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Effective Latent Representation for Prediction of remaining useful life

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Computer Systems Science & Engineering 2021年第1期36卷 225-237页

作者： Qihang Wang Gang Wu Shanghai Jiaotong University Shanghai200240China

AI approaches have been introduced to predict the remaining useful life(RUL)of a machine in modern industrial *** apply them well,challenges regarding the high dimension of the data space and noisy data should be met to improve model efficiency and *** this study,we propose an end-toend model,termed ACB,for RUL predictions;it combines an autoencoder,convolutional neural network(CNN),and bidirectional long short-term memory.A new penalized root mean square error loss function is included to avoid an overestimation of the *** the CNN-based autoencoder,a high-dimensional data space can be mapped into a lower-dimensional latent space,and the noisy data can be greatly *** compared ACB with five state-of-the-art models on the Commercial Modular Aero-Propulsion System Simulation *** model achieved the lowest score value on all four *** robustness of our model to noise is also supported by the experiments.

关键词： Deep learning predictive maintenance remaining useful life

An adaptive data-driven method for accurate prediction of remaining useful life of rolling bearings

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Frontiers of Mechanical Engineering 2018年第2期13卷 301-310页

作者： Yanfeng PENG Junsheng CHENG Yanfei LIU Xuejun LI Zhihua PENG State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan University Changsha 410082 China College of Mechanical and Vehicle Engineering Hunan UniversityChangsha 410082 China Hunan-Provincial Key Laboratory of Health Maintenance for Mechanical Equipment Hunan University of Science and Technology Xiangtan 411201 China School of Mathematics and Physics University of South ChinaHengyang 421001 China

A novel data-driven method based on Gaussian mixture model （GMM） and distance evaluation technique （DET） is proposed to predict the remaining useful life （RUL） of rolling bearings. The data sets are clustered by GMM to divide all data sets into several health states adaptively and reasonably. The number of clusters is determined by the minimum description length principle. Thus, either the health state of the data sets or the number of the states is obtained automatically. Meanwhile, the abnormal data sets can be recognized during the clustering process and removed from the training data sets. After obtaining the health states, appropriate features are selected by DET for increasing the classification and prediction accuracy. In the prediction process, each vibration signal is decomposed into several components by empirical mode decomposition. Some common statis- tical parameters of the components are calculated first and then the features are clustered using GMM to divide the data sets into several health states and remove the abnormal data sets. Thereafter, appropriate statistical parameters of the generated components are selected using DET. Finally, least squares support vector machine is utilized to predict the RUL of rolling *** results indicate that the proposed method reliably predicts the RUL of rolling bearings.

关键词： Gaussian mixture model distance evaluation technique health state remaining useful life rolling bearing

A Review of Data-Driven Prognostic for IGBT remaining useful life

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Chinese Journal of Electrical Engineering 2018年第3期4卷 73-79页

作者： Xiaochun Fang Shuai Lin Xianjin Huang Fei Lin Zhongping Yang Seiki Igarashi School of Electrical Engineering Beijing Jiaotong UniversityBeijing100044China Fuji Electric Co. LtdTokyo 141-0032Japan

Power converters with insulated gate bipolar transistor(IGBT)are widely used in diverse industrial applications such as traction *** the IGBT is one of the most fragile components in power electronics converter,remaining useful life(RUL)prognostic of IGBT is important to guarantee system *** paper presents a review of data-driven prognostic for IGBT *** this paper,common data-driven prognostic methods are *** of data-driven prognostic approaches of IGBT are discussed,and main approaches are compared to each *** common problems of these schemes are presented and *** addition,some other desirable studies to improve IGBT RUL estimation are proposed.

关键词： Prognostic remaining useful life data-driven IGBT

Equipment remaining useful life prediction oriented symbiotic simulation driven by real-time degradation data

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International Journal of Modeling, Simulation, and Scientific Computing 2018年第2期9卷 1-22页

作者： Chenglong Ge Yuanchang Zhu Yanqiang Di Department of Electronic and Optics Engineering Mechanical Engineering College Shijiazhuang 050003P.R.China

As an emerging simulation technology in the field of system modeling and simulation,the equipment symbiotic simulation has become research *** the field of equipment maintenance support,the outstanding problem of equipment remaining useful life(RUL)prediction is analyzed,i.e.,the stable model parameters without self-evolution ability,which has become the primary factor that hinders self-adaptive prediction of equipment *** with parallel systems theory,the equipment RUL prediction oriented symbiotic simulation framework is proposed on the basis of modeling analysis and Wiener state space model(SSM)is taken as the basic simulation model in the *** by the dynamic injected equipment degradation observation data,the model parameters are updated online by using expectation maximum(EM)algorithm and the data assimilation between simulation outputs and observation data is executed by using Kalman filter,so as to realize dynamic evolution of the simulation *** simulation model evolution which makes the simulation outputs close to equipment real degradation state provides high fidelity model and data for predicting equipment RUL *** framework is verified by the performance degradation data of a *** simulation results show that the symbiotic simulation method can accurately simulate the equipment performance degradation process and the self-adaptive prediction of equipment RUL is realized on the basis of improving prediction accuracy,proving the feasibility and effectiveness of symbiotic simulation method.

关键词： Symbiotic simulation model evolution remaining useful life data assimilation parameter estimation.

Evaluation of remaining useful life for corroded pipeline with finite element simulation and reliability theory

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Journal of Southeast University(English Edition) 2022年第1期38卷 70-76页

作者： Wang Yifei Su Chun Xie Mingjiang School of Mechanical Engineering Southeast UniversityNanjing 211189China Hunan Provincial Key Lab of Health Maintenance for Mechanical Egquipment Hunan University of Science and TechnologyXiangtan 411201China

An integrated approach was proposed to evaluate the remaining useful life(RUL)of corroded petroleum *** types of failure modes(i.e.,leakage and burst failure)were considered,and the corresponding limit state functions(LSFs)were established with the structural reliability theory.A power-law function was applied to model the growth of corrosion defects,and the effect of external environmental factors on the growth of the pipeline s defect was ***,the result was compared with the commonly used linear growth *** that,a finite element simulation model was established to calculate the burst pressure of the pipeline with corrosion defects,and its accuracy was verified through hydraulic burst test and by comparison with international *** that basis,the probability that the pipeline may fail was calculated with Monte Carlo simulation(MCS)and by considering the LSFs,and the pipeline s RUL was obtained ***,sensitivity analysis was conducted to determine the sensitivity parameters for the corrosion and RUL of the *** results indicate that the radial corrosion rate,wall thickness and working pressure have a great influence on the failure probability of the ***,corresponding measures should be adopted during the operation process of the pipeline to reduce the corrosion rate and increase the wall thickness,so as to prolong the pipeline s RUL.

关键词： pipeline burst pressure finite element method remaining useful life Monte Carlo simulation

Prognostics and remaining useful life Prediction of Machinery:Advances,Opportunities,and Challenges

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Journal of Dynamics, Monitoring and Diagnostics 2023年第1期2卷 1-12页

作者： JDMD Editorial Office Nagi Gebraeel Yaguo Lei Naipeng Li Xiaosheng Si Enrico Zio Editorial Office of JDMD Chongqing University of TechnologyChongqingPeople’s Republic of China H.Milton Stewart School of Industrial and Systems Engineering Georgia Institute of TechnologyAtlantaGAUSA Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System Xi’an Jiaotong UniversityXi’anPeople’s Republic of China Zhijian Laboratory Rocket Force University of EngineeringXi’anPeople’s Republic of China MINES Paris PSL Research UniversitySophia AntipolisFrance Energy Department Politecnico di MilanoMilanItaly

As the fundamental and key technique to ensure the safe and reliable operation of vital systems,prognostics with an emphasis on the remaining useful life(RUL)prediction has attracted great attention in the last *** this paper,we briefly discuss the general idea and advances of various prognostics and RUL prediction methods for machinery,mainly including data-driven methods,physics-based methods,hybrid methods,*** on the observations fromthe state of the art,we provide comprehensive discussions on the possible opportunities and challenges of prognostics and RUL prediction of machinery so as to steer the future development.

关键词： prognostics remaining useful life data-driven machine learning degradation modeling

remaining useful life Prediction Based on Stacked Sparse Autoencoder and Echo State Network

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Remaining Useful Life Prediction Based on Stacked Sparse Aut...

Prediction Method Study on the remaining useful life of Plant New Varieties Rights Based on Weibull Survival Function and Gaussian Model——Taking Hybrid Rice Variety for Example

第三十九届中国控制会议

作者： Yinghua Yang Dandan Yao Xiaozhi Liu College of Information Science and Engineering Northeastern University

Nowadays, the prediction of industry components’ remaining useful life（RUL） has already become a hot topic. In this paper, a RUL prediction method based on stacked sparse autoencoder（SAE） and echo state network（ESN） is ***（AE） is an unsupervised learning method that can be used for feature extraction to obtain a health index（HI）. To enhance the performance of the HI, a sparse constraint is added and a stacked structure is used to increase depth. The RUL of the industry components is then predicted using a method that maps directly to the RUL value based on the health factor curve. With the capability of encapsulating dynamic time behavior and saving historical information of input data, ESN is selected as the prediction network. The proposed method is verified using the C-MPASS dataset. The experimental results show that the method has better performance than the stacked AE based method.

关键词： remaining useful life stacked sparse autoencoder echo state network

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Agricultural Science & Technology 2016年第4期17卷 995-1001页

作者：任静宋敏中国农业科学院农业资源与农业区划研究所北京100081 中国农业科学院农业知识产权研究中心北京100081

In view of the difficulty in determining remaining useful life of plant new variety right in economic analysis, Weibull Survival Analysis Method and Gaussian Model to were used to study how to accurately estimate the remaining useful life of plant new variety right. The results showed that the average life of the granted rice varieties was 10.013 years. With the increase of the age of plant variety rights, the probability of the same residual life Ttreaching x was smaller and smaller, the reliability lower and lower, while the probability of the variety rights becoming invalid became greater. The remaining useful life of a specific granted rice variety was closely related to the demonstration promotion age when the granted rice variety reached its maximum area and the appearance of alternative varieties, and when the demonstration promotion age of the granted rice variety reaching the one with the maximum area, the promotion area would be decreased once a new alternative variety appeared, correspondingly with the shortening of the remaining useful life of the variety. Therefore, Weibull Survival Analysis Method and Gaussian Model could describe the remaining useful life＇s time trend, as well as determine the remaining useful life of a concrete plant variety right, clarify the entire life time of varieties rights, and make the economic analysis of plant new varieties rights more accurate and reasonable.

关键词： remaining useful life Weibull Survival Function Gaussian

Research on remaining useful life Prediction Method of Rolling Bearing Based on Health Indicator Extraction and Trajectory Enhanced Particle Filter

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Journal of Dynamics, Monitoring and Diagnostics 2022年第2期1卷 66-83页

作者： Peng Luo Jiao Hu Lun Zhang Niaoqing Hu Zhengyang Yin Laboratory of Science and Technology on Integrated Logistics Support National University of Defense TechnologyChangsha 410073China College of Intelligence Science and Technology National University of Defense TechnologyChangsha 410073China

Aiming at the difficulty of mining fault prognosis starting points and constructing prognostic models for remaining useful life(RUL)prediction of rolling bearings,a RUL prediction method is proposed based on health indicator(HI)extraction and trajectory-enhanced particle filter(TE-PF).By extracting a HI that can accurately track the trending of bearing degradation and combining it with the early fault enhancement technology,early abnormal sample nodes can be mined to provide more samples with fault information for the construction and training of subsequent prediction *** at the problem that traditional degradation rate models based on PF are vulnerable to HI mutations,a TE-PF prediction method is proposed based on comprehensive utilization of historical degradation information to timely modify prediction model *** from a rolling bearing prognostic study show that prediction starting points can be accurately detected and a reasonable prediction model can be conveniently constructed by the RUL prediction method based on HI amplitude abnormal detection and ***,aiming at the RUL prediction problem under the condition of HI mutation,RUL prediction with probability and statistics characteristics under a confidence interval can be obtained based on the method proposed.

关键词： health indicator prediction model prediction starting point remaining useful life trajectory-enhanced particle filter