Application of transient Rayleigh wave in detection of tunnel lining void area

Transient Rayleigh wave detection is a high-precision nondestructive detection method.At present,it has been widely used in shallow exploration,but rarely used in tunnel lining quality detection.Through the tunnel lining physical model experiment,the layout defects of the double-layer reinforcement lining area were detected and the Rayleigh wave velocity profile and dispersion curve were analyzed after data process-ing,which finally verified the feasibility and accuracy of Rayleigh wave method in detecting the tunnel lining void area.The results show that the method is not affected by the reinforcement inside the lining,the shallow detection is less disturbed and the accuracy is higher,and the data will fluctuate slightly with the deepening of the detection depth.At the same time,this method responds quite accurately to the thickness of the concrete,allowing for the assessment of the tunnel lining’s lack of compactness.This method has high efficiency,good reliability,and simple data processing,and is suitable for nondestructive detection of internal defects of tun-nel lining structure.

Numerical Simulation Research on Response Characteristics of Grouting Defects of Ground Penetrating Radar for Detection of Grouting Quality behind Tunnel Wall

The effect of grouting behind tunnel wall directly affects the surrounding ground settlement and the stability of tunnel structure,so the grouting quality detection is very necessary.As an efficient and convenient shallow geophysical exploration method,ground-penetrating radar can meet the high-resolution and non-destructive requirements of grouting quality detection behind the tunnel wall,so it is widely used in engineering in recent years.Most of the existing studies have obvious regional pertinence and special geological conditions,and there are few universal studies on the characteristics of the ground penetrating radar reflection image of the grouting defect behind the tunnel wall.In view of this,this paper uses the finite difference time domain method to simulate several grouting defects behind the wall,such as voids,water-bearing anomaly,cracks,and other grouting defects.The simulation results show that the reflection image of the direct wave is characterized by a white band with strong amplitude;the interface between primary support and second lining,primary support,and surrounding rock is also banded;the circular cavity and water anomaly characteristics are all hyperbolic,the difference is that the phase of the lower part of the radar image of the cavity anomaly is 0,and there are only hyperbolic tails on both sides,and the water-bearing anomaly also has obvious hyperbolic characteristics at each interface;the reflected wave characteristics of the rectangular crack are striped and watery and the reflected wave characteristic of rectangular cracks is striped,and the abnormal range of water-bearing cracks on the radar image is larger than that of air.The research results can provide an effective theoretical reference for the engineering application of ground penetrating radar detection of grouting defects behind the tunnel wall.

Food Safety Detection Methods Applied to National Special Rectification of Product Quality and Food Safety

Afour-month period of national special rectification for product quality and food safety officially started on August 25, and was focused on eight fields, including those of agricultural products and processed foods.……

Promising real-time fruit and vegetable quality detection technologies applicable to manipulator picking process

In recent years,worldwide research on fruit and vegetable quality detection technology includes machine vision,spectroscopy,acoustic vibration,tactile sensors,etc.These technologies have also been gradually applied to fruit and vegetable grading and sorting lines in recent years,greatly improving the income of farmers.There have been numerous reviews of these techniques.Most of the published research on fruit and vegetable quality detection technology is still carried out in the laboratory.The emphases have been on quality feature extraction,model establishment and experimental verification.The successful application in the fruit and vegetable sorting production line proves that these studies have high application potential and value,and we look forward to the performance of these sensing technologies in the fruit and vegetable picking field.Therefore,in this paper,based on the future highly automated fruit and vegetable picking mode,we will focus on three kinds of fruit and vegetable quality detection technologies including machine vision,tactile sensor and spectroscopy,to provide some reference for future research.Since there are currently limited cases of detecting quality during the fruit and vegetable picking,experiments performed on prototypes of manipulator,or devices such as Nanocilia sensors,portable spectrometers,etc.,which are compact and convenient to mount on manipulator will be reviewed.Several tables and mosaics showing the performance of the three technologies in the detection of fruit and vegetable quality over the past five years have been listed.The performance of each sensing technology was relatively satisfactory in the laboratory in general.However,in the picking scenario,there are still many challenges to be solved.Different from industrial environments,agricultural scenarios are complex and changeable.Fragile and vulnerable agricultural products pose another challenge.The development of portable devices and nanomaterials have become important breakthroughs.Optical and tactile detection methods,as well as the integration of different quality detection methods,are expected to be the trends of research and development.

Research on Infrared Image Fusion Technology Based on Road Crack Detection

This study aimed to propose road crack detection method based on infrared image fusion technology.By analyzing the characteristics of road crack images,this method uses a variety of infrared image fusion methods to process different types of images.The use of this method allows the detection of road cracks,which not only reduces the professional requirements for inspectors,but also improves the accuracy of road crack detection.Based on infrared image processing technology,on the basis of in-depth analysis of infrared image features,a road crack detection method is proposed,which can accurately identify the road crack location,direction,length,and other characteristic information.Experiments showed that this method has a good effect,and can meet the requirement of road crack detection.

Application of Ground Penitrating Radar Method in Pipe Laying Detection

Ground Penetrating Radar method was used in detecting the flaws of underground pipeline. The GPR layer disturbing image was summarized by using a rational method in fieldwork and the in-door interpretation of data. The mark radar images of disturbance of slight, middle, and strong were obtained. The result shows that the radar method can not only determine the position of the concrete pipeline underground, but it can detect the laying quality of pipeline as well.

超声技术在混凝土离析检测中的应用

1超声测缺和测强原理超声测缺的基本原理:超声波在不同的介质中传播时,将产生反射、折射、散射、绕射和衰减等现象,使得由接收换能器上接收的超声波信号的声时、振幅、波形或频率发生了相应的变化,测定这些变化就可以判定混凝土材料某些方面的性质和结构内部构造的情况。如图1所示。

A Hardware Trojan Detection Method Based on the Electromagnetic Leakage

Hardware Trojan(HT) refers to a special module intentionally implanted into a chip or an electronic system. The module can be exploited by the attacker to achieve destructive functions. Unfortunately the HT is difficult to detecte due to its minimal resource occupation. In order to achieve an accurate detection with high efficiency, a HT detection method based on the electromagnetic leakage of the chip is proposed in this paper. At first, the dimensionality reduction and the feature extraction of the electromagnetic leakage signals in each group(template chip, Trojan-free chip and target chip) were realized by principal component analysis(PCA). Then, the Mahalanobis distances between the template group and the other groups were calculated. Finally, the differences between the Mahalanobis distances and the threshold were compared to determine whether the HT had been implanted into the target chip. In addition, the concept of the HT Detection Quality(HTDQ) was proposed to analyze and compare the performance of different detection methods. Our experiment results indicate that the accuracy of this detection method is 91.93%, and the time consumption is 0.042s in average, which shows a high HTDQ compared with three other methods.

Research on modeling method of continuous spectrum water quality online detection based on random forest

It's common to use the method of continuous spectroscopy in water quality testing. But there're some problems with it. For example, the scanning results have a large number of nonlinear signals, and the covariance between variables is serious, which can lead to a decrease in the model prediction accuracy. In this paper, the standard solutions of nitrate nitrogen(NO_(3)-N) and nitrite nitrogen(NO_(2)-N) were used as the subject to be tested, and the data of the scanned waves and absorbance were obtained by use of spectral detector. The data were processed by noise reduction first and then the random forest(RF) algorithm was adopted to establish the regression relationship between concentration and absorbance. For comparison, partial least squares(PLS) and support vector machine(SVM) algorithm models were also established. For the same given data, the three reverse models can make the projection of the concentration respectively. The experimental results show that the RF algorithm predicts NO_(2)-N concentrations significantly better than the SVM algorithm and PLS algorithm. This proves that the RF algorithm has good prediction ability in spectral water quality detection because of its high model accuracy and better adaptability, which could be a reference for similar research on continuous spectral water quality online detection.

Cucumber appearance quality detection under complex background based on image processing

Cucumber fruit appearance quality is an important basis of growth status.In order to improve the quality detection accuracy and processing efficiency of cucumber color image under complicated background,an improved GrabCut algorithm was proposed to extract the cucumber boundary.Firstly,including pixel size normalization,rectangular box set and scale image resolution,pretreatments of cucumber image were adopted to reduce the iteration times and operation time of GrabCut algorithm.Then,the Gaussian mixture model was chosen to find out the possible prospect of target region and background region in the preprocessed rectangular frame on the preliminary modeling.Meanwhile,by the optimization of K-means cluster to the initial GMM model,the effective target area was extracted.Finally,the whole image noise and serrated boundary was removed by morphological operations to segment the outline of the complete target prospects with appropriate structure size.And then the cucumber appearance quality detection instrument was designed to extract the texture and shape features exactly,so that it could obtain cucumber appearance quality and evaluate its growth effectively.With the segmentation experiments by almost 300 cucumber original images from greenhouse in Shandong Province,the results showed that the improved GrabCut algorithm could effectively extract the complete and smooth boundary of cucumber.With relatively high segmentation evaluation index,the precision was 93.88%,the recall rate was 99.35%,the F-Measure reached 96.53%,and the misclassification error was controlled at minimum 5.84%.The average running time was shortened to 1.4023 s.The comparison results showed that the improved GrabCut algorithm was the best,followed by the SLIC and traditional GrabCut method.Cucumber appearance quality detection instrument could also extract more accurate feature parameters.And it could meet the basic growth condition assessment by automatic image processing.

A new method of rapid quality detection of vacuum insulation panels

A new method of measuring gas pressure in vacuum insulation panels(VIPs)is reported in this study,which provides a fast and efficient quality control option of production.Although there are different methods of measuring gas pressure for VIPs,connecting an internal measurement gauge to external data acquisition units is problematic.The thin high barrier film covering the panel’s core usually prevents external electrical wires or mechanical devices being connected to the inside of the VIPs.To solve this problem,a micro capacitive pressure sensor with 0 to 250 Pa detection range is developed to detect the vacuum pressure.The sensor has high linearity and a sensitivity of 10 mV/Pa.Moreover,through the communication mode study,an ultrasound communications system for VIPs is designed.It shows from operation that this system is stable and reliable,and quick for communication speed.This new method enables the quality detection of VIPs to be completed within 1 second.The minimum detectable pressure of VIPs is below 1 Pa,and the measurement error can be controlled around 5%.