Knowledge-based fault prediction expert system for complex milling machine tool

Abstract

The invention relates to a knowledge-based fault prediction expert system for a complex milling machine tool, which comprises a man-machine interface module, a data acquisition and preprocessing module, a knowledge acquisition module based on data mining, a self-adaptive fault prediction module, a fault diagnosis expert system, an interpreter, an inference machine, a prediction method library, an integrated knowledge library, a model library and a diagnosis module; wherein the man-machine interface module is used for transmitting real-detection data and historical data to other modules; the data acquisition and preprocessing module is used for preprocessing the received data and inputting the preprocessed data to the knowledge acquisition module for data mining; the knowledge acquisition module is connected with the fault diagnosis expert system through the fault prediction module; the fault prediction module and the fault diagnosis expert system input fault prediction and diagnosis results into the inference machine, and the inference machine search in the integrated knowledge library and the model library; and the fault prediction module establishes a selection target function, and the inference machine selects a proper prediction method for fault prediction from the prediction method library. The invention can be widely applied in the fault diagnosis of various numerically-controlled machine tools.

Description

technical field [0001] The invention relates to a fault diagnosis and prediction system for a CNC machine tool, in particular to a knowledge-based fault prediction expert system for a turning-milling compound machine tool. Background technique [0002] As a typical electromechanical system of CNC machine tools, its fault diagnosis and early warning technology is one of the core technologies to ensure the reliable operation of machine tools and improve the service performance of machine tools. As one of the development directions of mechanical processing, compound processing is also a main direction of the development of numerical control equipment. The turning-milling compound machine tool combines the functions of turning and milling, and realizes the turning processing of the rotary body, end face, etc., and the milling processing of planes and grooves after the parts are clamped once. The installation positioning error is reduced, the loading and unloading time is greatl...

AI Technical Summary

Problems solved by technology

[0003] Traditional expert systems are widely used in various fields, but there are some insurmountable shortcomings: 1. Most expert systems use knowledge expressions based on production rules, but this expression cannot effectively express and reflect the intrinsic nature of things. In-depth knowledge, especially not suitable for expressing process control, numerical calculation and description of domain concepts and domain objects

2. The traditional expert system often adopts a single reasoning strategy, so it has poor flexibility when solving problems, the system structure is not good, and it is not easy to maintain, modify and expand

Therefore, the traditional expert system cannot diagnose and predict the fault trend of machine tools, cannot effectively convert raw data into valuable knowledge, and cannot analyze past trends and predict future trends

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