scholarly journals Reliability Modeling for Humidity Sensors Subject to Multiple Dependent Competing Failure Processes with Self-Recovery

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2714 ◽  
Author(s):  
Jia Qi ◽  
Zhen Zhou ◽  
Chenchen Niu ◽  
Chunyu Wang ◽  
Juan Wu
Keyword(s):  
Reliability Model ◽  
Humidity Sensors ◽  
Reliability Modeling ◽  
Reliability Models ◽  
Soft Failure ◽  
Recent Developments ◽  
General Reliability ◽  
Hard Failure ◽  
Mechanism Of Failure ◽  
Random Shocks

Recent developments in humidity sensors have heightened the need for reliability. Seeing as many products such as humidity sensors experience multiple dependent competing failure processes (MDCFPs) with self-recovery, this paper proposes a new general reliability model. Previous research into MDCFPs has primarily focused on the processes of degradation and random shocks, which are appropriate for most products. However, the existing reliability models for MDCFPs cannot fully characterize the failure processes of products such as humidity sensors with significant self-recovery, leading to an underestimation of reliability. In this paper, the effect of self-recovery on degradation was analyzed using a conditional probability. A reliability model for soft failure with self-recovery was obtained. Then, combined with the model of hard failure due to random shocks, a general reliability model with self-recovery was established. Finally, reliability tests of the humidity sensors were presented to verify the proposed reliability model. Reliability modeling for products subject to MDCFPs with considering self-recovery can provide a better understanding of the mechanism of failure and offer an alternative method to predict the reliability of products.

scholarly journals Reliability modeling for competing failure systems with instant-shift hard failure threshold

2018 ◽  
Vol 42 (4) ◽  
pp. 457-467 ◽  
Author(s):  
Jingyi Liu ◽  
Yugang Zhang ◽  
Bifeng Song
Keyword(s):  
Sensitivity Analysis ◽  
System Reliability ◽  
Reliability Model ◽  
External Shocks ◽  
Reliability Modeling ◽  
Soft Failure ◽  
Random Shock ◽  
Hard Failure ◽  
Engineering Practices ◽  
Random Shocks

Many researchers have modeled systems under multiple dependent competing failure processes (MDCFP) in recent years. Typically, those failure processes consist of degradation (soft failure) and random shock (hard failure). In previous papers the threshold of hard failure has been a fixed value, which does not reflect engineering practices. Threshold refers to the ability to resist external random shocks, which shifts with time as the system is used. Thus, this paper establishes a model for MDCFP with instant-shift hard threshold. The hard failure threshold changes with time instantaneously, and it is also influenced by external shocks. This paper also presents a system reliability model. The effectiveness of the presented model is demonstrated by a reliability analysis of the micro-engine at Sandia National Laboratories. In addition, a sensitivity analysis is performed for specific parameters.

scholarly journals Reliability Evaluation of Multiple DCFP System subject to Shifting Threshold

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Chunping Li ◽  
Huibing Hao ◽  
Fang Xu ◽  
Guotao Zhao
Keyword(s):  
Wiener Process ◽  
System Reliability ◽  
Failure Process ◽  
Reliability Evaluation ◽  
Probabilistic Methods ◽  
Reliability Models ◽  
Soft Failure ◽  
Evaluation Models ◽  
Hard Failure ◽  
Random Shocks

This paper focuses on system reliability analysis with dependent competing failure process due to soft failure and hard failure. Some new probabilistic methods based on cumulative shock model and nonlinear Wiener process under different shifting thresholds situation are obtained. Considering that nonlinearity exists extensively in practice, the continuous soft failure process is governed by random effected nonlinear Wiener process. Firstly, reliability evaluation models for hard failure and soft failure are obtained under the cumulative shock, respectively. Furthermore, some system reliability models under different shifting thresholds situation are studied, in which failure threshold will decrease after a certain number of shocks. A real numerical example about fatigue crack growth dataset is carried out to demonstrate the proposed procedure. Numerical results indicate that both random shocks and shifting threshold have significant effect on system reliability. Finally, some sensitivity analysis are also been given.

Method for Determining the Reliable Life Parameter of Turbine Wheel of Turbocharger with Over-Speed Failure Mode

2012 ◽  
Vol 544 ◽  
pp. 251-255
Author(s):  
Zheng Wang ◽  
A Na Wang ◽  
Kai Guo ◽  
Li Zhuang ◽  
Lin Hua
Keyword(s):  
Failure Mode ◽  
Design Parameters ◽  
Series System ◽  
Reliability Model ◽  
Turbine Wheel ◽  
Reliability Modeling ◽  
Reliability Models ◽  
Modeling Process ◽  
Life Parameter ◽  
The Relationship

For the over-speed failure mode, the method for determining the reliable life parameter of turbine wheel of turbocharger is proposed in this paper. The shortage of design criteria based on conventional safety factor for turbine wheel with over-speed failure mode is analyzed. In order to embody the characteristics of structure and over-speed failure mode, the turbine wheel is taken as a series system consisting of several blade symmetrical components in the reliability modeling process. The time-reliability models of turbine wheel are derived and the relationship between the reliability and failure rate of turbine wheel and life parameter is studied. Then, the method for determining the reliable life parameter of turbine wheel of turbocharger with over-speed failure mode is proposed based on the reliability model and reliability curve. As long as the design parameters including the number of blades, speed, stress, and strength are given, the reliable life of turbine wheel of turbocharger with over-speed failure mode can be determined with the method proposed.

scholarly journals Reliability Modeling and Estimation of the Gear System

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Enjun Bai ◽  
Liyang Xie ◽  
Hongyi Ma ◽  
Jungang Ren ◽  
Shijian Zhang
Keyword(s):  
Order Statistics ◽  
Least Square Method ◽  
Small Sample ◽  
Gear System ◽  
Least Square ◽  
Linear Regression Method ◽  
Reliability Model ◽  
Statistical Parameters ◽  
Reliability Modeling ◽  
Reliability Models

Traditional reliability models of the gear system either simplify the gear system unreasonably or are too complicated to be applicable for some gear systems. Therefore, a reliability model of the gear system considering statistically dependent failure based on the theory of the order statistics is developed in this paper. Firstly, the gear bending fatigue test of small sample is implemented to obtain the P-S-N curves that are fitted by using the least square method and the linear regression method of the statistical parameters under the test stress levels. Then, according to stress-strength interference theory and the theory of the order statistics, the reliability models considering the number of load cycles from a gear to gear system are built, which indicates clear modeling process of the gear system. Finally, the proposed reliability model of gear system is validated by using the Monte Carlo Simulation (MCS) and the system reliability under special load history is analyzed qualitatively.

Reliability modeling and analysis for systems governed by multiple competing failures processes

2020 ◽  
pp. 1748006X2097447
Author(s):  
Hongda Gao ◽  
Dejing Kong ◽  
Yixin Sun
Keyword(s):  
Process Model ◽  
Failure Modes ◽  
Failure Process ◽  
Extended Model ◽  
Reliability Modeling ◽  
Modeling And Analysis ◽  
Soft Failure ◽  
Shock Process ◽  
Hard Failure ◽  
Reliability Systems

Due to that the operating environment is becoming more and more complex and rigorous, the multiple competing failure modes for the reliability system is much commonly seen. In order to improve the system performance, a sensor-based degradation calibration policy (SBDC policy) is presented in this paper. The model considers the competing failure process which is described by the soft and hard failure modes. In detail, the soft failures occur when the degradation of the system exceeds the failure threshold, and the hard failures are caused by the same shock process. We use the Wiener process model to describe the soft failure and the shock process to describe the catastrophic failure. Meanwhile, in the shock process, the damage associated with the system is normal distributed which is related to the duration of the adjacent shocks. This extended model with calibrations has a good application value for the corresponding complex reliability systems which are subject to the dependent competing failure modes. By the model in this article, the system reliability and safety can be improved and the risk of the abrupt damage shall be reduced as the circumstance changes.

scholarly journals Reliability modeling for dependent competing failure processes with phase-type distribution considering changing degradation rate

2021 ◽  
Vol 23 (4) ◽  
pp. 627-635
Author(s):  
Hao Lyu ◽  
Shuai Wang ◽  
Xiaowen Zhang ◽  
Zaiyou Yang ◽  
Michael Pecht
Keyword(s):  
Degradation Rate ◽  
Failure Process ◽  
Survival Function ◽  
Interarrival Time ◽  
Reliability Model ◽  
Shock Model ◽  
Ph Distribution ◽  
Soft Failure ◽  
Phase Type ◽  
Hard Failure

In this paper, a system reliability model subject to Dependent Competing Failure Processes (DCFP) with phase-type (PH) distribution considering changing degradation rate is proposed. When the sum of continuous degradation and sudden degradation exceeds the soft failure threshold, soft failure occurs. The interarrival time between two successive shocks and total number of shocks before hard failure occurring follow the continuous PH distribution and discrete PH distribution, respectively. The hard failure reliability is calculated using the PH distribution survival function. Due to the shock on soft failure process, the degradation rate of soft failure will increase. When the number of shocks reaches a specific value, degradation rate changes. The hard failure is calculated by the extreme shock model, cumulative shock model, and run shock model, respectively. The closed-form reliability function is derived combining with the hard and soft failure reliability model. Finally, a Micro-Electro-Mechanical System (MEMS) demonstrates the effectiveness of the proposed model.

Reliability Modeling of Wind Farm Considering the Outages of Connection Cables

2013 ◽  
Vol 291-294 ◽  
pp. 461-466
Author(s):  
Guo Bing Qiu ◽  
Wen Xia Liu ◽  
Jian Hua Zhang
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Power Output ◽  
Complex Terrain ◽  
Wind Farm ◽  
Sequential Monte Carlo ◽  
Reliability Model ◽  
Wake Effect ◽  
Reliability Modeling ◽  
Wake Model

Considering the randomness of wind speed and wind direction, the partial wake effect between wind turbines (WTs) in complex terrain was analyzed and a multiple wake model in complex terrain was established. Taking the power output characteristic of WT into consideration, a wind farm reliability model which considered the outages of connection cables was presented. The model is implemented in MATLAB using sequential Monte Carlo simulation and the results show that this model corrects the power output of wind farm, while improving the accuracy of wind farm reliability model.

Reliability Modeling of Dependent Competitive Failure with Continuous Degradation and Random Shocks

2021 ◽  
Author(s):  
Jialin Ma ◽  
Guo Xie ◽  
Lingxia Mu ◽  
Jing Xin ◽  
Wenbin Chen ◽  
...  
Keyword(s):  
Reliability Modeling ◽  
Random Shocks

scholarly journals Characteristics and Application of the NHPP Log-Logistic Reliability Model

2018 ◽  
Vol 8 (1) ◽  
pp. 44
Author(s):  
Lutfiah Ismail Al turk
Keyword(s):  
Evaluation Criteria ◽  
Real Data ◽  
Least Square ◽  
Estimation Methods ◽  
Data Sets ◽  
Reliability Model ◽  
Reliability Engineering ◽  
Reliability Models ◽  
Time Domain Data ◽  
Linear Least Square

In this paper, a Nonhomogeneous Poisson Process (NHPP) reliability model based on the two-parameter Log-Logistic (LL) distribution is considered. The essential model’s characteristics are derived and represented graphically. The parameters of the model are estimated by the Maximum Likelihood (ML) and Non-linear Least Square (NLS) estimation methods for the case of time domain data. An application to show the flexibility of the considered model are conducted based on five real data sets and using three evaluation criteria. We hope this model will help as an alternative model to other useful reliability models for describing real data in reliability engineering area.

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