CN113204212A - Numerical control machine tool fault diagnosis method based on double-expert system - Google Patents
Numerical control machine tool fault diagnosis method based on double-expert system Download PDFInfo
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/18—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form
- G05B19/406—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by monitoring or safety
- G05B19/4063—Monitoring general control system
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- G—PHYSICS
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
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Abstract
The invention discloses a numerical control machine tool fault diagnosis method based on a double-expert system. Firstly, a numerical control machine tool system collects real-time detection signals and judges fault characteristic signals; then, the fault signals are respectively transmitted to a fault diagnosis expert system of the numerical control machine tool and a case base fault diagnosis expert system of the cloud service; further, the two fault diagnosis expert systems respectively reason the fault signals and obtain an inference decision; and finally, the two fault reasoning decisions are respectively provided for the user, and the user selects a proper reasoning decision according to the actual situation. The novel numerical control machine tool fault diagnosis method based on the double-expert system can be used for accurately diagnosing the faults of the numerical control machine tool and accumulating fault cases more quickly, so that the maintenance efficiency of the numerical control machine tool is improved, and the production and development of the machining industry are promoted.
Description
Technical Field
The invention relates to a numerical control machine tool fault diagnosis method based on a double-expert system, which can be used for fault diagnosis of a numerical control machine tool and belongs to the field of fault diagnosis of the numerical control machine tool.
Background
With the vigorous development of the machinery manufacturing industry in China, the production requirements of the fine industry are increasingly raised. The numerical control machine tool is popular in the fine industry because the numerical control machine tool can effectively solve the machining problem of complex, precise and multi-change small parts.
However, the numerical control machine is a complex and precise instrument, and the operation precision and reliability of the whole numerical control machine can be affected by one fault, so that the economic benefit of an enterprise is affected. The numerical control machine tool has high complex, technical and professional properties, and general maintenance personnel are difficult to find out fault reasons in time, so that the maintenance time and the cost are increased rapidly, the requirement of talents in mechanical specialties is increased rapidly, and the production cost of products is increased greatly. In order to solve the problems, a fault diagnosis system for a numerical control machine tool is developed.
At present, the fault diagnosis method for the numerical control machine tool mainly comprises the following steps: communication diagnosis, artificial intelligence expert system, neural network diagnosis, multi-sensor information fusion diagnosis and intelligent integrated diagnosis. In the method, the fault diagnosis method based on the artificial intelligence expert system has certain advantages and is relatively in line with the current development trend.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides the numerical control machine tool fault diagnosis method based on the double-expert system, so that the problem of low fault cause diagnosis accuracy is solved, and the Internet is connected, thereby being beneficial to other networked numerical control machine tools to quickly solve the faults. The method can rapidly expand the fault case base, so that the fault processing speed is higher, and the fault reason searching accuracy is higher.
In order to achieve the purpose, the invention adopts the technical scheme that: a numerical control machine tool fault diagnosis method based on a double-expert system comprises the following steps;
the method comprises the following steps: the numerical control machine tool system collects detection signals in real time and judges fault characteristic signals;
step two: the fault information is respectively made reasoning decision in a fault diagnosis expert system of the numerical control machine tool and a case base expert system of the cloud service;
step three: and reasoning decisions made by the numerical control machine fault diagnosis expert system and the case base expert system of the cloud service are respectively provided for users.
Further, the first step specifically comprises: the numerical control machine tool system collects detection signals in real time and collects information through the numerical control machine tool system information collection module; the information acquisition module of the numerical control system of the numerical control machine tool comprises a real-time data acquisition module, a historical data recording module, an alarm event data recording module and a network interface.
Furthermore, the information acquisition module of the numerical control machine tool numerical control system acquires signals of a detection object through sensors such as a current sensor, a voltage sensor, a vibration sensor, a temperature sensor and a noise sensor, and the numerical control center judges fault characteristic signals to realize acquisition at the first time and find fault signals of the numerical control machine tool.
Further, in the second step, the fault information is respectively transmitted to a fault diagnosis expert system of the numerical control machine and a case base fault diagnosis expert system of the cloud service; the fault diagnosis expert system of the numerical control machine tool is established according to a fault tree analysis method, and the fault reason is deduced according to reverse thinking logic and a solution is given; the case base fault diagnosis expert system of the cloud service is established according to a case base, a knowledge base of the case base comprises a plurality of reasons for generating fault signals and solutions with reliable corresponding reasons, and the same or similar fault cases in the case base are searched to obtain a final reasoning decision.
Further, the third step is specifically: the numerical control machine tool provides two kinds of inference decisions of expert systems for a user, the inference decisions of a fault diagnosis expert system of the machine tool and the inference decisions of a case base expert system of cloud service are respectively provided, and the user can select a proper solution according to the actual situation of the user.
The invention has the beneficial effects that: the numerical control machine tool fault diagnosis method based on the double-expert system is simple, rapid and accurate in detection method, only the fault signal of the numerical control machine tool needs to be collected and sent, and the fault signal is subjected to reasoning decision by the expert system of the numerical control system and the case library expert system on the cloud service platform, so that the correctness of the reasoning decision is improved, and the hysteresis caused by the fact that the numerical control machine tool is not updated is made up.
Drawings
FIG. 1 is a schematic diagram of a fault diagnosis process for the dual expert system of the present invention;
FIG. 2 is a schematic flow chart of a half-section of a fault characteristic signal of the numerical control machine tool according to the invention;
FIG. 3 is an expert system fault diagnosis model of the present invention;
FIG. 4 is a case base fault diagnosis model of the present invention;
FIG. 5 is a schematic diagram of a fault tree analysis method according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood, however, that the description herein of specific embodiments is only intended to illustrate the invention and not to limit the scope of the invention.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs, and the terms used herein in the specification of the present invention are for the purpose of describing particular embodiments only and are not intended to limit the present invention.
As shown in fig. 1, 2, 3, 4 and 5, the numerical control machine tool fault diagnosis method of the dual-expert system is mainly characterized in that fault diagnosis is performed not only by a fault diagnosis expert system of the numerical control machine tool itself, but also by being combined with the internet of things, so that case base expert system diagnosis of the cloud service platform is realized. Specifically, the numerical control machine tool fault diagnosis method based on the dual system comprises the following steps:
step 1: a numerical control system of the numerical control machine tool acquires fault information; the method specifically comprises the following steps:
the method comprises the steps of detecting a plurality of functional systems of the numerical control machine tool in real time, transmitting a fault characteristic signal to a numerical control system center when the signal is collected, identifying whether the signal is the fault signal by the numerical control center, and respectively transmitting the fault signal to a fault diagnosis expert system of the numerical control machine tool and a case base expert system of cloud service when the signal is judged to be the fault signal, wherein the steps are shown in the fault signal judgment shown in fig. 2.
Step 2: the fault information is respectively made reasoning decision in a fault diagnosis expert system of the numerical control machine tool and a case base expert system of the cloud service; the method specifically comprises the following steps:
and the numerical control center respectively transmits the determined fault signals to a fault diagnosis expert system of the numerical control machine and a case base fault diagnosis expert system of the cloud service. The expert system of the numerical control machine tool inputs expert knowledge and experience in the numerical control field into a computer, so that the computer can 'think' and 'reason' like people, thereby solving the problem of faults in the numerical control machine tool. The knowledge base and the rules of the expert system of the numerical control machine tool are established according to a fault tree analysis method, the schematic diagram of the fault tree analysis method is shown in figure 5, the fault tree takes a fault which is not expected to occur in the system as a top event, all intermediate events which can cause the top event are found out, all factors which cause the intermediate events are found out, a bottom event which causes the fault is traced back according to the method, and the top event and the bottom event are connected through a logical relation, so that the fault tree is formed. The fault diagnosis expert system of the numerical control machine tool uses reverse thinking, knows a top event, and carries out layer-by-layer reasoning analysis by utilizing a logical relationship until a bottom event forming the top event is found, so that a fault reason is found; the expert system in the cloud service is established according to the case base, and the knowledge acquisition sources of the case base are mainly summarized into two categories: one type is fault information uploaded by a networked numerical control machine tool system, and after the fault information needs to be maintained or a professional solves a fault, the fault reason and the solution of the fault information are determined and uploaded to a case library of a cloud server, so that the effect of perfecting the case library is achieved. The other type is case accumulation in an enterprise, cases of the type are mainly provided by maintenance personnel and experts of numerical control machine tool manufacturers, and the fault knowledge is not only accurate and reliable, but also more detailed in classification. The fault diagnosis model based on the case base is shown in fig. 4.
And step 3: reasoning decisions made by the numerical control machine fault diagnosis expert system and the case base expert system of the cloud service are output to a human-computer interaction interface for selection by a user; the method specifically comprises the following steps:
and the fault diagnosis expert system of the numerical control machine tool obtains a reasoning decision according to the layer indexes of the fault signals in the knowledge base. Meanwhile, the case base diagnostic expert system in the cloud service also carries out fault indexing on the fault signal to obtain a specialized fault diagnosis reason and a corresponding solution, and sends the inference decision to the numerical control machine tool, and the numerical control machine tool displays the two inference decisions together to a user so that the user can select the solution of the fault by self.
The numerical control machine tool fault diagnosis method based on the double-expert system is simple, rapid and accurate in detection method, only the fault signal of the numerical control machine tool needs to be collected and sent, and the fault signal is subjected to reasoning decision by the expert system of the numerical control system and the case library expert system on the cloud service platform, so that the correctness of the reasoning decision is improved, and the hysteresis caused by the fact that the numerical control machine tool is not updated is made up.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents or improvements made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (5)
1. A numerical control machine tool fault diagnosis method based on a double-expert system is characterized by comprising the following steps;
the method comprises the following steps: the numerical control machine tool system collects detection signals in real time and judges fault characteristic signals;
step two: the fault information is respectively made reasoning decision in a fault diagnosis expert system of the numerical control machine tool and a case base expert system of the cloud service;
step three: and reasoning decisions made by the numerical control machine fault diagnosis expert system and the case base expert system of the cloud service are respectively provided for users.
2. The numerical control machine tool fault diagnosis method based on the dual expert system according to claim 1, characterized in that the first step is specifically: the numerical control machine tool system collects detection signals in real time and collects information through the numerical control machine tool system information collection module; the information acquisition module of the numerical control system of the numerical control machine tool comprises a real-time data acquisition module, a historical data recording module, an alarm event data recording module and a network interface.
3. The numerical control machine tool fault diagnosis method based on the dual expert system as claimed in claim 2, wherein the numerical control machine tool numerical control system information acquisition module acquires a detection object signal through sensors such as a current sensor, a voltage sensor, a vibration sensor, a temperature sensor and a noise sensor, and the numerical control center judges a fault characteristic signal, so that the first time acquisition is realized and a fault signal of the numerical control machine tool is found.
4. The numerical control machine tool fault diagnosis method based on the dual-expert system as claimed in claim 1, wherein in the second step, fault information is respectively transmitted to a fault diagnosis expert system of the numerical control machine tool and a case base fault diagnosis expert system of a cloud service; the fault diagnosis expert system of the numerical control machine tool is established according to a fault tree analysis method, and the fault reason is deduced according to reverse thinking logic and a solution is given; the case base fault diagnosis expert system of the cloud service is established according to a case base, a knowledge base of the case base comprises a plurality of reasons for generating fault signals and solutions with reliable corresponding reasons, and the same or similar fault cases in the case base are searched to obtain a final reasoning decision.
5. The numerical control machine tool fault diagnosis method based on the dual expert system according to claim 1, wherein the third step is specifically: the numerical control machine tool provides two kinds of inference decisions of expert systems for a user, the inference decisions of a fault diagnosis expert system of the machine tool and the inference decisions of a case base expert system of cloud service are respectively provided, and the user can select a proper solution according to the actual situation of the user.
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| CN116382244A (en) * | 2023-04-28 | 2023-07-04 | 润芯微科技(江苏)有限公司 | Intelligent automobile online monitoring and diagnosing system and method based on embedded intelligent automobile online monitoring and diagnosing system |
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