CN-122017037-A - Elastic wave tomography detection method for embankment quality

CN122017037ACN 122017037 ACN122017037 ACN 122017037ACN-122017037-A

Abstract

The invention discloses a dike quality elastic wave tomography detection method which comprises the steps of synchronously obtaining a source end reference signal at a vibration source of a road roller and a ground surface response signal of the surface of a detected area, establishing a unified time reference of the source end reference signal and the ground surface response signal, calculating a cross-correlation function of the source end reference signal and the ground surface response signal, and determining rough estimated arrival time based on a peak value. And extracting characteristic frequency components from the signals, acquiring phase information of the analysis signals, calculating phase difference of the earth surface response signals relative to the source end reference signals at the time of coarse estimation, and determining a fine time correction amount by utilizing the phase difference. And correcting the rough estimated arrival time by using the fine time correction quantity to obtain the final elastic wave arrival time and inverting to generate an elastic wave velocity distribution image. The invention breaks through the limitation of the sampling rate on the measurement precision by collecting the real source end waveform and combining the phase refinement technology, and improves the resolution and reliability of compaction quality detection.

Inventors

HE XIANWU
LIU YANZE
WANG YULEI
ZHANG ZHONGSHUN
YE XINYING
TANG CHAO
LI CUNXIN
CHEN DAXI
YAO YETING
LU WEIHUA
LIU ZHIHAO
ZHANG SHENGXING
XU YOU
YI CHENGLIANG
GUO CHENWEI
XU CHANGDONG
TANG LEI
CHEN CHEN
CHEN WEIYUN
CHEN SUMING

Assignees

水利部交通运输部国家能源局南京水利科学研究院
浙江省水利防汛技术中心(浙江省水利防汛机动抢险总队)

Dates

Publication Date: 20260512
Application Date: 20260416

Claims (10)

1. The method for detecting the dike quality elastic wave tomography is characterized by comprising the following steps of: Synchronously acquiring a source end reference signal at a vibration source of a road roller and a ground surface response signal of the surface of a region to be tested, and establishing a unified time reference of the source end reference signal and the ground surface response signal; Calculating a cross-correlation function of a source end reference signal and a ground surface response signal, and determining a rough estimated arrival time based on a peak value of the cross-correlation function; respectively extracting at least one characteristic frequency component from a source end reference signal and a ground surface response signal, and acquiring analysis signal phase information corresponding to each characteristic frequency component; Calculating the phase difference of the earth surface response signal relative to the source end reference signal at the time of coarse estimation based on the phase information of the analytic signal, and determining a fine time correction amount by utilizing the phase difference; and correcting the rough estimated arrival time by using the fine time correction amount to obtain final elastic wave arrival time, and inverting to generate an elastic wave velocity distribution image of the detected region based on a plurality of final elastic wave arrival times.
2. The method of claim 1, wherein the source side reference signal is a vibratory acceleration signal; Acquiring a source end reference signal at a vibration source of a road roller comprises: and acquiring vibration acceleration signals in real time through an acceleration sensor arranged at a vibration drum bearing seat of the road roller, wherein the sampling frequency of the acceleration sensor is more than 10 times of the fundamental frequency of a vibration source.
3. The method of claim 2, wherein establishing a uniform time reference for the source reference signal and the surface response signal comprises: performing anti-aliasing filtering treatment on the acquired source end reference signal, and performing data compression on the treated signal by using differential pulse code modulation to obtain a compressed reference waveform; Performing spectrum analysis on a source end reference signal, determining the current vibration fundamental frequency, and broadcasting a synchronous data frame according to a preset period, wherein the synchronous data frame comprises a compression reference waveform, a time stamp of the current reference signal and current vibration fundamental frequency parameters; And receiving the synchronous data frame, analyzing the compressed reference waveform, decoding the compressed reference waveform to reconstruct the source end reference signal, and mapping the time axis of the source end reference signal to a local time system based on the time stamp.
4. The method of claim 1, wherein calculating a cross-correlation function of the source reference signal and the surface response signal, determining a coarse estimate based on a peak value of the cross-correlation function, comprises: Removing direct current components of a source end reference signal and a ground surface response signal respectively, and filtering out-of-band noise by using a band-pass filter; calculating a normalized cross-correlation function of the preprocessed source-end reference signal and the ground surface response signal; searching the maximum value of the normalized cross-correlation function in a preset searching time window, and determining the corresponding time delay as coarse estimated arrival time.
5. The method of claim 1, wherein obtaining the resolved signal phase information for each characteristic frequency component comprises: filtering the source end reference signal and the earth surface response signal respectively by utilizing a narrow-band filter with the center frequency corresponding to the characteristic frequency component; hilbert transformation is carried out on the filtered signals, and complex-form analysis signals are constructed; Based on the real and imaginary parts of the analytic signal, the instantaneous phase over time is calculated as analytic signal phase information.
6. The method of claim 5, wherein the characteristic frequency component comprises a fundamental vibration frequency; Calculating a phase difference of the surface response signal relative to the source side reference signal at the time of the coarse estimation based on the resolved signal phase information, and determining a fine time correction amount using the phase difference, comprising: Obtaining an observation phase of a ground surface response signal at the rough estimated arrival time and a reference phase of a source end reference signal at the initial moment; calculating the difference value between the observed phase and the reference phase, and normalizing the difference value to be in a vibration period to obtain a phase difference; The fine time correction is calculated using the formula Δτ=ΔΦ/2ρf 0 , where Δτ is the fine time correction, ΔΦ is the phase difference, and f 0 is the fundamental vibration frequency.
7. The method as recited in claim 5, further comprising: The characteristic frequency component comprises a vibration fundamental frequency and at least one higher harmonic component with the frequency being integral multiple of the vibration fundamental frequency; based on the resolved signal phase information, calculating a phase difference of the surface response signal relative to the source reference signal at the time of the coarse estimation, comprising: And respectively calculating the difference value between the observed phase of the earth surface response signal at the rough estimation arrival time and the reference phase of the source end reference signal at the starting moment for each characteristic frequency component to obtain a multi-frequency phase difference set corresponding to different frequencies.
8. The method of claim 7, wherein determining the fine time correction using the phase difference comprises: Constructing a multi-frequency consistency cost function for representing the consistency degree between the estimated phase corresponding to the candidate time correction quantity and each observed value in the multi-frequency phase difference set; searching candidate time correction quantity in a preset range with rough estimated time as a center, and determining the candidate time correction quantity which enables the multi-frequency consistency cost function to reach the minimum value as a fine time correction quantity.
9. The method of claim 8, wherein constructing the multi-frequency consistency cost function and searching for candidate time corrections comprises: According to the spectrum analysis result of the source end reference signal, determining the signal-to-noise ratio of each characteristic frequency component, and distributing weight factors for each phase deviation item in the multi-frequency consistency cost function according to the signal-to-noise ratio; Constructing a discrete candidate time correction quantity set in a preset range by taking a vibration period corresponding to the vibration fundamental frequency as a step length; and calculating the multi-frequency consistency cost function value corresponding to each element in the candidate time correction set to find a weighted consistency minimum value.
10. The method of claim 1, wherein generating an elastic wave velocity profile image of the region under test based on a plurality of final elastic wave arrival time inversions comprises: According to the space position coordinates corresponding to the source end reference signals and the earth surface response signals, meshing the area to be detected, and constructing a ray path matrix; calculating a theoretical arrival time based on the initial velocity model by utilizing a joint iterative reconstruction technology; and calculating the residual error between the final arrival time and the theoretical arrival time, and back projecting the residual error to each grid unit by utilizing the ray path matrix to update the speed model until iteration converges to obtain an elastic wave speed distribution image.

Description

Elastic wave tomography detection method for embankment quality Technical Field The invention relates to the technical field of geotechnical engineering nondestructive testing and digital construction, in particular to a dike quality elastic wave tomography detection method. Background The compaction quality of the embankment subgrade determines the stability and service life of the traffic infrastructure, and the method has important engineering significance for high-precision and full-coverage detection of the compaction degree. The traditional detection means such as a sand filling method or a nuclear densitometer have the limitations of large destructiveness, sparse measuring points, low efficiency, radiation risk and the like. Continuous vibration generated by the road roller in the construction process is used as an elastic wave excitation source, and is matched with a distributed intelligent sensing network to perform tomography, so that continuous monitoring of the ground structure of the rolling area can be realized on the premise of not interrupting construction, and key data support is provided for digital construction quality control. The current collaborative monitoring technology mainly adopts a passive source detection mode, namely, an elastic wave signal is acquired through a detector array deployed on a road surface, and a cross-correlation technology is utilized to extract propagation time. In prior art solutions, it is generally assumed that the vibration signal of the road roller is an ideal single-frequency sine wave, or that the theoretical reference signal is generated only as a function of the set nominal frequency. The processing system carries out cross-correlation operation on the collected earth surface vibration signals and the theoretical reference signals, determines the arrival time of elastic waves by searching the peak time of a cross-correlation function, and inverts the wave velocity distribution of the underground by using a travel time tomography algorithm. However, the accuracy of the time-in-flight measurement and the imaging resolution of the prior art are doubly limited by signal source distortion and discrete sampling limitations when facing complex construction environments. In particular, the vibration of an actual road roller is not an ideal sine wave, but a complex signal containing mechanical transmission harmonic waves, frequency drift and amplitude modulation, if only an ideal waveform is taken as a reference, cross-correlation peak broadening and serious phase mismatch are caused, meanwhile, the traditional measurement resolution based on peak picking is limited by sampling frequency, for example, a distance error of about 150 mm corresponding to a1 millisecond sampling interval, the travel time difference of microsecond level is difficult to capture, and a single frequency model is difficult to effectively remove multipath effects and dispersion interference, so that a final inverted compactness image is difficult to accurately reflect a tiny structural defect. Disclosure of Invention The invention aims to provide a dike quality elastic wave tomography detection method for solving the problems in the prior art. The technical scheme is that the method for detecting the elastic wave tomography of the dike quality comprises the following steps: synchronously acquiring a source end reference signal at a vibration source of a road roller and a ground surface response signal of the surface of a region to be tested, and establishing a unified time reference of the source end reference signal and the ground surface response signal; calculating a cross-correlation function of a source end reference signal and a ground surface response signal, and determining a rough estimated arrival time based on a peak value of the cross-correlation function; respectively extracting at least one characteristic frequency component from a source end reference signal and a ground surface response signal, and acquiring analysis signal phase information corresponding to each characteristic frequency component; Calculating the phase difference of the earth surface response signal relative to the source end reference signal at the time of coarse estimation based on the phase information of the analytic signal, and determining a fine time correction amount by utilizing the phase difference; and correcting the rough estimated arrival time by using the fine time correction amount to obtain final elastic wave arrival time, and inverting to generate an elastic wave velocity distribution image of the detected region based on a plurality of final elastic wave arrival times. The method has the beneficial effects that the limitation of the sampling rate on the measurement precision is broken through by collecting the waveform of the real source end and combining the phase refinement technology, and the resolution and the reliability of compaction quality detection are improved. Drawings Fig. 1 i