Research On The Inversion Method For The Location Of Leakage Bag In Bag Filter

Industrial bag filter has the advantages of high dust removal efficiency and reliable operation,so it has been widely used for the flue gas purification in various industries such as steel,cement,electricity and waste incineration.The filter bag is the core part of bag filter,once damaged in the operation process,it is easy to cause the dust concentration in the outlet exceeding the standard,causing serious air pollution and endangering human health.The working conditions of industrial bag filter are complex and changeable,and the number of filter bags hanging in the dust collectors is numerous.How to locate the leakage filter bags quickly and accurately and replace them in time is an important issue to be resolved.In this dissertation,an inversion positioning model of leakage bag in bag filter was proposed to solve the problems of high cost,poor real-time performance and high false positive rate of the existing bag filter leakage bag positioning technology.The main research work of this article is listed as follows:1.The existing leakage bag positioning technologies and source inversion methods were summarized,and their advantages and disadvantages were analyzed.Combined with the working mechanism of bag filter and the common leakage bag forms,the complexity of the flow field in the bag filter under the leakage bag state and the factors affecting the inversion positioning were analyzed.On this basis,the whole process of leakage bag positioning based on data-driven was defined.2.Based on the summary and analysis of the existing source inversion methods,and combined with the flow field characteristics of the bag filter in the leakage bag state,the simulation-optimization inversion theory was used to solve the problem of leakage bag positioning in the bag filter.Firstly,the forward model of the numerical simulation of the flow field in the bag filter under the condition of bag breaking was established by Fluent software.Based on the characteristics of the flow field under complex conditions,the nonlinear mapping law between numerical simulation information and detection signal of bag breaking flow field was obtained.After that,BP neural network and RBF function were used to build the surrogate model of forward law in the leakage bag state,the validity and accuracy of the two models were analyzed and compared.Then,the surrogate model was embedded into the optimization model in the form of constraints,and the surrogate optimization model(nonlinear programming optimization model)was constructed.Finally,according to the actual needs of the bag filter,a matching model was constructed with genetic algorithm.This paper completed the construction of the leakage bag location inversion model,and verified the accuracy and feasibility of the inversion positioning model of this paper.3.The leakage bag inversion positioning system of bag filter was developed.This paper introduced the hardware and software structure of the system,and compiled the algorithm of inversion positioning model,which was embedded in Lab VIEW system.The effectiveness and feasibility of the leakage bag inversion positioning system were proved by the application analysis of the leakage bag inversion positioning system.The leakage bag inversion positioning system of bag filter in this paper can accurately locate the leakage bag in a short time according to the limited detectable signal,and detect the size of the break area at the same time.It has the advantages of low cost,fast calculation speed,high accuracy and fast convergence speed,which improves the automation and intelligence of leakage bag positioning technology.