Online fault diagnosing method for Fast RVM (relevance vector machine) sewage treatment

Abstract

The invention discloses an online fault diagnosing method for Fast RVM (relevance vector machine) sewage treatment. The method includes the steps of firstly, removing samples with incomplete attributes in sewage data, normalizing the samples into a [0, 1] interval, and determining a historical data set and an updating test set; secondly, using a relevance vector machine method based on clustering to compress the majority data of the historical data set; thirdly, using a virtual minority upward sampling method to extend the minority data of the historical data set; fourth, building a 'one-to-one' fast relevance vector machine multi-classification training model; fifthly, adding new samples from the updating test set into the model for testing, and updating the historical data set; sixthly, returning to the second step, reprocessing unbalanced historical data, training the model, and repeating the above process until online data testing is finished. By the online fault diagnosing method, the unbalance of the sewage data is lowered effectively, classification accuracy is increased, online updating speed is increased, operation faults can be diagnosed in real time, and the safety operation of a sewage treatment plant is guaranteed.

Description

technical field [0001] The invention relates to the field of sewage treatment, in particular to an online fault diagnosis method for Fast RVM sewage treatment. Background technique [0002] At present, environmental protection has become an important basis for the sustainable development of my country's economy. With the rapid development of my country's industrial economy and the continuous acceleration of urban processes, the discharge of industrial wastewater has grown rapidly with the increase in industrial water consumption. Most of the direct discharge of wastewater It has seriously polluted the water bodies of rivers and rivers, destroyed the ecological balance, and indirectly affected people's lives. As a key protective barrier for natural water bodies, sewage treatment plants will directly affect the safety of the water environment if their operation is good or bad. The sewage biochemical treatment process is complex, and there are many influencing factors. It is di...

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Problems solved by technology

[0003] The fault diagnosis of the operation state of the sewage treatment process is essentially a pattern classification problem. In the actual state operation classification, the distribution of the sewage data set is often unbalanced. The existing technology has certain limitations. When balancing data classification, the correct rate of model classification cannot meet the requirements, which brings great difficulties to the fault diagnosis of sewage biochemical treatment; at the same time, in the actual process, fault diagnosis is actually a continuous learning process, and one of its outstanding features That is, learning is not done offline at one time, but is a process of adding data one by one and continuously optimizing

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