Intelligent electrical-automation dust removal control system and method

Abstract

The invention belongs to the technical field of dust removal and discloses an intelligent electrical-automation dust removal control system and a method. The intelligent electrical-automation dust removal control system comprises a power supplying module, a smoke and dust detection module, a parameter input module, a main control module, a power regulation module, an air exhaust module, a filtering module, a fault detection module, a data storage module and a display module. According to the system and the method, a discharged dust concentration from a very low concentration, i.e., 0.01mg / kg to a high concentration, i.e., 50mg / kg or more can be measured by using an image sensor, i.e., a CCD or CMOS area array or linear array digital camera and a laser beam through the smoke and dust detection module, so that the requirements of online smoke and dust monitoring on ultralow discharging are met; and meanwhile, fault data fragments are mapped into image data through the fault detection module, and a data processing problem is changed into a fault recognition problem, so that the risk of information loss caused by direct preprocessing of the data is lowered, the fault recognition rate of a blower driftage system is increased, and meanwhile, visualized displaying is performed very vividly and lively.

Description

technical field [0001] The invention belongs to the technical field of dust removal, and in particular relates to an intelligent electric automatic dust removal control system and method. Background technique [0002] Dust removal device, commonly known as dust collector, is a device that removes or reduces the content of fly ash in flue gas. The types of dust removal devices can be divided into bionano film dust suppression devices, cloud and fog dust suppression devices, cloud and fog dust suppression devices, bag dust removal devices, cyclone dust removal devices, wet dust removal devices, electrostatic dust removal devices, and desulfurization and dust removal devices. Used in chemical industry, petroleum, metallurgy, construction, mining, machinery, textile and other industries. The dust collector is composed of ash hopper, upper box, middle box, lower box and other parts. The upper, middle and lower boxes are divided into chambers. When working, the dusty gas enters ...

AI Technical Summary

Problems solved by technology

[0004] (1) The existing smoke detection method must use a suction sampling system to pump the smoke containing smoke into the measuring device, which cannot be measured online, and the measurement time is long. It takes a long time to obtain the measurement results, and real-time measurement cannot be realized; at the same time , wind power equipment for dust removal is prone to failure, and many problems are encountered in failure analysis, such as large amount of data, low efficiency of algorithm operation, poor interpretability of results, etc.

[0005] (2) In the prior art, the main control module processes the dust removal parameters in the processing parameter input module. In the production process, the data fusion of the parameters adopts a traditional algorithm, which cannot reflect the real dust removal situation and reduces the accuracy of data processing. Increased control error

[0006] (3) In the process of adjusting the power of the exhaust fan through the power adjustment circuit according to the smoke concentration in the prior art, when a fault occurs, the location of the faulty component and the identification of the parameter interval cannot be realized

[0007] (4) In the prior art, in the process of data storage module storing collected soot data and fault information through the memory, it is necessary to classify the unbalanced data sets in the collected soot data and fault information data. The memory adopts the current algorithm, which is easy It leads to overall changes in the distribution of unbalanced data sets and fuzzy positive and negative class boundaries, reducing the classification results of data, making it inconvenient for the storage to better store smoke data and fault information data, and prone to errors

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