The Quantitative Diagnosis And Research On Condenser Vacuum Reduction In Power Plant Based On FAHP

Because the design, installation, maintenance, operation and other reasons, the condenser vacuum is often lower than the design value in a power plant. The causes of condenser vacuum reduce are diverse, and the impact of various factors have strong fuzziness, uncertainty and coupling. Therefore, so many production and scientific people pay attention to the fault diagnosis of the condenser vacuum reduce. Considering the fault features of condenser vacuum reduce, the traditional fault diagnosis methods tend to have certain limitation. The fuzzy analytic hierarchy process (FAHP)——the method that operations research combining with fuzzy math can reflect a certain superiority in the fault diagnosis field in power plant. The so-called fuzzy analytic hierarchy process (FAHP), in a word, it classified many factors that likely lead to condenser vacuum reduce, then we can construct gradually analytic system by the factor layers, rule layers and target layer; Through the comparison between the influence factors, we can establish a fuzzy consistent matrix. The matrix can reflect the consistency between people’s thinking judgment and objectivity. because it satisfied a constraint programming problem between the fuzzy consistent matrix and the weight of those factors leading to condenser vacuum reduce, we can complete the condenser vacuum reduce quantitative diagnosis after accurately solving the programming problem. The core content of fuzzy analytic hierarchy process (FAHP) is how to build objective and strongly convincing fuzzy consistent matrix.We can establish the fault set and sign set of condenser vacuum reduce by the working principle and role of condenser, the basic theories that the reasons, phenomenon and damage of the condenser vacuum decreasing. The quantitative relationship between the fault causes and signs is described by the fault-sign two value logic relation table of condenser vacuum reduce, then establish the vector list-classic between fault and symptom of the condenser vacuum reduce; We can derive the membership deviation matrix of the factors layer and criteria layer in the analytic hierarchy system by comparing the fuzzy membership degree between the fault feature vector and classical fault vector for condenser vacuum reduce. The maximum membership grade deviation numerical interval is divided into several subintervals, and each subinterval is corresponded to the scale of0.1-0.9, we can derive the assignment rule of fuzzy Judgment matrix; Next, we can obtain the fuzzy Judgment matrix of factor layers and rule layers by assigning every element in the membership grade deviation matrix according to the new assignment rule. Then we can finally establish objective fuzzy consistent matrix after checking consistency. It can be considered improved for fuzzy analytic hierarchy process.Finally, comparing the diagnosis result of the fuzzy analytic hierarchy process (FAHP) and the traditional scene experimental checking condenser fault, we can deduce the conclusion that the application research of FAHP for condenser vacuum reduce fault diagnosis has feasibility, accuracy and practice. We can also provide a new research method for the field of thermal equipment and system fault diagnosis in power plant.