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.

Wave‑Shaped Piezoelectric Nanofber Membrane Nanogenerator for Acoustic Detection and Recognition

With the rapid development of internet of things and wearable electronics,how to conveniently power uncountable sensors remains a huge challenge.Energy harvesting strategy is suggested to collect and convert environmental energies into electrical energy.Thereinto,piezoelectric polymers are utilized as fexible harvesters to convert mechanical energy.The latter widely distributes in both our daily life and industrial environment.Intrinsic piezoelectric property further drives piezoelectric polymers to construct fexible self-powered strain sensors.However,relatively low piezoelectric performance restricts their application in detection and conversion of weak mechanical excitations.Herein,wave-shaped 3D piezoelectric device was fabricated by embossing electrospun polyvinylidene fuoride nanofbers.This 3D structured device presents better longitudinal and transverse piezoelectric performance than usual fat-type one.This wave-shaped piezoelectric device was developed for acoustic detection and recognition with a frequency resolution better than 0.1 Hz.This wave-shaped device was capable of frequency spectrum analyses of various sound sources from human and animals and well presents its potential for future wearable acoustic sensors and transducers.

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).

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.

Research on Acoustic Localization Algorithm Based on Dual Four-Element Arrays

The passive acoustic locating technology is widely used in military fields. The traditional locating method with single array has low precision of distance estimation, but comparatively high precision of angle estimation. According to the characteristic, the algorithm for acoustic passive localization based on the azimuth angle and geometry position of the two arrays is derived to estimate the target distance, and the simulation for the factors that affect the localization precision also proceeds. The result of the simulation shows the precision of localization estimation with dual arrays is superior to that of single array, and the passive localization algorithm based on dual array can meet the practical demands.

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.

A feedback control method for phase signal demodulation in fber-optic hydrophones

In the realm of acoustic signal detection,the identification of weak signals,particularly in the presence of negative signal-to-noise ratios,poses a significant challenge.This challenge is further heightened when signals are acquired through fiber-optic hydrophones,as these signals often lack physical significance and resist clear systematic modeling.Conventional processing methods,e.g.,low-pass filter(LPF),require a thorough understanding of the effective signal bandwidth for noise reduction,and may introduce undesirable time lags.This paper introduces an innovative feedback control method with dual Kalman filters for the demodulation of phase signals with noises in fiber-optic hydrophones.A mathematical model of the closed-loop system is established to guide the design of the feedback control,aiming to achieve a balance with the input phase signal.The dual Kalman filters are instrumental in mitigating the effects of signal noise,observation noise,and control execution noise,thereby enabling precise estimation for the input phase signals.The effectiveness of this feedback control method is demonstrated through examples,showcasing the restoration of low-noise signals,negative signal-to-noise ratio signals,and multi-frequency signals.This research contributes to the technical advancement of high-performance devices,including fiber-optic hydrophones and phase-locked amplifiers.

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 analysis of acoustic emission sources for rail crack detection by the finite element method

The safety of rail is very important for the development of high speed railway, and it is necessary to investigate the features of inner cracks in rail. In order to obtain the features of Acoustic Emission （AE） sources of inner cracks in rail, AE sources with different types, depths and propagation distances are examined for crack in rail. The finite element method is utilized to model the rail with cracks and the results of experiment demonstrate the effectiveness of this model. Wavelet transform and Rayleigh-Lamb equations are utilized to extract the features of crack AE sources. The results illustrate that the intensity ratio among AE modes can identify the AE source types and the AE sources with different frequencies in rail. There are uniform AE mode features existing in the AE signals from AE sources in rail web, however AE signals from AE sources in rail head and rail base have the complex and unstable AE modes. Different AE source types have the different propagation features in rail. It is helpful to understand the rail cracks and detect the rail cracks based on the AE technique.

A rapid audio event detection method by adopting 2D-Haar acoustic super feature vector

For accuracy and rapidity of audio event detection in the mass-data audio pro- cessing tasks, a generic method of rapidly recognizing audio event based on 2D-Haar acoustic super feature vector and AdaBoost is proposed. Firstly, it combines certain number of con- tinuous audio frames to be an ＂acoustic feature image＂, secondly, uses AdaBoost.MH or fast Random AdaBoost feature selection algorithm to select high representative 2D-Haar pattern combinations to construct super feature vectors; thirdly, analyzes the commonality and differ- ences between subcategories, then extracts common features and reduces different features to obtain a generic audio event template, which can support the accurate identification of multi- ple sub-classes and detect and locate the specific audio event from the audio stream accurately. Experimental results show that the use of 2D-Haar acoustic feature super vector can make recog- nition accuracy 5% higher than ones that MFCC, PLP, LPCC and other traditional acoustic features yielded, and can make tile training processing 7 20 times faster and the recognition processing 5-10 times faster, it can even achieve an average precision of 93.38%, an average recall of 95.03% under the optimal parameter configuration found by grid method. Above all, it can provide an accurate and fast mass-data processing method for audio event detection.

Acoustic Signal Feature Extraction of Vehicle Targets

Acoustic signal feature extraction is an important part of target recognition. The mechanisms for producing acoustic signals and their propagation are analyzed to extract the features of the radiated noise from different targets. Analysis of the acoustic spectra of typical vehicle targets acquired outdoors shows that the vehicles can be classified based on the acoustic spectra and amplitudes.

Ultrasensitive broadband position-sensitive detector based on graphitic carbon nitride

As a typical two-dimensional material,graphitic carbon nitride(g-CN)has attracted great interest because of its distinctive electronic,optical,and catalytic properties.However,the absence of a feasible route toward large-area and high-quality films hinders its development in optoelectronics.Herein,high-quality g-CN films have been grown on Si substrate via a vapor-phase transport-assisted condensation method.The g-CN/Si heterojunction shows an obvious response to ultraviolet–visible-near infrared photons with a responsivity of 133 A·W−1,which is two orders of magnitude higher than the best value ever reported for g-CN photodetectors.A position-sensitive detector(PSD)has been developed using the lateral photovoltaic effect of the g-CN/Si heterojunction.The PSD shows a wide response spectrum ranging from 300 to 1,100 nm,and a position sensitivity and rise/decay time of 395 mV·mm−1 and 3.1/50μs,respectively.Moreover,the application of the g-CN/Si heterojunction photodetector in trajectory tracking and acoustic detection has been realized for the first time.This work unveils the potential of g-CN for large-area photodetectors,and prospects for their applications in trajectory tracking and acoustic detection.