In order to solve the problem of low prediction accuracy when only vibration or oil signal is used to predict the remaining life of gear wear,a gear wear life feature fusion prediction method based on temporal pattern...In order to solve the problem of low prediction accuracy when only vibration or oil signal is used to predict the remaining life of gear wear,a gear wear life feature fusion prediction method based on temporal pattern attention mechanism is proposed.Firstly,deep residual shrinkage network(DRSN)is used to extract the features of the original vibration time series signals with low signal-tonoise ratio,and the vibration features associated with gear wear evolution are obtained.Secondly,the extracted vibration features and the oil monitoring data that can intuitively reflect the wear process information are jointly input into the bi-directional long short-term memory neural network based on temporal pattern attention mechanism(TPA-BiLSTM),the complex nonlinear relationship between vibration features,oil features and gear wear process evolution is further explored to improve the prediction accuracy.The gear life cycle dynamic response and wear process signals are obtained based on the gear numerical simulation model,and the feasibility of the proposed method is verified.Finally,the proposed method is applied to the residual life prediction of gear on a test bench,and the comparison between different methods proved the validity of the proposed method.展开更多
Misalignment is one of the most common faults for the diesel engine.In order to eliminate the misalignment fault of the diesel engine in the process of operation,a targeting self-recovery regulation system is construc...Misalignment is one of the most common faults for the diesel engine.In order to eliminate the misalignment fault of the diesel engine in the process of operation,a targeting self-recovery regulation system is constructed by using a movable base and displacement sensors.Misalignment is monitored and detected in real time,the value of misalignment is calculated rapidly and accurately,andintelligent decision is made.Then,the base is moved reversely with a definite target to drive the shaft to translate or rotate,so that the shafts can be recovered to alignment online.A co-simulation model for the self-recovery system is established which consists of a dynamic model of the crankshaft system and control model.The self-recovery regulation process of misalignment is simulated.The simulation results show that the system can accurately calculate the misalignment values,with an error of less than 5%,and can automatically eliminate the misalignment fault of the diesel engine online.The research results provide theoretical support for the self-recovery regulation of misalignment fault,and due to the universality of structure and principle,the self-recovery system is not only suitable for diesel engine,but also for other rotating machineries.展开更多
The fault detection and diagnosis of diesel engine valve clearance can effectively improve the availability and safety of diesel engine and have extremely important value and significance.Diesel engines generally oper...The fault detection and diagnosis of diesel engine valve clearance can effectively improve the availability and safety of diesel engine and have extremely important value and significance.Diesel engines generally operate in various stable operating conditions,which have important influence on the fault diagnosis.However,many fault diagnosis methods have been put forward under specific stable operating condition based on vibration signal.As the result of great impact caused by operating conditions,corresponding diagnosis models cannot deal with the fault diagnosis under different operating conditions with required accuracy.In this paper,a fault diagnosis of diesel engine valve clearance under variable operating condition based on soft interval support vector machine(SVM)is proposed.Firstly,the fault features with weak condition sensitivity have been extracted according to the influence analysis of fault on vibration signal.Moreover,soft interval constraint has been applied to SVM algorithm to reduce the random influence of vibration signal on fault features.In addition,different machine learning algorithms based on different feature sets are adopted to conduct the fault diagnosis under different operating conditions for comparison.Experimental results show that the proposed method is applicable for fault diagnosis under variable operating condition with good accuracy.展开更多
Full-period signal acquisition of vibration signal plays a vital role in the health monitoring and fault diagnosis of modern industrial equipment group. The traditional full-period signal acquisition methods usually n...Full-period signal acquisition of vibration signal plays a vital role in the health monitoring and fault diagnosis of modern industrial equipment group. The traditional full-period signal acquisition methods usually need not only a reference signal generated from special key phase device but also a reserved position, which is only suitable for a small number of particular equipment. A novel full-period signal acquisition method without key phase is proposed to construct the time-frequency method with strong energy concentration called the synchrosqueezing generalized S-Transform(SGST), combining together the Teager energy operator(TEO) and self-adaptive correlation analysis(SACA) based on the vibration signals of both gear and cylinder head. Actual vibration signals of diesel engine are employed to verify the feasibility and effectiveness of the proposed method by comparing with traditional method with special key phase device. By comparisons, the results show that full-period signal acquisition method without key phase has approximate accuracy for diesel engine under different working conditions.展开更多
面向适航审定的飞行试验是验证民用飞机满足设计需求、表明适航条款符合性、形成审定证据的高风险、高成本的重要取证活动。定义和设计民机审定试飞场景是进行民机适航审定飞行试验的前提。由此提出了基于适航符合性证据链的审定试飞场...面向适航审定的飞行试验是验证民用飞机满足设计需求、表明适航条款符合性、形成审定证据的高风险、高成本的重要取证活动。定义和设计民机审定试飞场景是进行民机适航审定飞行试验的前提。由此提出了基于适航符合性证据链的审定试飞场景设计方法及流程。以"符合性证据链"为核心,规划了逻辑严密、可追溯的适航符合性证据。通过引入基于模型的系统工程(model-based systems engineering,MBSE)方法,实现了审定试飞场景符合性证据链构建过程的模型化。为提升可操作性,以适航要求"地面航向操纵性"为典型案例,演示了审定试飞场景需求分析、设计与需求确认的过程。最终设计得到的审定试飞场景能够支持民机适航审定飞行试验的开展。展开更多
基于方位特征集理论(Position and Orientation Characteristic,POC),揭示并联机构拓扑结构分析的理论内涵,建立基于神经网络的并联机构拓扑结构描述方法,提出一种基于神经网络的并联机构拓扑结构自动分析算法。详细说明了并联机构POC...基于方位特征集理论(Position and Orientation Characteristic,POC),揭示并联机构拓扑结构分析的理论内涵,建立基于神经网络的并联机构拓扑结构描述方法,提出一种基于神经网络的并联机构拓扑结构自动分析算法。详细说明了并联机构POC集神经网络模型以及模型中对应的6种算法规则,并给出该方法的主要步骤及实例分析。首先,通过对并联机构拓扑结构分析的理论分析,归纳出其本质;其次,基于神经网络理论基础,对并联机构拓扑结构描述数字化表达;此外,通过分析并联机构POC集自动分析的本质内涵,建立并联机构POC集神经网络模型以及提出6种模型算法规则。最后通过实例分析证明了并联机构POC集自动分析算法的正确性和有效性。展开更多
基金Supported by the National Natural Science Foundation of China(No.52101343)the Aeronautical Science Foundation(ASFC)(No.201834S9002)Chongqing Technology Innovation and Application Development Special General Project(No.cstc2020jscx-msxm0411).
文摘In order to solve the problem of low prediction accuracy when only vibration or oil signal is used to predict the remaining life of gear wear,a gear wear life feature fusion prediction method based on temporal pattern attention mechanism is proposed.Firstly,deep residual shrinkage network(DRSN)is used to extract the features of the original vibration time series signals with low signal-tonoise ratio,and the vibration features associated with gear wear evolution are obtained.Secondly,the extracted vibration features and the oil monitoring data that can intuitively reflect the wear process information are jointly input into the bi-directional long short-term memory neural network based on temporal pattern attention mechanism(TPA-BiLSTM),the complex nonlinear relationship between vibration features,oil features and gear wear process evolution is further explored to improve the prediction accuracy.The gear life cycle dynamic response and wear process signals are obtained based on the gear numerical simulation model,and the feasibility of the proposed method is verified.Finally,the proposed method is applied to the residual life prediction of gear on a test bench,and the comparison between different methods proved the validity of the proposed method.
基金National Natural Science Foundation of China(No.52101343)the Doubule First-rate Construction Special Funds(No.ZD1601)。
文摘Misalignment is one of the most common faults for the diesel engine.In order to eliminate the misalignment fault of the diesel engine in the process of operation,a targeting self-recovery regulation system is constructed by using a movable base and displacement sensors.Misalignment is monitored and detected in real time,the value of misalignment is calculated rapidly and accurately,andintelligent decision is made.Then,the base is moved reversely with a definite target to drive the shaft to translate or rotate,so that the shafts can be recovered to alignment online.A co-simulation model for the self-recovery system is established which consists of a dynamic model of the crankshaft system and control model.The self-recovery regulation process of misalignment is simulated.The simulation results show that the system can accurately calculate the misalignment values,with an error of less than 5%,and can automatically eliminate the misalignment fault of the diesel engine online.The research results provide theoretical support for the self-recovery regulation of misalignment fault,and due to the universality of structure and principle,the self-recovery system is not only suitable for diesel engine,but also for other rotating machineries.
基金Supported by the National Key Research and Development Plan(No.2016YFF0203305)the Fundamental Research Funds for the Central Universities(No.JD1912,ZY1940)Double First-rate Construction Special Funds(No.ZD1601).
文摘The fault detection and diagnosis of diesel engine valve clearance can effectively improve the availability and safety of diesel engine and have extremely important value and significance.Diesel engines generally operate in various stable operating conditions,which have important influence on the fault diagnosis.However,many fault diagnosis methods have been put forward under specific stable operating condition based on vibration signal.As the result of great impact caused by operating conditions,corresponding diagnosis models cannot deal with the fault diagnosis under different operating conditions with required accuracy.In this paper,a fault diagnosis of diesel engine valve clearance under variable operating condition based on soft interval support vector machine(SVM)is proposed.Firstly,the fault features with weak condition sensitivity have been extracted according to the influence analysis of fault on vibration signal.Moreover,soft interval constraint has been applied to SVM algorithm to reduce the random influence of vibration signal on fault features.In addition,different machine learning algorithms based on different feature sets are adopted to conduct the fault diagnosis under different operating conditions for comparison.Experimental results show that the proposed method is applicable for fault diagnosis under variable operating condition with good accuracy.
基金Supported by the National Key Research and Development Plan of China(No.2016YFF0203305)the Fundamental Research Funds for the Central Universities of China(No.JD1912)Double First-Rate Construction Special Funds(No.ZD1601).
文摘Full-period signal acquisition of vibration signal plays a vital role in the health monitoring and fault diagnosis of modern industrial equipment group. The traditional full-period signal acquisition methods usually need not only a reference signal generated from special key phase device but also a reserved position, which is only suitable for a small number of particular equipment. A novel full-period signal acquisition method without key phase is proposed to construct the time-frequency method with strong energy concentration called the synchrosqueezing generalized S-Transform(SGST), combining together the Teager energy operator(TEO) and self-adaptive correlation analysis(SACA) based on the vibration signals of both gear and cylinder head. Actual vibration signals of diesel engine are employed to verify the feasibility and effectiveness of the proposed method by comparing with traditional method with special key phase device. By comparisons, the results show that full-period signal acquisition method without key phase has approximate accuracy for diesel engine under different working conditions.
文摘面向适航审定的飞行试验是验证民用飞机满足设计需求、表明适航条款符合性、形成审定证据的高风险、高成本的重要取证活动。定义和设计民机审定试飞场景是进行民机适航审定飞行试验的前提。由此提出了基于适航符合性证据链的审定试飞场景设计方法及流程。以"符合性证据链"为核心,规划了逻辑严密、可追溯的适航符合性证据。通过引入基于模型的系统工程(model-based systems engineering,MBSE)方法,实现了审定试飞场景符合性证据链构建过程的模型化。为提升可操作性,以适航要求"地面航向操纵性"为典型案例,演示了审定试飞场景需求分析、设计与需求确认的过程。最终设计得到的审定试飞场景能够支持民机适航审定飞行试验的开展。
文摘基于方位特征集理论(Position and Orientation Characteristic,POC),揭示并联机构拓扑结构分析的理论内涵,建立基于神经网络的并联机构拓扑结构描述方法,提出一种基于神经网络的并联机构拓扑结构自动分析算法。详细说明了并联机构POC集神经网络模型以及模型中对应的6种算法规则,并给出该方法的主要步骤及实例分析。首先,通过对并联机构拓扑结构分析的理论分析,归纳出其本质;其次,基于神经网络理论基础,对并联机构拓扑结构描述数字化表达;此外,通过分析并联机构POC集自动分析的本质内涵,建立并联机构POC集神经网络模型以及提出6种模型算法规则。最后通过实例分析证明了并联机构POC集自动分析算法的正确性和有效性。
