Structural health monitoring is widely utilized in outdoor environments,especially under harsh conditions,which can introduce noise into the monitoring system.Therefore,designing an effective denoising strategy to enh...Structural health monitoring is widely utilized in outdoor environments,especially under harsh conditions,which can introduce noise into the monitoring system.Therefore,designing an effective denoising strategy to enhance the performance of guided wave damage detection in noisy environments is crucial.This paper introduces a local temporal principal component analysis(PCA)reconstruction approach for denoising guided waves prior to implementing unsupervised damage detection,achieved through novel autoencoder-based reconstruction.Experimental results demonstrate that the proposed denoising method significantly enhances damage detection performance when guided waves are contaminated by noise,with SNR values ranging from 10 to-5 dB.Following the implementation of the proposed denoising approach,the AUC score can elevate from 0.65 to 0.96 when dealing with guided waves corrputed by noise at a level of-5 dB.Additionally,the paper provides guidance on selecting the appropriate number of components used in the denoising PCA reconstruction,aiding in the optimization of the damage detection in noisy conditions.展开更多
Acoustic emission （AE） sensors are used to monitor tool conditions in micro-milling operations. Together with the microphone, the AE sensor can detect the tool breakage more accurately and more effectively by applyi...Acoustic emission （AE） sensors are used to monitor tool conditions in micro-milling operations. Together with the microphone, the AE sensor can detect the tool breakage more accurately and more effectively by applying the wavelet analysis. The processed tool breakage technique by AE sensor is used to perform the wavelet analysis on the experimental data. Results indicate the feasibility of using the AE signals for monitoring the tool condition in micro-milling.展开更多
To extract the cable forces due to dead load in cable-stayed bridges from the monitoring data,the effects of various factors are eliminated step by step by different statistical methods.The information of cable tensio...To extract the cable forces due to dead load in cable-stayed bridges from the monitoring data,the effects of various factors are eliminated step by step by different statistical methods.The information of cable tension sensors recorded by the health monitoring system of Nanjing No.3 Yangtze River Bridge is taken as an example. Temperature effects are eliminated by linear fitting analysis;a 5-level wavelet de-noising method is applied to eliminate the noise signal by the wavelet basis function of DB8.The rest cable force data is tested by the method of extreme-value type-Ⅲ distribution, and the fitted location parameter is selected as the cable force due to dead load.The results show that the cable force has a linear relationship with temperature. Sometimes, the temperature effect is significant.Noise effect accounts for a small percentage,and the vehicle loads effect has twice the temperature effect on the traffic volume in 2007. The calculation results of other stay cables verify the reliability and validity of the proposed method.展开更多
Aiming at the problem of on-line damage diagnosis in structural health monitoring （SHM）, an algorithm of feature extraction and damage alarming based on auto-regressive moving-average （ARMA） time series analysis i...Aiming at the problem of on-line damage diagnosis in structural health monitoring （SHM）, an algorithm of feature extraction and damage alarming based on auto-regressive moving-average （ARMA） time series analysis is presented. The monitoring data were first modeled as ARMA models, while a principalcomponent matrix derived from the AR coefficients of these models was utilized to establish the Mahalanobisdistance criterion functions. Then, a new damage-sensitive feature index DDSF is proposed. A hypothesis test involving the t-test method is further applied to obtain a decision of damage alarming as the mean value of DDSF had significantly changed after damage. The numerical results of a three-span-girder model shows that the defined index is sensitive to subtle structural damage, and the proposed algorithm can be applied to the on-line damage alarming in SHM.展开更多
基金National Science Foundation of Zhejiang under Contract(LY23E010001)。
文摘Structural health monitoring is widely utilized in outdoor environments,especially under harsh conditions,which can introduce noise into the monitoring system.Therefore,designing an effective denoising strategy to enhance the performance of guided wave damage detection in noisy environments is crucial.This paper introduces a local temporal principal component analysis(PCA)reconstruction approach for denoising guided waves prior to implementing unsupervised damage detection,achieved through novel autoencoder-based reconstruction.Experimental results demonstrate that the proposed denoising method significantly enhances damage detection performance when guided waves are contaminated by noise,with SNR values ranging from 10 to-5 dB.Following the implementation of the proposed denoising approach,the AUC score can elevate from 0.65 to 0.96 when dealing with guided waves corrputed by noise at a level of-5 dB.Additionally,the paper provides guidance on selecting the appropriate number of components used in the denoising PCA reconstruction,aiding in the optimization of the damage detection in noisy conditions.
基金Supported by the National Natural Science Foundation of China (50775114)the Natural Scienc Foundation of Jiangsu Province (BK2007198)~~
文摘Acoustic emission （AE） sensors are used to monitor tool conditions in micro-milling operations. Together with the microphone, the AE sensor can detect the tool breakage more accurately and more effectively by applying the wavelet analysis. The processed tool breakage technique by AE sensor is used to perform the wavelet analysis on the experimental data. Results indicate the feasibility of using the AE signals for monitoring the tool condition in micro-milling.
基金The National Natural Science Foundation of China(No.51208096)the Major Scientific and Technological Special Project of Jiangsu Provincial Communications Department(No.2014Y02)
文摘To extract the cable forces due to dead load in cable-stayed bridges from the monitoring data,the effects of various factors are eliminated step by step by different statistical methods.The information of cable tension sensors recorded by the health monitoring system of Nanjing No.3 Yangtze River Bridge is taken as an example. Temperature effects are eliminated by linear fitting analysis;a 5-level wavelet de-noising method is applied to eliminate the noise signal by the wavelet basis function of DB8.The rest cable force data is tested by the method of extreme-value type-Ⅲ distribution, and the fitted location parameter is selected as the cable force due to dead load.The results show that the cable force has a linear relationship with temperature. Sometimes, the temperature effect is significant.Noise effect accounts for a small percentage,and the vehicle loads effect has twice the temperature effect on the traffic volume in 2007. The calculation results of other stay cables verify the reliability and validity of the proposed method.
基金The National High Technology Research and Devel-opment Program of China (863Program) (No2006AA04Z416)the National Natural Science Foundation of China (No50538020)
文摘Aiming at the problem of on-line damage diagnosis in structural health monitoring （SHM）, an algorithm of feature extraction and damage alarming based on auto-regressive moving-average （ARMA） time series analysis is presented. The monitoring data were first modeled as ARMA models, while a principalcomponent matrix derived from the AR coefficients of these models was utilized to establish the Mahalanobisdistance criterion functions. Then, a new damage-sensitive feature index DDSF is proposed. A hypothesis test involving the t-test method is further applied to obtain a decision of damage alarming as the mean value of DDSF had significantly changed after damage. The numerical results of a three-span-girder model shows that the defined index is sensitive to subtle structural damage, and the proposed algorithm can be applied to the on-line damage alarming in SHM.
