Aerospace relay is one kind of electronic components which is used widely in national defense system and aerospace system. The existence of remainder particles induces the reliability declining, which has become a sev...Aerospace relay is one kind of electronic components which is used widely in national defense system and aerospace system. The existence of remainder particles induces the reliability declining, which has become a severe problem in the development of aerospace relay. Traditional particle impact noise detection (PIND) method for remainder detection is ineffective for small particles, due to its low precision and involvement of subjective factors. An auto-detection method for PIND output signals is proposed in this paper, which is based on direct wavelet de-noising (DWD), cross-correlation analysis (CCA) and homo-filtering (HF), the method enhances the affectivity of PIND test about the small particles. In the end, some practical PIND output signals are analysed, and the validity of this new method is proved.展开更多
Using numerical simulation data of the forward differential propagation shift (ΦDP) of polarimetric radar,the principle and performing steps of noise reduction by wavelet analysis are introduced in detail.Profiting...Using numerical simulation data of the forward differential propagation shift (ΦDP) of polarimetric radar,the principle and performing steps of noise reduction by wavelet analysis are introduced in detail.Profiting from the multiscale analysis,various types of noises can be identified according to their characteristics in different scales,and suppressed in different resolutions by a penalty threshold strategy through which a fixed threshold value is applied,a default threshold strategy through which the threshold value is determined by the noise intensity,or a ΦDP penalty threshold strategy through which a special value is designed for ΦDP de-noising.Then,a hard-or soft-threshold function,depending on the de-noising purpose,is selected to reconstruct the signal.Combining the three noise suppression strategies and the two signal reconstruction functions,and without loss of generality,two schemes are presented to verify the de-noising effect by dbN wavelets:(1) the penalty threshold strategy with the soft threshold function scheme (PSS); (2) the ΦDP penalty threshold strategy with the soft threshold function scheme (PPSS).Furthermore,the wavelet de-noising is compared with the mean,median,Kalman,and finite impulse response (FIR) methods with simulation data and two actual cases.The results suggest that both of the two schemes perform well,especially when ΦDP data are simultaneously polluted by various scales and types of noises.A slight difference is that the PSS method can retain more detail,and the PPSS can smooth the signal more successfully.展开更多
A wavelet method was applied to detect inhomogeneities in daily meteorological series, data which are being increasingly applied in studies of climate extremes. The wavelet method has been applied to a few well- estab...A wavelet method was applied to detect inhomogeneities in daily meteorological series, data which are being increasingly applied in studies of climate extremes. The wavelet method has been applied to a few well- established long-term daily temperature series back to the 18th century, which have been "homogenized" with conventional approaches. Various types of problems remaining in the series were revealed with the wavelet method. Their influences on analyses of change in climate extremes are discussed. The results have importance for understanding issues in conventional climate data processing and for development of improved methods of homogenization in order to improve analysis of climate extremes based on daily data.展开更多
Interference in the data of geochemical hydrocarbon exploration is a large obstacle for anomaly recognition. The multiresolution analysis of wavelet analysis can extract the information at different scales so as to pr...Interference in the data of geochemical hydrocarbon exploration is a large obstacle for anomaly recognition. The multiresolution analysis of wavelet analysis can extract the information at different scales so as to provide a powerful tool for information analysis and processing. Based on the analysis of the geometric nature of hydrocarbon anomalies and background, Mallat wavelet and symmetric border treatment are selected and data pre-processing (logarithm-normalization) is established. This approach provide good results in Shandong and Inner Mongolia, China. It is demonstrated that this approach overcome the disadvantage of backgound variation in the window (interference in window), used in moving average, frame filtering and spatial and scaling modeling methods.展开更多
Wavelet transforms (WT) are proposed as an alternative tool to overcome the limitations of Fourier transforms (FFT) in the analysis of electrochemical noise (EN) data. The most relevant feature of this method of analy...Wavelet transforms (WT) are proposed as an alternative tool to overcome the limitations of Fourier transforms (FFT) in the analysis of electrochemical noise (EN) data. The most relevant feature of this method of analysis is its capability of decomposing electrochemical noise records into different sets of wavelet coefficients, which contain information about the time scale characteristic of the associated corrosion event. In this context, the potential noise fluctuations during the free corrosion of pure aluminum in sodium chloride solution was recorded and analyzed with wavelet transform technique. The typical results showed that the EN signal is composed of distinct type of events, which can be classified according to their scales, i.e. their time constants. Meanwhile, the energy distribution plot (EDP) can be used as 'fingerprints' of EN signals and can be very useful for analyzing EN data in the future.展开更多
Powdery mildew (Blumeria graminis) is one of the most destructive crop diseases infecting winter wheat plants, and has devastated millions of hectares of farmlands in China. The objective of this study is to detect ...Powdery mildew (Blumeria graminis) is one of the most destructive crop diseases infecting winter wheat plants, and has devastated millions of hectares of farmlands in China. The objective of this study is to detect the disease damage of powdery mildew on leaf level by means of the hyperspectral measurements, particularly using the continuous wavelet analysis. In May 2010, the reflectance spectra and the biochemical properties were measured for 114 leaf samples with various disease severity degrees. A hyperspectral imaging system was also employed for obtaining detailed hyperspectral information of the normal and the pustule areas within one diseased leaf. Based on these spectra data, a continuous wavelet analysis (CWA) was carried out in conjunction with a correlation analysis, which generated a so-called correlation scalogram that summarizes the correlations between disease severity and the wavelet power at different wavelengths and decomposition scales. By using a thresholding approach, seven wavelet features were isolated for developing models in determining disease severity. In addition, 22 conventional spectral features (SFs) were also tested and compared with wavelet features for their efficiency in estimating disease severity. The multivariate linear regression (MLR) analysis and the partial least square regression (PLSR) analysis were adopted as training methods in model mildew on leaf level were found to be closely related with the development. The spectral characteristics of the powdery spectral characteristics of the pustule area and the content of chlorophyll. The wavelet features performed better than the conventional SFs in capturing this spectral change. Moreover, the regression model composed by seven wavelet features outperformed (R2=0.77, relative root mean square error RRMSE=0.28) the model composed by 14 optimal conventional SFs (R2---0.69, RRMSE--0.32) in estimating the disease severity. The PLSR method yielded a higher accuracy than the MLR method. A combination of CWA and PLSR was found to be promising in providing relatively accurate estimates of disease severity of powdery mildew on leaf level.展开更多
This study applies the wavelet analysis to the tidal gauge records, alongshore winds, atmospheric temperature and pressure along the China coast in winter 2008. The analysis results show three events of sea level osci...This study applies the wavelet analysis to the tidal gauge records, alongshore winds, atmospheric temperature and pressure along the China coast in winter 2008. The analysis results show three events of sea level oscillations (SLOs) on the shelf induced by winter storms. The first event occurred from January 9 to 21. The SLO periods were double-peaked at 1.6-5.3 and 7.0-16.0 d with the power densities of 0.04-0.05 and 0.10-0.15 m^2.d, respectively. The second event occurred from February 5 to 18. The SLO period was single-peaked at 2.3-3.5 d with power density of 0.03-0.04 m^2.d. The third event occurred from February 20 to March 8. The SLO periods were double- peaked at 1.5-4.3 and 6.1-8.2 d with the power densities of 0.08-0.11 and 0.02-0.08 me.d, respectively. The SLOs propagated along the coast from Zhejiang in north to Guangdong in south. The phase speeds ranged about 9-29 m/s from Kanmen to Pingtan, 5-11 m/s from Xiamen to Huizhou and 11-22 m/s from Huizhou to Shuidong. The dispersion relation of the SLOs shows their nature of coastal-trapped wave.展开更多
The Heihe River drainage basin is one of the endangered ecological regions of China. The shortage of water resources is the bottleneck, which constrains the sustainable development of the region. Many scholars in Chin...The Heihe River drainage basin is one of the endangered ecological regions of China. The shortage of water resources is the bottleneck, which constrains the sustainable development of the region. Many scholars in China have done researches concerning this problem. Based on previous researches, this paper analyzed characteristics, tendencies, and causes of annual runoff variations in the Yingluo Gorge (1944-2005) and the Zhengyi Gorge (1954-2005), which are the boundaries of the upper reaches, the middle reaches, and the lower reaches of the Heihe River drainage basin, by wavelet analysis, wavelet neural network model, and GIS spatial analysis. The results show that: (1) annual runoff variations of the Yingluo Gorge have principal periods of 7 years and 25 years, and its increasing rate is 1.04 m^3/s.10y; (2) annual runoff variations of the Zhengyi Gorge have principal periods of 6 years and 27 years, and its decreasing rate is 2.25 m^3/s.10y; (3) prediction results show that: during 2006-2015, annual runoff variations of the Yingluo and Zhengyi gorges have ascending tendencies, and the increasing rates are respectively 2.04 m^3/s.10y and 1.61 m^3/s.10y; (4) the increase of annual runoff in the Yingluo Gorge has causal relationship with increased temperature and precipitation in the upper reaches, and the decrease of annual runoff in the Zhengyi Gorge in the past decades was mainly caused by the increased human consumption of water resources in the middle researches. The study results will provide scientific basis for making rational use and allocation schemes of water resources in the Heihe River drainage basin.展开更多
During the service life of civil engineering structures such as long-span bridges, local damage at key positions may continually accumulate, and may finally result in their sudden failure. One core issue of global vib...During the service life of civil engineering structures such as long-span bridges, local damage at key positions may continually accumulate, and may finally result in their sudden failure. One core issue of global vibration-based health monitoring methods is to seek some damage indices that are sensitive to structural damage, This paper proposes an online structural health monitoring method for long-span suspension bridges using wavelet packet transform (WPT). The WPT- based method is based on the energy variations of structural ambient vibration responses decomposed using wavelet packet analysis. The main feature of this method is that the proposed wavelet packet energy spectrum (WPES) has the ability to detect structural damage from ambient vibration tests of a long-span suspension bridge. As an example application, the WPES-based health monitoring system is used on the Runyang Suspension Bridge under daily environmental conditions. The analysis reveals that changes in environmental temperature have a long-term influence on the WPES, while the effect of traffic loadings on the measured WPES of the bridge presents instantaneous changes because of the nonstationary properties of the loadings. The condition indication indices VD reflect the influences of environmental temperature on the dynamic properties of the Runyang Suspension Bridge. The field tests demonstrate that the proposed WPES-based condition indication index VD is a good candidate index for health monitoring of long-span suspension bridges under ambient excitations.展开更多
In this study we propose an analytical method based on orthogonal wavelet transforms for detecting harmonic noise and Electromagnetic Interference (EMI) from power supply systems and equipment in coal mines. The metho...In this study we propose an analytical method based on orthogonal wavelet transforms for detecting harmonic noise and Electromagnetic Interference (EMI) from power supply systems and equipment in coal mines. The method will separate interference from signals through wavelet packet decomposition and then accomplish wavelet packet synthesis towards decomposition results after filtering, to remove harmonic noise and electromagnetic interference. Detailed simulation experiments are presented to study power harmonics and Electrical Fast Transient Burst (EFT/B) interference and to validate the effectiveness of our proposed method. The experimental results show that the proposed method, suitable for mutant and non-stationary signal detection, can accurately analyze harmonic interference and EMI in coal mines, as well as establish EMI source models and perform underground Electromagnetic Compatibility (EMC) prediction analyses.展开更多
An ultrasonic test of spot welding for stainless steel is conducted. Based on wavelet packet decomposition, the ultrasonic echo signal has been analyzed deeply in time - frequency domain, which can easily distinguish ...An ultrasonic test of spot welding for stainless steel is conducted. Based on wavelet packet decomposition, the ultrasonic echo signal has been analyzed deeply in time - frequency domain, which can easily distinguish the nugget from the corona bond. The 2D C-scan images produced by ultrasonic C scan which contribute to quantitatively calculate the nugget diameter for the computer are further analyzed. The spot welding nugget diameter can be automatically obtained by image enhancement, edge detection and equivalent diameter algorithm procedure. The ultrasonic detection values in this paper show good agreement with the metallographic measured values. The mean value of normal distribution curve is 0.006 67, and the standard deviation is 0.087 11. Ultrasonic C-scan test based on wavelet packet signal analysis is of high accuracy and stability.展开更多
The construction of basic wavelet was discussed and many basic analyzing wavelets was compared. Acomplex analyzing wavelet which is continuous, smoothing, orthogonal and exponential decreasing was presented, andit was...The construction of basic wavelet was discussed and many basic analyzing wavelets was compared. Acomplex analyzing wavelet which is continuous, smoothing, orthogonal and exponential decreasing was presented, andit was used to decompose two blasting seismic signals with the continuous wavelet transforms (CWT). The resultshows that wavelet analysis is the better method to help us determine the essential factors which create damage effectsthan Fourier analysis.展开更多
In the ultrasonic nondestructive evaluation of the quality of solid state welded joints, such as friction bonding and diffusion bonding, the main difficulty is the identification of micro defects which are most likel...In the ultrasonic nondestructive evaluation of the quality of solid state welded joints, such as friction bonding and diffusion bonding, the main difficulty is the identification of micro defects which are most likely to emerge in the welding process. The ultrasonic echo on the screen of a commercial ultrasonic detector due to a micro defect is so weak that it is completely masked by noise, and impossible to be pointed out. In the present paper, wavelet analysis (WA) is utilized to process A scan ultrasonic signals from weak bonding defects in friction bonding joints and porosity in diffusion bonding joints. First, perception of WA for engineers is given, which demonstrates the physical mechanism of WA when applied to signal processing. From this point of view, WA can be understood easily and more thoroughly. Then the signals from welding joints are decomposed into a time scale plane by means of WA. We notice that noise and the signal echo attributed to the micro defect occupy different scales, which make it possible to enhance the signal to noise ratio of the signals by proper selection and threshold processing of the time scale components of the signals, followed by reconstruction of the processed components.展开更多
This paper analyses the five years’ monitored strains collected from a long-term health monitoring system installed on a bridge with wavelet transform.In the analysis,the monitored strains are pre-processed,features ...This paper analyses the five years’ monitored strains collected from a long-term health monitoring system installed on a bridge with wavelet transform.In the analysis,the monitored strains are pre-processed,features of the monitored data are summarized briefly.The influences of the base functions on the results of wavelet analysis are studied simultaneously.The results show that the db wavelet is a good mother wavelet function in the analysis,and the order N should be larger than 20,but less than 46 in decomposing the monitored strains of the bridge.According to the strain variation features of concrete bridge,the proper decomposition level is 4 in the wavelet multi-resolution analysis.With the present method,the strains caused by random loads and daily sunlight can be accurately extracted from the monitored strains.The decomposed components of the monitored strains show that the amplitudes of the strains caused by random loads,daily sunlight,and annual temperature effect,are about 5 με,25 με,and 50 με respectively.The structural response under random load is smaller than the other parts.展开更多
Some new theory and algorithms on wavelet analysis are proposed, including continuous wavelet transform (CWT), discrete wavelet transform (DWT), wavelet package transform (WPT), wavelet denosing and mother wavel...Some new theory and algorithms on wavelet analysis are proposed, including continuous wavelet transform (CWT), discrete wavelet transform (DWT), wavelet package transform (WPT), wavelet denosing and mother wavelet selection, etc. Using the component-based hierarchy mode, the platform for virtual instrument (VI) is constructed, and the functions such as data sampling, data analysis and data present, etc are provided. Subsequently, the wavelet analysis library is designed and developed. The library consists of expert system, experienced database, development platform and abundant wavelet analysis functional module, which together implement general and special wavelet analysis in the field of mechanical engineering, energy source, transportation and biomedicine, etc. Finally, the wavelet analysis virtual instrument library is applied to detect fault called engine knock. Experimental result indicates that the wavelet analysis virtual instrument library can efficiently solve the engineering problem such as detecting engine knock.展开更多
In this paper four families of orthogonal wavelets are applied to analyze the turbulent counter gradient transport phenomena in fully developed asymmetric channel flows. The results show that: (1) In the instance of c...In this paper four families of orthogonal wavelets are applied to analyze the turbulent counter gradient transport phenomena in fully developed asymmetric channel flows. The results show that: (1) In the instance of counter gradient transport, the principal scale of the coherent structure is responsible for the strong local counter gradient transport; (2) Counter gradient transport phenomena have a strong effect on the intermittency of turbulence; (3) Non-Gaussian part of the principal coherent structure is essential for counter gradient transport phenomena.展开更多
After brief describing the Principle of wavelet transform (WT) of signals, a new signals analysis system based on wavelet transform is introduced. The design and development of the instryment of wavelet transform are ...After brief describing the Principle of wavelet transform (WT) of signals, a new signals analysis system based on wavelet transform is introduced. The design and development of the instryment of wavelet transform are described. A number of practical uses of this system demonstrate that wavelet transform system is specially functional in identifying and processing impulse, singular and non-smooth signals, so that it should be evaluated the most advanced signal analyzing system.展开更多
Based on sine and cosine functions, the compactly supported orthogonal wavelet filter coefficients with arbitrary length are constructed for the first time. When N = 2(k-1) and N = 2k, the unified analytic constructio...Based on sine and cosine functions, the compactly supported orthogonal wavelet filter coefficients with arbitrary length are constructed for the first time. When N = 2(k-1) and N = 2k, the unified analytic constructions of orthogonal wavelet filters are put forward, respectively. The famous Daubechies filter and some other well-known wavelet filters are tested by the proposed novel method which is very useful for wavelet theory research and many application areas such as pattern recognition.展开更多
A discriminant analysis technique using wavelet transformation(WT)and influence matrixanalysis(CAIMAN)method is proposed for the near infrared(NIR)spectroscopy classifi-cation.In the proposed methodology,NIR spectra a...A discriminant analysis technique using wavelet transformation(WT)and influence matrixanalysis(CAIMAN)method is proposed for the near infrared(NIR)spectroscopy classifi-cation.In the proposed methodology,NIR spectra are decomposed by WT for data com-pression and a forward feature selection is further employed to extract the relevant informationfrom the wavelet coefficients,reducing both classification errors and model complexity.Adiscriminant-CAIMAN(D-CAIMAN)method is utilized to build the classification model inwavelet domain on the basis of reduced wavelet coefficients of spectral variables.NIR spectradata set of 265 salviae miltiorrhizae radia samples from 9 different geographical origins is usedas an example to test the classification performance of the algorithm.For a comparison,k-nearest neighbor(KNN),linear discriminant analysis(LDA)and quadratic discriminant analysis(QDA)methods are also employed.D-CAIMAN with wavelet-based feature selection(WD-CAIMAN)method shows the best performance,achieving the total classification rate of ioo%in both cross-validation set and prediction set.It is worth noting that the WD-CAIMANclassifier also shows improved sensitivity,selectivity and model interpretability in thecla.ssifications.展开更多
The Bouguer gravity anomaly data of Sichuan-Yunnan region and its vicinity were analyzed with wavelet trans- formation method. In the process, complete orthogonal wavelet function system with good symmetry and higher ...The Bouguer gravity anomaly data of Sichuan-Yunnan region and its vicinity were analyzed with wavelet trans- formation method. In the process, complete orthogonal wavelet function system with good symmetry and higher vanishing moment was selected to decompose the gravity anomaly into two parts. With the power spectral analysis on the decomposed anomalies, we interpreted that the two parts of anomalies represent the density variation in upper and middle crust, and in deep crust and uppermost mantle, respectively. The two parts of anomalies indicate the difference between shallow and deep tectonics. The results of shallow-layer apparent density mapping reveal that: a) the crustal density in Sichuan basin is higher than that in Songpan-Garze orogenic zone; b) the density of Kangdian rhombic block is heterogeneous; c) the boundary faults of Kangdian block are of different density fea- tures, suggesting different tectonic signification. The results of deep-layer apparent density mapping show a similar, but not the same, density distribution pattern as the shallow results, and indicate that the tectonics of shallow and deep crust are different, they may be in a status of incomplete coupling. Our results also show that the earthquakes in this area are controlled not only by the fracture zones but also by the deep density distribution.展开更多
基金Chinese Science Technology and Industry Foundation for National Defense(FEBG27100001)
文摘Aerospace relay is one kind of electronic components which is used widely in national defense system and aerospace system. The existence of remainder particles induces the reliability declining, which has become a severe problem in the development of aerospace relay. Traditional particle impact noise detection (PIND) method for remainder detection is ineffective for small particles, due to its low precision and involvement of subjective factors. An auto-detection method for PIND output signals is proposed in this paper, which is based on direct wavelet de-noising (DWD), cross-correlation analysis (CCA) and homo-filtering (HF), the method enhances the affectivity of PIND test about the small particles. In the end, some practical PIND output signals are analysed, and the validity of this new method is proved.
基金funded by National Natural Science Foundation of China (Grant No. 41375038)China Meteorological Administration Special Public Welfare Research Fund (Grant No. GYHY201306040,GYHY201306075)
文摘Using numerical simulation data of the forward differential propagation shift (ΦDP) of polarimetric radar,the principle and performing steps of noise reduction by wavelet analysis are introduced in detail.Profiting from the multiscale analysis,various types of noises can be identified according to their characteristics in different scales,and suppressed in different resolutions by a penalty threshold strategy through which a fixed threshold value is applied,a default threshold strategy through which the threshold value is determined by the noise intensity,or a ΦDP penalty threshold strategy through which a special value is designed for ΦDP de-noising.Then,a hard-or soft-threshold function,depending on the de-noising purpose,is selected to reconstruct the signal.Combining the three noise suppression strategies and the two signal reconstruction functions,and without loss of generality,two schemes are presented to verify the de-noising effect by dbN wavelets:(1) the penalty threshold strategy with the soft threshold function scheme (PSS); (2) the ΦDP penalty threshold strategy with the soft threshold function scheme (PPSS).Furthermore,the wavelet de-noising is compared with the mean,median,Kalman,and finite impulse response (FIR) methods with simulation data and two actual cases.The results suggest that both of the two schemes perform well,especially when ΦDP data are simultaneously polluted by various scales and types of noises.A slight difference is that the PSS method can retain more detail,and the PPSS can smooth the signal more successfully.
文摘A wavelet method was applied to detect inhomogeneities in daily meteorological series, data which are being increasingly applied in studies of climate extremes. The wavelet method has been applied to a few well- established long-term daily temperature series back to the 18th century, which have been "homogenized" with conventional approaches. Various types of problems remaining in the series were revealed with the wavelet method. Their influences on analyses of change in climate extremes are discussed. The results have importance for understanding issues in conventional climate data processing and for development of improved methods of homogenization in order to improve analysis of climate extremes based on daily data.
文摘Interference in the data of geochemical hydrocarbon exploration is a large obstacle for anomaly recognition. The multiresolution analysis of wavelet analysis can extract the information at different scales so as to provide a powerful tool for information analysis and processing. Based on the analysis of the geometric nature of hydrocarbon anomalies and background, Mallat wavelet and symmetric border treatment are selected and data pre-processing (logarithm-normalization) is established. This approach provide good results in Shandong and Inner Mongolia, China. It is demonstrated that this approach overcome the disadvantage of backgound variation in the window (interference in window), used in moving average, frame filtering and spatial and scaling modeling methods.
基金the financial support of the National Key Basic Research Foundation of China (Project G19990650), the National Natural Science Foundation of China (Project 50071054) and the financial support of State Key
文摘Wavelet transforms (WT) are proposed as an alternative tool to overcome the limitations of Fourier transforms (FFT) in the analysis of electrochemical noise (EN) data. The most relevant feature of this method of analysis is its capability of decomposing electrochemical noise records into different sets of wavelet coefficients, which contain information about the time scale characteristic of the associated corrosion event. In this context, the potential noise fluctuations during the free corrosion of pure aluminum in sodium chloride solution was recorded and analyzed with wavelet transform technique. The typical results showed that the EN signal is composed of distinct type of events, which can be classified according to their scales, i.e. their time constants. Meanwhile, the energy distribution plot (EDP) can be used as 'fingerprints' of EN signals and can be very useful for analyzing EN data in the future.
基金the National Natural Science Foundation of China (41101395, 41071276, 31071324)the Beijing Municipal Natural Science Foundation, China (4122032)the National Basic Research Program of China (2011CB311806)
文摘Powdery mildew (Blumeria graminis) is one of the most destructive crop diseases infecting winter wheat plants, and has devastated millions of hectares of farmlands in China. The objective of this study is to detect the disease damage of powdery mildew on leaf level by means of the hyperspectral measurements, particularly using the continuous wavelet analysis. In May 2010, the reflectance spectra and the biochemical properties were measured for 114 leaf samples with various disease severity degrees. A hyperspectral imaging system was also employed for obtaining detailed hyperspectral information of the normal and the pustule areas within one diseased leaf. Based on these spectra data, a continuous wavelet analysis (CWA) was carried out in conjunction with a correlation analysis, which generated a so-called correlation scalogram that summarizes the correlations between disease severity and the wavelet power at different wavelengths and decomposition scales. By using a thresholding approach, seven wavelet features were isolated for developing models in determining disease severity. In addition, 22 conventional spectral features (SFs) were also tested and compared with wavelet features for their efficiency in estimating disease severity. The multivariate linear regression (MLR) analysis and the partial least square regression (PLSR) analysis were adopted as training methods in model mildew on leaf level were found to be closely related with the development. The spectral characteristics of the powdery spectral characteristics of the pustule area and the content of chlorophyll. The wavelet features performed better than the conventional SFs in capturing this spectral change. Moreover, the regression model composed by seven wavelet features outperformed (R2=0.77, relative root mean square error RRMSE=0.28) the model composed by 14 optimal conventional SFs (R2---0.69, RRMSE--0.32) in estimating the disease severity. The PLSR method yielded a higher accuracy than the MLR method. A combination of CWA and PLSR was found to be promising in providing relatively accurate estimates of disease severity of powdery mildew on leaf level.
基金The National Basic Research Program of China under contract No.2015CB954004the Natural Science Foundation of China under contract Nos 41276006 and U1405233+1 种基金the US National Science Foundation Award under contract No.AGS-1061998(for Zheng)the China Scholarship Council under contract No.201306310082
文摘This study applies the wavelet analysis to the tidal gauge records, alongshore winds, atmospheric temperature and pressure along the China coast in winter 2008. The analysis results show three events of sea level oscillations (SLOs) on the shelf induced by winter storms. The first event occurred from January 9 to 21. The SLO periods were double-peaked at 1.6-5.3 and 7.0-16.0 d with the power densities of 0.04-0.05 and 0.10-0.15 m^2.d, respectively. The second event occurred from February 5 to 18. The SLO period was single-peaked at 2.3-3.5 d with power density of 0.03-0.04 m^2.d. The third event occurred from February 20 to March 8. The SLO periods were double- peaked at 1.5-4.3 and 6.1-8.2 d with the power densities of 0.08-0.11 and 0.02-0.08 me.d, respectively. The SLOs propagated along the coast from Zhejiang in north to Guangdong in south. The phase speeds ranged about 9-29 m/s from Kanmen to Pingtan, 5-11 m/s from Xiamen to Huizhou and 11-22 m/s from Huizhou to Shuidong. The dispersion relation of the SLOs shows their nature of coastal-trapped wave.
基金National Natural Science Foundation of China, No.40335046
文摘The Heihe River drainage basin is one of the endangered ecological regions of China. The shortage of water resources is the bottleneck, which constrains the sustainable development of the region. Many scholars in China have done researches concerning this problem. Based on previous researches, this paper analyzed characteristics, tendencies, and causes of annual runoff variations in the Yingluo Gorge (1944-2005) and the Zhengyi Gorge (1954-2005), which are the boundaries of the upper reaches, the middle reaches, and the lower reaches of the Heihe River drainage basin, by wavelet analysis, wavelet neural network model, and GIS spatial analysis. The results show that: (1) annual runoff variations of the Yingluo Gorge have principal periods of 7 years and 25 years, and its increasing rate is 1.04 m^3/s.10y; (2) annual runoff variations of the Zhengyi Gorge have principal periods of 6 years and 27 years, and its decreasing rate is 2.25 m^3/s.10y; (3) prediction results show that: during 2006-2015, annual runoff variations of the Yingluo and Zhengyi gorges have ascending tendencies, and the increasing rates are respectively 2.04 m^3/s.10y and 1.61 m^3/s.10y; (4) the increase of annual runoff in the Yingluo Gorge has causal relationship with increased temperature and precipitation in the upper reaches, and the decrease of annual runoff in the Zhengyi Gorge in the past decades was mainly caused by the increased human consumption of water resources in the middle researches. The study results will provide scientific basis for making rational use and allocation schemes of water resources in the Heihe River drainage basin.
基金National Hi-Tech Research and Development Program of China (863 Program) (No. 2006AA04Z416)the National Natural Science Foundation of China Under Grant No. 50538020
文摘During the service life of civil engineering structures such as long-span bridges, local damage at key positions may continually accumulate, and may finally result in their sudden failure. One core issue of global vibration-based health monitoring methods is to seek some damage indices that are sensitive to structural damage, This paper proposes an online structural health monitoring method for long-span suspension bridges using wavelet packet transform (WPT). The WPT- based method is based on the energy variations of structural ambient vibration responses decomposed using wavelet packet analysis. The main feature of this method is that the proposed wavelet packet energy spectrum (WPES) has the ability to detect structural damage from ambient vibration tests of a long-span suspension bridge. As an example application, the WPES-based health monitoring system is used on the Runyang Suspension Bridge under daily environmental conditions. The analysis reveals that changes in environmental temperature have a long-term influence on the WPES, while the effect of traffic loadings on the measured WPES of the bridge presents instantaneous changes because of the nonstationary properties of the loadings. The condition indication indices VD reflect the influences of environmental temperature on the dynamic properties of the Runyang Suspension Bridge. The field tests demonstrate that the proposed WPES-based condition indication index VD is a good candidate index for health monitoring of long-span suspension bridges under ambient excitations.
基金the financial support for our work by the Doctoral Foundation of Ministry of Education of China (No.200802900008)
文摘In this study we propose an analytical method based on orthogonal wavelet transforms for detecting harmonic noise and Electromagnetic Interference (EMI) from power supply systems and equipment in coal mines. The method will separate interference from signals through wavelet packet decomposition and then accomplish wavelet packet synthesis towards decomposition results after filtering, to remove harmonic noise and electromagnetic interference. Detailed simulation experiments are presented to study power harmonics and Electrical Fast Transient Burst (EFT/B) interference and to validate the effectiveness of our proposed method. The experimental results show that the proposed method, suitable for mutant and non-stationary signal detection, can accurately analyze harmonic interference and EMI in coal mines, as well as establish EMI source models and perform underground Electromagnetic Compatibility (EMC) prediction analyses.
基金Funded by Key Laboratory of Automobile Materials of Ministry of Education and Department of Materials Science & Engineering,Jilin University
文摘An ultrasonic test of spot welding for stainless steel is conducted. Based on wavelet packet decomposition, the ultrasonic echo signal has been analyzed deeply in time - frequency domain, which can easily distinguish the nugget from the corona bond. The 2D C-scan images produced by ultrasonic C scan which contribute to quantitatively calculate the nugget diameter for the computer are further analyzed. The spot welding nugget diameter can be automatically obtained by image enhancement, edge detection and equivalent diameter algorithm procedure. The ultrasonic detection values in this paper show good agreement with the metallographic measured values. The mean value of normal distribution curve is 0.006 67, and the standard deviation is 0.087 11. Ultrasonic C-scan test based on wavelet packet signal analysis is of high accuracy and stability.
文摘The construction of basic wavelet was discussed and many basic analyzing wavelets was compared. Acomplex analyzing wavelet which is continuous, smoothing, orthogonal and exponential decreasing was presented, andit was used to decompose two blasting seismic signals with the continuous wavelet transforms (CWT). The resultshows that wavelet analysis is the better method to help us determine the essential factors which create damage effectsthan Fourier analysis.
基金This work is financially supported by the Beijing Natural Science Foundation!(No.2 962 0 0 4 )
文摘In the ultrasonic nondestructive evaluation of the quality of solid state welded joints, such as friction bonding and diffusion bonding, the main difficulty is the identification of micro defects which are most likely to emerge in the welding process. The ultrasonic echo on the screen of a commercial ultrasonic detector due to a micro defect is so weak that it is completely masked by noise, and impossible to be pointed out. In the present paper, wavelet analysis (WA) is utilized to process A scan ultrasonic signals from weak bonding defects in friction bonding joints and porosity in diffusion bonding joints. First, perception of WA for engineers is given, which demonstrates the physical mechanism of WA when applied to signal processing. From this point of view, WA can be understood easily and more thoroughly. Then the signals from welding joints are decomposed into a time scale plane by means of WA. We notice that noise and the signal echo attributed to the micro defect occupy different scales, which make it possible to enhance the signal to noise ratio of the signals by proper selection and threshold processing of the time scale components of the signals, followed by reconstruction of the processed components.
文摘This paper analyses the five years’ monitored strains collected from a long-term health monitoring system installed on a bridge with wavelet transform.In the analysis,the monitored strains are pre-processed,features of the monitored data are summarized briefly.The influences of the base functions on the results of wavelet analysis are studied simultaneously.The results show that the db wavelet is a good mother wavelet function in the analysis,and the order N should be larger than 20,but less than 46 in decomposing the monitored strains of the bridge.According to the strain variation features of concrete bridge,the proper decomposition level is 4 in the wavelet multi-resolution analysis.With the present method,the strains caused by random loads and daily sunlight can be accurately extracted from the monitored strains.The decomposed components of the monitored strains show that the amplitudes of the strains caused by random loads,daily sunlight,and annual temperature effect,are about 5 με,25 με,and 50 με respectively.The structural response under random load is smaller than the other parts.
基金This project is supported by National Natural Science Foundation of China(No.50575233).
文摘Some new theory and algorithms on wavelet analysis are proposed, including continuous wavelet transform (CWT), discrete wavelet transform (DWT), wavelet package transform (WPT), wavelet denosing and mother wavelet selection, etc. Using the component-based hierarchy mode, the platform for virtual instrument (VI) is constructed, and the functions such as data sampling, data analysis and data present, etc are provided. Subsequently, the wavelet analysis library is designed and developed. The library consists of expert system, experienced database, development platform and abundant wavelet analysis functional module, which together implement general and special wavelet analysis in the field of mechanical engineering, energy source, transportation and biomedicine, etc. Finally, the wavelet analysis virtual instrument library is applied to detect fault called engine knock. Experimental result indicates that the wavelet analysis virtual instrument library can efficiently solve the engineering problem such as detecting engine knock.
基金The project supported by the National Natural Science Foundation of China(10272071.10472063)
文摘In this paper four families of orthogonal wavelets are applied to analyze the turbulent counter gradient transport phenomena in fully developed asymmetric channel flows. The results show that: (1) In the instance of counter gradient transport, the principal scale of the coherent structure is responsible for the strong local counter gradient transport; (2) Counter gradient transport phenomena have a strong effect on the intermittency of turbulence; (3) Non-Gaussian part of the principal coherent structure is essential for counter gradient transport phenomena.
基金This project is supported by National Natural Science Foundation of China
文摘After brief describing the Principle of wavelet transform (WT) of signals, a new signals analysis system based on wavelet transform is introduced. The design and development of the instryment of wavelet transform are described. A number of practical uses of this system demonstrate that wavelet transform system is specially functional in identifying and processing impulse, singular and non-smooth signals, so that it should be evaluated the most advanced signal analyzing system.
文摘Based on sine and cosine functions, the compactly supported orthogonal wavelet filter coefficients with arbitrary length are constructed for the first time. When N = 2(k-1) and N = 2k, the unified analytic constructions of orthogonal wavelet filters are put forward, respectively. The famous Daubechies filter and some other well-known wavelet filters are tested by the proposed novel method which is very useful for wavelet theory research and many application areas such as pattern recognition.
基金Financial support from China Postdoctoral Science Foundation Special Funded Project(2013T60604)Zhejang Provincial Public Welfare Application Project of China(2012C21102)are gratefully acknowledged.
文摘A discriminant analysis technique using wavelet transformation(WT)and influence matrixanalysis(CAIMAN)method is proposed for the near infrared(NIR)spectroscopy classifi-cation.In the proposed methodology,NIR spectra are decomposed by WT for data com-pression and a forward feature selection is further employed to extract the relevant informationfrom the wavelet coefficients,reducing both classification errors and model complexity.Adiscriminant-CAIMAN(D-CAIMAN)method is utilized to build the classification model inwavelet domain on the basis of reduced wavelet coefficients of spectral variables.NIR spectradata set of 265 salviae miltiorrhizae radia samples from 9 different geographical origins is usedas an example to test the classification performance of the algorithm.For a comparison,k-nearest neighbor(KNN),linear discriminant analysis(LDA)and quadratic discriminant analysis(QDA)methods are also employed.D-CAIMAN with wavelet-based feature selection(WD-CAIMAN)method shows the best performance,achieving the total classification rate of ioo%in both cross-validation set and prediction set.It is worth noting that the WD-CAIMANclassifier also shows improved sensitivity,selectivity and model interpretability in thecla.ssifications.
基金National Natural Science Foundation of China (403334041)
文摘The Bouguer gravity anomaly data of Sichuan-Yunnan region and its vicinity were analyzed with wavelet trans- formation method. In the process, complete orthogonal wavelet function system with good symmetry and higher vanishing moment was selected to decompose the gravity anomaly into two parts. With the power spectral analysis on the decomposed anomalies, we interpreted that the two parts of anomalies represent the density variation in upper and middle crust, and in deep crust and uppermost mantle, respectively. The two parts of anomalies indicate the difference between shallow and deep tectonics. The results of shallow-layer apparent density mapping reveal that: a) the crustal density in Sichuan basin is higher than that in Songpan-Garze orogenic zone; b) the density of Kangdian rhombic block is heterogeneous; c) the boundary faults of Kangdian block are of different density fea- tures, suggesting different tectonic signification. The results of deep-layer apparent density mapping show a similar, but not the same, density distribution pattern as the shallow results, and indicate that the tectonics of shallow and deep crust are different, they may be in a status of incomplete coupling. Our results also show that the earthquakes in this area are controlled not only by the fracture zones but also by the deep density distribution.