Study On The Safety Risk Identification And Analysis Of Train Control System Of High-Speed Railway

The development of high-speed railway leads to the great improvement of train speed, which decreases the time and distance between cities, facilitates trips, promotes the economic development and culture exchange. Manual driving and monitoring can no longer ensure traffic safety when speed is over certain level. According to international union of railways rules, trains with speed higher than160km/h must be equipped with train control system to ensure safety. Train control system is the core equipment and safety-critical system of high-speed railway which real-time controls train safe operation distance and protects train from over speed. It plays an important role in ensuring the high-speed railway safety and improving transport efficiency. Train control system integrates technology of computer, modern communication and automation, and it is an immense system that composed of on-board unit and ground equipment. It is very complex at composition, structure, functional level, function execution process and state transition aspects. So it has more oppressive safety requirements compared with traditional railway signaling systems, all kinds of random failure and system failure may leads to extremely serious results. Because high-speed railway train control system is the new technique in Chinese railway signaling area, it hasn’t experienced tests with long-term field application, part of its technical manual are still under revise and polish, many potential safety risks are not mastered yet. So, traditional safety methods can no longer fulfill safety requirements of train control system.This thesis uses system safety risk theory and method, together with modeling theories including Fuzzy uncertainty theory, TOPSIS, Bayesian Network, Extenics, Petri Net, to do research on key problems of high-speed railway train control system safety risk identification and analysis. The main research contents and achievements are listed below.1. Train control system was divided into system level, subsystem level, constitutional unit level, unit board level and module level from top to bottom. Base on such hierarchy, the thesis integrated the views of composition, functional level, state transition and function execution process to propose build and test methods of structural reference model, function hierarchical model, state transition model based on P/T system and function execution process model based on SPN of train control system. Combined with HAZOP, it also raised safety risk identification method which based on structural reference model, function hierarchical model state transition model and function execution process model. In the way, the systematicness and comprehensiveness of train control system safety risk identification was increased. Took train control centre as an example, the thesis set up structural reference model, function hierarchy model, state transition model and temporary speed restriction execution model, and also provided examples of hazard identification.2. Aiming at fuzzy uncertainty of safety risk level analysis, the thesis established the safety risk level analysis model of train control system hazard which based on Fuzzy uncertainty theory. Firstly, it set up hazard safety risk level inference rule library based risk matrix. Then, according to possibility and seriousness of hazard, it used FGDM FAHP and fuzzy comprehensive evaluation to build analytical models of hazard frequency grade and consequence seriousness grade. At last, combined with inference rule, it completed fuzzy inference of hazard safety risk level.3. Raised the question about how to reordering hazards with the same safety risk level based on safety level analysis. Set up risk assessment index system of hazard from possibility and seriousness and calculate weight of each index using FAHP. According to such evaluation index system, the thesis used TOPSIS and fuzzy set theory to build train control system hazard safety risk ordering model which based on multilevel fuzzy TOPSIS. Using this ordering model, more serious hazard can be isolated from hazards with the same safety risk level. In this way, scientific basis of enhancing hazard control was provided.4. The thesis raised train control system hazard quantitative safety risk analysis model which based on Bayesian Network by researching Bayesian network model construction method which based on fault tree and event tree, the algorithm of prior probability of Bayesian network root node based on multiple experts fuzzy evaluation, computing method of hazards quantitative safety risk which based on equivalent of death, and also combining Bayesian network, fuzzy set theory and probability safety risk analysis method which based on fault tree and event tree. This model integrated hazard’s causes and consequences analysis model, inherited the advantage of fault tree and event tree modeling, decreased the difficulty of Bayesian network model structure and obtaining prior probability. It not only quantitatively calculated hazard’s safety risk, but also diagnosed dominant factors and posterior probability for different consequences. Used error-driven signal relay in train control center as an example, the thesis established its Bayesian network model, and calculated prior probability of each root node in Bayesian network model according to algorithm based on multiple experts’fuzzy evaluation. At last, it used cluster Bayesian network inferential algorithm and causal inference to quantitatively calculate the probability of every possible consequence of error-driven signal relay, and also quantitatively analyzed major factors and posterior probability of each possible consequence through diagnostic reasoning.5. Posed the problems of train control system operational safety risk analysis from the system layer and operating aspect. Set up evaluation index system of train control system operational safety risks, calculated weight of each index using FAHP from equipments, operation, maintaining, management, environment and updating aspects. Then introduced Extenics to train control system operational safety extermination, built train control system operational safety risks multiple grade extenics evaluation model. So it can not only estimate the overall safety risks level of train control system operation, but also estimate single index of safety risks level. In this way the scientific basis for seeking vulnerable spot of train control system during the operation service period was provided.