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 lin...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.展开更多
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 Gr...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.展开更多
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 sha...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.展开更多
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 foo... 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.……展开更多
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 pr...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.展开更多
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 difficu...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.展开更多
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 covari...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.展开更多
基金Supported by Project of Natural Science Foundation of Jilin Province(No.20220101172JC).
文摘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.
基金This study was financially supported by the National Science and Technology Support Project(2014BAD04B05)Transformation and popularization project of agricultural scientific and technological achievements in Tianjin-“Integrated application of core information technology for early warning,diagnosis and prevention of greenhouse vegetable diseases”(201704070).
文摘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.
文摘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.
文摘 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.……
文摘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.
基金supported by the Special Funds for Basic Scientific Research Business Expenses of Central Universities No. 2014GCYY0the Beijing Natural Science Foundation No. 4163076the Fundamental Research Funds for the Central Universities No. 328201801
文摘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.
基金supported by the National Natural Science Foundation of China (No.51205005)the Beijing Science and Technology Innovation Service Ability Building (No.PXM2017-014212-000013)。
文摘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.
