中文摘要：

提出了一种新颖的动态系统实际故障可诊断性量化评价方法.该方法无需设计任何诊断算法,仅通过解析模型即可给出动态系统故障检测和隔离的难易程度,从而为实现在系统设计阶段提高故障诊断能力的工程目标提供理论指导和参考依据.首先,通过标准化模型和等价空间变换,将状态空间描述的随机动态系统实际故障可诊断性评价问题转化为概率统计中多元分布相似度判别的数学问题;然后,根据严格的数学证明,指出距离相似度判别准则在进行可诊断性量化评价中存在的不足.进而,为弥补该不足,利用故障矢量的分布概率以及不同故障矢量之间的余弦相似度,设计基于方向相似度的可诊断性量化评价新方法;最后,通过数学仿真验证该方法的有效性和优越性。

英文摘要：

This paper proposes a novel approach to quantitative evaluation of actual fault diagnosability for dynamic systems. This approach, which can quantify the difficult level to detect and isolate a fault without designing a diagnosis algorithm, provides a guidance and reference for the technical purpose of improving fault diagnosis ability in the system design phase. First, fault diagnosability evaluation for the dynamic system described by a state space model is converted to a statistical probability problem for distinguishing the similarity of different multivariate distributions through the model standardization and the parity space method. KLD（Kullback-Leibler divergence） is introduced to present the principle of evaluating fault diagnosability based on the criterion of distance similarity, and the shortages of this method are pointed out through rigorous proofs. To make up these shortages, a new method for quantitative diagnosability evaluation is designed, which is derived from the probability distribution of fault vectors and the cosine similarity between two different fault vectors in the view of directional similarity. Finally, the validity and superiority of the proposed approach are verified by numerical simulations.