Shaft furnace fault condition forecasting method based on improved case-based reasoning

A case and fault technology, applied in the field of automation, can solve the problem of low fault prediction accuracy

Inactive Publication Date: 2013-08-14
BEIJING UNIV OF TECH
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Problems solved by technology

However, whether the results given by the traditional CBR method are reasonable depends on the richness of experience and its learning ability. In the process of CBR reasoning and solving, there are still some problems that have not been completely resolved, such as the weight distribution of case attributes, the correction of case solutions, etc. If these problems are not solved, the accuracy of fault prediction is also not high

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  • Shaft furnace fault condition forecasting method based on improved case-based reasoning
  • Shaft furnace fault condition forecasting method based on improved case-based reasoning
  • Shaft furnace fault condition forecasting method based on improved case-based reasoning

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Embodiment Construction

[0054] The specific implementation manners of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0055] see figure 1 Shown is the schematic diagram of the shaft furnace roasting process and faults. Blower V 1 delivered air and regulating valve V 2 The transported gas is mixed and combusted in the combustion chambers on both sides, and the raw ore to be processed entering the furnace from the top of the shaft furnace is heated to 700-850°C, and the ore falls to the reduction zone and cools down to about 570°C, and is connected with the regulating valve V 3 The transported gas undergoes a reduction reaction to generate a strong magnetic roasted ore, and finally passes through the motor V 4 Move out of the oven. In the production process of the shaft furnace, there are 5 most common failures, which are burning y 1 , fire y 2 , blast y 3 , furnace y 4 and overreduction y 5 , these types of faults may occur simultaneou...

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Abstract

The invention relates to a shaft furnace condition fault forecasting method based on improved case-based reasoning. An attribute weight allocation model is added on the basis of a 4R cognitive model, and the GDM (global data manager) theory is utilized to improve a case-correcting model. The shaft furnace fault condition forecasting method includes initializing variables, normalizing current variables to keep values ranging from 0 to 1; displaying a case, establishing a case base; calculating correlation coefficients based on the water filling weight allocating algorithm, calculating case attribute weight; calculating similarity between target cases and source cases, confirming numbers of matching cases according to a similarity threshold value; judging reusing effect; performing GDM calibration to forecast results; storing the corresponding cases, and outputting operation guides. The shaft furnace condition fault forecast based on improved case-based reasoning is realized by utilizing online process data. Compared with a method for judging furnace condition manually, the shaft furnace condition fault forecasting method based on improved case-based reasoning reduces workload of operators, reduces uncertainty of manual judgment and increases timeliness of fault forecast.

Description

technical field [0001] The invention belongs to the technical field of automation, and in particular relates to an intelligent prediction method for furnace condition faults in a shaft furnace roasting production process in the metallurgical industry. technical background [0002] In the shaft furnace roasting process, the condition of the shaft furnace is relatively complicated, and there are many fault points. Once a fault occurs, it will affect the production and threaten the safety of personnel and equipment. Therefore, it is necessary to detect early fault symptoms in time and carry out Corresponding treatment to avoid failure deterioration and unnecessary economic losses. However, there are many disturbances in the roasting process of the shaft furnace and the mechanism model is difficult to obtain, which makes it difficult for the conventional failure prediction method to work. Therefore, it is necessary and urgent to find a suitable method to establish a prediction m...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
Inventor 严爱军郭振邵宏赡
Owner BEIJING UNIV OF TECH
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