【作者】 李园芳；

【导师】 叶阳东；

【作者基本信息】 郑州大学 ， 计算机软件与理论， 2013， 硕士

【摘要】 模糊系统是对确定性系统的推广。与确定性系统不同,模糊系统的输入和输出约束于某一模糊区间,令其状态和行为表现出一定的不确定性。对模糊系统不确定性的描述和分析,以及在信息不完备的情况下,能够准确地给出系统当前的状态是研究的重点。当系统的状态超过某一临界状态值时,可能会产生不可预料的影响,造成不同程度的经济损失。因此,对模糊系统的不确定性进行研究具有重要的应用价值。针对模糊系统中的不确定性问题,特别是在存在不完备信息和存在差错数据的情况下,基于模糊集理论、混杂系统理论和Petri网理论及贝叶斯网络,提出一类可能性Petri网模型,并以此为基础定义了非确定性混杂Petri网模型和时间概率Petri网模型。本文所提出的非确定性混杂Petri网模型将模糊系统分为离散和连续两个部分,对其间的相互作用进行建模,从而分析系统的实时状态及其发展趋势,进而可依据分析结果采取相应的措施,使得系统高效安全的运行；时间概率Petri网模型则利用时间这二模糊系统中的重要属性,利用时序一致性判定函数判断系统中含有时间信息的状态是否相容,由推理演化并融合不同的状态信息而得到系统的最终状态。本文运用非确定性混杂Petri网和时间概率Petri网分别对变压器系统和输电网系统进行了仿真实验。针对变压器系统故障分析的仿真实验表明,非确定性混杂Petri网是一种混杂系统状态检测和趋势分析的有效工具,运用该模型可为混杂系统的状态感知、预测、评估和实时控制提供有效方法；针对输电网系统进行的仿真实验表明,运用时间概率Petri网模型可综合分析系统元件中的时间延迟和概率因素,在信息不完备或存在数据差错的情况下,仍然能够给出较准确的诊断结果。对比试验表明,本文提出的方法提高了诊断的正确率。更多还原

【Abstract】 The fuzzy system is an extension of deterministic system. Unlike the deterministic system, the value of its input and output is fuzzy. Therefore, there is uncertainty in fuzzy system state. It is the focus of study which describes and analyses the uncertainty of fuzzy system, and gives current state of system accurately in the case of incomplete information.The probability Petri net is proposed based on fuzzy set theory, hybrid system theory, Petri net theory and Bayesian networks for uncertainty problems in fuzzy system. Two Petri nets which are uncertainty hybrid Petri net model and time probability Petri net are defined based on the probability Petri net. One is proposed a perceived trend analysis, method based on hybrid system power equipment which aims at predicting state and analyzing problems difficultly. This kind of systems is modeled by uncertain hybrid Petri net. It makes the tokens transfer through transitions triggering. So the states of system are changed. It can deduce the recent state of system by identify the state of system, and thus analyzes the tendency. The other model is time probability Petri net against the large amount of signal in the power system and difficult to model. Time interval in the model represents delay of alarm signal. And probability represents uncertainty of system which is component mal-operation and mis-operation of system component. The final state of the model is obtained by deduction of model. The possible failure system components are confirmed by calculating the final state probability. Using the timing consistency determination function determine whether system states are compatible, and reason out system state.Using the example of transformers and electricity systems simulate two kinds of probability Petri net models which are non-deterministic hybrid Petri net and time probability Petri net. So, fault diagnosis of transformers in the power system as the background, a hybrid Petri net model is built which simulate state detection and process of trend analysis. The results verify the validity of the method. The model provides an effective method to predict the current status and predict, assess and real-time control future state. The time probability Petri net for power system takes the time delay and probability factor of the system components. In the case of incomplete fault information, the model is still able to give more accurate state results of system.更多还原