Hertz signal digitization method and system for underground pipeline detection

Abstract

The invention relates to the technical field of underground pipeline detection, in particular to a Hertz signal digitization method and system for underground pipeline detection. A digital detection excitation signal with stable Hertz frequency is generated by adopting a phase accumulation mechanism of a DDS (direct digital synthesis) technology and digital interpolation translation; a controllable random jitter frequency division strategy is introduced to generate multiple groups of single-frequency-point voltage signals to reduce spectrum aliasing and background noise; a response signal is sampled and filtered through a high-precision ADC and a self-adaptive FIR low-pass filter; and carrying out detection analysis and alarm on the target underground pipeline in combination with the frequency band energy normalization analysis and feature vector construction of the wavelet sub-band. According to the invention, digital improvement can be carried out on a 512 Hz analog signal detected by a traditional underground pipeline, and the sensitivity, the anti-interference capability and the signal processing precision of underground pipeline detection are greatly improved.

Description

Technical Field

[0001] The present invention 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 Art

[0002] In underground pipeline detection technology, traditional detection instruments usually use analog circuits with a frequency of 512 Hz to transmit and receive signals. Although this type of analog circuit has a simple structure and is widely used, the Hertz analog signals it generates are extremely susceptible to external electromagnetic interference during the actual detection process of complex underground pipeline environments. In complex or high-noise underground environments, the signal stability is poor, resulting in unstable detection results. Secondly, false signals or false responses often appear in the analog circuit, making it difficult to distinguish between pipeline signals and background noise, which brings great difficulties to detection and judgment. At the same time, since components are prone to aging or performance drift due to factors such as temperature, the long-term reliability of the system is greatly reduced. In addition, the analog circuit structure limits its signal processing accuracy and cannot meet the requirements for high-precision extraction of weak signals and signals with a high dynamic range.

[0003] Furthermore, traditional analog circuits struggle to integrate and execute complex digital signal processing algorithms, such as filtering, adaptive detection, or signal enhancement and feature extraction. This limits the intelligent and sophisticated development of underground pipeline detection technology. Furthermore, analog system debugging and maintenance are complex and tedious, relying heavily on skilled personnel and resulting in high maintenance costs. Therefore, a method for efficiently and accurately digitizing and improving Hertzian analog signals is needed to address these challenges. Summary of the Invention

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

[0005] In order to achieve the above object, the technical solution adopted by the present invention is: A first aspect of the present invention provides a Hertzian signal digitization method for underground pipeline detection, comprising the following steps: S102: Parameters of the desired detection operating condition of the digital pipeline detection device are formulated using DDS technology phase accumulation to generate a step-by-step phase gradient. The step-by-step phase gradient is digitally interpolated and translated using iterative rotation based on an accumulation mapping rule of an analog sine wave of a 512 Hz analog signal to obtain a digital detection excitation signal. S104: Starting the power supply boost IC of the digital pipeline detection device to tune and obtain the natural oscillation frequency of the digital detection excitation signal, accumulating the periodic phase error of the natural oscillation frequency and applying controllable random jitter to perform digital frequency division, thereby generating multiple sets of single-frequency voltage signals; S106: The coil driver IC converts multiple sets of single-frequency voltage signals into operating signals to drive the inductive transmitting coil. The inductive transmitting coil and the radio frequency antenna are used to radiate the digital detection excitation signal in the form of a single-frequency electromagnetic wave to the target underground pipeline. S108: Using a high-precision ADC to digitally acquire a plurality of discrete response signals of the target underground pipeline, filtering out high-frequency noise items after mixing the discrete response signals using an adaptive FIR low-pass filter, and performing filtering optimization for error simulation analysis to generate a 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, perform detection analysis on the target underground pipeline based on the hidden detection feature vector, obtain a detection result, and control the digital pipeline detection equipment to issue an alarm based on the detection result.

[0006] Preferably, the step S102 specifically includes the following steps: Obtaining a detection plan record of the target underground pipeline, reading the detection object type of the target underground pipeline through the detection plan record, and obtaining the expected detection working condition parameters pre-evaluated and determined by the digital pipeline detection device in the target underground pipeline based on the detection object type; Introducing DDS technology to obtain the closed-loop clock cycle of the digital pipeline detection device, designing a phase accumulation strategy in DDS technology based on the closed-loop clock cycle, and constructing a phase accumulator; According to the expected detection conditions, the sampling frequency and accumulation bit width of the detection object are preset and matched with the parameters. The frequency step control word is calculated in accordance with the sampling frequency and accumulation bit width in the DDS technology. The frequency step control word is used to accumulate the phase in the phase accumulator once every closed-loop clock cycle to generate a step-by-step phase gradient. The standard 512 Hz analog signal detected by the digital pipeline detection equipment was extracted through the memo log. The quadrant symmetry of the intercept and slope of the corresponding sine waveform of the standard 512 Hz analog signal was analyzed and recorded. The symmetry overlap of the sub-waveform segments in the cross-quadrant area and the accumulation mapping rule of the simulated sine wave were obtained. According to the high-order gradient of the step-by-step phase gradient, the cross-quadrant area corresponding to the sub-waveform segment with the minimum symmetric overlap is located, and the waveform blueprint accumulation address is obtained. The low-order vector of the iterative step-by-step phase gradient is rotated 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.

[0007] Preferably, the method of extracting the standard Hz 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 sine waveform corresponding to the standard 512 Hz analog signal, and obtaining the symmetric overlap of the sub-waveform segments in the cross-quadrant area and the accumulation mapping rule of the simulated sine wave specifically includes the following steps: Obtaining a memo log of the digital pipeline detection device, and obtaining, through the memo log, a standard 512 Hz analog signal of the digital pipeline detection device applying the target underground pipeline to search for the type of detection object within a preset time unit; A Hilbert-Huang transform algorithm is introduced to perform a symmetry transformation of the waveform period of the standard 512 Hz analog signal on quadrant coordinates to obtain a simulated sine wave, and an equally divided quadrant domain is constructed, and the simulated sine wave is divided into N sub-waveform segments in the equally divided quadrant domain; Utilizing MATLAB digital software, each sub-waveform segment is converted into a spline waveform differential equation and the linear equation solution of the spline interpolation control points is performed, and the intercept coefficient and slope value of each spline waveform differential equation are output; During the solution process, a sub-waveform segment is locked at a bird's-eye view angle in 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 the sub-waveform segment one by one, and the cross-symmetric mapping record is performed with each sub-waveform segment in the other quadrants to obtain the symmetric overlap of the sub-waveform segments in the cross-quadrant area, and construct the accumulation mapping rule of the simulated sine wave.

[0008] Preferably, the method of locating the cross-quadrant region where the sub-waveform segment corresponding to the minimum symmetric overlap degree is located based on the high-order gradient of the stepwise phase gradient, obtaining the waveform blueprint accumulation address, rotating the low-order vector of the iterative stepwise phase gradient on the waveform blueprint accumulation address, and performing a digital interpolation translation operation according to the accumulation mapping rule to obtain the digital detection excitation signal specifically includes the following steps: Extracting the gradient recorded in the phase high interval from the stepwise phase gradient, which is defined as the high gradient parameter, and obtaining the vector recorded in the phase low interval, which is defined as the low vector parameter; A symmetric overlap threshold is preset according to the high-order gradient parameter, and only the cross-quadrant area corresponding to the sub-waveform segment with the minimum symmetric overlap below the symmetric overlap threshold is extracted, and marked as the waveform blueprint accumulation address. The low-order vector parameter is gradually iteratively rotated on the waveform blueprint accumulation address so that the low-order vector tends to the quadrant X-axis. The rotation angle of the waveform phase is continuously accumulated during the iterative rotation process to obtain the quadrant coordinate of the rotation angle; Get the Y-axis component value and polar angle coordinate area contained in the low-order vector parameter. If the Y-axis component value is infinitely close to or equal to 0 and the rotation angle quadrant coordinate reaches the polar angle coordinate area, then stop the rotation iteration operation of the low-order vector parameter and output the modulus amplitude and iterative phase angle. The digital complement processing of the intercept coefficient and the slope value is performed on the return mapping modulus amplitude and the iterative phase angle on the waveform blueprint accumulation address to obtain a series of adjacent and continuous waveform amplitude address codes. The series of waveform amplitude address codes are subjected to sinusoidal quadrant symmetric second-order interpolation according to the accumulation mapping rule to finally generate a sinusoidal digital waveform; A digital-to-analog converter is constructed, and the sinusoidal digital waveform is sent into the digital-to-analog converter for smooth translation of the 512 Hz analog signal to obtain a digital detection excitation signal.

[0009] Preferably, the step S104 specifically includes the following steps: Start the power boost IC of the digital pipeline detection equipment, obtain the origin oscillation frequency of the digital detection excitation signal, and build an oscillation stability evaluation model by weighing the past node circuit changes of the topology power boost IC; The origin oscillation frequency is evaluated by using an oscillation stability evaluation model to obtain the frequency stability of the origin oscillation frequency; 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 adjusted until the frequency stability is highly parallel to the preset frequency stability. At this time, the natural oscillation frequency of the digital detection excitation signal after adjustment is obtained. The frequency division requirements of the digital detection excitation signal are obtained through the detection planning record, and the ideal frequency division ratio and ideal transmission period of the natural oscillation frequency are preset according to the frequency division requirements. The phase accumulator is used to accumulate the fractional part of the natural oscillation frequency divided by the ideal frequency division ratio during an ideal transmission period to generate a frequency phase accumulation value; If the frequency phase accumulation value is greater than 1, a frequency division pulse is generated at this time, and the integer part of the ideal frequency division ratio is deducted synchronously to form a series of frequency division period error values ​​for the natural oscillation frequency to achieve the ideal transmission period and a frequency division pulse layout diagram corresponding to maintaining 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 injected into a series of frequency-divided 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-divided pulse corresponding to the controllable jitter period error value is triggered in advance through the frequency-divided pulse layout diagram; otherwise, the standardized frequency division is maintained, and finally multiple groups of single-frequency voltage signals are generated.

[0010] Preferably, the step S108 specifically includes the following steps: The receiving coil of the digital pipeline detection equipment is combined with a high-precision ADC to digitally collect 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, we obtain the working condition cases of Hertz analog signals. According to the detection plan, we extract the local oscillator reference signal that meets the working conditions of the standard Hertz analog signal and is orthogonal to the actual modulation frequency from the working condition cases. Constructing a DC demodulation domain, based on the signal spectrum, each discrete response signal and the local oscillator reference signal are migrated to the DC demodulation domain for point-by-point coherent demodulation, thereby obtaining multiple groups of mixed signal components. An adaptive FIR low-pass filter designed by a Hanning window function and having a cutoff frequency higher than the signal bandwidth is introduced, and each group of the mixed signal components is filtered using the adaptive FIR low-pass filter to remove high-frequency noise terms and obtain a demodulated DC component value of the feedback response discrete signal after filtering; A signal receiving and decoding simulation model is constructed based on the decoding rules of the digital pipeline detection equipment. The demodulated DC component value is imported into the signal receiving and decoding simulation model for simulation to obtain the simulated bit error rate after filtering the feedback response discrete signal. 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, and the current signal-to-noise ratio of the first filtered signal is obtained. At the same time, based on the big data, the filtered feedback response discrete signal that satisfies the detection planning record and is defined as the second filtered signal is obtained, 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 expected 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 processing is performed until the signal-to-noise ratio deviation value is eliminated, thereby generating a digital response feedback signal of the target underground pipeline.

[0011] Preferably, the step S110 specifically includes the following steps: Acquiring existing time series dynamic characteristics and frequency fluctuation range of the digital response feedback signal, and dividing the frequency fluctuation range into wavelet sub-bands with different detail coefficient scales based on the existing time series dynamic characteristics; Introducing a wavelet transform algorithm to transfer the digital response feedback signal from the time domain to the frequency domain, thereby obtaining a dynamic change spectrum of the digital response feedback signal that fluctuates over time; Extract the spectrum amplitude corresponding to each wavelet sub-band in the dynamically changing spectrum, construct a power periodic spectrum based on the spectrum amplitude, calculate the power spectrum density of the detail coefficient scale of each layer based on the power periodic spectrum, and perform square summation to obtain the band power energy value of each wavelet sub-band; Presetting a reference frequency band power energy threshold, calculating the ratio of each frequency band power energy value to the reference frequency band power energy threshold, eliminating individual frequency band differences of the digital response feedback signal, and obtaining multiple frequency band power energy ratios; Taking the dynamic time sequence as the context clue track, the context clue track is tracked according to the frequency band power energy ratio to perform feature normalization organization on the frequency band power energy value of each wavelet sub-band to form the hidden detection feature vector of the digital response feedback signal; Based on big data, the accurate detection feature vector of the detection object type is obtained, and the degree of consistency between the hidden detection feature vector and the accurate detection feature vector is calculated. If the degree of consistency is greater than the preset degree of consistency, 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.

[0012] A second aspect of the present invention provides a Hertz signal digitization system for underground pipeline detection, which is applied to any of the Hertz signal digitization methods for underground pipeline detection, and the system 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 division unit, a coil driver IC unit, and an inductor coil unit, and 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 collect several discrete response signals of the target underground pipeline and perform mixing and filtering processing to improve the signal-to-noise ratio; Intelligent signal analysis module: The intelligent signal analysis module is responsible for frequency band calculation of 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 according to the detection results.

[0013] The present invention solves the technical defects existing in the background technology, and the beneficial technical effects of the present invention are: By combining the phase accumulation mechanism of DDS (direct digital synthesis) technology with a digital interpolation translation algorithm, 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 phase, a frequency division strategy using controllable random dithering is introduced to generate multiple sets of single-frequency voltage signals, effectively reducing spectral aliasing and background noise, improving the detection signal's penetration and positioning resolution for the target underground pipeline. The response signal is sampled and filtered using a high-precision ADC and an adaptive FIR low-pass filter, significantly enhancing the ability to extract weak underground response signals and reducing the interference of mixed high-frequency noise. Furthermore, by combining wavelet subband energy normalization analysis and feature vector construction, high-dimensional expression and intelligent discrimination of underground pipeline characteristics are achieved, improving the accuracy of target identification and the reliability of detection results. In summary, the present invention digitally improves the 512Hz underground pipeline detection analog circuit, achieving full-link digital optimization from signal excitation to response analysis, effectively improving the sensitivity, anti-interference capability, and signal processing accuracy of underground pipeline detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, without paying any creative work, they can also obtain drawings of other embodiments based on these drawings.

[0015] Figure 1 A first method flow chart of a Hertzian signal digitization method for underground pipeline detection is shown; Figure 2 A second method flow chart of the Hertzian signal digitization method for underground pipeline detection is shown; Figure 3 A system framework diagram of a Hertzian signal digitization method for underground pipeline detection is shown; Figure 4 The system hardware architecture diagram of the signal transmission module is shown. DETAILED DESCRIPTION

[0016] In order to more clearly understand the above-mentioned objects, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that, in the absence of conflict, the embodiments of the present application and the features therein can be combined with each other.

[0017] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the scope of protection of the present invention is not limited to the specific embodiments disclosed below.

[0018] The first aspect of the present invention provides a Hertz signal digitization method for underground pipeline detection, such as Figure 1 As shown, the following steps are included: S102: Parameters of the desired detection operating condition of the digital pipeline detection device are formulated using DDS technology phase accumulation to generate a step-by-step phase gradient. The step-by-step phase gradient is digitally interpolated and translated using iterative rotation based on an accumulation mapping rule of an analog sine wave of a 512 Hz analog signal to obtain a digital detection excitation signal. S104: Starting the power supply boost IC of the digital pipeline detection device to tune and obtain the natural oscillation frequency of the digital detection excitation signal, accumulating the periodic phase error of the natural oscillation frequency and applying controllable random jitter to perform digital frequency division, thereby generating multiple sets of single-frequency voltage signals; S106: The coil driver IC converts multiple sets of single-frequency voltage signals into operating signals to drive the inductive transmitting coil. The inductive transmitting coil and the radio frequency antenna are used to radiate the digital detection excitation signal in the form of a single-frequency electromagnetic wave to the target underground pipeline. S108: Using a high-precision ADC to digitally acquire a plurality of discrete response signals of the target underground pipeline, filtering out high-frequency noise items after mixing the discrete response signals using an adaptive FIR low-pass filter, and performing filtering optimization for error simulation analysis to generate a 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, perform detection analysis on the target underground pipeline based on the hidden detection feature vector, obtain a detection result, and control the digital pipeline detection equipment to issue an alarm based on the detection result.

[0019] It should be noted that during field detection, the present invention usually requires one RF antenna to be set up for basic transmission and reception in single-frequency application scenarios of 512Hz digital detection excitation signals; while in multi-frequency application scenarios such as ranging, geodesy or depth measurement that require multi-point detection and solution through geometric relationships, at least three or more RF antennas need to be set up to maintain signal transmission and reception at multiple different frequencies (such as GPS L1+L2), using frequency differential to eliminate ionospheric delay and improve the accuracy of digital signal pipeline space detection.

[0020] Preferably, the S102, as Figure 2 As shown, the specific steps include: Obtaining a detection plan record of the target underground pipeline, reading the detection object type of the target underground pipeline through the detection plan record, and obtaining the expected detection working condition parameters pre-evaluated and determined by the digital pipeline detection device in the target underground pipeline based on the detection object type; Introducing DDS technology to obtain the closed-loop clock cycle of the digital pipeline detection device, designing a phase accumulation strategy in DDS technology based on the closed-loop clock cycle, and constructing a phase accumulator; According to the expected detection conditions, the sampling frequency and accumulation bit width of the detection object are preset and matched with the parameters. The frequency step control word is calculated in accordance with the sampling frequency and accumulation bit width in the DDS technology. The frequency step control word is used to accumulate the phase in the phase accumulator once every closed-loop clock cycle to generate a step-by-step phase gradient. The standard 512 Hz analog signal detected by the digital pipeline detection equipment was extracted through the memo log. The quadrant symmetry of the intercept and slope of the corresponding sine waveform of the standard 512 Hz analog signal was analyzed and recorded. The symmetry overlap of the sub-waveform segments in the cross-quadrant area and the accumulation mapping rule of the simulated sine wave were obtained. According to the high-order gradient of the step-by-step phase gradient, the cross-quadrant area corresponding to the sub-waveform segment with the minimum symmetric overlap is located, and the waveform blueprint accumulation address is obtained. The low-order vector of the iterative step-by-step phase gradient is rotated 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.

[0021] It should be noted that traditional digital pipeline detection equipment cannot accurately and directly generate digital signals that match 512 Hz analog signals, and their frequency stability is less than 0.1 ppm. To address this, this method leverages DDS technology within the digital pipeline detection equipment to generate a highly targeted and adaptable periodic waveform frequency that meets the requirements of the target underground pipeline detection equipment's search for detection targets. DDS technology also constructs a phase accumulator that continuously accumulates the phase values ​​of the periodic waveform frequency, generating a linear digital phase sequence that conforms to 512 Hz. This is equivalent to generating a digital phase ramp, enabling high-precision control of the digital waveform's progress. The frequency step control word determines the phase amplitude that should be accumulated during each clock cycle of the digital pipeline detection equipment to perform parameter sampling and search for detection targets according to the desired detection conditions. This allows for direct control of the output waveform frequency, thereby converting the traditional analog frequency into digital domain control, rapidly capturing frequency jumps or sweeps, and significantly improving the output smoothness and resolution of the 512 Hz digital signal frequency. For the periodic accumulation of the phase accumulator, the phase value of its accumulated output represents the timing node position of the 512Hz digital waveform adapted to the detection object in a sampling period, and the gradual phase gradient shows the prototype of the progressive cyclic trend of the digital waveform. It effectively follows the expected detection working conditions to formulate parameters and control the output period of the digital waveform, so that the 512Hz digital signal meets the requirements of the detection plan and better replaces the 512Hz analog signal to achieve the detection effect of the target underground pipeline.

[0022] It should be noted that DDS technology, known in Chinese as direct digital frequency synthesis, is used to synthesize and output high-precision and high-stability sine, square, or triangle wave signals without the need for circuit reconstruction. In this method, a standard Hertz analog signal is used as a reference template for a sine waveform generated as a 512Hz digital signal. The waveform of this standard Hertz analog signal is then transformed and decomposed using quadrant coordinates, and the intercept and slope symmetry rules are analyzed using differential equations. This method then constructs a waveform characteristic mapping rule that closely adheres to the traditional standardized Hertz analog signal and can accurately search for the type of detection object. This rule, namely the accumulation mapping rule for the Hertz frequency domain signal sine wave, provides a highly reliable and trustworthy waveform reconstruction underlying logic for the accurate generation of 512Hz digital signal waveform planning. Furthermore, this method uses a rotational iteration method to resolve the gradual phase gradient in the quadrant domain, thereby achieving dynamic programmable control of the sinusoidal waveform. This replaces the inefficient step of using a lookup table to define the waveform amplitude in traditional DDS technology. Ultimately, based on the constructed accumulation mapping rule, digital interpolation tracks the rotational phase vector planned by the phase accumulator for the 512Hz digital waveform, forming a more accurate 512Hz digital detection excitation signal and ensuring a digital signal frequency stability better than 0.1ppm. This method achieves digital improvement of the traditional 512Hz analog signal, improving the frequency controllability and phase continuity of the signal source, thereby alleviating the analog signal's susceptibility to environmental noise interference and significantly reducing the emission rate of false signals.

[0023] Preferably, the method of extracting the standard Hz 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 sine waveform corresponding to the standard 512 Hz analog signal, and obtaining the symmetric overlap of the sub-waveform segments in the cross-quadrant area and the accumulation mapping rule of the simulated sine wave specifically includes the following steps: Obtaining a memo log of the digital pipeline detection device, and obtaining, through the memo log, a standard 512 Hz analog signal of the digital pipeline detection device applying the target underground pipeline to search for the type of detection object within a preset time unit; A Hilbert-Huang transform algorithm is introduced to perform a symmetry transformation of the waveform period of the standard 512 Hz analog signal on quadrant coordinates to obtain a simulated sine wave, and an equally divided quadrant domain is constructed, and the simulated sine wave is divided into N sub-waveform segments in the equally divided quadrant domain; Utilizing MATLAB digital software, each sub-waveform segment is converted into a spline waveform differential equation and the linear equation solution of the spline interpolation control points is performed, and the intercept coefficient and slope value of each spline waveform differential equation are output; During the solution process, a sub-waveform segment is locked at a bird's-eye view angle in 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 the sub-waveform segment one by one, and the cross-symmetric mapping record is performed with each sub-waveform segment in the other quadrants to obtain the symmetric overlap of the sub-waveform segments in the cross-quadrant area, and construct the accumulation mapping rule of the simulated sine wave.

[0024] It should be noted that for the construction of the accumulation mapping rule of the sine wave of the Hertz frequency domain signal, this method linearly fragments the waveform of the standard Hertz analog signal on the quadrant coordinates, namely sub-waveform segments, and the quadrant coordinates are four equally divided quadrants (the first quadrant, the second quadrant, the third quadrant and the fourth quadrant). The layout of the sub-waveform segments in the equally divided quadrants can explain the quadrant symmetry mechanism of the sine wave period. The sine wave usually has a special four-quadrant symmetry characteristic, so that each sine waveform in each quadrant has a symmetry rule that can be followed with the sine waveforms in other quadrants. For example, the second quadrant is the opposite of the first quadrant or the third quadrant is the negative value of the first quadrant, etc. This provides a tracking clue for the accurate reconstruction of the periodic waveform of the digital signal. Therefore, based on this symmetry characteristic, this method converts and solves each sub-waveform segment in the form of a spline waveform differential equation, where the intercept coefficient represents the intersection of the local sinusoidal waveform of the standard Hertz analog signal and the quadrant period time axis, clarifying the starting point of the sinusoidal waveform amplitude of the standard Hertz analog signal; and 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 climbing or descending speed of the corresponding band of the sinusoidal waveform data. The combination of 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 symmetric relationship between the intercept coefficient and the slope value of the sub-waveform segment in each quadrant is recorded by cross-mapping, and the accumulation mapping rule of the sine wave of the Hertz frequency domain signal is constructed. By using this accumulation mapping rule, the values ​​in the remaining quadrants can be obtained by mapping the phase of the digital signal, so that the correct waveform of the 512Hz digital signal can be quickly established, effectively reducing the periodic drift error phenomenon generated by traditional digital signals and improving the detection and transmission reliability of digital signals. In addition, due to the quadrant symmetry of the sine wave, this method only needs to discretely write one-quarter of the quadrants (such as the first quadrant 0~ ) can be used to deduce the waveform trend profiles of the remaining quadrants using the digital sampling waveform data (sine rotation vector of 64 or 256 points), which greatly reduces the generation and processing of unnecessary digital waveforms, saves storage space, improves the transmission efficiency of digital signals, and has high economic benefits.

[0025] Preferably, the method of locating the cross-quadrant region where the sub-waveform segment corresponding to the minimum symmetric overlap degree is located based on the high-order gradient of the stepwise phase gradient, obtaining the waveform blueprint accumulation address, rotating the low-order vector of the iterative stepwise phase gradient on the waveform blueprint accumulation address, and performing a digital interpolation translation operation according to the accumulation mapping rule to obtain the digital detection excitation signal specifically includes the following steps: Extracting the gradient recorded in the phase high interval from the stepwise phase gradient, which is defined as the high gradient parameter, and obtaining the vector recorded in the phase low interval, which is defined as the low vector parameter; A symmetric overlap threshold is preset according to the high-order gradient parameter, and only the cross-quadrant area corresponding to the sub-waveform segment with the minimum symmetric overlap below the symmetric overlap threshold is extracted, and marked as the waveform blueprint accumulation address. The low-order vector parameter is gradually iteratively rotated on the waveform blueprint accumulation address so that the low-order vector tends to the quadrant X-axis. The rotation angle of the waveform phase is continuously accumulated during the iterative rotation process to obtain the quadrant coordinate of the rotation angle; Get the Y-axis component value and polar angle coordinate area contained in the low-order vector parameter. If the Y-axis component value is infinitely close to or equal to 0 and the rotation angle quadrant coordinate reaches the polar angle coordinate area, then stop the rotation iteration operation of the low-order vector parameter and output the modulus amplitude and iterative phase angle. The digital complement processing of the intercept coefficient and the slope value is performed on the return mapping modulus amplitude and the iterative phase angle on the waveform blueprint accumulation address to obtain a series of adjacent and continuous waveform amplitude address codes. The series of waveform amplitude address codes are subjected to sinusoidal quadrant symmetric second-order interpolation according to the accumulation mapping rule to finally generate a sinusoidal digital waveform; A digital-to-analog converter is constructed, and the sinusoidal digital waveform is sent into the digital-to-analog converter for smooth translation of the 512 Hz analog signal to obtain a digital detection excitation signal.

[0026] It should be noted that the high-order gradient parameters recorded by the step-by-step phase gradient can locate the area position of the current phase, and extract the cross-quadrant area where the sub-waveform segment that does not exceed the symmetry overlap threshold and has minimized symmetry overlap is located. Therefore, the quadrant of the 512Hz digital signal starting waveform that is adapted to the detection object type search is determined according to the high-order phase. The cross-quadrant area is the waveform starting area for generating the 512Hz digital signal, that is, the waveform blueprint accumulation address, which is mainly used to accumulate and store the rotation phase data of the signal frequency to achieve the effect of high-order phase identification quadrant, and then reconstruct the complete periodic waveform without increasing the scale of waveform data processing, ensuring waveform continuity and accuracy. The low-order vector parameters (x, y) are then loaded into the waveform template accumulation address for iterative rotation. This iterative rotation of the low-order vectors yields the waveform data's modulus amplitude and iterative phase angle. The modulus amplitude reveals the oscillographic amplitude of the waveform vector in the phase accumulation process, adapted to the detection object type, while the iterative phase angle characterizes the phase angle orientation of the waveform vector. This ensures smoother and more consistent symmetry reconstruction of the digital signal, avoids redundancy and missing waveform mapping, and improves the fidelity and spatial penetration of the digital signal output. If the Y-axis component value approaches or equals zero, the direction is determined to ensure that each rotation decreases the y-component (approaching 0), thereby convergently determining the direction of waveform data rotation and improving modulus accuracy. The determination of whether the rotation angle quadrant coordinates reach the polar coordinate region is performed to detect whether the waveform phase rotation angle converges to the vector polar angle, thereby maintaining a high degree of fidelity in the phase angle radian change. Finally, the frequency of the digital detection excitation signal obtained by using the digital complement of the accumulation mapping rule and the second-order interpolation is 512Hz, which can achieve a high degree of consistency with the frequency of the traditional Hertz analog signal, and improve the detection arrival rate and penetration accuracy of the digital pipeline detection equipment for the blind spots of the target underground pipeline space.

[0027] Preferably, the step S104 specifically includes the following steps: Start the power boost IC of the digital pipeline detection equipment, obtain the origin oscillation frequency of the digital detection excitation signal, and build an oscillation stability evaluation model by weighing the past node circuit changes of the topology power boost IC; The origin oscillation frequency is evaluated by using an oscillation stability evaluation model to obtain the frequency stability of the origin oscillation frequency; 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 adjusted until the frequency stability is highly parallel to the preset frequency stability. At this time, the natural oscillation frequency of the digital detection excitation signal after adjustment is obtained. The frequency division requirements of the digital detection excitation signal are obtained through the detection planning record, and the ideal frequency division ratio and ideal transmission period of the natural oscillation frequency are preset according to the frequency division requirements. The phase accumulator is used to accumulate the fractional part of the natural oscillation frequency divided by the ideal frequency division ratio during an ideal transmission period to generate a frequency phase accumulation value; If the frequency phase accumulation value is greater than 1, a frequency division pulse is generated at this time, and the integer part of the ideal frequency division ratio is deducted synchronously to form a series of frequency division period error values ​​for the natural oscillation frequency to achieve the ideal transmission period and a frequency division pulse layout diagram corresponding to maintaining 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 injected into a series of frequency-divided 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-divided pulse corresponding to the controllable jitter period error value is triggered in advance through the frequency-divided pulse layout diagram; otherwise, the standardized frequency division is maintained, and finally multiple groups of single-frequency voltage signals are generated.

[0028] It should be noted that the originating oscillation frequency of the digital detection excitation signal is the initial oscillation frequency generated during the initial generation of the digital detection excitation signal, influenced by the oscillation of the power supply boost IC node circuit. This serves as an evaluation indicator for the frequency stability of the digital detection excitation signal. If the frequency stability falls below the preset frequency stability, it indicates that the current power supply boost IC is unable to maintain a high degree of stability when transmitting the digital detection excitation signal, significantly reducing the detection quality of the digital detection excitation signal. Therefore, this method first adjusts and optimizes the frequency of the digital detection excitation signal output by the power supply boost IC at the boost control strategy level to ensure that the frequency stability of the digital detection excitation signal is maintained at a level of 10ppm, thereby improving the transmission reliability of the 512Hz digital detection excitation signal. Subsequently, a phase accumulator continuously accumulates the natural frequency phase of the digital detection excitation signal based on the frequency division requirements. Specifically, the fractional portion of the natural oscillation frequency divided by the ideal frequency division ratio is accumulated over an ideal transmission period. This converts the fractional error into a periodic integer frequency division adjustment, tracking the accumulated phase error of the fractional frequency division. If the accumulated frequency phase value is greater than 1, it indicates that the fractional error has reached the critical point of periodic integer division, triggering the integer carry mechanism, deducting the integer portion of the ideal division ratio, and generating a frequency-division pulse, effectively stacking and locking the periodic error term of the digital signal frequency decomposition. This method then introduces a controllable jitter factor, namely a random jitter value, through the LFSR pseudo-random generation mechanism to randomize the fixed periodic error into a non-deterministic sequence. If the controllable jitter accumulated error value is greater than a preset threshold, it indicates that the noise position of the periodic error generated by the digital detection excitation signal frequency division is relatively fixed. Since periodic error generates spurious signals in the frequency domain, random jitter converts them into broadband noise. By pre-triggering the frequency division pulse corresponding to the controllable jitter frequency division periodic error value, the position of the frequency division pulse can be randomized, transforming the fractional frequency division error into random noise instead of fixed spurious signals, thereby reducing the spurious amplitude. This method then disrupts the periodic error by perturbing the carry decision of the accumulator, achieving controllable elimination of periodic error spurious signals.

[0029] In summary, on the one hand, this method can optimize the frequency stability of the initial generation of the 512Hz digital detection excitation signal and reduce the signal transmission drift phenomenon; on the other hand, by applying controllable random jitter to randomize the error distribution and dynamically adjust the frequency division ratio, the suppression rate and elimination rate of the frequency division periodic noise are improved. Compared with the traditional frequency division method, it avoids the interference embedding of the digital detection excitation signal in the sensitive boost frequency band of the power supply boost IC, ensures the frequency division balance of the digital detection excitation signal, and improves the penetration and positioning resolution of the digital signal for target underground pipeline detection.

[0030] Preferably, the step S108 specifically includes the following steps: The receiving coil of the digital pipeline detection equipment is combined with a high-precision ADC to digitally collect 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, we obtain the working condition cases of Hertz analog signals. According to the detection plan, we extract the local oscillator reference signal that meets the working conditions of the standard Hertz analog signal and is orthogonal to the actual modulation frequency from the working condition cases. Constructing a DC demodulation domain, based on the signal spectrum, each discrete response signal and the local oscillator reference signal are migrated to the DC demodulation domain for point-by-point coherent demodulation, thereby obtaining multiple groups of mixed signal components. An adaptive FIR low-pass filter designed by a Hanning window function and having a cutoff frequency higher than the signal bandwidth is introduced, and each group of the mixed signal components is filtered using the adaptive FIR low-pass filter to remove high-frequency noise terms and obtain a demodulated DC component value of the feedback response discrete signal after filtering; A signal receiving and decoding simulation model is constructed based on the decoding rules of the digital pipeline detection equipment. The demodulated DC component value is imported into the signal receiving and decoding simulation model for simulation to obtain the simulated bit error rate after filtering the feedback response discrete signal. 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, and the current signal-to-noise ratio of the first filtered signal is obtained. At the same time, based on the big data, the filtered feedback response discrete signal that satisfies the detection planning record and is defined as the second filtered signal is obtained, 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 expected 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 processing is performed until the signal-to-noise ratio deviation value is eliminated, thereby generating a digital response feedback signal of the target underground pipeline.

[0031] It should be noted that because traditional equipment typically only captures discrete response signals, signal detection and analysis of target underground pipelines can be subject to weak signals, risk of loss, and extensive noise interference, resulting in inaccurate detection results. This method addresses this issue by point-by-point multiplication of discrete response signals with a local oscillator reference signal in a DC demodulation domain, shifting the target frequency to DC. This mixing of the discrete response signals results in 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 both amplitude and phase, while the sum frequency component contains interfering noise particles located near the 2f high-frequency component. Synchronous phase-sensitive mixing of the signals enables downconversion of specific frequency information to near 0Hz DC, thereby completely separating the digital response feedback signal from broadband noise. This facilitates subsequent filter extraction of the critical weak signal, achieving frequency-selective detection and improving the phase-locked amplification gain and integrity of the discrete response signal. Then, an adaptive FIR low-pass filter is used to filter each group of mixed signal components. This allows the response signal processing to have an extremely high level of sensitivity only to the target frequency component, exerting a frequency selectivity effect. This suppresses the 2f high-frequency component noise after mixing, maximizes the retention of the target signal strength information, and obtains the demodulated DC component signal value that has filtered out large-scale noise. This demodulated DC component signal represents the projection of the response signal at 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, ensuring that there is no phase distortion during the process of retaining the difference frequency DC component and filtering the sum frequency component, protecting the integrity of the digital signal waveform and improving the signal feedback quality.

[0032] It should be noted that if the simulated bit error rate is greater than 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 response distortion, delay, or waveform loss, causing nonlinear signal feedback distortion. To address this issue, this method reconfigures the filtering parameters of the adaptive FIR low-pass filter by calculating the signal-to-noise ratio deviation between the current signal-to-noise ratio of the first filtered signal and the expected signal-to-noise ratio, and performs double filtering on the response discrete signal, thereby eliminating signal feedback errors, optimizing the fidelity of the 512Hz digital signal, and providing a reliable solution for subsequent digital signal detection feedback analysis.

[0033] Preferably, the step S110 specifically includes the following steps: Acquiring existing time series dynamic characteristics and frequency fluctuation range of the digital response feedback signal, and dividing the frequency fluctuation range into wavelet sub-bands with different detail coefficient scales based on the existing time series dynamic characteristics; Introducing a wavelet transform algorithm to transfer the digital response feedback signal from the time domain to the frequency domain, thereby obtaining a dynamic change spectrum of the digital response feedback signal that fluctuates over time; Extract the spectrum amplitude corresponding to each wavelet sub-band in the dynamically changing spectrum, construct a power periodic spectrum based on the spectrum amplitude, calculate the power spectrum density of the detail coefficient scale of each layer based on the power periodic spectrum, and perform square summation to obtain the band power energy value of each wavelet sub-band; Presetting a reference frequency band power energy threshold, calculating the ratio of each frequency band power energy value to the reference frequency band power energy threshold, eliminating individual frequency band differences of the digital response feedback signal, and obtaining multiple frequency band power energy ratios; Taking the dynamic time sequence as the context clue track, the context clue track is tracked according to the frequency band power energy ratio to perform feature normalization organization on the frequency band power energy value of each wavelet sub-band to form the hidden detection feature vector of the digital response feedback signal; Based on big data, the accurate detection feature vector of the detection object type is obtained, and the degree of consistency between the hidden detection feature vector and the accurate detection feature vector is calculated. If the degree of consistency is greater than the preset degree of consistency, 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.

[0034] It should be noted that the digital response feedback signal, due to its temporal variations, can become non-stationary. This can obscure or obscure the specific frequency components of the target object type, making it difficult to accurately capture the relevant features of the target underground pipeline, leading to significant errors in the detection results. To address this issue, this method uses the dynamic signal characteristics (presumably temporal dynamic characteristics) of the digital response feedback signal to segment the frequency bins. This adapts to the local frequency characteristics of the non-stationary signal. The resulting wavelet subbands with different detail coefficient scales significantly enhance the phenotypic ability of the detected object type, enabling the visualization and identification of the features embedded in the digital response feedback signal with superior resolution. The digital response feedback signal is then mapped from the time domain wavelet to the frequency domain to further reveal the frequency components of the digital received signal. This time-series nature captures the dynamic and transient changes of the features, improving the scanning clarity and locking accuracy of abnormal waveforms, and optimizing the local edge highlighting ability to determine whether the detected object type has abnormal features. A power periodogram is then constructed based on the spectral amplitudes recorded in the dynamically changing spectrum. This power periodogram is an unbiased estimate of the signal's power spectrum, presenting the local frequency power distribution of the digital response feedback signal. The independence of each power periodogram makes the subsequent square summation of the power spectrum density more efficient. Based on the power periodogram, the frequency band power energy values ​​at each level of detail coefficient scale are calculated to quantify the signal's intensity in specific frequency bands. This improves the sensitivity to capturing implicit mutation signals at different scales due to abnormal characteristics of the detected object type, thereby achieving more accurate detection of abnormal characteristics in underground pipelines. Finally, the frequency band power energy values ​​of the wavelet sub-bands are normalized and organized according to the frequency band power energy ratio, tracking the context clue trajectory characteristics. This eliminates the influence of environmental differences on absolute energy, compresses the dynamic range, and further enhances the digital pipeline detection equipment's recognition of weak digital signals with abnormal characteristics, thereby structuring the formation of hidden detection feature vectors associated with the detected object type (anomaly) in the digital response feedback signal.

[0035] It should be noted that if the degree of fit is greater than the preset degree of fit, it indicates that the target underground pipeline contains a detection object type, which includes damage, cracks, deformation, scaling, corrosion, and foreign body blockage. Therefore, the target underground pipeline needs to be marked as abnormal and an alarm is activated. This method can implicitly identify the detection object type characteristics of the digital feedback signal received by the device, achieve a structural representation effect, and accurately depict the global characteristics of the detection object type, thereby performing a low-blind-angle abnormality analysis on the target underground pipeline, greatly improving the analytical reliability and early warning accuracy of underground pipeline detection, and reducing the abnormal false alarm or missed alarm phenomenon of underground pipeline detection.

[0036] The 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 above-mentioned methods includes: 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 division unit, a coil driver IC unit, and an inductor coil unit, and 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 collect several discrete response signals of the target underground pipeline and perform mixing and filtering processing to improve the signal-to-noise ratio; Intelligent signal analysis module: The intelligent signal analysis module is responsible for frequency band calculation of 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 according to the detection results.

[0037] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person 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 based on the scope of protection of the claims.

Claims

1. A Hertzian signal digitization method for underground pipeline detection, characterized in that: The following steps are involved: S102: Parameters of the desired detection operating condition of the digital pipeline detection device are formulated using DDS technology phase accumulation to generate a step-by-step phase gradient. The step-by-step phase gradient is digitally interpolated and translated using iterative rotation based on an accumulation mapping rule of an analog sine wave of a 512 Hz analog signal to obtain a digital detection excitation signal. S104: Starting the power supply boost IC of the digital pipeline detection device to tune and obtain the natural oscillation frequency of the digital detection excitation signal, accumulating the periodic phase error of the natural oscillation frequency and applying controllable random jitter to perform digital frequency division, thereby generating multiple sets of single-frequency voltage signals; S106: The coil driver IC converts multiple sets of single-frequency voltage signals into operating signals to drive the inductive transmitting coil. The inductive transmitting coil and the radio frequency antenna are used to radiate the digital detection excitation signal in the form of a single-frequency electromagnetic wave to the target underground pipeline. S108: Using a high-precision ADC to digitally acquire a plurality of discrete response signals of the target underground pipeline, filtering out high-frequency noise items after mixing the discrete response signals using an adaptive FIR low-pass filter, and performing filtering optimization for error simulation analysis to generate a 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, perform detection analysis on the target underground pipeline based on the hidden detection feature vector, obtain a detection result, and control the digital pipeline detection equipment to issue an alarm based on the detection result.

2. The Hertzian signal digitization method for underground pipeline detection according to claim 1, characterized in that: The S102 specifically includes the following steps: Obtaining a detection plan record of the target underground pipeline, reading the detection object type of the target underground pipeline through the detection plan record, and obtaining the expected detection working condition parameters pre-evaluated and determined by the digital pipeline detection device in the target underground pipeline based on the detection object type; Introducing DDS technology to obtain the closed-loop clock cycle of the digital pipeline detection device, designing a phase accumulation strategy in DDS technology based on the closed-loop clock cycle, and constructing a phase accumulator; According to the expected detection conditions, the sampling frequency and accumulation bit width of the detection object are preset and matched with the parameters. The frequency step control word is calculated in accordance with the sampling frequency and accumulation bit width in the DDS technology. The frequency step control word is used to accumulate the phase in the phase accumulator once every closed-loop clock cycle to generate a step-by-step phase gradient. The standard 512 Hz analog signal detected by the digital pipeline detection equipment was extracted through the memo log. The quadrant symmetry of the intercept and slope of the corresponding sine waveform of the standard 512 Hz analog signal was analyzed and recorded. The symmetry overlap of the sub-waveform segments in the cross-quadrant area and the accumulation mapping rule of the simulated sine wave were obtained. According to the high-order gradient of the step-by-step phase gradient, the cross-quadrant area corresponding to the sub-waveform segment with the minimum symmetric overlap is located, and the waveform blueprint accumulation address is obtained. The low-order vector of the iterative step-by-step phase gradient is rotated 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 Hertzian signal digitization method for underground pipeline detection according to claim 2, characterized in that: The method of extracting the standard Hz 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 sine waveform corresponding to the standard 512 Hz analog signal, and obtaining the symmetry overlap of the sub-waveform segments in the cross-quadrant area and the accumulation mapping rule of the simulated sine wave specifically includes the following steps: Obtaining a memo log of the digital pipeline detection device, and obtaining, through the memo log, a standard 512 Hz analog signal of the digital pipeline detection device applying the target underground pipeline to search for the type of detection object within a preset time unit; A Hilbert-Huang transform algorithm is introduced to perform a symmetry transformation of the waveform period of the standard 512 Hz analog signal on quadrant coordinates to obtain a simulated sine wave, and an equally divided quadrant domain is constructed, and the simulated sine wave is divided into N sub-waveform segments in the equally divided quadrant domain; Utilizing MATLAB digital software, each sub-waveform segment is converted into a spline waveform differential equation and the linear equation solution of the spline interpolation control points is performed, and the intercept coefficient and slope value of each spline waveform differential equation are output; During the solution process, a sub-waveform segment is locked at a bird's-eye view angle in 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 the sub-waveform segment one by one, and the cross-symmetric mapping record is performed with each sub-waveform segment in the other quadrants to obtain the symmetric overlap of the sub-waveform segments in the cross-quadrant area, and construct the accumulation mapping rule of the simulated sine wave.

4. The Hertzian signal digitization method for underground pipeline detection according to claim 2, characterized in that: The method of locating the cross quadrant region where the sub-waveform segment corresponding to the minimum symmetric overlap degree is located according to the high-order gradient of the stepwise phase gradient, obtaining the waveform blueprint accumulation address, rotating the low-order vector of the iterative stepwise phase gradient on the waveform blueprint accumulation address, and performing a digital interpolation translation operation according to the accumulation mapping rule to obtain a digital detection excitation signal specifically includes the following steps: Extracting the gradient recorded in the phase high interval from the stepwise phase gradient, which is defined as the high gradient parameter, and obtaining the vector recorded in the phase low interval, which is defined as the low vector parameter; A symmetric overlap threshold is preset according to the high-order gradient parameter, and only the cross-quadrant area corresponding to the sub-waveform segment with the minimum symmetric overlap below the symmetric overlap threshold is extracted, and marked as the waveform blueprint accumulation address. The low-order vector parameter is gradually iteratively rotated on the waveform blueprint accumulation address so that the low-order vector tends to the quadrant X-axis. The rotation angle of the waveform phase is continuously accumulated during the iterative rotation process to obtain the quadrant coordinate of the rotation angle; Get the Y-axis component value and polar angle coordinate area contained in the low-order vector parameter. If the Y-axis component value is infinitely close to or equal to 0 and the rotation angle quadrant coordinate reaches the polar angle coordinate area, then stop the rotation iteration operation of the low-order vector parameter and output the modulus amplitude and iterative phase angle. The digital complement processing of the intercept coefficient and the slope value is performed on the return mapping modulus amplitude and the iterative phase angle on the waveform blueprint accumulation address to obtain a series of adjacent and continuous waveform amplitude address codes. The series of waveform amplitude address codes are subjected to sinusoidal quadrant symmetric second-order interpolation according to the accumulation mapping rule to finally generate a sinusoidal digital waveform; A digital-to-analog converter is constructed, and the sinusoidal digital waveform is sent into the digital-to-analog converter for smooth translation of the 512 Hz analog signal to obtain a digital detection excitation signal.

5. The Hertzian signal digitization method for underground pipeline detection according to claim 1, characterized in that: The S104 specifically includes the following steps: Start the power boost IC of the digital pipeline detection equipment, obtain the origin oscillation frequency of the digital detection excitation signal, and build an oscillation stability evaluation model by weighing the past node circuit changes of the topology power boost IC; The origin oscillation frequency is evaluated by using an oscillation stability evaluation model to obtain the frequency stability of the origin oscillation frequency; 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 adjusted until the frequency stability is highly parallel to the preset frequency stability. At this time, the natural oscillation frequency of the digital detection excitation signal after adjustment is obtained. The frequency division requirements of the digital detection excitation signal are obtained through the detection planning record, and the ideal frequency division ratio and ideal transmission period of the natural oscillation frequency are preset according to the frequency division requirements. The phase accumulator is used to accumulate the fractional part of the natural oscillation frequency divided by the ideal frequency division ratio during an ideal transmission period to generate a frequency phase accumulation value; If the frequency phase accumulation value is greater than 1, a frequency division pulse is generated at this time, and the integer part of the ideal frequency division ratio is deducted synchronously to form a series of frequency division period error values ​​for the natural oscillation frequency to achieve the ideal transmission period and a frequency division pulse layout diagram corresponding to maintaining 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 injected into a series of frequency-divided 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-divided pulse corresponding to the controllable jitter period error value is triggered in advance through the frequency-divided pulse layout diagram; otherwise, the standardized frequency division is maintained, and finally multiple groups of single-frequency voltage signals are generated.

6. The Hertzian signal digitization method for underground pipeline detection according to claim 1, characterized in that: The S108 specifically includes the following steps: The receiving coil of the digital pipeline detection equipment is combined with a high-precision ADC to digitally collect 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, we obtain the working condition cases of Hertz analog signals. According to the detection plan, we extract the local oscillator reference signal that meets the working conditions of the standard Hertz analog signal and is orthogonal to the actual modulation frequency from the working condition cases. Constructing a DC demodulation domain, based on the signal spectrum, each discrete response signal and the local oscillator reference signal are migrated to the DC demodulation domain for point-by-point coherent demodulation, thereby obtaining multiple groups of mixed signal components. An adaptive FIR low-pass filter designed by a Hanning window function and having a cutoff frequency higher than the signal bandwidth is introduced, and each group of the mixed signal components is filtered using the adaptive FIR low-pass filter to remove high-frequency noise terms and obtain a demodulated DC component value of the feedback response discrete signal after filtering; A signal receiving and decoding simulation model is constructed based on the decoding rules of the digital pipeline detection equipment. The demodulated DC component value is imported into the signal receiving and decoding simulation model for simulation to obtain the simulated bit error rate after filtering the feedback response discrete signal. 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, and the current signal-to-noise ratio of the first filtered signal is obtained. At the same time, based on the big data, the filtered feedback response discrete signal that satisfies the detection planning record and is defined as the second filtered signal is obtained, 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 expected 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 processing is performed until the signal-to-noise ratio deviation value is eliminated, thereby generating a digital response feedback signal of the target underground pipeline.

7. The Hertzian signal digitization method for underground pipeline detection according to claim 1, characterized in that: The S110 specifically includes the following steps: Acquiring existing time series dynamic characteristics and frequency fluctuation range of the digital response feedback signal, and dividing the frequency fluctuation range into wavelet sub-bands with different detail coefficient scales based on the existing time series dynamic characteristics; Introducing a wavelet transform algorithm to transfer the digital response feedback signal from the time domain to the frequency domain, thereby obtaining a dynamic change spectrum of the digital response feedback signal that fluctuates over time; Extract the spectrum amplitude corresponding to each wavelet sub-band in the dynamically changing spectrum, construct a power periodic spectrum based on the spectrum amplitude, calculate the power spectrum density of the detail coefficient scale of each layer based on the power periodic spectrum, and perform square summation to obtain the band power energy value of each wavelet sub-band; Presetting a reference frequency band power energy threshold, calculating the ratio of each frequency band power energy value to the reference frequency band power energy threshold, eliminating individual frequency band differences of the digital response feedback signal, and obtaining multiple frequency band power energy ratios; Taking the dynamic time sequence as the context clue track, the context clue track is tracked according to the frequency band power energy ratio to perform feature normalization organization on the frequency band power energy value of each wavelet sub-band to form the hidden detection feature vector of the digital response feedback signal; Based on big data, the accurate detection feature vector of the detection object type is obtained, and the degree of consistency between the hidden detection feature vector and the accurate detection feature vector is calculated. If the degree of consistency is greater than the preset degree of consistency, 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.

8. 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 according to any one of claims 1 to 7, comprising: 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 division unit, a coil driver IC unit, and an inductor coil unit, and 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 collect several discrete response signals of the target underground pipeline and perform mixing and filtering processing to improve the signal-to-noise ratio; Intelligent signal analysis module: The intelligent signal analysis module is responsible for frequency band calculation of 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 according to the detection results.

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