故障诊断论文：故障诊断人工免疫克隆选择免疫抗体记忆分类思维进化

1、故障诊断论文：故障诊断人工免疫克隆选择免疫抗体记忆 分类思维进化【中文摘要】电力变压器是电力系统中的关键设备，其稳定可靠 的运行是电力系统安全可靠运行的重要保障。一旦发生故障，将会影 响电力系统的稳定运行，给人们的生产生活带来极大地不便，因此电 力变压器故障诊断一直为国内外学者所关注。 本文简要介绍了课题的 来源,背景及意义，通过参阅大量文献分析国内外研究现状并对各种 诊断方法的优劣做了比较。 本文详细介绍了人工免疫算法原理及在变 压器故障诊断中的应用，针对传统克隆免疫算法在变压器故障诊断应 用中学习速度慢、无分类能力及抗体空间小的限制提出了免疫抗体记 忆分类算法，该算法基于免疫空间抗体识别抗

2、原原理和抗体记忆功能 将克隆选择与进化算法相结合，学习训练抗原及附属类型信息，得到 不同类型检测集组成的故障信息库。并在抗体训练克隆过程中，对传统的克隆算子进行改进，形成了免疫抗体记忆分类算法。该算法在保 证亲和力的前提下提高了学习速度，扩大了免疫搜索空间，丰富了抗 体空间多样性，提升了故障诊断的准确率。同时以人工识别球（ARB） 为基本诊断单元，利用 ARB 与刺激水平线性关系对故障类型诊断，保 证了诊断的快速性。人工免疫算法本身具有动态学习，自适应,记忆，并行处理等优点。但是在免疫算法中高频变异算子可能造成本来具有 足够亲和力的抗体在通过变异后形成无功能的或是亲和力较差的抗 体,减缓了训练

3、学习速度。针对以上不足本文引入思维进化算法，在抗 体的训练中将抗体群分为多个子抗体群，在趋同和异化操作的交替作 用下进行抗体亲和力训练，在保证亲和力稳步增高的同时加快了亲和 力训练的速度。【英文摘要】 Power transformer is the key equipment in the powersystem, the stable and reliableoperation of which is animportant guarantee for successful operation of power system. Oncefaulted, it will affect the

4、 stability operation of power system, and lead ing toa greatly inconvenience in the production and people s lives.As a result,power transformer fault diag no sis has bee n a concern to scholars. Thepaper brieflyin troduced the source,backgro und and sig nifica neeofthe topic , an alyze the domestic

5、and foreig n research status andcompared the quality of all kinds of diag no stic methods through reading alarge number of documents. It introduces the principle of artificial immunealgorithm and the application of tran sformer fault diag no sis. In order tomake up the shortages of traditional Cloni

6、ng immune algorithm for the transformer fault diag no sis applicati ons, such as the slowly learning speed,non-classified ability and the small antibody space. This paper proposes aclassification algorithm of antibody memory based on the principle that theantibodies recognize the antigens in the imm

7、unespace and antibodymemoryfunction.The algorithm, combining the clone selection and theevoluti onary algorithm, lear ns the training an tige n and subsidiary type informati on to build the fault in formati on database which is composed ofdiffere nt types of detecti on aggregate. The lear ning speed

8、 of thisalgorithm is very fast while the affinity is high eno ugh. At the same time, ithas an expanded immunization search space and improves the antibodiesspatial diversity. Therefore, this algorithm can improve the accuracy offault diag no sis. Besides, it use the artificial recognition ball (ARB)

9、 as thebasic diagnostic unit. As a result, the speed of diag no sis is greatlyimproved because of the lin ear relati on ship betwee n the ARB and thestimulati on level.The artificial immunealgorithm has the ability of dynamiclearning, adaptive, memory, parallel processing and so on. However, thehype

10、rmutati on mecha nism would lead to the non-fun cti onal or pooraffinity antibodies from sufficient affinity antibodies and a slower lear ningspeed. In order to make up the shortco min gs, this article in troduces in mind evoluti onary algorithm that the an tibody groups will be divided intomultiple sub-antibodi