Application of HMC-SS Method in Pipeline Reliability Analysis and Residual Life Assessment

In this paper, the reliability analysis and residual life assessment model of gas pipelines with multiple corrosion pits are established. Aiming at the simulation evaluation of small failure probability of gas pipelines, a new method for reliability analysis and residual life assessment of gas pipelines with multiple internal corrosion pits is proposed, which is called the Hamiltonian Monte Carlo subset simulation (HMC-SS) method. Compared with the traditional MCS (Monte Carlo simulation) algorithm, the HMC-SS method has the advantages of less sampling, low cost, and high accuracy. And compared with the random walk SS method, the HMC-SS method can analyze the state space more efficiently and achieve faster convergence. In this paper, the HMC-SS method is applied to the reliability analysis and residual life assessment of gas pipeline engineering, and the sensitivity analysis of the random parameters affecting the failure probability of the pipeline is carried out. The results show that the corrosion rate, the depth of corrosion defects, and the wall thickness of the pipeline have great influence on the residual life of the pipeline, while the yield strength, working pressure, and the length of corrosion pits have no obvious influence on the failure probability and residual life of the pipeline. The analysis shows that the proposed HMC-SS method can be used as a reasonable tool for failure assessment of natural gas pipelines affected by corrosion to determine the remaining life of the pipeline system. This method provides a reliable theoretical basis for the integrity management of the gas pipeline.

MODEL AND ALGORITHM FOR ESTIMATING THE RESIDUAL LIFE OF ELECTROMECHANICAL EQUIPMENT BASED ON COMPREHENSIVE ANALYSIS OF CURRENT AND VIBRATION

В работе описаны модель и алгоритм оценки остаточного ресурса электромеханического оборудования. В качестве объекта контроля использовался асинхронный привод с зубчатой передачей. Оценка остаточного ресурса проводилась на основе комплексного анализа данных вибрации (с зубчатой передачи) и потребляемого тока асинхронным двигателем. В качестве диагностических параметров выделены виброскорость, виброускорение и ток в фазах обмотки статора приводного электродвигателя. Из выделенных диагностических параметров вычисляются коэффициенты дискретного вейвлет-преобразования (с применением материнского вейвлета Добеши, 8 уровней разложения). После чего выделяются диагностические признаки: среднеквадратические и пиковые (максимальные) значения каждого из вейвлет-коэффициентов и всего сигнала (общий уровень) по каждому диагностическому параметру. В работе приведена разработка и апробация модели и алгоритма оценки остаточного ресурса на основе анализа наиболее чувствительных диагностических признаков к возникновению и развитию неисправностей. В лабораторных условиях получены данные по изменению выделенных диагностических признаков в условиях отсутствия смазки в зубчатом редукторе. В работе показана возможность повышения эффективности оценки остаточного ресурса электромеханического оборудования путем использования комплексного анализа тока и вибрации. Особенностью предлагаемых модели и алгоритма является возможность проводить оценку в условиях изменяющихся режимов работы и внешних нагрузок, что наиболее актуально для оборудования железнодорожного транспорта. Таким образом, на лабораторном стенде получены результаты оценки остаточного ресурса с достоверностью до 96%. The paper describes a model and an algorithm for assessing the residual life of electromechanical equipment. An asynchronous gear drive was used as a control object. The residual life assessment was carried out on the basis of a comprehensive analysis of vibration data (from a gear drive) and the current consumed by an induction motor. Vibration velocity, vibration acceleration and current in the phases of the stator winding of the drive electric motor are distinguished as diagnostic signs. From the selected diagnostic features, the coefficients of the discrete wavelet transform are calculated (using the mother Daubechies wavelet, 8 decomposition levels). After that, diagnostic features are identified: RMS and Peak (maximum) values ​​of each of the wavelet coefficients and the entire signal (general level) for each diagnostic feature. The paper presents the development and testing of a model and an algorithm for assessing the residual resource based on the analysis of the most sensitive diagnostic signs to the occurrence and development of faults. In laboratory conditions, data were obtained on the change in the identified diagnostic signs in the absence of lubrication in the gear reducer. The paper shows the possibility of increasing the efficiency of assessing the residual life of electromechanical equipment by using a comprehensive analysis of current and vibration. A feature of the proposed model and algorithm is the ability to conduct an assessment under conditions of changing operating modes and external loads, which is most important for railway equipment. Thus, on the laboratory bench, the results of the residual life assessment were obtained with a reliability of up to 96%.

Residual service life estimation of bridges

<p>While concrete structures perform well in many situations, lack of durability has emerged as a significant issue for asset owners. A review of past bridge failures was done to identify the most probable causes of bridge failures. This study has tended to focus on current models used for estimating the time to deterioration of concrete bridges instigated by Chloride ingress and Fatigue. Subsequently, mathematical modelling of the best-suited deterioration model is done to arrive at the residual life of two existing bridges. This work has highlighted high variability in the parameters used to describe the durability related properties of in-situ aged concrete. A realistic residual life assessment can be achieved by correct evaluation of these parameters by periodic testing of bridge samples</p>