The Risk Assessment For The Lower Extremity Exoskeleton System With Consideration Of Correlations

Lower limb exoskeleton robots are complex electromechanical devices that can be divided into lower limb power-assisted exoskeletons and walking-assisted exoskeletons according to their applications.The research object of this article is the lower limb walking-assisted exoskeleton robot.Lower limb walking-assisted exoskeletons are mostly used in the field of medical rehabilitation to help paraplegic patients stand and walk,as well as for daily rehabilitation training.Since the users are mainly paraplegic patients,safety during use is extremely important.Once a failure occurs during use,it may cause secondary injuries to the patients.Therefore,it is of great practical significance to conduct risk assessment on lower limb walking-assisted exoskeletons.This article evaluates the failure risk of lower limb walking-assisted exoskeletons from the perspective of system as a whole and the internal system,focusing on the robot as the research object.The specific research content is as follows:(1)Conducting structural and functional analysis on the lower limb exoskeleton system.Firstly,based on the working principle of the entire machine,a functional block diagram of the entire machine was drawn.Then,the entire system was divided into six subsystems from a structural level,and structural and functional analysis was conducted on each of the six subsystems.(2)A risk propagation prediction algorithm based on ER stochastic network is proposed,and the risk impact importance analysis of the lower extremity exoskeleton subsystem is completed.Firstly,the Failure Mode Effects and Criticality Analysis(FMECA)was used to complete the failure risk mode impact analysis of the lower extremity exoskeleton subsystem,and the risk score was evaluated according to the probability impact matrix to obtain the risk impact matrix among subsystems;Then,the risk propagation network of the lower extremity exoskeleton subsystem is obtained by using the risk impact matrix as the input of the risk propagation prediction algorithm;finally,with the help of the degree distribution characteristics of the complex network(Complex Network,CN),the degree value is used as the evaluation value of the risk of the subsystem nodes.The medium importance index in the network evaluates the risk impact importance of the subsystem.(3)A risk assessment of the higher importance subsystems in the lower limb exoskeleton system was completed based on Bayesian network.Firstly,the fault tree and Bayesian network modeling of the subsystems were completed.Then,the prior probability of the root node was calculated based on the electronic product reliability formula.Finally,the failure probability of the leaf nodes was calculated using Genie,and the failure probability of the leaf nodes was used as an indicator to evaluate the subsystem failure risk,completing the subsystem failure risk assessment.(4)The occurrence probability of subsystem failure risk is compared when the dependency failure is considered.Firstly,the common cause failure(Common Cause Failure,CCF)analysis is carried out on the failure risk of the subsystem,and the CCF factor in the subsystem is determined;then,the Bayesian network modeling is carried out on the failure risk of the subsystem when considering the correlation failure;finally Use Genie to calculate the failure probability of the leaf node when considering the dependency failure,and compare the results with the results without considering the dependency failure.This article identified the subsystems with higher risk impact on the overall risk of the lower limb exoskeleton system through risk impact importance analysis.The analysis also considered the correlated failures of subsystems,and quantitatively calculated the probability of internal failure risk with correlation.The results can provide a basis for improving and optimizing the lower limb exoskeleton system,and offer a feasible approach for the risk assessment of complex systems.