Fault prognosis is mainly referred to the estimation of the operating time before a failure occurs,which is vital for ensuring the stability,safety and long lifetime of degrading industrial systems.According to the re...Fault prognosis is mainly referred to the estimation of the operating time before a failure occurs,which is vital for ensuring the stability,safety and long lifetime of degrading industrial systems.According to the results of fault prognosis,the maintenance strategy for underlying industrial systems can realize the conversion from passive maintenance to active maintenance.With the increased complexity and the improved automation level of industrial systems,fault prognosis techniques have become more and more indispensable.Particularly,the datadriven based prognosis approaches,which tend to find the hidden fault factors and determine the specific fault occurrence time of the system by analysing historical or real-time measurement data,gain great attention from different industrial sectors.In this context,the major task of this paper is to present a systematic overview of data-driven fault prognosis for industrial systems.Firstly,the characteristics of different prognosis methods are revealed with the data-based ones being highlighted.Moreover,based on the different data characteristics that exist in industrial systems,the corresponding fault prognosis methodologies are illustrated,with emphasis on analyses and comparisons of different prognosis methods.Finally,we reveal the current research trends and look forward to the future challenges in this field.This review is expected to serve as a tutorial and source of references for fault prognosis researchers.展开更多
In order to increase the fault diagnosis efficiency and make the fault data mining be realized, the decision table containing numerical attributes must be discretized for further calculations. The discernibility matri...In order to increase the fault diagnosis efficiency and make the fault data mining be realized, the decision table containing numerical attributes must be discretized for further calculations. The discernibility matrix-based reduction method depends on whether the numerical attributes can be properly discretized or not.So a discretization algorithm based on particle swarm optimization(PSO) is proposed. Moreover, hybrid weights are adopted in the process of particles evolution. Comparative calculations for certain equipment are completed to demonstrate the effectiveness of the proposed algorithm. The results indicate that the proposed algorithm has better performance than other popular algorithms such as class-attribute interdependence maximization(CAIM)discretization method and entropy-based discretization method.展开更多
The Hori＇s inverse method based on spectral decomposition was applied to estimate coseismic slip distribution on the rupture plane of the 14 November 2001 Ms8.1 Kunlun earthquake based on GPS survey results. The inve...The Hori＇s inverse method based on spectral decomposition was applied to estimate coseismic slip distribution on the rupture plane of the 14 November 2001 Ms8.1 Kunlun earthquake based on GPS survey results. The inversion result shows that the six sliding models can be constrained by the coseismic GPS data. The established slips mainly concentrated along the eastern segment of the fault rupture, and the maximum magnitude is about 7 m. Slip on the eastern segment of the fault rupture represents as purely left-lateral strike-slip. Slip on the western segment of the seismic rupture represents as mainly dip-stip with the maximum dip-slip about 1 m. Total predicted scalar seismic moment is 5.196× 10^2° N.m. Our results constrained by geodetic data are consistent with seismological results.展开更多
The data-driven fault diagnosis methods can improve the reliability of analog circuits by using the data generated from it. The data have some characteristics, such as randomness and incompleteness, which lead to the ...The data-driven fault diagnosis methods can improve the reliability of analog circuits by using the data generated from it. The data have some characteristics, such as randomness and incompleteness, which lead to the diagnostic results being sensitive to the specific values and random noise. This paper presents a data-driven fault diagnosis method for analog circuits based on the robust competitive agglomeration （RCA）, which can alleviate the incompleteness of the data by clustering with the competing process. And the robustness of the diagnostic results is enhanced by using the approach of robust statistics in RCA. A series of experiments are provided to demonstrate that RCA can classify the incomplete data with a high accuracy. The experimental results show that RCA is robust for the data needed to be classified as well as the parameters needed to be adjusted. The effectiveness of RCA in practical use is demonstrated by two analog circuits.展开更多
We analyze co-seismic displacement field of the 26 December 2004, giant Sumatra–Andaman earthquake derived from Global Position System observations,geological vertical measurement of coral head, and pivot line observ...We analyze co-seismic displacement field of the 26 December 2004, giant Sumatra–Andaman earthquake derived from Global Position System observations,geological vertical measurement of coral head, and pivot line observed through remote sensing. Using the co-seismic displacement field and AK135 spherical layered Earth model, we invert co-seismic slip distribution along the seismic fault. We also search the best fault geometry model to fit the observed data. Assuming that the dip angle linearly increases in downward direction, the postfit residual variation of the inversed geometry model with dip angles linearly changing along fault strike are plotted. The geometry model with local minimum misfits is the one with dip angle linearly increasing along strike from 4.3oin top southernmost patch to 4.5oin top northernmost path and dip angle linearly increased. By using the fault shape and geodetic co-seismic data, we estimate the slip distribution on the curved fault. Our result shows that the earthquake ruptured ＊200-km width down to a depth of about 60 km.0.5–12.5 m of thrust slip is resolved with the largest slip centered around the central section of the rupture zone78N–108N in latitude. The estimated seismic moment is8.2 9 1022 N m, which is larger than estimation from the centroid moment magnitude（4.0 9 1022 N m）, and smaller than estimation from normal-mode oscillation data modeling（1.0 9 1023 N m）.展开更多
Based on GPS velocity during 1999-2007,GPS baseline time series on large scale during1999-2008 and cross-fault leveling data during 1985-2008,the paper makes some analysis and discussion to study and summarize the mov...Based on GPS velocity during 1999-2007,GPS baseline time series on large scale during1999-2008 and cross-fault leveling data during 1985-2008,the paper makes some analysis and discussion to study and summarize the movement,tectonic deformation and strain accumulation evolution characteristics of the Longmenshan fault and the surrounding area before the MS8. 0 Wenchuan earthquake,as well as the possible physical mechanism late in the seismic cycle of the Wenchuan earthquake. Multiple results indicate that:GPS velocity profiles show that obvious continuous deformation across the eastern Qinghai-Tibetan Plateau before the earthquake was distributed across a zone at least 500 km wide,while there was little deformation in Sichuan Basin and Longmenshan fault zone,which means that the eastern Qinghai-Tibetan Plateau provides energy accumulation for locked Longmenshan fault zone continuously. GPS strain rates show that the east-west compression deformation was larger in the northwest of the mid-northern segment of the Longmenshan fault zone,and deformation amplitude decreased gradually from far field to near fault zone,and there was little deformation in fault zone. The east-west compression deformation was significant surrounding the southwestern segment of the Longmenshan fault zone,and strain accumulation rate was larger than that of mid-northern segment.Fault locking indicates nearly whole Longmenshan fault was locked before the earthquake except the source of the earthquake which was weakly locked,and a 20 km width patch in southwestern segment between 12 km to 22. 5 km depth was in creeping state. GPS baseline time series in northeast direction on large scale became compressive generally from 2005 in the North-South Seismic Belt,which reflects that relative compression deformation enhances. The cross-fault leveling data show that annual vertical change rate and deformation trend accumulation rate in the Longmenshan fault zone were little,which indicates that vertical activity near the fault was very weak and the fault was tightly locked. According to analyses of GPS and cross-fault leveling data before the Wenchuan earthquake,we consider that the Longmenshan fault is tightly locked from the surface to the deep,and the horizontal and vertical deformation are weak surrounding the fault in relatively small-scale crustal deformation. The process of weak deformation may be slow,and weak deformation area may be larger when large earthquake is coming. Continuous and slow compression deformation across eastern Qinghai-Tibetan Plateau before the earthquake provides dynamic support for strain accumulation in the Longmenshan fault zone in relative large-scale crustal deformation.展开更多
As the demand for wind energy continues to grow at exponential rate, reducing operation and maintenance (O & M) costs and improving reliability have become top priorities in wind turbine maintenance strategies. Pr...As the demand for wind energy continues to grow at exponential rate, reducing operation and maintenance (O & M) costs and improving reliability have become top priorities in wind turbine maintenance strategies. Prediction of wind turbine failures before they reach a catastrophic stage is critical to reduce the O & M cost due to unnecessary scheduled maintenance. A SCADA-data based condition monitoring system, which takes advantage of data already collected at the wind turbine controller, is a cost-effective way to monitor wind turbines for early warning of failures. This article proposes a methodology of fault prediction and automatically generating warning and alarm for wind turbine main bearings based on stored SCADA data using Artificial Neural Network (ANN). The ANN model of turbine main bearing normal behavior is established and then the deviation between estimated and actual values of the parameter is calculated. Furthermore, a method has been developed to generate early warning and alarm and avoid false warnings and alarms based on the deviation. In this way, wind farm operators are able to have enough time to plan maintenance, and thus, unanticipated downtime can be avoided and O & M costs can be reduced.展开更多
The bug tracking system is well known as the project support tool of open source software. There are many categorical data sets recorded on the bug tracking system. In the past, many reliability assessment methods hav...The bug tracking system is well known as the project support tool of open source software. There are many categorical data sets recorded on the bug tracking system. In the past, many reliability assessment methods have been proposed in the research area of software reliability. Also, there are several software project analyses based on the software effort data such as the earned value management. In particular, the software reliability growth models can </span><span style="font-family:Verdana;">apply to the system testing phase of software development. On the other</span><span style="font-family:Verdana;"> hand, the software effort analysis can apply to all development phase, because the fault data is only recorded on the testing phase. We focus on the big fault data and effort data of open source software. Then, it is difficult to assess by using the typical statistical assessment method, because the data recorded on the bug tracking system is large scale. Also, we discuss the jump diffusion process model based on the estimation method of jump parameters by using the discriminant analysis. Moreover, we analyze actual big fault data to show numerical examples of software effort assessment considering many categorical data set.展开更多
Focusing on the networked control system with long time-delays and data packet dropout,the problem of observerbased fault detection of the system is studied.According to conditions of data arrival of the controller,th...Focusing on the networked control system with long time-delays and data packet dropout,the problem of observerbased fault detection of the system is studied.According to conditions of data arrival of the controller,the state observers of the system are designed to detect faults when they occur in the system.When the system is normal,the observers system is modeled as an uncertain switched system.Based on the model,stability condition of the whole system is given.When conditions are satisfied,the system is asymptotically stable.When a fault occurs,the observers residual can change rapidly to detect the fault.A numerical example shows the effectiveness of the proposed method.展开更多
In this study, Landsat 5 Thematic Mapper (TM) and SPOT HRV Panchromatic data were analysed to determine the geometry of an active fault segment (the Ganos segment) in Gazikoy-Saros region, west of Marmara Sea, Turkey....In this study, Landsat 5 Thematic Mapper (TM) and SPOT HRV Panchromatic data were analysed to determine the geometry of an active fault segment (the Ganos segment) in Gazikoy-Saros region, west of Marmara Sea, Turkey. Gazikoy-Saros/Ganos segment is a part of North Anatolian Fault Zone (NAFZ). North-Anatolian fault is considered to be one of the most important active strike-slip faults in the world. Thus far in relevant researches based on Gazikoy-Saros segment a single straight fault line representation is used on the fault descriptive geological maps. This study, with the aid of enhanced remotely sensed data aims to reveal the linear details of the NAFZ fault segment, which subsequently were superposed with a Digital Elevation Model (DEM) data. Respectively, using these data the surface geometry expression of Gazikoy-Saros fault segment was detailed and remapped. According to the results of the analysis two small releasing steps were identified on this segment. The first one is situated between Mürseli and Güzelkoy villages, and the second one is between Mürseli and Yorguc villages. In addition to this, it is found that the fault strike bends approximately 7° further to in south-eastern (SE) direction between Yenikoy and Sofular villages. This angular change was defined with the advantage of multi-angular viewing capability of the multi-satellite sensors and DEM data. The newly generated surface geometry expression of Ganos segment was compared with Global Positioning System (GPS) velocity vectors.展开更多
By systemic processing, comprehensive analysis, and interpretation of gravity data, we confirmed the existence of the west segment of the coastal fault zone(west of Yangjiang to Beibu Bay) in the coastal region of Sou...By systemic processing, comprehensive analysis, and interpretation of gravity data, we confirmed the existence of the west segment of the coastal fault zone(west of Yangjiang to Beibu Bay) in the coastal region of South China. This showed an apparent high gravity gradient in the NEE direction, and worse linearity and less compactness than that in the Pearl River month. This also revealed a relatively large curvature and a complicated gravity structure. In the finding images processed by the gravity data system, each fault was well reflected and primarily characterized by isolines or thick black stripes with a cutting depth greater than 30 km. Though mutually cut by NW-trending and NE-trending faults, the apparent NEE stripe-shaped structure of the west segment of the coastal fault zone remained unchanged,with good continuity and an activity strength higher than that of NW and NE-trending faults. Moreover,we determined that the west segment of the coastal fault zone is the major seismogenic structure responsible for strong earthquakes in the coastal region in the border area of Guangdong, Guangxi, and Hainan.展开更多
Wind energy is one of the widely applied renewable energies in the world. Wind turbine as the main wind energy converter at present has very complex technical system containing a huge number of components,actuators an...Wind energy is one of the widely applied renewable energies in the world. Wind turbine as the main wind energy converter at present has very complex technical system containing a huge number of components,actuators and sensors. However, despite of the hardware redundancy, sensor faults have often affected the wind turbine normal operation and thus caused energy generation loss. In this paper, aiming at the wind turbine hydraulic pitch system, data-driven design of process monitoring(PM) and diagnosis has been realized in the wind turbine benchmark. Fault tolerant control(FTC) strategies focused on sensor faults have also been presented here, where with the implementation of soft sensor the sensor fault can be handled and the performance of the system is improved. The performance of this method is demonstrated with the wind turbine benchmark provided by Math Works.展开更多
This article studies the fault recorder in power system and introduces the Comtrade format. Andituses C++ programming to read recorded fault data and adopts Fourier analysis and symmetrical component method to filter ...This article studies the fault recorder in power system and introduces the Comtrade format. Andituses C++ programming to read recorded fault data and adopts Fourier analysis and symmetrical component method to filter and extract fundamental waves. Finally the effectiveness of the data processing method introduced in this paper is verified by CAAP software.展开更多
The </span></span><span><span><span style="font-family:"">software reliability model is the stochastic model to measure the software <span>reliability quantitatively....The </span></span><span><span><span style="font-family:"">software reliability model is the stochastic model to measure the software <span>reliability quantitatively. A Hazard-Rate Model is </span></span></span></span><span><span><span style="font-family:"">the </span></span></span><span><span><span style="font-family:"">well</span></span></span><span><span><span style="font-family:"">-</span></span></span><span><span><span style="font-family:"">known one as the</span></span></span><span><span><span style="font-family:""> typical software reliability model. We propose Hazard-Rate Models Consider<span>ing Fault Severity Levels (CFSL) for Open Source Software (OSS). The purpose of </span><span>this research is to </span></span></span></span><span><span><span style="font-family:"">make </span></span></span><span><span><span style="font-family:"">the Hazard-Rate Model considering CFSL adapt to</span></span></span><span><span><span style="font-family:""> </span></span></span><span><span><span style="font-family:"">baseline hazard function and 2 kinds of faults data in Bug Tracking System <span>(BTS)</span></span></span></span><span><span><span style="font-family:"">,</span></span></span><span><span><span style="font-family:""> <i>i.e.</i>, we use the covariate vectors in Cox proportional Hazard-Rate</span></span></span><span><span><span style="font-family:""> Model. Also, <span>we show the numerical examples by evaluating the performance of our pro</span><span>posed model. As the result, we compare the performance of our model with the</span> Hazard-Rate Model CFSL.展开更多
While sensor networks have been used in various applications because of the automatic sensing capability and ad-hoc organization of sensor nodes, the fault-prone characteristic of sensor networks has challenged the ev...While sensor networks have been used in various applications because of the automatic sensing capability and ad-hoc organization of sensor nodes, the fault-prone characteristic of sensor networks has challenged the event detection and the anomaly detection which, to some extent, have neglected the importance of discriminating events and errors. Considering data uncertainty, in this article, we present the problem of data discrimination in fault-prone sensor networks, analyze the similarities and the differences between events and errors, and design a multi-level systematic discrimination framework. In each step, the framework filters erroneous data from the raw data and marks potential event samples for the next-step processing. The raw data set D is finally partitioned into three subsets, Devent, Derror and Dordinary. Both the scenario-based simulations and the experiments on real-sensed data are carried out. The statistical results of various discrimination metrics demonstrate high distinction ratio as well as the robustness in different cases of the network.展开更多
Wind power generation is a mature kind of technology, economic, environmental protection of new energy, it has a broad space for development. Wind turbine is a complex electromechanical system with complex structure a...Wind power generation is a mature kind of technology, economic, environmental protection of new energy, it has a broad space for development. Wind turbine is a complex electromechanical system with complex structure and many components. It is often located in remote mountainous areas, often encountering storms, lightning, ice, salt fog and other extreme weather. Due to its harsh working environment, it has appeared a lot of faults, and its low reliability and high maintenance cost, which brings great challenges to the safe operation of wind power generation equipment. Based on this, this paper is based on the actual failure data of domestic wind turbine, uses the Pareto curve and other analysis methods of the main components of domestic wind turbine, and accordingly formulated the corresponding maintenance countermeasures.展开更多
According to the time-frequency localization characteristic of the wavelet transform (WT)and the nonlinear reflection of the neural network,this paper presents the neural network data fusion fault diagnosis method bas...According to the time-frequency localization characteristic of the wavelet transform (WT)and the nonlinear reflection of the neural network,this paper presents the neural network data fusion fault diagnosis method based on wavelet transform.The network construction and the signal processing steps are introduced in detail.The correct result was attained by using this method in rotary machinery fault diagnosis.It proves the method efficient in fault diagnosis, which is expected to have a wide application.展开更多
Field experimental seismic sounding permitted us to obtain optimal shallow seismic reflection sounding parameters.In process of data processing,we obtained a high-qualitative shallow seismic reflection sounding profil...Field experimental seismic sounding permitted us to obtain optimal shallow seismic reflection sounding parameters.In process of data processing,we obtained a high-qualitative shallow seismic reflection sounding profile by using the techniques such as filtering,edition surgical blanking,prediction deconvolution,fitting static correlation of first arrival time,and velocity analysis.Comprehensive analysis on the information of reflection wave groups along the seismic sounding profile and the stratigraphic and neogeochronological data obtained from many drills near the sounding line reveals that the upper termination of the detected fault zone is located at depth of 75~80 m,in the Middle Pleistocene deposits dated to be about 220 ka BP.The continuity,discontinuity,increasing and decreasing amount of reflection wave groups and change of their configurations,in combination with geological columns of drills,permitted us to know that the width of upper termination of the fault zone is 100 m.It can be inferred from the variation of number of reflection wave groups along the profile that the scarp of hidden fault is 200 m wide and the fault is a synsedimentary active fault in the Early Pleistocene and the early stage of Middle Pleistocene.No tectonic movement,which offset the covering deposits,had occurred since the late stage of Middle Pleistocene.展开更多
基金supported by the National Natural Science Foundation of China(61773087)the National Key Research and Development Program of China(2018YFB1601500)High-tech Ship Research Project of Ministry of Industry and Information Technology-Research of Intelligent Ship Testing and Verifacation([2018]473)
文摘Fault prognosis is mainly referred to the estimation of the operating time before a failure occurs,which is vital for ensuring the stability,safety and long lifetime of degrading industrial systems.According to the results of fault prognosis,the maintenance strategy for underlying industrial systems can realize the conversion from passive maintenance to active maintenance.With the increased complexity and the improved automation level of industrial systems,fault prognosis techniques have become more and more indispensable.Particularly,the datadriven based prognosis approaches,which tend to find the hidden fault factors and determine the specific fault occurrence time of the system by analysing historical or real-time measurement data,gain great attention from different industrial sectors.In this context,the major task of this paper is to present a systematic overview of data-driven fault prognosis for industrial systems.Firstly,the characteristics of different prognosis methods are revealed with the data-based ones being highlighted.Moreover,based on the different data characteristics that exist in industrial systems,the corresponding fault prognosis methodologies are illustrated,with emphasis on analyses and comparisons of different prognosis methods.Finally,we reveal the current research trends and look forward to the future challenges in this field.This review is expected to serve as a tutorial and source of references for fault prognosis researchers.
基金the National Natural Science Foundation of China(No.51775090)the General Program of Civil Aviation Flight University of China(No.J2015-39)
文摘In order to increase the fault diagnosis efficiency and make the fault data mining be realized, the decision table containing numerical attributes must be discretized for further calculations. The discernibility matrix-based reduction method depends on whether the numerical attributes can be properly discretized or not.So a discretization algorithm based on particle swarm optimization(PSO) is proposed. Moreover, hybrid weights are adopted in the process of particles evolution. Comparative calculations for certain equipment are completed to demonstrate the effectiveness of the proposed algorithm. The results indicate that the proposed algorithm has better performance than other popular algorithms such as class-attribute interdependence maximization(CAIM)discretization method and entropy-based discretization method.
基金supported by Chinese Joint Seismological Science Foundation(A07005)basic research foundation from Institute of Earthquake Science,and State Key Basic Research De-velopment and Programming Project of China(2004CB418403)
文摘The Hori＇s inverse method based on spectral decomposition was applied to estimate coseismic slip distribution on the rupture plane of the 14 November 2001 Ms8.1 Kunlun earthquake based on GPS survey results. The inversion result shows that the six sliding models can be constrained by the coseismic GPS data. The established slips mainly concentrated along the eastern segment of the fault rupture, and the maximum magnitude is about 7 m. Slip on the eastern segment of the fault rupture represents as purely left-lateral strike-slip. Slip on the western segment of the seismic rupture represents as mainly dip-stip with the maximum dip-slip about 1 m. Total predicted scalar seismic moment is 5.196× 10^2° N.m. Our results constrained by geodetic data are consistent with seismological results.
基金supported by the National Natural Science Foundation of China (61202078 61071139)the National High Technology Research and Development Program of China (863 Program)(SQ2011AA110101)
文摘The data-driven fault diagnosis methods can improve the reliability of analog circuits by using the data generated from it. The data have some characteristics, such as randomness and incompleteness, which lead to the diagnostic results being sensitive to the specific values and random noise. This paper presents a data-driven fault diagnosis method for analog circuits based on the robust competitive agglomeration （RCA）, which can alleviate the incompleteness of the data by clustering with the competing process. And the robustness of the diagnostic results is enhanced by using the approach of robust statistics in RCA. A series of experiments are provided to demonstrate that RCA can classify the incomplete data with a high accuracy. The experimental results show that RCA is robust for the data needed to be classified as well as the parameters needed to be adjusted. The effectiveness of RCA in practical use is demonstrated by two analog circuits.
基金Supported by National Basic Research Program of China （973 Program） （2009CB320600）, National Natural Science Foundation of China （60828007, 60534010, 60821063）, the Leverhulme Trust （F/00. 120/BC） in the United Kingdom, and the 111 Project （B08015）
基金supported by the Special Fund of Fundamental Scientific Research Business Expense for Higher School of Central Government(Projects for creation teams ZY20110101)NSFC 41090294talent selection and training plan project of Hebei university
文摘We analyze co-seismic displacement field of the 26 December 2004, giant Sumatra–Andaman earthquake derived from Global Position System observations,geological vertical measurement of coral head, and pivot line observed through remote sensing. Using the co-seismic displacement field and AK135 spherical layered Earth model, we invert co-seismic slip distribution along the seismic fault. We also search the best fault geometry model to fit the observed data. Assuming that the dip angle linearly increases in downward direction, the postfit residual variation of the inversed geometry model with dip angles linearly changing along fault strike are plotted. The geometry model with local minimum misfits is the one with dip angle linearly increasing along strike from 4.3oin top southernmost patch to 4.5oin top northernmost path and dip angle linearly increased. By using the fault shape and geodetic co-seismic data, we estimate the slip distribution on the curved fault. Our result shows that the earthquake ruptured ＊200-km width down to a depth of about 60 km.0.5–12.5 m of thrust slip is resolved with the largest slip centered around the central section of the rupture zone78N–108N in latitude. The estimated seismic moment is8.2 9 1022 N m, which is larger than estimation from the centroid moment magnitude（4.0 9 1022 N m）, and smaller than estimation from normal-mode oscillation data modeling（1.0 9 1023 N m）.
基金supported by the National Key R&D Program of China(2018YFC1503606 2017YFC1500502)Earthquake Tracking Task(2019010215)
文摘Based on GPS velocity during 1999-2007,GPS baseline time series on large scale during1999-2008 and cross-fault leveling data during 1985-2008,the paper makes some analysis and discussion to study and summarize the movement,tectonic deformation and strain accumulation evolution characteristics of the Longmenshan fault and the surrounding area before the MS8. 0 Wenchuan earthquake,as well as the possible physical mechanism late in the seismic cycle of the Wenchuan earthquake. Multiple results indicate that:GPS velocity profiles show that obvious continuous deformation across the eastern Qinghai-Tibetan Plateau before the earthquake was distributed across a zone at least 500 km wide,while there was little deformation in Sichuan Basin and Longmenshan fault zone,which means that the eastern Qinghai-Tibetan Plateau provides energy accumulation for locked Longmenshan fault zone continuously. GPS strain rates show that the east-west compression deformation was larger in the northwest of the mid-northern segment of the Longmenshan fault zone,and deformation amplitude decreased gradually from far field to near fault zone,and there was little deformation in fault zone. The east-west compression deformation was significant surrounding the southwestern segment of the Longmenshan fault zone,and strain accumulation rate was larger than that of mid-northern segment.Fault locking indicates nearly whole Longmenshan fault was locked before the earthquake except the source of the earthquake which was weakly locked,and a 20 km width patch in southwestern segment between 12 km to 22. 5 km depth was in creeping state. GPS baseline time series in northeast direction on large scale became compressive generally from 2005 in the North-South Seismic Belt,which reflects that relative compression deformation enhances. The cross-fault leveling data show that annual vertical change rate and deformation trend accumulation rate in the Longmenshan fault zone were little,which indicates that vertical activity near the fault was very weak and the fault was tightly locked. According to analyses of GPS and cross-fault leveling data before the Wenchuan earthquake,we consider that the Longmenshan fault is tightly locked from the surface to the deep,and the horizontal and vertical deformation are weak surrounding the fault in relatively small-scale crustal deformation. The process of weak deformation may be slow,and weak deformation area may be larger when large earthquake is coming. Continuous and slow compression deformation across eastern Qinghai-Tibetan Plateau before the earthquake provides dynamic support for strain accumulation in the Longmenshan fault zone in relative large-scale crustal deformation.
文摘As the demand for wind energy continues to grow at exponential rate, reducing operation and maintenance (O & M) costs and improving reliability have become top priorities in wind turbine maintenance strategies. Prediction of wind turbine failures before they reach a catastrophic stage is critical to reduce the O & M cost due to unnecessary scheduled maintenance. A SCADA-data based condition monitoring system, which takes advantage of data already collected at the wind turbine controller, is a cost-effective way to monitor wind turbines for early warning of failures. This article proposes a methodology of fault prediction and automatically generating warning and alarm for wind turbine main bearings based on stored SCADA data using Artificial Neural Network (ANN). The ANN model of turbine main bearing normal behavior is established and then the deviation between estimated and actual values of the parameter is calculated. Furthermore, a method has been developed to generate early warning and alarm and avoid false warnings and alarms based on the deviation. In this way, wind farm operators are able to have enough time to plan maintenance, and thus, unanticipated downtime can be avoided and O & M costs can be reduced.
基金Supported by State Key Program of National Natural Science Foundation of China （60934009） National Natural Science Foundations of China （60801048 60974062）
文摘The bug tracking system is well known as the project support tool of open source software. There are many categorical data sets recorded on the bug tracking system. In the past, many reliability assessment methods have been proposed in the research area of software reliability. Also, there are several software project analyses based on the software effort data such as the earned value management. In particular, the software reliability growth models can </span><span style="font-family:Verdana;">apply to the system testing phase of software development. On the other</span><span style="font-family:Verdana;"> hand, the software effort analysis can apply to all development phase, because the fault data is only recorded on the testing phase. We focus on the big fault data and effort data of open source software. Then, it is difficult to assess by using the typical statistical assessment method, because the data recorded on the bug tracking system is large scale. Also, we discuss the jump diffusion process model based on the estimation method of jump parameters by using the discriminant analysis. Moreover, we analyze actual big fault data to show numerical examples of software effort assessment considering many categorical data set.
基金supported by the Natural Science Foundation of Jiangsu Province (BK2006202)
文摘Focusing on the networked control system with long time-delays and data packet dropout,the problem of observerbased fault detection of the system is studied.According to conditions of data arrival of the controller,the state observers of the system are designed to detect faults when they occur in the system.When the system is normal,the observers system is modeled as an uncertain switched system.Based on the model,stability condition of the whole system is given.When conditions are satisfied,the system is asymptotically stable.When a fault occurs,the observers residual can change rapidly to detect the fault.A numerical example shows the effectiveness of the proposed method.
文摘In this study, Landsat 5 Thematic Mapper (TM) and SPOT HRV Panchromatic data were analysed to determine the geometry of an active fault segment (the Ganos segment) in Gazikoy-Saros region, west of Marmara Sea, Turkey. Gazikoy-Saros/Ganos segment is a part of North Anatolian Fault Zone (NAFZ). North-Anatolian fault is considered to be one of the most important active strike-slip faults in the world. Thus far in relevant researches based on Gazikoy-Saros segment a single straight fault line representation is used on the fault descriptive geological maps. This study, with the aid of enhanced remotely sensed data aims to reveal the linear details of the NAFZ fault segment, which subsequently were superposed with a Digital Elevation Model (DEM) data. Respectively, using these data the surface geometry expression of Gazikoy-Saros fault segment was detailed and remapped. According to the results of the analysis two small releasing steps were identified on this segment. The first one is situated between Mürseli and Güzelkoy villages, and the second one is between Mürseli and Yorguc villages. In addition to this, it is found that the fault strike bends approximately 7° further to in south-eastern (SE) direction between Yenikoy and Sofular villages. This angular change was defined with the advantage of multi-angular viewing capability of the multi-satellite sensors and DEM data. The newly generated surface geometry expression of Ganos segment was compared with Global Positioning System (GPS) velocity vectors.
基金financially supported by Guangdong Provincial Science and Technology Plan Projects(20178030314082)General Project of National Natural Science Foundation of China (41676057)National Science and Technology Support Program (2015BAK18B01)
文摘By systemic processing, comprehensive analysis, and interpretation of gravity data, we confirmed the existence of the west segment of the coastal fault zone(west of Yangjiang to Beibu Bay) in the coastal region of South China. This showed an apparent high gravity gradient in the NEE direction, and worse linearity and less compactness than that in the Pearl River month. This also revealed a relatively large curvature and a complicated gravity structure. In the finding images processed by the gravity data system, each fault was well reflected and primarily characterized by isolines or thick black stripes with a cutting depth greater than 30 km. Though mutually cut by NW-trending and NE-trending faults, the apparent NEE stripe-shaped structure of the west segment of the coastal fault zone remained unchanged,with good continuity and an activity strength higher than that of NW and NE-trending faults. Moreover,we determined that the west segment of the coastal fault zone is the major seismogenic structure responsible for strong earthquakes in the coastal region in the border area of Guangdong, Guangxi, and Hainan.
基金the National Natural Science Foundation of China(No.51205018)the Fundamental Research Funds for the Central Universities of China(No.FRF-TP-14-121A2)the Research Project of State Key Laboratory of Mechanical System and Vibration(No.MSV-2014-09)
文摘Wind energy is one of the widely applied renewable energies in the world. Wind turbine as the main wind energy converter at present has very complex technical system containing a huge number of components,actuators and sensors. However, despite of the hardware redundancy, sensor faults have often affected the wind turbine normal operation and thus caused energy generation loss. In this paper, aiming at the wind turbine hydraulic pitch system, data-driven design of process monitoring(PM) and diagnosis has been realized in the wind turbine benchmark. Fault tolerant control(FTC) strategies focused on sensor faults have also been presented here, where with the implementation of soft sensor the sensor fault can be handled and the performance of the system is improved. The performance of this method is demonstrated with the wind turbine benchmark provided by Math Works.
文摘This article studies the fault recorder in power system and introduces the Comtrade format. Andituses C++ programming to read recorded fault data and adopts Fourier analysis and symmetrical component method to filter and extract fundamental waves. Finally the effectiveness of the data processing method introduced in this paper is verified by CAAP software.
文摘The </span></span><span><span><span style="font-family:"">software reliability model is the stochastic model to measure the software <span>reliability quantitatively. A Hazard-Rate Model is </span></span></span></span><span><span><span style="font-family:"">the </span></span></span><span><span><span style="font-family:"">well</span></span></span><span><span><span style="font-family:"">-</span></span></span><span><span><span style="font-family:"">known one as the</span></span></span><span><span><span style="font-family:""> typical software reliability model. We propose Hazard-Rate Models Consider<span>ing Fault Severity Levels (CFSL) for Open Source Software (OSS). The purpose of </span><span>this research is to </span></span></span></span><span><span><span style="font-family:"">make </span></span></span><span><span><span style="font-family:"">the Hazard-Rate Model considering CFSL adapt to</span></span></span><span><span><span style="font-family:""> </span></span></span><span><span><span style="font-family:"">baseline hazard function and 2 kinds of faults data in Bug Tracking System <span>(BTS)</span></span></span></span><span><span><span style="font-family:"">,</span></span></span><span><span><span style="font-family:""> <i>i.e.</i>, we use the covariate vectors in Cox proportional Hazard-Rate</span></span></span><span><span><span style="font-family:""> Model. Also, <span>we show the numerical examples by evaluating the performance of our pro</span><span>posed model. As the result, we compare the performance of our model with the</span> Hazard-Rate Model CFSL.
文摘While sensor networks have been used in various applications because of the automatic sensing capability and ad-hoc organization of sensor nodes, the fault-prone characteristic of sensor networks has challenged the event detection and the anomaly detection which, to some extent, have neglected the importance of discriminating events and errors. Considering data uncertainty, in this article, we present the problem of data discrimination in fault-prone sensor networks, analyze the similarities and the differences between events and errors, and design a multi-level systematic discrimination framework. In each step, the framework filters erroneous data from the raw data and marks potential event samples for the next-step processing. The raw data set D is finally partitioned into three subsets, Devent, Derror and Dordinary. Both the scenario-based simulations and the experiments on real-sensed data are carried out. The statistical results of various discrimination metrics demonstrate high distinction ratio as well as the robustness in different cases of the network.
文摘Wind power generation is a mature kind of technology, economic, environmental protection of new energy, it has a broad space for development. Wind turbine is a complex electromechanical system with complex structure and many components. It is often located in remote mountainous areas, often encountering storms, lightning, ice, salt fog and other extreme weather. Due to its harsh working environment, it has appeared a lot of faults, and its low reliability and high maintenance cost, which brings great challenges to the safe operation of wind power generation equipment. Based on this, this paper is based on the actual failure data of domestic wind turbine, uses the Pareto curve and other analysis methods of the main components of domestic wind turbine, and accordingly formulated the corresponding maintenance countermeasures.
文摘According to the time-frequency localization characteristic of the wavelet transform (WT)and the nonlinear reflection of the neural network,this paper presents the neural network data fusion fault diagnosis method based on wavelet transform.The network construction and the signal processing steps are introduced in detail.The correct result was attained by using this method in rotary machinery fault diagnosis.It proves the method efficient in fault diagnosis, which is expected to have a wide application.
基金A High-new Technique Project by State Development and Planning Commission of China (2001977).
文摘Field experimental seismic sounding permitted us to obtain optimal shallow seismic reflection sounding parameters.In process of data processing,we obtained a high-qualitative shallow seismic reflection sounding profile by using the techniques such as filtering,edition surgical blanking,prediction deconvolution,fitting static correlation of first arrival time,and velocity analysis.Comprehensive analysis on the information of reflection wave groups along the seismic sounding profile and the stratigraphic and neogeochronological data obtained from many drills near the sounding line reveals that the upper termination of the detected fault zone is located at depth of 75~80 m,in the Middle Pleistocene deposits dated to be about 220 ka BP.The continuity,discontinuity,increasing and decreasing amount of reflection wave groups and change of their configurations,in combination with geological columns of drills,permitted us to know that the width of upper termination of the fault zone is 100 m.It can be inferred from the variation of number of reflection wave groups along the profile that the scarp of hidden fault is 200 m wide and the fault is a synsedimentary active fault in the Early Pleistocene and the early stage of Middle Pleistocene.No tectonic movement,which offset the covering deposits,had occurred since the late stage of Middle Pleistocene.
