Acoustic Non-Destructive Testing Technology in Concrete Bridge Inspection and Pile Foundation Detection

This article takes the actual construction project of a certain concrete bridge project as an example to analyze the application of acoustic non-destructive testing technology in its detection.It includes an overview of a certain bridge construction project studied and acoustic non-destructive testing technology and the application of acoustic non-destructive testing technology in actual testing.This analysis hopes to provide some guidelines for acoustic non-destructive testing of modern concrete bridge projects.

Detecting Photoacoustic Signals of Sulfur Hexafluoride at Varying Microphone Positions

Photoacoustic spectroscopy was used to test the photoacoustic properties of sulfur hexafluoride, an optically thick and potent greenhouse gas. While exploring the photoacoustic effect of sulfur hexafluoride, the effects of the position of the microphone within a gas cell were determined. Using a 35 cm gas cell, microphones were positioned at 17.5 cm, the middle of the gas cell, 12.5 cm, 7.5 cm, and 2.5 cm from the window of the cell. From the photoacoustic signal produced for each resonance frequency at each microphone position, the effects of acoustic pressure produced at each position on the signal recorded were observed. This is the first study done by experimentation with the photoacoustic effect to show that standing waves have different amplitudes at different microphone positions.

Passive Acoustic Radar for Detecting Supersonic Cruise Missile

A Passive Acoustic Radar is presented as a necessary complement to electromagnetic wave radar, which will be expected to be an effective means for detecting cruise missiles. Acoustic characteristics of supersonic flying projectiles with diverse shapes are expounded via experiment. It is pointed out that simulation experiment could be implemented using bullet or shell instead of cruise missile. Based on theoretical analysis and experiment, the "acoustic fingerprint" character of cruise missile is illustrated to identify it in a strong noise environment. After establishing a locating mathematical model,the technique of acoustic embattling is utilized to resolve a problem of confirming the time of early-warning, considering the fact that velocity of sound is much slower than that of light. Thereby, a whole system of passive acoustic radar for detecting supersonic cruise missile is formed.

Fracture identification based on remote detection acoustic reflection logging

Fracture identification is important for the evaluation of carbonate reservoirs. However, conventional logging equipment has small depth of investigation and cannot detect rock fractures more than three meters away from the borehole. Remote acoustic logging uses phase-controlled array-transmitting and long sound probes that increase the depth of investigation. The interpretation of logging data with respect to fractures is typically guided by practical experience rather than theory and is often ambiguous. We use remote acoustic reflection logging data and high-order finite-difference approximations in the forward modeling and prestack reverse-time migration to image fractures. First, we perform forward modeling of the fracture responses as a function of the fracture-borehole wall distance, aperture, and dip angle. Second, we extract the energy intensity within the imaging area to determine whether the fracture can be identified as the formation velocity is varied. Finally, we evaluate the effect of the fracture-borehole distance, fracture aperture, and dip angle on fracture identification.

Regression-Based Method of Acoustic Detection

Based on the signal detection theory. a target detection method with the regression calculation which is easily achieved by computer software or hardware was developed in order to insure the acoustic detection system working with high detection possibility and under the condition of low signal to noise ratio. Meanwhile. the physical implication of detection formula wsa discussed and computer result was shown.

Acoustic Emission Recognition Based on a Three-Streams Neural Network with Attention

Acoustic emission(AE)is a nondestructive real-time monitoring technology,which has been proven to be a valid way of monitoring dynamic damage to materials.The classification and recognition methods of the AE signals of the rotor are mostly focused on machine learning.Considering that the huge success of deep learning technologies,where the Recurrent Neural Network(RNN)has been widely applied to sequential classification tasks and Convolutional Neural Network(CNN)has been widely applied to image recognition tasks.A novel three-streams neural network(TSANN)model is proposed in this paper to deal with fault detection tasks.Based on residual connection and attention mechanism,each stream of the model is able to learn the most informative representation from Mel Frequency Cepstrum Coefficient(MFCC),Tempogram,and short-time Fourier transform(STFT)spectral respectively.Experimental results show that,in comparison with traditional classification methods and single-stream CNN networks,TSANN achieves the best overall performance and the classification error rate is reduced by up to 50%,which demonstrates the availability of the model proposed.

Object Detection and Tracking Method of AUV Based on Acoustic Vision

This paper describes a new framework for object detection and tracking of AUV including underwater acoustic data interpolation, underwater acoustic images segmentation and underwater objects tracking. This framework is applied to the design of vision-based method for AUV based on the forward looking sonar sensor. First, the real-time data flow （underwater acoustic images） is pre-processed to form the whole underwater acoustic image, and the relevant position information of objects is extracted and determined. An improved method of double threshold segmentation is proposed to resolve the problem that the threshold cannot be adjusted adaptively in the traditional method. Second, a representation of region information is created in light of the Gaussian particle filter. The weighted integration strategy combining the area and invariant moment is proposed to perfect the weight of particles and to enhance the tracking robustness. Results obtained on the real acoustic vision platform of AUV during sea trials are displayed and discussed. They show that the proposed method can detect and track the moving objects underwater online, and it is effective and robust.

Acoustic wave detection of laser shock peening

In order to overcome the existing disadvantages of offline laser shock peening detection methods, an online detection method based on acoustic wave signals energy is provided. During the laser shock peening, an acoustic emission sen- sor at a defined position is used to collect the acoustic wave signals that propagate in the air. The acoustic wave signal is sampled, stored, digitally filtered and analyzed by the online laser shock peening detection system. Then the system gets the acoustic wave signal energy to measure the quality of the laser shock peening by establishing the correspondence between the acoustic wave signal energy and the laser pulse energy. The surface residual stresses of the samples are measured by X-ray stress analysis instrument to verify the reliability. The results show that both the surface residual stress and acoustic wave signal energy are increased with the laser pulse energy, and their growth trends are consistent. Finally, the empirical formula between the surface residual stress and the acoustic wave signal energy is established by the cubic equation fitting, which will provide a theoretical basis for the real-time online detection of laser shock peening.

Using acoustic technique to detect leakage in city gas pipelines

For solving the difficult problem of leakage detection in city gas pipelines, a method using acoustic technique based on instantaneous energy (IE) distribution and correlation analysis was proposed. Firstly, the basic theory of leakage detection and location was introduced. Then the physical relationship between instantaneous energy and structural state variation of a system was analyzed theoretically. With HILBERT-HUANG transformation (HHT), the instantaneous energy distribution feature of an unstable acoustic signal was obtained. According to the relative contribution method of the instantaneous energy, the noise in signal was eliminated effectively. Furthermore, in order to judge the leakage, the typical characteristic of the instantaneous energy of signal in the input and output end was discussed using correlative analysis. A number of experiments were carried out to classify the leakage from normal operations, and the results show that the leakages are successfully detected and the average recognition rate reaches 93.3% among three group samples. It is shown that the method using acoustic technique with IED and correlative analysis is effective and it may be referred in other pipelines.

Leak Detection of Gas Pipelines Based on Characteristics of Acoustic Leakage and Interfering Signals

When acoustic method is used in leak detection for natural gas pipelines,the external interferences including operation of compressor and valve,pipeline knocking,etc.,should be distinguished with acoustic leakage signals to improve the accuracy and reduce false alarms.In this paper,the technologies of extracting characteristics of acoustic signals were summarized.The acoustic leakage signals and interfering signals were measured by experiments and the characteristics of time-domain,frequency-domain and time-frequency domain were extracted.The main characteristics of time-domain are mean value,root mean square value,kurtosis,skewness and correlation function,etc.The features in frequency domain were obtained by frequency spectrum analysis and power spectrum density,while time-frequency analysis was accomplished by short time Fourier transform.The results show that the external interferences can be removed effectively by the characteristics of time domain,frequency domain and time-frequency domain.It can be drawn that the acoustic leak detection method can be applied to natural gas pipelines and the characteristics can help reduce false alarms and missing alarms.

Numerical analysis of the resonance mechanism of the lumped parameter system model for acoustic mine detection

The method of numerical analysis is employed to study the resonance mechanism of the lumped parameter system model for acoustic mine detection. Based on the basic principle of the acoustic resonance technique for mine detection and the characteristics of low-frequency acoustics, the “soil-mine” system could be equivalent to a damping “mass-spring” resonance model with a lumped parameter analysis method. The dynamic simulation software, Adams, is adopted to analyze the lumped parameter system model numerically. The simulated resonance frequency and anti-resonance frequency are 151 Hz and 512 Hz respectively, basically in agreement with the published resonance frequency of 155 Hz and anti-resonance frequency of 513 Hz, which were measured in the experiment. Therefore, the technique of numerical simulation is validated to have the potential for analyzing the acoustic mine detection model quantitatively. The influences of the soil and mine parameters on the resonance characteristics of the soil–mine system could be investigated by changing the parameter setup in a flexible manner.

Acoustic emission detection of slag performance in coal gasifiers

This work first investigated the detection of slags,slag pool liquid level,and slag accumulation height in laboratory scale based on acoustic emission(AE)detection,and further tried the feasibility of this method in an industrial scale coal gasifier.Results show that the energy and variance of acoustic signals can realize the accurate detection of large slag(criterion:E>1.5 E0,S>1.2 S0),and the average relative error is only 0.28%.The acoustic energy in the frequency range of 20–40 k Hz is defined as the characteristic energy,which can realize the accurate detection of slag accumulation height and slag pool liquid level,and the average relative error is only 3.94%.Furthermore,AE detection also realize accurate detection of large slag in an industrial scale gasifier and the acoustic signals at slag screen can be used to realize the early warning of the slag collapse(5 h earlier).

Research on Electromagnetic Acoustic Emission Signal Recognition Based on Local Mean Decomposition and Least Squares Support Vector Machine

Electromagnetic acoustic emission technology is one of nondestructive testing, which can be used for defect detection of metal specimens. In this study, round and cracked metal specimens, round metal specimens, and intact metal specimens were prepared. And the electromagnetic acoustic emission signals of the three specimens were collected. In addition, the local mean decomposition(LMD), Autoregressive model(AR model) and least squares support vector machine (LSSVM) algorithms were combined to identify the eletromagnetic acoustic emission signals of round and cracked, round, and intact specimens. According to the algorithm recognition results, the recognition accuracy of can reach above 97.5%, which has a higher recognition rate compared with SVM and BP neural network. The results of the study show that the algorithm is able to identify quickly and accurately crack defect in metal specimens.

RLS and LMS blind adaptive multi-user detection method and comparison in acoustic communication

RLS and LMS blind adaptive multi-user detection algorithm and multi-user detector was proposed to solve the problem of multi-user signal detection problem encountered in underwater acoustic communication networks.In simulation analysis,RLS and the LMS blind adaptive multi-user detector were designed and tested for synchronous and asynchronous multi-user communication process.The results of SIR comparison and MMSE comparison show that,both of the two methods can realize blind adaptive detection when any user change in multi-user communication,during this process,the training communication sequences are not needed.The RLS algorithm has about 5 dB higher in SIR compared with LMS algorithm,and the convergence velocity of RLS algorithm is also higher than LMS algorithm when the communication users change.RLS algorithm has better ability in multi-user detection than that of LMS algorithm,and it has great attraction and guiding significance for solving the problem of multiple access interference(MAI) in multi-user communication.

Influence of roughness on the detection of mechanical characteristics of low-k film by the surface acoustic waves

The surface acoustic wave （SAW） technique is a precise and nondestructive method to detect the mechanical charac- teristics of the thin low dielectric constant （low-k） film by matching the theoretical dispersion curve with the experimental dispersion curve. In this paper, the influence of sample roughness on the precision of SAW mechanical detection is inves- tigated in detail. Random roughness values at the surface of low-k film and at the interface between this low-k film and the substrate are obtained by the Monte Carlo method. The dispersive characteristic of SAW on the layered structure with rough surface and rough interface is modeled by numerical simulation of finite element method. The Young＇s moduli of the Black DiamondTM samples with different roughness values are determined by SAWs in the experiment. The results show that the influence of sample roughness is very small when the root-mean-square （RMS） of roughness is smaller than 50 nm and correlation length is smaller than 20 μm. This study indicates that the SAW technique is reliable and precise in the nondestructive mechanical detection for low-k films.

Defect detection in brazed weldment with lattice structure using acoustic shadow technique

Brazed weldment with lattice structure has been widely used in aerospace industry. The non-destructive testing is often difficult because of the poor inspection accessibility. The present paper illustrates how the plane-like defect lack of brazing can be detected rapidly in this kind of structure by using ultrasonic Lamb wave. Experimental weldments are prepared and weld defect are tested using S2 mode Lamb wave. Acoustic shadow technique is employed based on Lamb wave testing method. The character of the tested D-scan image and A-scan signal is studied. The experimental results show that acoustic shadow based Lamb wave testing method is effective in detecting through-wall lack of brazing. Meanwhile, the D-scan tested data can be rapidly collected and easily interpreted compared with pulse echo bused Lamb wave testing method.

Arbitrary acoustic orbital angular momentum detection using dual-layer metasurfaces

Orbital angular momentum(OAM),with its unique physical properties and vast application prospects,has attracted widespread attention in various fields.Nonetheless,the development of valid and practical acoustic OAM detection methods continues to be a challenging endeavor.In this paper,we propose a novel construction method of dual-layer metasurfaces to achieve a doubleconversion process for the waveform reshaping and differentiated focusing of two-dimensional vortex sources with different OAMs.Specifically,by utilizing a concise formula,a one-to-one correspondence is established between the OAM of incident vortex waves and different imaging points.The fundamental principle of this special conversion relationship is rigorously constrained by the directional compensation of phase and the material parameters of dual-layer metasurfaces with different quadratic phase distributions.More importantly,the highly consistent results between numerical demonstrations and acoustic experiments further confirm the feasibility and effectiveness of the proposed OAM detection scheme.Our work provides a new perspective on the precise manipulation for the phase of vortex fields,holding potential applications in super-resolution imaging and the design of acoustic OAM-based devices.

3D Characteristic Diagram of Acoustically Induced Surface Vibration with Different Landmines Buried

The 3D characteristic diagram of acoustically induced surface vibration was employed to study the influence of different buried landmines on the acoustic detection signal. By using the vehicular experimental system for acoustic landmine detection and the method of scanning detection, the 3D characteristic diagrams of surface vibration were measured when different objects were buried underground, including big plastic landmine, small plastic landmine, big metal landmine and bricks. The results show that, under the given conditions, the surface vibration amplitudes of big plastic landmine, big metal landmine, small plastic landmine and bricks decrease in turn. The 3D characteristic diagrams of surface vibration can be used to further identify the locations of buried landmines.

Feature Extraction for Acoustic Scattering from a Buried Target

Elastic acoustic scattering is important for buried target detection and identification. For elastic spherical objects, studies have shown that a series of narrowband energetic arrivals follow the first specular one. However, in practice, the elastic echo is rather weak because of the acoustic absorption, propagation loss, and reverberation, which makes it difficult to extract elastic scattering features, especially for buried targets. To remove the interference and enhance the elastic scattering, the de-chirping method was adopted here to address the target scattering echo when a linear frequency modulation (LFM) signal is transmitted. The parameters of the incident signal were known. With the de-chirping operation, a target echo was transformed into a cluster of narrowband signals, and the elastic components could be extracted with a band-pass filter and then recovered by remodulation. The simulation results indicate the feasibility of the elastic scattering extraction and recovery. The experimental result demonstrates that the interference was removed and the elastic scattering was visibly enhanced after de-chirping, which facilitates the subsequent resonance feature extraction for target classification and recognition.

Simulation on the Models of Small Scale Passive Acoustic Sensor Arrays Based on Time-Delay Estimation Method

The passive acoustic localization with planar sensor array is introduced. Based on a method to eliminate the influence of effective sound velocity in passive detection, a new five-sensors solid array and its localization model are put forward. The factors that influence the precision of the localization are analyzed. Considering the errors from the factors synchronously, the simulation compares the solid array with the planar array. It can be proved that the five-sensor solid array is better than the four-sensor planar array in the estimation of bearing elements.