer part of the ideal frequency division ratio is subtracted simultaneously to form a series of frequency division period error values ​​for achieving the ideal transmission period and the frequency division pulse layout diagram corresponding to the ideal transmission period.

[0101] An LFSR pseudo-random generation mechanism is introduced. Based on the ideal transmission period, a random jitter value within a constant range is constructed in the LFSR pseudo-random generation mechanism. The random jitter value is applied and injected into a series of frequency division period error values ​​to obtain a controllable jitter period error value for each frequency phase.

[0102] If the controllable jitter period error value is greater than the preset threshold, the frequency division pulse corresponding to the controllable jitter period error value is triggered in advance through the frequency division pulse layout diagram; otherwise, the standardized frequency division is maintained, and multiple sets of single-frequency voltage signals are finally generated.

[0103] It should be noted that the origin oscillation frequency of the digital probe excitation signal is the initial oscillation frequency under the influence of the power supply boost IC node circuit when the digital probe excitation signal is initially generated. It is an evaluation index for the stability of the digital probe excitation signal frequency. If the frequency stability is lower than the preset frequency stability, it means that the current power supply boost IC is unable to maintain a high degree of stability when transmitting the digital probe excitation signal, which greatly reduces the detection quality of the digital probe excitation signal. Therefore, this method first adjusts and optimizes the frequency output of the digital probe excitation signal through the power supply boost IC from the boost control strategy level, thereby ensuring that the frequency stability of the digital probe excitation signal is maintained at the 10ppm level, thereby improving the transmission reliability of the 512Hz digital probe excitation signal. Subsequently, according to the frequency division requirements, the phase of the inherent frequency of the digital probe excitation signal is continuously accumulated using a phase accumulator. Specifically, the inherent oscillation frequency is accumulated according to the ideal frequency division fractional part over one ideal transmission cycle, thereby converting the fractional error into periodic integer frequency division adjustment and tracking the cumulative phase error of the fractional frequency division. If the frequency phase accumulation value is greater than 1, it indicates that the fractional error has reached the critical point of periodic integer frequency division, triggering the integer carry mechanism. This subtracts the integer part of the ideal frequency division ratio and generates a frequency division pulse, effectively stacking and locking the periodic error term of the digital signal frequency decomposition. Then, this method introduces a controllable jitter factor, i.e., a random jitter value, through the LFSR pseudo-random generation mechanism, thereby randomizing the fixed periodic error into a non-deterministic sequence. If the controllable jitter accumulation error value is greater than a preset threshold, it indicates that the noise position of the periodic error generated by the digital probe excitation signal frequency division is relatively fixed. Since the periodic error generates spurious signals in the frequency domain, and random jitter converts them into broadband noise, by triggering the frequency division pulse corresponding to the controllable jitter frequency division periodic error value in advance, the position of the frequency division pulse can be randomized, changing the fractional frequency division error into random noise rather than fixed spurious signals. This reduces the spurious signal amplitude, thereby breaking the periodic error through the carry decision of the perturbation accumulator and achieving a controllable effect of eliminating periodic error spurious signals.

[0104] In summary, this method optimizes the initial frequency stability of the 512Hz digital detection excitation signal and reduces signal transmission drift. Furthermore, by applying controllable random jitter to randomize the error distribution and dynamically adjust the frequency division ratio, it improves the suppression and elimination rate of periodic noise. Compared to traditional frequency division methods, it avoids interference embedding of the digital detection excitation signal in the sensitive boost frequency band of the power supply boost IC, ensuring the frequency division balance of the digital detection excitation signal and improving the penetration and positioning resolution of the digital signal for detecting underground pipelines.

[0105] Preferably, step S108 specifically includes the following steps:

[0106] The receiving coil of the digital pipeline detection equipment is combined with a high-precision ADC to digitally acquire the response samples of the digital detection excitation signal, thereby obtaining several discrete response signals of the target underground pipeline and the actual modulation frequency of the discrete response signals.

[0107] Based on big data, the working condition case of Hertz analog signal is obtained. According to the detection plan, the working condition case is extracted to obtain the local oscillator reference signal that conforms to the standard Hertz analog signal and is orthogonal and in the same frequency as the actual modulation frequency.

[0108] A DC demodulation domain is constructed, and each discrete response signal and the local oscillator reference signal are migrated to the DC demodulation domain for point-by-point coherent demodulation based on the signal spectrum to obtain multiple sets of mixing signal components;

[0109] An adaptive FIR low-pass filter with a cutoff frequency higher than the signal bandwidth, designed using the Hanning window function, is introduced. The adaptive FIR low-pass filter is used to filter each group of the mixed signal components to remove high-frequency noise terms and obtain the demodulated DC component value of the feedback response discrete signal after filtering.

[0110] Based on the decoding rules of digital pipeline detection equipment, a signal receiving and decoding simulation model is constructed. The demodulated DC component value is imported into the signal receiving and decoding simulation model for simulation, and the analog bit error rate after filtering the feedback response discrete signal is obtained.

[0111] If the simulated bit error rate is greater than the preset bit error rate threshold, the filtered feedback response discrete signal is defined as the first filtered signal, the current signal-to-noise ratio of the first filtered signal is obtained, and the filtered directional benchmark feedback response discrete signal that satisfies the detection planning record is obtained based on big data and defined as the second filtered signal, and the expected signal-to-noise ratio of the second filtered signal is obtained.

[0112] The deviation between the current signal-to-noise ratio and the desired signal-to-noise ratio is calculated to obtain the signal-to-noise ratio deviation value. Based on the signal-to-noise ratio deviation value, the filtering parameters of the adaptive FIR low-pass filter are reconfigured and double filtering is performed until the signal-to-noise ratio deviation value is eliminated, thereby generating the digital response feedback signal of the target underground pipeline.

[0113] It should be noted that traditional equipment can typically only acquire discrete response signals, leading to issues such as weak signals, risk of signal loss, and large-scale noise interference in the detection and analysis of underground pipelines, resulting in inaccurate detection results. To address this, this method shifts the target frequency to DC by multiplying discrete response signals with the local oscillator reference signal point-by-point in a DC demodulation domain. This results in the mixed discrete response signal having two fluctuating frequency components: a difference frequency (low frequency) and a sum frequency (high frequency). The difference frequency component retains the target frequency information, reflecting amplitude and phase, while the sum frequency component contains interference noise particles located near the 2f high-frequency component. Synchronous phase-sensitive mixing of the signal enables down-conversion of specific frequency information to near 0Hz DC, thus completely separating the digital response feedback signal from broadband noise. This facilitates subsequent filtering to extract key weak signals, achieving selective frequency detection and improving the lock-in amplification gain and integrity of the discrete response signal. Then, an adaptive FIR low-pass filter is used to filter each group of mixing signal components. This enables the response signal processing to have a very high level of sensitivity to the target frequency components, exerting a frequency selectivity effect. This suppresses the 2f high-frequency component noise after mixing, preserves the target signal strength information to the maximum extent, and obtains the demodulated DC component signal value after filtering out large-scale noise. This demodulated DC component signal represents the projection of the response signal onto the target frequency, significantly improving the signal-to-noise ratio of the 512Hz digital signal feedback reception, especially for high-frequency interference suppression. The adaptive FIR low-pass filter used in this method has a cutoff frequency set slightly higher than the signal bandwidth, which ensures no phase distortion during the preservation of the difference frequency DC component and the filtering of the sum frequency component, thus guaranteeing the integrity of the digital signal waveform and improving the signal feedback quality.

[0114] It should be noted that if the analog bit error rate exceeds the preset bit error rate threshold, it indicates that the filter parameters (such as cutoff frequency, order, or window function) may be improperly set, resulting in a small amount of residual noise in the filtered feedback response discrete signal, or even phenomena such as response distortion, delay, or waveform loss, causing nonlinear signal feedback distortion. To address this, this method reconfigures the filtering parameters of the adaptive FIR low-pass filter by calculating the current signal-to-noise ratio (SNR) of the first filtered signal and its deviation from the desired SNR, and performs double filtering on the response discrete signal, thereby eliminating the bit error phenomenon in the signal feedback, optimizing the fidelity of the 512Hz digital signal, and providing a reliable basis for subsequent digital signal detection feedback analysis.

[0115] Preferably, step S110 specifically includes the following steps:

[0116] The existing time-series dynamic characteristics and frequency fluctuation range of the digital response feedback signal are obtained, and the frequency fluctuation range is divided into wavelet sub-bands with different detail coefficient scales based on the existing time-series dynamic characteristics.

[0117] The wavelet transform algorithm is introduced to transfer the digital response feedback signal from the time domain to the frequency domain, and the dynamic change spectrum of the digital response feedback signal fluctuates over time is obtained.

[0118] Extract the spectral amplitude of each wavelet sub-band within the dynamic transition spectrum, construct a power periodicity map based on the spectral amplitude, calculate the power spectral density at each level of detail coefficients based on the power periodicity map, and sum the squares to obtain the band power energy value of each wavelet sub-band.

[0119] A preset reference frequency band power energy threshold is established, and the ratio of the power energy value of each frequency band to the reference frequency band power energy threshold is calculated to eliminate the individual frequency band differences in the digital response feedback signal and obtain multiple frequency band power energy ratios.

[0120] Using dynamic time sequence as the contextual clue trajectory, the frequency band power energy value of each wavelet sub-band is normalized and organized according to the frequency band power energy ratio to form the hidden detection feature vector of the digital response feedback signal.

[0121] Based on big data, the accurate detection feature vector of the target type is obtained, and the degree of matching between the hidden detection feature vector and the accurate detection feature vector is calculated. If the degree of matching is greater than the preset degree of matching, the digital response feedback signal is marked and output as the target detection signal result, and the digital pipeline detection equipment is controlled to issue an alarm.

[0122] It should be noted that the digital response feedback signal may become non-stationary due to changes in the reception time. This non-stationarity can mask or obscure specific frequency components of the target object type, making it difficult to accurately capture the relevant features of the underground pipeline and resulting in a high error rate in the detection results. To address this, this method uses the dynamic signal characteristics (including temporal dynamic characteristics) of the digital response feedback signal to segment frequency ranges in detail. This adapts to the local frequency characteristics of the non-stationary signal, and the resulting wavelet sub-bands with different detail coefficient scales significantly enhance the phenotypic ability of the target object type features, resulting in superior resolution for the representation of features contained in the digital response feedback signal. Furthermore, the digital response feedback signal is mapped from the time-domain wavelet to the frequency domain to further reveal the frequency components of the received digital signal. This temporal mapping captures the dynamic and transient changes of features, improving the scanning clarity and locking accuracy of abnormal waveforms and optimizing the ability to highlight local edges indicating the presence of abnormal features in the target object type. Subsequently, a power periodicity map is constructed based on the spectral amplitude recorded in the dynamic change spectrum. This power periodicity map is an unbiased estimate of the signal power spectrum, presenting the local frequency power distribution of the digital response feedback signal. The independence between each power periodicity map makes the subsequent summation of the squares of the power spectral density more effective. Based on the power periodicity map, the band power energy values ​​at each level of detail coefficients are calculated, quantifying the signal intensity in specific frequency bands. This improves the sensitivity to capturing implicit abrupt changes in signals due to the abnormal characteristics of the detected object type at different scales, achieving higher precision in detecting underground pipeline anomalies. Finally, the band power energy values ​​of wavelet sub-bands are normalized according to the band power energy ratio to trace the trajectory features. This eliminates the influence of environmental differences on absolute energy, compresses the dynamic range, and further enhances the digital pipeline detection equipment's interest in recognizing weak digital signals of anomalies, thereby structurally forming a hidden detection feature vector in the digital response feedback signal that is associated with the detected object type (anomaly).

[0123] It should be noted that if the degree of agreement is significantly higher than the preset degree of agreement, it indicates the presence of a detected object type in the target underground pipeline. Detected object types include damage, cracks, deformation, scaling, corrosion, and foreign object blockage. Therefore, the target underground pipeline needs to be marked as abnormal and an alarm should be triggered. This method can implicitly identify the characteristics of the detected object type in the digital feedback signals received by the equipment, achieving a concrete structural effect and accurately depicting the global characteristics of the detected object type. This allows for low-blind-spot anomaly analysis of the target underground pipeline, significantly improving the reliability of underground pipeline detection analysis and the accuracy of early warning, and reducing false alarms or missed alarms in underground pipeline detection.

[0124] A second aspect of the present invention provides a Hertz signal digitization system for underground pipeline detection, such as... Figure 3As shown, the Hertz signal digitization method for underground pipeline detection, applied to any one of the claims, includes the following system:

[0125] Digital signal generation module: The digital signal generation module is equipped with DDS technology, which is used for phase accumulation and digital interpolation translation to generate a 512Hz digital detection excitation signal;

[0126] Signal transmission module: The digital signal transmission module includes a power supply boost IC unit, a digital frequency divider unit, a coil drive IC unit, and an inductor coil unit, which is responsible for transmitting a 512Hz digital detection excitation signal to the target underground pipeline;

[0127] Digital signal processing module: The digital signal processing module is equipped with high-precision ADC technology and adaptive FIR filter, which is used to digitally acquire several discrete response signals of the target underground pipeline and perform mixing and filtering to improve the signal-to-noise ratio;

[0128] Intelligent signal analysis module: The intelligent signal analysis module is responsible for calculating the frequency band energy power of the digital response feedback signal to detect and analyze the target underground pipeline;

[0129] Pipeline detection alarm module: The pipeline detection alarm module is used to control the digital pipeline detection equipment to issue an alarm based on the detection results.

[0130] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for digitizing Hertzian signals for underground pipeline detection, characterized in that, Includes the following steps: S102: The desired detection conditions of the digital pipeline detection equipment using DDS technology are determined, and a progressive phase gradient is generated. Based on the accumulation mapping rule of the simulated sine wave of the 512 Hz analog signal, the progressive phase gradient is iteratively rotated and digitally interpolated to obtain the digital detection excitation signal. S104: Start the power supply boost IC of the digital pipeline detection equipment to optimize and obtain the inherent oscillation frequency of the digital detection excitation signal, accumulate the periodic phase error of the inherent oscillation frequency and apply controllable random jitter to perform digital frequency division, and generate multiple sets of single-frequency voltage signals. S106: The coil driver IC converts multiple single-frequency voltage signals into running signals to drive the inductor transmitting coil. The inductor transmitting coil and the radio frequency antenna are responsible for radiating the digital detection excitation signal to the target underground pipeline in the form of a single-frequency electromagnetic wave. S108: Use a high-precision ADC to digitally acquire several discrete response signals of the target underground pipeline, filter out the high-frequency noise terms after mixing of the discrete response signals using an adaptive FIR low-pass filter, and perform filtering optimization through bit error simulation analysis to generate the digital response feedback signal of the target underground pipeline. S110: Calculate the frequency band energy power of the digital response feedback signal in different wavelet sub-bands and normalize the organization to form a hidden detection feature vector. Based on the hidden detection feature vector, perform detection and analysis on the target underground pipeline to obtain the detection results. Control the digital pipeline detection equipment to issue an alarm based on the detection results. Specifically, S104 includes the following steps: The power supply boost IC of the digital pipeline detection equipment is activated to obtain the origin oscillation frequency of the digital detection excitation signal. An oscillation stability evaluation model is constructed by weighing the changes in the past node circuits of the topology power supply boost IC. The frequency stability of the originating oscillation frequency is obtained by evaluating the oscillation stability assessment model. If the frequency stability is lower than the preset frequency stability, the boost control strategy of the power supply boost IC for the digital detection excitation signal is optimized until the frequency stability is highly parallel to the preset frequency stability. At this time, the inherent oscillation frequency of the optimized digital detection excitation signal is obtained. The frequency division requirement of the digital detection excitation signal is obtained by detecting the planning record. Based on the frequency division requirement, the ideal frequency division ratio and ideal transmission period of the inherent oscillation frequency are preset. The phase accumulator is used to accumulate the fractional part of the inherent oscillation frequency according to the ideal frequency division ratio when one ideal transmission period is experienced, and the frequency phase accumulation value is generated. If the frequency phase accumulation value is greater than 1, then a frequency division pulse is generated at this time, and the integer part of the ideal frequency division ratio is subtracted simultaneously to form a series of frequency division period error values ​​for achieving the ideal transmission period and the frequency division pulse layout diagram corresponding to the ideal transmission period. An LFSR pseudo-random generation mechanism is introduced. Based on the ideal transmission period, a random jitter value within a constant range is constructed in the LFSR pseudo-random generation mechanism. The random jitter value is applied and injected into a series of frequency division period error values ​​to obtain a controllable jitter period error value for each frequency phase. If the controllable jitter period error value is greater than the preset threshold, the frequency division pulse corresponding to the controllable jitter period error value is triggered in advance through the frequency division pulse layout diagram; otherwise, the standardized frequency division is maintained, and multiple sets of single-frequency voltage signals are finally generated.

2. The Hertz signal digitization method for underground pipeline detection according to claim 1, characterized in that, S102 specifically includes the following steps: The detection planning record of the target underground pipeline is obtained. The detection object type of the target underground pipeline is read from the detection planning record. The expected detection working conditions of the digital pipeline detection equipment in the target underground pipeline are pre-evaluated and decided for the detection object type. DDS technology is introduced to obtain the closed-loop clock period of digital pipeline detection equipment. Based on the closed-loop clock period, a phase accumulation strategy is designed in DDS technology to construct a phase accumulator. Based on the desired detection conditions, the parameters are set to adapt to the sampling frequency and accumulation bit width of the detection object. The frequency step control word is calculated in DDS technology according to the sampling frequency and accumulation bit width. The phase is accumulated once in the phase accumulator after each closed-loop clock cycle using the frequency step control word to generate a gradual phase gradient. The standard 512 Hz analog signal detected by the digital pipeline detection equipment is extracted by memo log. The quadrant symmetry of the intercept and slope of the corresponding sinusoidal waveform of the standard 512 Hz analog signal is analyzed and recorded. The symmetry overlap of the sub-waveform segments in the cross quadrant domain and the accumulation mapping rule of the analog sine wave are obtained. Based on the high-order gradient of the progressive phase gradient, the cross quadrant region of the sub-waveform segment corresponding to the minimum symmetry overlap is located, and the waveform blueprint accumulation address is obtained. The low-order vector of the progressive phase gradient is rotated and iterated on the waveform blueprint accumulation address, and the digital interpolation translation operation is performed according to the accumulation mapping rule to obtain the digital detection excitation signal.

3. The Hertz signal digitization method for underground pipeline detection according to claim 2, characterized in that, The process of extracting the standard Hertz analog signal detected by the digital pipeline detection device through the memo log, analyzing and recording the quadrant symmetry of the intercept and slope of the corresponding sine waveform of the standard 512 Hertz analog signal, and obtaining the symmetry overlap of sub-waveform segments in the cross-quadrant domain and the accumulation mapping rule of the analog sine wave specifically includes the following steps: Obtain the memo log of the digital pipeline detection equipment, and obtain the standard 512 Hz analog signal of the digital pipeline detection equipment applying the target underground pipeline to find the type of object to be detected within a preset time unit from the memo log; The Hilbert-Huang transform algorithm is introduced to perform a symmetrical transformation of the waveform period of the standard 512 Hz analog signal on the quadrant coordinates to obtain an analog sine wave. An equally divided quadrant domain is constructed, and the analog sine wave is divided into N sub-waveform segments in the equally divided quadrant domain. Using MATLAB digital software, each sub-waveform segment is converted into a spline waveform differential equation and the linear equation of the spline interpolation control points is solved, outputting the intercept coefficient and slope value of each spline waveform differential equation; During the solution process, a sub-waveform segment is locked from a bird's-eye view of a certain quadrant. At this time, according to the quadrant symmetry characteristics of the sine wave, the corresponding intercept coefficient and slope value are generated for each sub-waveform segment. The corresponding intercept coefficient and slope value are then generated and the sub-waveform segments in the other quadrants are cross-symmetrically mapped. The symmetry overlap of the sub-waveform segments in the cross quadrants is obtained, and the accumulation mapping rule of the simulated sine wave is constructed.

4. The Hertz signal digitization method for underground pipeline detection according to claim 2, characterized in that, The process of locating the cross-quadrant region of the sub-waveform segment corresponding to the minimum symmetry overlap based on the high-order gradient of the progressive phase gradient, obtaining the waveform blueprint accumulation address, rotating and iterating the low-order vector of the progressive phase gradient on the waveform blueprint accumulation address, and performing digital interpolation translation operation according to the accumulation mapping rule to obtain the digital detection excitation signal specifically includes the following steps: The gradient recorded in the high-order interval of the phase gradient is extracted from the stepwise phase gradient and defined as the high-order gradient parameter; and the vector recorded in the low-order interval of the phase is obtained and defined as the low-order vector parameter. Based on the high-order gradient parameter, a symmetry overlap threshold is preset. Only the cross quadrant area corresponding to the sub-waveform segment with the minimum symmetry overlap below the symmetry overlap threshold is extracted and marked as the waveform blueprint accumulation address. The low-order vector parameter is iteratively rotated on the waveform blueprint accumulation address so that the low-order vector tends to the quadrant X-axis. During the iterative rotation process, the rotation angle of the waveform phase is continuously accumulated to obtain the quadrant coordinate of the rotation angle. Obtain the Y-axis component value and polar coordinate range contained in the low-order vector parameter. If the Y-axis component value approaches or equals 0 and the rotation angle quadrant coordinate reaches the polar coordinate range, then stop the rotation iteration operation of the low-order vector parameter and output the magnitude and iteration phase angle. On the waveform blueprint accumulation address, the amplitude of the back-mapping and the phase angle of the iteration are processed by digital complementation of the intercept coefficient and slope value to obtain a series of adjacent and continuous waveform amplitude address codes. According to the accumulation mapping rule, the series of waveform amplitude address codes are subjected to sinusoidal quadrant symmetrical second-order interpolation to finally generate a sinusoidal digital waveform. A digital-to-analog converter (DAC) is constructed to input the sinusoidal digital waveform into the DAC for smooth calibration and translation of the 512 Hz analog signal, thereby obtaining the digital detection excitation signal.

5. The Hertz signal digitization method for underground pipeline detection according to claim 1, characterized in that, S108 specifically includes the following steps: The receiving coil of the digital pipeline detection equipment is combined with a high-precision ADC to digitally acquire the response samples of the digital detection excitation signal, thereby obtaining several discrete response signals of the target underground pipeline and the actual modulation frequency of the discrete response signals. Based on big data, the working condition case of Hertz analog signal is obtained. According to the detection plan, the working condition case is extracted to obtain the local oscillator reference signal that conforms to the standard Hertz analog signal and is orthogonal and in the same frequency as the actual modulation frequency. A DC demodulation domain is constructed, and each discrete response signal and the local oscillator reference signal are migrated to the DC demodulation domain for point-by-point coherent demodulation based on the signal spectrum to obtain multiple sets of mixing signal components; An adaptive FIR low-pass filter with a cutoff frequency higher than the signal bandwidth, designed using the Hanning window function, is introduced. The adaptive FIR low-pass filter is used to filter each group of the mixed signal components to remove high-frequency noise terms and obtain the demodulated DC component value of the feedback response discrete signal after filtering. Based on the decoding rules of digital pipeline detection equipment, a signal receiving and decoding simulation model is constructed. The demodulated DC component value is imported into the signal receiving and decoding simulation model for simulation, and the analog bit error rate after filtering the feedback response discrete signal is obtained. If the simulated bit error rate is greater than the preset bit error rate threshold, the filtered feedback response discrete signal is defined as the first filtered signal, the current signal-to-noise ratio of the first filtered signal is obtained, and the filtered directional benchmark feedback response discrete signal that satisfies the detection planning record is obtained based on big data and defined as the second filtered signal, and the expected signal-to-noise ratio of the second filtered signal is obtained. The deviation between the current signal-to-noise ratio and the desired signal-to-noise ratio is calculated to obtain the signal-to-noise ratio deviation value. Based on the signal-to-noise ratio deviation value, the filtering parameters of the adaptive FIR low-pass filter are reconfigured and double filtering is performed until the signal-to-noise ratio deviation value is eliminated, thereby generating the digital response feedback signal of the target underground pipeline.

6. The Hertz signal digitization method for underground pipeline detection according to claim 1, characterized in that, S110 specifically includes the following steps: The existing time-series dynamic characteristics and frequency fluctuation range of the digital response feedback signal are obtained, and the frequency fluctuation range is divided into wavelet sub-bands with different detail coefficient scales based on the existing time-series dynamic characteristics. The wavelet transform algorithm is introduced to transfer the digital response feedback signal from the time domain to the frequency domain, and the dynamic change spectrum of the digital response feedback signal fluctuates over time is obtained. Extract the spectral amplitude of each wavelet sub-band within the dynamic transition spectrum, construct a power periodicity map based on the spectral amplitude, calculate the power spectral density at each level of detail coefficients based on the power periodicity map, and sum the squares to obtain the band power energy value of each wavelet sub-band. A preset reference frequency band power energy threshold is established, and the ratio of the power energy value of each frequency band to the reference frequency band power energy threshold is calculated to eliminate the individual frequency band differences in the digital response feedback signal and obtain multiple frequency band power energy ratios. Using dynamic time sequence as the contextual clue trajectory, the frequency band power energy value of each wavelet sub-band is normalized and organized according to the frequency band power energy ratio to form the hidden detection feature vector of the digital response feedback signal. Based on big data, the accurate detection feature vector of the target type is obtained, and the degree of matching between the hidden detection feature vector and the accurate detection feature vector is calculated. If the degree of matching is greater than the preset degree of matching, the digital response feedback signal is marked and output as the target detection signal result, and the digital pipeline detection equipment is controlled to issue an alarm.

7. A Hertz signal digitization system for underground pipeline detection, characterized in that, The system is applied to implement the Hertz signal digitization method for underground pipeline detection as described in any one of claims 1-6, and comprises: Digital signal generation module: The digital signal generation module is equipped with DDS technology, which is used for phase accumulation and digital interpolation translation to generate a 512Hz digital detection excitation signal; Signal transmission module: The digital signal transmission module includes a power supply boost IC unit, a digital frequency divider unit, a coil drive IC unit, and an inductor coil unit, which is responsible for transmitting a 512Hz digital detection excitation signal to the target underground pipeline; Digital signal processing module: The digital signal processing module is equipped with high-precision ADC technology and adaptive FIR filter, which is used to digitally acquire several discrete response signals of the target underground pipeline and perform mixing and filtering to improve the signal-to-noise ratio; Intelligent signal analysis module: The intelligent signal analysis module is responsible for calculating the frequency band energy power of the digital response feedback signal to detect and analyze the target underground pipeline; Pipeline detection alarm module: The pipeline detection alarm module is used to control the digital pipeline detection equipment to issue an alarm based on the detection results.

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