This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for ...This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for identifying critical failure modes and their root causes,while BN introduces flexibility in probabilistic reasoning,enabling dynamic updates based on new evidence.This dual methodology overcomes the limitations of static FTA models,offering a comprehensive framework for system reliability analysis.Critical failures,including External Leakage(ELU),Failure to Start(FTS),and Overheating(OHE),were identified as key risks.By incorporating redundancy into high-risk components such as pumps and batteries,the likelihood of these failures was significantly reduced.For instance,redundant pumps reduced the probability of ELU by 31.88%,while additional batteries decreased the occurrence of FTS by 36.45%.The results underscore the practical benefits of combining FTA and BN for enhancing system reliability,particularly in maritime applications where operational safety and efficiency are critical.This research provides valuable insights for maintenance planning and highlights the importance of redundancy in critical systems,especially as the industry transitions toward more autonomous vessels.展开更多
This paper presents an approximate algorithm based on simulated annealing to achieve the maximum probability of the minimal cut sets for a fault tree. Near optimal minimal cut sets and important sequence of the basic ...This paper presents an approximate algorithm based on simulated annealing to achieve the maximum probability of the minimal cut sets for a fault tree. Near optimal minimal cut sets and important sequence of the basic events are also solved by the method. Computer simulations show that the algorithm performs very well.展开更多
Epidemic hemorrhagic fever has been an ongoing threat to laboratory personnel involved in animal care and use. Laboratory transmissions and severe infections occurred over the past twenty years, even though the standa...Epidemic hemorrhagic fever has been an ongoing threat to laboratory personnel involved in animal care and use. Laboratory transmissions and severe infections occurred over the past twenty years, even though the standards and regulations for laboratory biosafety have been issued, upgraded, and implemented in China. Therefore, there is an urgent need to identify risk factors and to seek effective preventive measures that can curb the incidences of epidemic hemorrhagic fever among laboratory personnel. In the present study, we reviewed literature that relevant to animals laboratory-acquired hemorrhagic fever infections reported from 1995 to 2015, and analyzed these incidences using fault tree analysis （FTA）.展开更多
Due to the strong attacking ability, fast speed, simple implementation and other characteristics, differential fault analysis has become an important method to evaluate the security of cryptosystem in the Internet of ...Due to the strong attacking ability, fast speed, simple implementation and other characteristics, differential fault analysis has become an important method to evaluate the security of cryptosystem in the Internet of Things. As one of the AES finalists, the Serpent is a 128-bit Substitution-Permutation Network(SPN) cryptosystem. It has 32 rounds with the variable key length between 0 and 256 bits, which is flexible to provide security in the Internet of Things. On the basis of the byte-oriented model and the differential analysis, we propose an effective differential fault attack on the Serpent cryptosystem. Mathematical analysis and simulating experiment show that the attack could recover its secret key by introducing 48 faulty ciphertexts. The result in this study describes that the Serpent is vulnerable to differential fault analysis in detail. It will be beneficial to the analysis of the same type of other iterated cryptosystems.展开更多
The lathes are basic machine tools for manufacturing cylindrical parts. In recent years, the DLseries computer numerical control(CNC) heavy-duty horizontal lathes(HDHLs) have been widely used in the transportation, en...The lathes are basic machine tools for manufacturing cylindrical parts. In recent years, the DLseries computer numerical control(CNC) heavy-duty horizontal lathes(HDHLs) have been widely used in the transportation, energy and aviation industries. High availability of the CNC heavy-duty lathes is demanded to guarantee the efficiency and benefit of these manufacturing industries. As one of the key subsystems of the HDHLs, the feeding control system is studied in this paper on reliability modeling and reliability analysis. The fault tree analysis(FTA) method is used for reliability modelling of the feeding control system. Considering the multiple common cause failure groups(CCFGs) existing in the system, a modified beta factor parametric model is introduced to model the common cause failure(CCF) in system. The reliability of feeding control system is then obtained and the effect of CCF on the reliability of the whole system is studied as well.展开更多
Based on wavelet packet decomposition （WPD） algorithm and Teager energy operator （TEO）, a novel gearbox fault detection and diagnosis method is proposed. Its process is expatiated after the principles of WPD and T...Based on wavelet packet decomposition （WPD） algorithm and Teager energy operator （TEO）, a novel gearbox fault detection and diagnosis method is proposed. Its process is expatiated after the principles of WPD and TEO modulation are introduced respectively. The preprocessed sigaaal is interpolated with the cubic spline function, then expanded over the selected basis wavelets. Grouping its wavelet packet components of the signal based on the minimum entropy criterion, the interpolated signal can be decomposed into its dominant components with nearly distinct fault frequency contents. To extract the demodulation information of each dominant component, TEO is used. The performance of the proposed method is assessed by means of several tests on vibration signals collected from the gearbox mounted on a heavy truck. It is proved that hybrid WPD-TEO method is effective and robust for detecting and diagnosing localized gearbox faults.展开更多
Fault degradation prognostic, which estimates the time before a failure occurs and process breakdowns, has been recognized as a key component in maintenance strategies nowadays. Fault degradation processes are, in gen...Fault degradation prognostic, which estimates the time before a failure occurs and process breakdowns, has been recognized as a key component in maintenance strategies nowadays. Fault degradation processes are, in general,slowly varying and can be modeled by autoregressive models. However, industrial processes always show typical nonstationary nature, which may bring two challenges: how to capture fault degradation information and how to model nonstationary processes. To address the critical issues, a novel fault degradation modeling and online fault prognostic strategy is developed in this paper. First, a fault degradation-oriented slow feature analysis(FDSFA) algorithm is proposed to extract fault degradation directions along which candidate fault degradation features are extracted. The trend ability assessment is then applied to select major fault degradation features. Second, a key fault degradation factor(KFDF) is calculated to characterize the fault degradation tendency by combining major fault degradation features and their stability weighting factors. After that, a time-varying regression model with temporal smoothness regularization is established considering nonstationary characteristics. On the basis of updating strategy, an online fault prognostic model is further developed by analyzing and modeling the prediction errors. The performance of the proposed method is illustrated with a real industrial process.展开更多
Finite Element (FE) modeling under plane stress condition is used to analyze the fault type variation with depth along and around the San Andreas Fault (SAF) zone. In this simulation elastic rheology was used and was ...Finite Element (FE) modeling under plane stress condition is used to analyze the fault type variation with depth along and around the San Andreas Fault (SAF) zone. In this simulation elastic rheology was used and was thought justifiable as the variation in depth from 0.5 km to 20 km was considered. Series of calculations were performed with the variation in domain properties. Three types of models were created based on simple geological map of California, namely, 1) single domain model considering whole California as one homogeneous domain, 2) three domains model including the North American plate, Pacific plate, and SAF zone as separate domains, and 3) Four domains model including the three above plus the Garlock Fault zone. Mohr-Coulomb failure criterion and Byerlee's law were used for the calculation of failure state. All the models were driven by displacement boundary condition imposing the fixed North American plate and Pacific plate motion along N34°W vector up to the northern terminus of SAF and N50°E vector motion for the subducting the Gorda and Juan de Fuca plates. Our simulated results revealed that as the depth increased, the fault types were generally normal, and at shallow depth greater strike slip and some thrust faults were formed. It is concluded that SAF may be terminated as normal fault at depth although the surface expression is clearly strike slip.展开更多
Expert knowledge is the key to modeling milling fault detection systems based on the belief rule base.The construction of an initial expert knowledge base seriously affects the accuracy and interpretability of the mil...Expert knowledge is the key to modeling milling fault detection systems based on the belief rule base.The construction of an initial expert knowledge base seriously affects the accuracy and interpretability of the milling fault detection model.However,due to the complexity of the milling system structure and the uncertainty of the milling failure index,it is often impossible to construct model expert knowledge effectively.Therefore,a milling system fault detection method based on fault tree analysis and hierarchical BRB(FTBRB)is proposed.Firstly,the proposed method uses a fault tree and hierarchical BRB modeling.Through fault tree analysis(FTA),the logical correspondence between FTA and BRB is sorted out.This can effectively embed the FTA mechanism into the BRB expert knowledge base.The hierarchical BRB model is used to solve the problem of excessive indexes and avoid combinatorial explosion.Secondly,evidence reasoning(ER)is used to ensure the transparency of the model reasoning process.Thirdly,the projection covariance matrix adaptation evolutionary strategies(P-CMA-ES)is used to optimize the model.Finally,this paper verifies the validity model and the method’s feasibility techniques for milling data sets.展开更多
Fault prognosis is one of the key techniques for prognosis and health management,and an effective fault feature can improve prediction accuracy and performance. A novel approach of feature extraction for fault prognos...Fault prognosis is one of the key techniques for prognosis and health management,and an effective fault feature can improve prediction accuracy and performance. A novel approach of feature extraction for fault prognosis based on fault trend analysis was proposed in this paper. In order to describe the ability of tracking fault growth process,definitions and calculations of fault trackability was developed, and the feature which had the maximum fault trackability was selected for fault prognosis. The vibration data in bearing life tests were used to verify the effectiveness of the method was proposed. The results showed that the trackability of energy entropy for bearing fault growth was the maximum,and it was the best fault feature among selected features root mean square( RMS),kurtosis,new moment and energy entropy. The proposed approach can provide a better strategy for fault feature extraction of bearings in order to improve prediction accuracy.展开更多
A novel approach named aligned mixture probabilistic principal component analysis(AMPPCA) is proposed in this study for fault detection of multimode chemical processes. In order to exploit within-mode correlations,the...A novel approach named aligned mixture probabilistic principal component analysis(AMPPCA) is proposed in this study for fault detection of multimode chemical processes. In order to exploit within-mode correlations,the AMPPCA algorithm first estimates a statistical description for each operating mode by applying mixture probabilistic principal component analysis(MPPCA). As a comparison, the combined MPPCA is employed where monitoring results are softly integrated according to posterior probabilities of the test sample in each local model. For exploiting the cross-mode correlations, which may be useful but are inadvertently neglected due to separately held monitoring approaches, a global monitoring model is constructed by aligning all local models together. In this way, both within-mode and cross-mode correlations are preserved in this integrated space. Finally, the utility and feasibility of AMPPCA are demonstrated through a non-isothermal continuous stirred tank reactor and the TE benchmark process.展开更多
Currently, some fault prognosis technology occasionally has relatively unsatisfied performance especially for in- cipient faults in nonlinear processes duo to their large time delay and complex internal connection. To...Currently, some fault prognosis technology occasionally has relatively unsatisfied performance especially for in- cipient faults in nonlinear processes duo to their large time delay and complex internal connection. To overcome this deficiency, multivariate time delay analysis is incorporated into the high sensitive local kernel principal component analysis. In this approach, mutual information estimation and Bayesian information criterion （BIC） are separately used to acquire the correlation degree and time delay of the process variables. Moreover, in order to achieve prediction, time series prediction by back propagation （BP） network is applied whose input is multivar- iate correlated time series other than the original time series. Then the multivariate time delayed series and future values obtained by time series prediction are combined to construct the input of local kernel principal component analysis （LKPCA） model for incipient fault prognosis. The new method has been exemplified in a sim- ple nonlinear process and the complicated Tennessee Eastman （TE） benchmark process. The results indicate that the new method has suoerioritv in the fault prognosis sensitivity over other traditional fault prognosis methods.展开更多
The behavior of matrix converter(MC) drive systems under the condition of MC short-circuit faults is comprehensively investigated. Two isolation strategies using semiconductors and high speed fuses(HSFs) for MC short-...The behavior of matrix converter(MC) drive systems under the condition of MC short-circuit faults is comprehensively investigated. Two isolation strategies using semiconductors and high speed fuses(HSFs) for MC short-circuit faults are examined and their performances are compared. The behavior of MC drive systems during the fuse action time under different operating conditions is explored. The feasibility of fault-tolerant operation during the fuse action time is also studied. The basic selection laws for the HSFs and the requirements for the passive components of the MC drive system from the point view of short-circuit faults are also discussed. Simulation results are used to demonstrate the feasibility of the proposed isolation strategies.展开更多
Substitution permutation network (SPN) is one important structure of block cipher cryptosystems. Prior work has shown different fault analyses on SPN. The formalization of fault analysis of both attack and protect on ...Substitution permutation network (SPN) is one important structure of block cipher cryptosystems. Prior work has shown different fault analyses on SPN. The formalization of fault analysis of both attack and protect on SPN have been given. The overhead and time tolerance of fault detection have been discussed. The pseudo-blinding method to detect fault attack is introduced, and the balance of the security, overhead and time tolerance based on the evaluation could be made.展开更多
SKINNY-64-64 is a lightweight block cipher with a 64-bit block length and key length,and it is mainly used on the Internet of Things(IoT).Currently,faults can be injected into cryptographic devices by attackers in a v...SKINNY-64-64 is a lightweight block cipher with a 64-bit block length and key length,and it is mainly used on the Internet of Things(IoT).Currently,faults can be injected into cryptographic devices by attackers in a variety of ways,but it is still difficult to achieve a precisely located fault attacks at a low cost,whereas a Hardware Trojan(HT)can realize this.Temperature,as a physical quantity incidental to the operation of a cryptographic device,is easily overlooked.In this paper,a temperature-triggered HT(THT)is designed,which,when activated,causes a specific bit of the intermediate state of the SKINNY-64-64 to be flipped.Further,in this paper,a THT-based algebraic fault analysis(THT-AFA)method is proposed.To demonstrate the effectiveness of the method,experiments on algebraic fault analysis(AFA)and THT-AFA have been carried out on SKINNY-64-64.In the THT-AFA for SKINNY-64-64,it is only required to activate the THT 3 times to obtain the master key with a 100%success rate,and the average time for the attack is 64.57 s.However,when performing AFA on this cipher,we provide a relation-ship between the number of different faults and the residual entropy of the key.In comparison,our proposed THT-AFA method has better performance in terms of attack efficiency.To the best of our knowledge,this is the first HT attack on SKINNY-64-64.展开更多
PRINCE is a 64-bit lightweight block cipher with a 128-bit key published at ASIACRYPT 2012. Assuming one nibble fault is injected, previous different fault analysis(DFA) on PRINCE adopted the technique from DFA on AES...PRINCE is a 64-bit lightweight block cipher with a 128-bit key published at ASIACRYPT 2012. Assuming one nibble fault is injected, previous different fault analysis(DFA) on PRINCE adopted the technique from DFA on AES and current results are different. This paper aims to make a comprehensive study of algebraic fault analysis(AFA) on PRINCE. How to build the equations for PRINCE and faults are explained. Extensive experiments are conducted. Under nibble-based fault model, AFA with three or four fault injections can succeed within 300 seconds with a very high probability. Under other fault models such as byte-based, half word-based, word-based fault models, the faults become overlapped in the last round and previous DFAs are difficult to work. Our results show that AFA can still succeed to recover the full master key. To evaluate security of PRINCE against fault attacks, we utilize AFA to calculate the reduced entropy of the secret key for given amount of fault injections. The results can interpret and compare the efficiency of previous work. Under nibble-based fault model, the master key of PRINCE can be reduced to 29.69 and 236.10 with 3 and 2 fault injections on average, respectively.展开更多
KLEIN-64 is a lightweight block cipher designed for resource-constrained environment,and it has advantages in software performance and hardware implementation.Recent investigation shows that KLEIN-64 is vulnerable to ...KLEIN-64 is a lightweight block cipher designed for resource-constrained environment,and it has advantages in software performance and hardware implementation.Recent investigation shows that KLEIN-64 is vulnerable to differential fault attack(DFA).In this paper,an improved DFA is performed to KLEIN-64.It is found that the differential propagation path and the distribution of the S-box can be fully utilized to distinguish the correct and wrong keys when a half-byte fault is injected in the 10th round.By analyzing the difference matrix before the last round of S-box,the location of fault injection can be limited to a small range.Thus,this improved analysis can greatly improve the attack efficiency.For the best case,the scale of brute-force attack is only 256.While for the worst case,the scale of brute-force attack is far less than 232 with another half byte fault injection,and the probability for this case is 1/64.Furthermore,the measures for KLEIN-64 in resisting the improved DFA are proposed.展开更多
A common software to analyze fuze fault tree is developed to simplify the trivialness in generating the fuze fault tree and reduce the manual calculation work. The overall structure, function and implementation of the...A common software to analyze fuze fault tree is developed to simplify the trivialness in generating the fuze fault tree and reduce the manual calculation work. The overall structure, function and implementation of the system are introduced. The software based on Windows platform is used to generate the fuze fault tree in graphics mode. A quantitative analysis of fuze fault tree can be obtained by the method of minimum cut sets. A calculation example is used to verify the function of the software. Consequently, the expected requirements of this software system are achieved to a certain level.展开更多
A fault sensitivity analysis（FSA）-resistance model based on time randomization is proposed.The randomization unit is composed of two parts,namely the configurable register array（R-A）and the decoder（chiefly random...A fault sensitivity analysis（FSA）-resistance model based on time randomization is proposed.The randomization unit is composed of two parts,namely the configurable register array（R-A）and the decoder（chiefly random number generator,RNG）.In this way,registers chosen can be either valid or invalid depending on the configuration information generated by the decoder.Thus,the fault sensitivity information can be confusing.Meanwhile,based on this model,a defensive scheme is designed to resist both fault sensitivity analysis（FSA）and differential power analysis（DPA）.This scheme is verified with our experiments.展开更多
In consideration of the uncertainty of basic events failure rate and lack of probability statistical information in fault tree analysis( FTA) of excavator variable-frequency speed control system, the interval theory w...In consideration of the uncertainty of basic events failure rate and lack of probability statistical information in fault tree analysis( FTA) of excavator variable-frequency speed control system, the interval theory was employed and combined with conventional FTA method. The basic events failure probabilities were described by interval numbers,and the interval operators of logical gates in FTA were deduced based on interval theory. Finally,the reliability assessment of excavator variable-frequency speed control system was done by interval FTA method. The result shows that the interval FTA method is suitable for the complex system with insufficient failure data.展开更多
基金supported by Istanbul Technical University(Project No.45698)supported through the“Young Researchers’Career Development Project-training of doctoral students”of the Croatian Science Foundation.
文摘This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for identifying critical failure modes and their root causes,while BN introduces flexibility in probabilistic reasoning,enabling dynamic updates based on new evidence.This dual methodology overcomes the limitations of static FTA models,offering a comprehensive framework for system reliability analysis.Critical failures,including External Leakage(ELU),Failure to Start(FTS),and Overheating(OHE),were identified as key risks.By incorporating redundancy into high-risk components such as pumps and batteries,the likelihood of these failures was significantly reduced.For instance,redundant pumps reduced the probability of ELU by 31.88%,while additional batteries decreased the occurrence of FTS by 36.45%.The results underscore the practical benefits of combining FTA and BN for enhancing system reliability,particularly in maritime applications where operational safety and efficiency are critical.This research provides valuable insights for maintenance planning and highlights the importance of redundancy in critical systems,especially as the industry transitions toward more autonomous vessels.
文摘This paper presents an approximate algorithm based on simulated annealing to achieve the maximum probability of the minimal cut sets for a fault tree. Near optimal minimal cut sets and important sequence of the basic events are also solved by the method. Computer simulations show that the algorithm performs very well.
基金supported by Special Fund for Health Sector of China[Grant No.201302006]
文摘Epidemic hemorrhagic fever has been an ongoing threat to laboratory personnel involved in animal care and use. Laboratory transmissions and severe infections occurred over the past twenty years, even though the standards and regulations for laboratory biosafety have been issued, upgraded, and implemented in China. Therefore, there is an urgent need to identify risk factors and to seek effective preventive measures that can curb the incidences of epidemic hemorrhagic fever among laboratory personnel. In the present study, we reviewed literature that relevant to animals laboratory-acquired hemorrhagic fever infections reported from 1995 to 2015, and analyzed these incidences using fault tree analysis （FTA）.
基金supported by the National Natural Science Foundation of China under Grant No.61003278,No.61073150 and No.61202371Innovation Program of Shanghai Municipal Education Commission under Grant No.14ZZ066+5 种基金the open research fund of State Key Laboratory of Information Securitythe Opening Project of Shanghai Key Laboratory of Integrate Administration Technologies for Information Securitythe Fundamental Research Funds for the Central Universities,National Key Basic Research Program of China under Grant No.2013CB338004China Postdoctoral Science Foundation under Grant No.2012M521829Shanghai Postdoctoral Research Funding Program under Grant No.12R21414500the National Social Science Foundation of China under Grant No.13CFX054
文摘Due to the strong attacking ability, fast speed, simple implementation and other characteristics, differential fault analysis has become an important method to evaluate the security of cryptosystem in the Internet of Things. As one of the AES finalists, the Serpent is a 128-bit Substitution-Permutation Network(SPN) cryptosystem. It has 32 rounds with the variable key length between 0 and 256 bits, which is flexible to provide security in the Internet of Things. On the basis of the byte-oriented model and the differential analysis, we propose an effective differential fault attack on the Serpent cryptosystem. Mathematical analysis and simulating experiment show that the attack could recover its secret key by introducing 48 faulty ciphertexts. The result in this study describes that the Serpent is vulnerable to differential fault analysis in detail. It will be beneficial to the analysis of the same type of other iterated cryptosystems.
基金the National Science and Technology Major Project of China(No.2014ZX04014-011)
文摘The lathes are basic machine tools for manufacturing cylindrical parts. In recent years, the DLseries computer numerical control(CNC) heavy-duty horizontal lathes(HDHLs) have been widely used in the transportation, energy and aviation industries. High availability of the CNC heavy-duty lathes is demanded to guarantee the efficiency and benefit of these manufacturing industries. As one of the key subsystems of the HDHLs, the feeding control system is studied in this paper on reliability modeling and reliability analysis. The fault tree analysis(FTA) method is used for reliability modelling of the feeding control system. Considering the multiple common cause failure groups(CCFGs) existing in the system, a modified beta factor parametric model is introduced to model the common cause failure(CCF) in system. The reliability of feeding control system is then obtained and the effect of CCF on the reliability of the whole system is studied as well.
基金This project is supported by National Natural Science Foundation of China (No.50605065)Natural Science Foundation Project of CQ CSTC (No.2007BB2142)
文摘Based on wavelet packet decomposition （WPD） algorithm and Teager energy operator （TEO）, a novel gearbox fault detection and diagnosis method is proposed. Its process is expatiated after the principles of WPD and TEO modulation are introduced respectively. The preprocessed sigaaal is interpolated with the cubic spline function, then expanded over the selected basis wavelets. Grouping its wavelet packet components of the signal based on the minimum entropy criterion, the interpolated signal can be decomposed into its dominant components with nearly distinct fault frequency contents. To extract the demodulation information of each dominant component, TEO is used. The performance of the proposed method is assessed by means of several tests on vibration signals collected from the gearbox mounted on a heavy truck. It is proved that hybrid WPD-TEO method is effective and robust for detecting and diagnosing localized gearbox faults.
基金Project(U1709211) supported by NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization,ChinaProject(ICT2021A15) supported by the State Key Laboratory of Industrial Control Technology,Zhejiang University,ChinaProject(TPL2019C03) supported by Open Fund of Science and Technology on Thermal Energy and Power Laboratory,China。
文摘Fault degradation prognostic, which estimates the time before a failure occurs and process breakdowns, has been recognized as a key component in maintenance strategies nowadays. Fault degradation processes are, in general,slowly varying and can be modeled by autoregressive models. However, industrial processes always show typical nonstationary nature, which may bring two challenges: how to capture fault degradation information and how to model nonstationary processes. To address the critical issues, a novel fault degradation modeling and online fault prognostic strategy is developed in this paper. First, a fault degradation-oriented slow feature analysis(FDSFA) algorithm is proposed to extract fault degradation directions along which candidate fault degradation features are extracted. The trend ability assessment is then applied to select major fault degradation features. Second, a key fault degradation factor(KFDF) is calculated to characterize the fault degradation tendency by combining major fault degradation features and their stability weighting factors. After that, a time-varying regression model with temporal smoothness regularization is established considering nonstationary characteristics. On the basis of updating strategy, an online fault prognostic model is further developed by analyzing and modeling the prediction errors. The performance of the proposed method is illustrated with a real industrial process.
文摘Finite Element (FE) modeling under plane stress condition is used to analyze the fault type variation with depth along and around the San Andreas Fault (SAF) zone. In this simulation elastic rheology was used and was thought justifiable as the variation in depth from 0.5 km to 20 km was considered. Series of calculations were performed with the variation in domain properties. Three types of models were created based on simple geological map of California, namely, 1) single domain model considering whole California as one homogeneous domain, 2) three domains model including the North American plate, Pacific plate, and SAF zone as separate domains, and 3) Four domains model including the three above plus the Garlock Fault zone. Mohr-Coulomb failure criterion and Byerlee's law were used for the calculation of failure state. All the models were driven by displacement boundary condition imposing the fixed North American plate and Pacific plate motion along N34°W vector up to the northern terminus of SAF and N50°E vector motion for the subducting the Gorda and Juan de Fuca plates. Our simulated results revealed that as the depth increased, the fault types were generally normal, and at shallow depth greater strike slip and some thrust faults were formed. It is concluded that SAF may be terminated as normal fault at depth although the surface expression is clearly strike slip.
基金This work was supported in part by the Natural Science Foundation of China under Grant 62203461 and Grant 62203365in part by the Postdoctoral Science Foundation of China under Grant No.2020M683736+3 种基金in part by the Teaching reform project of higher education in Heilongjiang Province under Grant Nos.SJGY20210456 and SJGY20210457in part by the Natural Science Foundation of Heilongjiang Province of China under Grant No.LH2021F038in part by the graduate academic innovation project of Harbin Normal University under Grant Nos.HSDSSCX2022-17,HSDSSCX2022-18 andHSDSSCX2022-19in part by the Foreign Expert Project of Heilongjiang Province under Grant No.GZ20220131.
文摘Expert knowledge is the key to modeling milling fault detection systems based on the belief rule base.The construction of an initial expert knowledge base seriously affects the accuracy and interpretability of the milling fault detection model.However,due to the complexity of the milling system structure and the uncertainty of the milling failure index,it is often impossible to construct model expert knowledge effectively.Therefore,a milling system fault detection method based on fault tree analysis and hierarchical BRB(FTBRB)is proposed.Firstly,the proposed method uses a fault tree and hierarchical BRB modeling.Through fault tree analysis(FTA),the logical correspondence between FTA and BRB is sorted out.This can effectively embed the FTA mechanism into the BRB expert knowledge base.The hierarchical BRB model is used to solve the problem of excessive indexes and avoid combinatorial explosion.Secondly,evidence reasoning(ER)is used to ensure the transparency of the model reasoning process.Thirdly,the projection covariance matrix adaptation evolutionary strategies(P-CMA-ES)is used to optimize the model.Finally,this paper verifies the validity model and the method’s feasibility techniques for milling data sets.
基金National Natural Science Foundation of China(No.51605482)
文摘Fault prognosis is one of the key techniques for prognosis and health management,and an effective fault feature can improve prediction accuracy and performance. A novel approach of feature extraction for fault prognosis based on fault trend analysis was proposed in this paper. In order to describe the ability of tracking fault growth process,definitions and calculations of fault trackability was developed, and the feature which had the maximum fault trackability was selected for fault prognosis. The vibration data in bearing life tests were used to verify the effectiveness of the method was proposed. The results showed that the trackability of energy entropy for bearing fault growth was the maximum,and it was the best fault feature among selected features root mean square( RMS),kurtosis,new moment and energy entropy. The proposed approach can provide a better strategy for fault feature extraction of bearings in order to improve prediction accuracy.
基金Supported by the National Natural Science Foundation of China(61374140)Shanghai Pujiang Program(12PJ1402200)
文摘A novel approach named aligned mixture probabilistic principal component analysis(AMPPCA) is proposed in this study for fault detection of multimode chemical processes. In order to exploit within-mode correlations,the AMPPCA algorithm first estimates a statistical description for each operating mode by applying mixture probabilistic principal component analysis(MPPCA). As a comparison, the combined MPPCA is employed where monitoring results are softly integrated according to posterior probabilities of the test sample in each local model. For exploiting the cross-mode correlations, which may be useful but are inadvertently neglected due to separately held monitoring approaches, a global monitoring model is constructed by aligning all local models together. In this way, both within-mode and cross-mode correlations are preserved in this integrated space. Finally, the utility and feasibility of AMPPCA are demonstrated through a non-isothermal continuous stirred tank reactor and the TE benchmark process.
基金Supported by the National Natural Science Foundation of China(61573051,61472021)the Natural Science Foundation of Beijing(4142039)+1 种基金Open Fund of the State Key Laboratory of Software Development Environment(SKLSDE-2015KF-01)Fundamental Research Funds for the Central Universities(PT1613-05)
文摘Currently, some fault prognosis technology occasionally has relatively unsatisfied performance especially for in- cipient faults in nonlinear processes duo to their large time delay and complex internal connection. To overcome this deficiency, multivariate time delay analysis is incorporated into the high sensitive local kernel principal component analysis. In this approach, mutual information estimation and Bayesian information criterion （BIC） are separately used to acquire the correlation degree and time delay of the process variables. Moreover, in order to achieve prediction, time series prediction by back propagation （BP） network is applied whose input is multivar- iate correlated time series other than the original time series. Then the multivariate time delayed series and future values obtained by time series prediction are combined to construct the input of local kernel principal component analysis （LKPCA） model for incipient fault prognosis. The new method has been exemplified in a sim- ple nonlinear process and the complicated Tennessee Eastman （TE） benchmark process. The results indicate that the new method has suoerioritv in the fault prognosis sensitivity over other traditional fault prognosis methods.
基金Project(50807002) supported by the National Natural Science Foundation of ChinaProject(SKLD10KM05) supported by Opening Fund of State Key Laboratory of Power System and Generation EquipmentsProject(201206025007) supported by the National Scholarship Fund,China
文摘The behavior of matrix converter(MC) drive systems under the condition of MC short-circuit faults is comprehensively investigated. Two isolation strategies using semiconductors and high speed fuses(HSFs) for MC short-circuit faults are examined and their performances are compared. The behavior of MC drive systems during the fuse action time under different operating conditions is explored. The feasibility of fault-tolerant operation during the fuse action time is also studied. The basic selection laws for the HSFs and the requirements for the passive components of the MC drive system from the point view of short-circuit faults are also discussed. Simulation results are used to demonstrate the feasibility of the proposed isolation strategies.
基金National Natural Science Foundation ofChina(No.60573031)Foundation of Na-tional Laboratory for Modern Communica-tions(No.51436060205JW0305)Founda-tion of Senior Visiting Scholarship of Fu-dan University
文摘Substitution permutation network (SPN) is one important structure of block cipher cryptosystems. Prior work has shown different fault analyses on SPN. The formalization of fault analysis of both attack and protect on SPN have been given. The overhead and time tolerance of fault detection have been discussed. The pseudo-blinding method to detect fault attack is introduced, and the balance of the security, overhead and time tolerance based on the evaluation could be made.
基金supported in part by the Natural Science Foundation of Heilongjiang Province of China(Grant No.LH2022F053)in part by the Scientific and technological development project of the central government guiding local(Grant No.SBZY2021E076)+2 种基金in part by the PostdoctoralResearch Fund Project of Heilongjiang Province of China(Grant No.LBH-Q21195)in part by the Fundamental Research Funds of Heilongjiang Provincial Universities of China(Grant No.145209146)in part by the National Natural Science Foundation of China(NSFC)(Grant No.61501275).
文摘SKINNY-64-64 is a lightweight block cipher with a 64-bit block length and key length,and it is mainly used on the Internet of Things(IoT).Currently,faults can be injected into cryptographic devices by attackers in a variety of ways,but it is still difficult to achieve a precisely located fault attacks at a low cost,whereas a Hardware Trojan(HT)can realize this.Temperature,as a physical quantity incidental to the operation of a cryptographic device,is easily overlooked.In this paper,a temperature-triggered HT(THT)is designed,which,when activated,causes a specific bit of the intermediate state of the SKINNY-64-64 to be flipped.Further,in this paper,a THT-based algebraic fault analysis(THT-AFA)method is proposed.To demonstrate the effectiveness of the method,experiments on algebraic fault analysis(AFA)and THT-AFA have been carried out on SKINNY-64-64.In the THT-AFA for SKINNY-64-64,it is only required to activate the THT 3 times to obtain the master key with a 100%success rate,and the average time for the attack is 64.57 s.However,when performing AFA on this cipher,we provide a relation-ship between the number of different faults and the residual entropy of the key.In comparison,our proposed THT-AFA method has better performance in terms of attack efficiency.To the best of our knowledge,this is the first HT attack on SKINNY-64-64.
基金supported in part by the Major State Basic Research Development Program (973 Plan) of China under thegrant 2013CB338004the National Natural Science Foundation of China under the grants 61173191, 61271124, 61272491, 61309021, 61472357+1 种基金by the Zhejiang Provincial Natural Science Foundation of China under the grant LY13F010001by the Fundamental Research Funds for the Central Universities under the grant 2015QNA5005
文摘PRINCE is a 64-bit lightweight block cipher with a 128-bit key published at ASIACRYPT 2012. Assuming one nibble fault is injected, previous different fault analysis(DFA) on PRINCE adopted the technique from DFA on AES and current results are different. This paper aims to make a comprehensive study of algebraic fault analysis(AFA) on PRINCE. How to build the equations for PRINCE and faults are explained. Extensive experiments are conducted. Under nibble-based fault model, AFA with three or four fault injections can succeed within 300 seconds with a very high probability. Under other fault models such as byte-based, half word-based, word-based fault models, the faults become overlapped in the last round and previous DFAs are difficult to work. Our results show that AFA can still succeed to recover the full master key. To evaluate security of PRINCE against fault attacks, we utilize AFA to calculate the reduced entropy of the secret key for given amount of fault injections. The results can interpret and compare the efficiency of previous work. Under nibble-based fault model, the master key of PRINCE can be reduced to 29.69 and 236.10 with 3 and 2 fault injections on average, respectively.
基金This work was supported in part by project supported by National Natural Science Foundation of China(Grant Nos.U1936115,61572182).
文摘KLEIN-64 is a lightweight block cipher designed for resource-constrained environment,and it has advantages in software performance and hardware implementation.Recent investigation shows that KLEIN-64 is vulnerable to differential fault attack(DFA).In this paper,an improved DFA is performed to KLEIN-64.It is found that the differential propagation path and the distribution of the S-box can be fully utilized to distinguish the correct and wrong keys when a half-byte fault is injected in the 10th round.By analyzing the difference matrix before the last round of S-box,the location of fault injection can be limited to a small range.Thus,this improved analysis can greatly improve the attack efficiency.For the best case,the scale of brute-force attack is only 256.While for the worst case,the scale of brute-force attack is far less than 232 with another half byte fault injection,and the probability for this case is 1/64.Furthermore,the measures for KLEIN-64 in resisting the improved DFA are proposed.
文摘A common software to analyze fuze fault tree is developed to simplify the trivialness in generating the fuze fault tree and reduce the manual calculation work. The overall structure, function and implementation of the system are introduced. The software based on Windows platform is used to generate the fuze fault tree in graphics mode. A quantitative analysis of fuze fault tree can be obtained by the method of minimum cut sets. A calculation example is used to verify the function of the software. Consequently, the expected requirements of this software system are achieved to a certain level.
文摘A fault sensitivity analysis（FSA）-resistance model based on time randomization is proposed.The randomization unit is composed of two parts,namely the configurable register array（R-A）and the decoder（chiefly random number generator,RNG）.In this way,registers chosen can be either valid or invalid depending on the configuration information generated by the decoder.Thus,the fault sensitivity information can be confusing.Meanwhile,based on this model,a defensive scheme is designed to resist both fault sensitivity analysis（FSA）and differential power analysis（DPA）.This scheme is verified with our experiments.
基金National High-Tech Research and Development Program(863 Program),China(No.2012AA062001)
文摘In consideration of the uncertainty of basic events failure rate and lack of probability statistical information in fault tree analysis( FTA) of excavator variable-frequency speed control system, the interval theory was employed and combined with conventional FTA method. The basic events failure probabilities were described by interval numbers,and the interval operators of logical gates in FTA were deduced based on interval theory. Finally,the reliability assessment of excavator variable-frequency speed control system was done by interval FTA method. The result shows that the interval FTA method is suitable for the complex system with insufficient failure data.
