Real-time Reliability Analysis Research Articles

Real-time reliability analysis of micro-milling processes considering the effects of tool wear

The development of micro-milling technology has promoted the high-precision machining of complex and small-size parts in modern manufacturing. Accurate cutting force control and reasonable machining parameters selection are conducive to the sustainable machining of micro-milling. In this work, a micro-milling mechanical model considering the change of tool wear, tool runout, and chip separation status with cutting time is proposed with the improved Gated Recurrent Unit with Multi-objective Dandelion Optimizer and mathematical modeling. The modeling accuracy is verified by experiments on Al6061. Combined with the established framework and the practical physical information, the posterior distribution of process parameters is inverted using the Bayesian updating method. Finally, the reliability calculation of machining system parameters is efficiently realized utilizing the posterior information and the High-dimensional Model Representation with the Stochastic configuration network method. The influence degree of the change of cutting parameters on the extreme value of micro-milling force is evaluated. The research results can provide analytical methods and theoretical guidance to ensure safe processing.

Reliability-monitoring data coupled model for concrete slab safety evaluation of CFRD and its engineering application

The concrete-faced rockfill dam (CFRD) is one of the widely constructed dam types, the concrete slab is the key anti-seepage structure of CFRD, and its safety directly affects the safety of the dam. In view of the traditional reliability analysis methods are complicated to calculate and cannot assess concrete slab cracking risk in real-time. In this paper, through the analysis of the response mechanism of slab stress and dam deformation, the coupling relationship between the reliability of concrete slab and monitoring data is revealed. Considering the randomness of the material parameters of CFRD, the limit state functions of concrete slab cracking are established by the response surface method (RSM). The accurate numerical simulation of the construction and operation process of CFRD is realized through the back analysis, then the time-variant reliability calculation of the concrete slab is realized. By analyzing the correlation between concrete slab reliability and some key factors such as dam displacement, water level, and time, a coupled evaluation model of reliability and monitoring data is proposed. Houziyan CFRD is selected as an example, the engineering application shows that the simulation relative error by using this coupled evaluation model is less than 5.0%, this model has the advantages of high efficiency, good precision, and strong applicability. The real-time reliability analysis of the concrete slab is realized and a new method for prediction and early warning of concrete slab cracking of CFRDs is provided.

Modeling and analysis of landing collision dynamics for a shipborne helicopter

A Lagrange dynamic model is established based on small-angle approximation to improve the simulation model for shipborne helicopter landing collision. To describe fuselage motion effectively, the proposed model considers ship motion, the interaction of the tires with the deck, and tire slippage. A mechanism of sliding motion is built, and a real-time reliability analysis of the algorithm is implemented to validate the proposed model. Numerical simulations are also conducted under different operation conditions. Results show that the proposed dynamic model can simulate the collision motion of helicopter landing in real time. Several suggestions for helicopter pilot landing are likewise provided.

A general failure-pursuing sampling framework for surrogate-based reliability analysis

Design of experiment and active learning strategy are vital for the surrogate-based reliability analysis. However, the existing sampling and modeling methods usually ignore some useful information that can guide the choice of training samples, or heavily rely on the characteristics of surrogates. These lead to the inefficiency of sampling strategies or limit the application respectively. Therefore, this work proposes a failure-pursuing sampling framework, which is able to adopt various surrogate models or active learning strategies. In each iteration, it organically and sequentially takes into account the joint probability density function of random variables, the individual information at candidate points and the improvement of the accuracy of predicted failure probability. To measure the probability of the improvement, a global predicted failure probability error is proposed based on the real-time reliability analysis result. Furthermore, Voronoi diagram is applied to partition the sampling region into some local cells for keeping the uniformity of the training samples. Besides, a model-free response-distance function is developed and combined with the framework to avoid relying on the characteristics of surrogates, such as the statistical information provided by Kriging. Finally, four examples are investigated to demonstrate the applicability, stability and generality of the proposed method.

Missile captive carry monitoring and helicopter identification using a capacitive microelectromechanical systems accelerometer

Military missiles are exposed to many sources of mechanical vibration that can affect system reliability, safety, and mission effectiveness. The US Army Aviation and Missile Research Development and Engineering Center has been developing missile health monitoring systems to assess and improve reliability, reduce life cycle costs, and increase system readiness. One of the most significant exposures to vibration occurs when the missile is being carried by a helicopter or other aviation platform, which is a condition known as captive carry. Recording the duration of captive carry exposure during the missile’s service life can enable the implementation of predictive maintenance and resource management programs. Since the vibration imparted by each class of helicopter varies in frequency and amplitude, tracking the vibration exposure from each helicopter separately can help quantify the severity and harmonic content of the exposure. To help address these needs, the authors have developed a captive carry health monitor for the Hellfire II missile. The captive carry health monitor is an embedded usage monitoring device installed on the outer skin of the Hellfire II missile to record the cumulative hours the host missile has been in captive carry mode. To classify the vibration by class of helicopter, the captive carry health monitor analyzes the amplitude and frequency content of the vibration with the Goertzel algorithm to detect the presence of distinctive rotor harmonics. This article provides an overview of the captive carry health monitor, presents vibration data collected on missiles during captive carry, describes data analysis techniques used to monitor captive carry and identify the class of helicopter, and discusses the potential application of missile health and usage data for real-time reliability analysis. More broadly, this article illuminates the challenges of developing a structural health monitor to classify transportation modes in an unstructured environment.

Real-Time Reliability Analysis and Optimal Distribution of the Reliability on Five-Axis Machining Center

The some five-axis machining center was investigated, and it divided ten subsystems. Based on analysis of fault data, the distribution of fault time submits to Weibull distribution, the distribution function and reliability function of each subsystem were confirmed. The reliability allocation model with the constraints of cost is established based on reliability prediction to get optimal reliability allocation results of the complicated mechano-electronic system. The most growth potential of the reliability of subsystem and growth situation of reliability of each subsystem could be got by using this method. The reliability allocation is an important part of reliability design, because its result influences system design directly. This provides reference for design improving of this series of new products.

A DEGRADATION MEASUREMENTS BASED REAL-TIME RELIABILITY PREDICTION METHOD

The problem of real-time reliability analysis and prediction is considered in this paper based on degradation measurements. Given the nonlinear degradation path model with random parameters, the prior distribution of the random parameters is updated into a posterior distribution according to Bayesian formula based on the measurable degradation information. Then, the reliability during a certain period in the future can be predicted by Monte Carlo integration. An example by use of the fatigue crack growth data is given for illustration.

A new approach to real-time reliability analysis of transmission system using fuzzy Markov model

To date the studies of power system reliability over a specified time period have used average values of the system transition rates in Markov techniques [Singh C, Billinton R. System reliability modeling and evaluation. London: Hutchison Educational; 1977]. However, the level of power systems reliability varies from time to time due to weather conditions, power demand and random faults [Billinton R, Wojczynski E. Distributional variation of distribution system reliability indices. IEEE Trans Power Apparatus Systems 1985; PAS-104(11):3152–60]. It is essential to obtain an estimate of system reliability under all environmental and operating conditions. In this paper, fuzzy logic is used in the Markov model to describe both transition rates and temperature-based seasonal variations, which identifies multiple weather conditions such as normal, less stormy, very stormy, etc. A three-bus power system model is considered to determine the variation of system reliability in real-time, using this newly developed fuzzy Markov model (FMM). The results cover different aspects such as daily and monthly reliability changes during January and August. The reliability of the power transmission system is derived as a function of augmentation in peak load level. Finally the variation of the system reliability with weather conditions is determined.