CN111275332A - System and method for evaluating quality of bulldozer blade assembly process based on fuzzy-association rule - Google Patents
System and method for evaluating quality of bulldozer blade assembly process based on fuzzy-association rule Download PDFInfo
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Abstract
The invention discloses a system and a method for evaluating the assembly process quality of a bulldozer blade based on a fuzzy-association rule, which comprises the following steps: collecting assembly test parameters and constructing a test parameter database; analyzing the parameter database to determine the distribution form of the test parameter data; analyzing the parameters by adopting a membership function in a fuzzy theory to obtain a maximum threshold and a minimum threshold of the tested parameters; subjectively evaluating the quality of the assembled assembly, and constructing a Boolean database of test parameters; and analyzing the Boolean database by adopting an Apriori algorithm in the association rule, determining the support degree, the promotion degree and the interest degree of the assembling quality abnormal parameters of each procedure and the subjective evaluation result of the assembling quality of the scraper knife in the assembling process, and generating a rule base. The system for evaluating the assembling process quality of the bulldozer blade is formed on the basis of the rule base and can be used for judging the assembling quality of the blade based on the assembling quality parameters on the assembling line.
Description
Technical Field
The invention relates to the technical field of bulldozer blade assembly, in particular to a system and a method for evaluating quality of a bulldozer blade assembly process based on a fuzzy-association rule.
Background
The statements in this section merely provide background information related to the present disclosure and may not constitute prior art.
In the process of implementing the invention, the inventor finds that the following technical problems exist in the prior art:
the blade is an important component of a bulldozer. The functionality and reliability of the bulldozer are closely related to the work of the blade. At present, assembly lines adopted by domestic bulldozer production and manufacturing enterprises are more in types, most of the assembly lines and sub-assembly lines use flexible conveying lines to convey workpieces, and automatic assembly equipment is arranged on the flexible conveying lines to achieve the purpose of improving the production efficiency.
After assembly is complete, there are a number of experienced experts who can subjectively evaluate the quality of the assembly process. In order to judge the quality of the assembly, in order to prevent the loss of the evaluation capability of the assembly quality due to the deputy of experts, the association relationship between the actual assembly quality and the subjective evaluation of the experts needs to be accumulated to form a knowledge base, and no similar applicable software exists at present.
Disclosure of Invention
In order to solve the technical problems in the prior art, the invention provides a system and a method for evaluating the assembling process quality of a bulldozer blade based on a fuzzy-association rule. The quality evaluation method can be used for judging the quality of the assembly of the scraper knife based on the assembly quality on an assembly line.
In a first aspect, the invention provides a method for evaluating the quality of a bulldozer blade assembly process based on fuzzy-association rules, which comprises the following steps:
collecting assembly test parameters and constructing a test parameter database;
analyzing the parameter database to determine the distribution form of the test parameter data;
analyzing the test parameters by adopting a membership function in a fuzzy theory to obtain a maximum threshold and a minimum threshold of the test parameters, and determining a Boolean value of the test parameter data according to the maximum threshold and the minimum threshold;
the quality of the assembled assembly is subjectively evaluated and processed into a Boolean value;
constructing a quality evaluation Boolean database by using the evaluation result and the Boolean values of the test parameters;
analyzing the Boolean database by adopting an Apriori algorithm in the association rule to obtain the support degree, the promotion degree and the interest degree of the assembling quality abnormal parameters of each procedure and the subjective evaluation result of the assembling quality of the scraper knife in the assembling process, and generating a rule base;
collecting real-time assembly parameter data, performing fuzzification processing on the real-time assembly parameter data, and determining Boolean-type abnormal parameters of assembly quality of each process;
and evaluating the quality of the assembled assembly by using the constructed rule base.
In a second aspect, the present invention further provides a system for evaluating the quality of a bulldozer blade assembly process based on fuzzy-association rules, comprising:
the device is used for collecting assembly test parameters and constructing a test parameter database;
means for analyzing the parameter database to determine the distribution pattern of the test parameter data;
a device for analyzing the parameters by adopting a membership function in a fuzzy theory to obtain a maximum threshold and a minimum threshold of the tested parameters, processing the maximum threshold and the minimum threshold into Boolean values, subjectively evaluating the quality of the assembled assembly, processing the quality into Boolean values, and constructing a quality evaluation Boolean database;
a device for analyzing the Boolean database by adopting an Apriori algorithm in the association rule, and generating a rule base by using Boolean type data of a subjective evaluation result of the assembly quality of the scraper knife obtained by analysis and the support degree, the promotion degree and the interest degree of abnormal assembly quality parameters of each procedure in the assembly process;
the device is used for acquiring assembly parameters in real time and acquiring the assembly parameters of each process;
the device is used for fuzzifying the real-time data and determining Boolean-type abnormal parameters of the assembly quality of each process;
a device for evaluating the quality of the assembled assembly by big data analysis by utilizing the established rule base;
and forming a bulldozer blade assembly process quality evaluation system based on the fuzzy-association rule.
In a third aspect, the present disclosure also provides an electronic device comprising a memory and a processor, and computer instructions stored on the memory and executed on the processor, wherein the computer instructions, when executed by the processor, perform the steps of the method of the first aspect.
In a fourth aspect, the present disclosure also provides a computer-readable storage medium for storing computer instructions which, when executed by a processor, perform the steps of the method of the first aspect.
The invention has the beneficial effects that:
based on historical bulldozer assembly data and subjective evaluation experience of experts, the assembly parameters and the subjective evaluation experience are solidified to form a rule base of a scraper blade assembly quality subjective evaluation result and assembly quality abnormal parameters of each procedure in the assembly process, and a bulldozer scraper blade assembly process quality evaluation system is established, so that the product quality can be effectively improved.
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The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.
FIG. 1 is a system for evaluating the quality of a bulldozer blade assembly process based on fuzzy-association rules.
Detailed Description
It is to be understood that the following detailed description is exemplary and is intended to provide further explanation of the invention as claimed. 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.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
The embodiments and features of the embodiments of the present invention may be combined with each other without conflict.
In a first aspect, the invention provides a method for evaluating the quality of a bulldozer blade assembly process based on fuzzy-association rules, which comprises the following steps:
collecting assembly test parameters and constructing a test parameter database;
analyzing the parameter database to determine the distribution form of the test parameter data;
analyzing the test parameters by adopting a membership function in a fuzzy theory to obtain a maximum threshold and a minimum threshold of the test parameters, and determining a Boolean value of the test parameter data according to the maximum threshold and the minimum threshold;
the quality of the assembled assembly is subjectively evaluated and processed into a Boolean value;
constructing a quality evaluation Boolean database by using the evaluation result and the Boolean values of the test parameters;
analyzing the Boolean database by adopting an Apriori algorithm in the association rule to obtain the support degree, the promotion degree and the interest degree of the assembling quality abnormal parameters of each procedure and the subjective evaluation result of the assembling quality of the scraper knife in the assembling process, and generating a rule base;
collecting real-time assembly parameter data, performing fuzzification processing on the real-time assembly parameter data, and determining Boolean-type abnormal parameters of assembly quality of each process;
and evaluating the quality of the assembled assembly by using the constructed rule base.
In some embodiments, the test parameters include bolt torque, sprocket pressure value, and bearing clearance.
In some embodiments, the distribution is in the form of a weber distribution, a chi-square distribution, a normal distribution, or an F-distribution, and a probability density function thereof is calculated.
In some embodiments, the test parameters are analyzed using membership functions in fuzzy theory, with a minimum threshold of 0.05 and a maximum threshold of 0.97.
Further, the data between the minimum threshold and the maximum threshold is a normal value with a boolean value of 0, and the data below the minimum threshold and above the maximum threshold are abnormal values with a boolean value of 1.
In some embodiments, the subjective assessment method is: evaluating the assembly quality of the bulldozer blade by three to five experts, wherein the score range is 0-100 points, and the score is greater than or equal to 85 points and is marked as 0; score less than 85, 1.
In a second aspect, the present invention further provides a system for evaluating the quality of a bulldozer blade assembly process based on fuzzy-association rules, comprising:
the device is used for collecting assembly test parameters and constructing a test parameter database;
means for analyzing the parameter database to determine the distribution pattern of the test parameter data;
a device for analyzing the parameters by adopting a membership function in a fuzzy theory to obtain a maximum threshold and a minimum threshold of the tested parameters, processing the maximum threshold and the minimum threshold into Boolean values, subjectively evaluating the quality of the assembled assembly, processing the quality into Boolean values, and constructing a quality evaluation Boolean database;
a device for analyzing the Boolean database by adopting an Apriori algorithm in the association rule, and generating a rule base by using Boolean type data of a subjective evaluation result of the assembly quality of the scraper knife obtained by analysis and the support degree, the promotion degree and the interest degree of abnormal assembly quality parameters of each procedure in the assembly process;
the device is used for acquiring assembly parameters in real time and acquiring the assembly parameters of each process;
the device is used for fuzzifying the real-time data and determining Boolean-type abnormal parameters of the assembly quality of each process;
a device for evaluating the quality of the assembled assembly by big data analysis by utilizing the established rule base;
and forming a bulldozer blade assembly process quality evaluation system based on the fuzzy-association rule.
In a third aspect, the present disclosure also provides an electronic device comprising a memory and a processor, and computer instructions stored on the memory and executed on the processor, wherein the computer instructions, when executed by the processor, perform the steps of the method of the first aspect.
In a fourth aspect, the present disclosure also provides a computer-readable storage medium for storing computer instructions which, when executed by a processor, perform the steps of the method of the first aspect.
Example 1
A bulldozer blade assembly process quality evaluation method based on fuzzy-association rules comprises the following steps:
the assembly test parameters are collected through industrial Internet of things data collection and assembly test equipment, and the test parameters comprise data such as bolt torque, a sprocket pressure value and a bearing gap in a transmission assembly, so that a parameter database is formed.
And determining distribution characteristics of data such as bolt torque, sprocket pressure value, bearing clearance and the like by using a big data analysis tool, carrying out big data analysis to obtain a distribution rule of characteristic items, selecting Weber distribution, chi-square distribution, normal distribution and F distribution to process data among bolt torque, sprocket pressure value and shaft, and calculating to obtain respective probability density functions.
Probability density function of weber distribution:
probability density function of normal distribution:
probability density function of chi-squared distribution:
probability density function of F distribution:
and on the basis of the obtained distribution morphology characteristics, selecting a membership function in a fuzzy theory to carry out fuzzy analysis on numerical value type data in a parameter database to obtain an assembly moment, a sprocket pressure value, a normal and abnormal threshold value of a bearing clearance and a subjective evaluation result of the assembled assembly quality, and constructing a Boolean database of the bulldozer blade assembly process parameters.
And calculating the bolt torque, the sprocket pressure value and the bearing clearance by adopting a membership function in a fuzzy theory. The bolt torque is obtained through calculation, the lower deviation threshold value of the sprocket pressure value and the sprocket pressure value is 0.05, the upper deviation threshold value is 0.97, the data between the upper deviation threshold value and the lower deviation threshold value is a normal value, the Boolean value of the data is 0, the data below the lower deviation threshold value is a low value, the data above the upper deviation threshold value is a high value, the low value and the high value are both regarded as abnormal values, and the Boolean value of the data is 1.
The subjective evaluation method is characterized in that three to five experts subjectively evaluate the assembly quality of the bulldozer blade, the score range is 0-100, the blade assembly quality score is greater than or equal to 85, the assembly quality is considered to be excellent, and the score is 0; an assembly quality below 85 is considered poor and is noted as 1.
And constructing a quality evaluation Boolean database of the bulldozer blade assembly process according to the Boolean values of the determined test parameter data and Boolean data of the subjective evaluation results.
And then, carrying out big data analysis on the Boolean data generated in the fuzzified assembly process by applying an Apriori algorithm in the association rule to obtain the support degree, the promotion degree and the interest degree of the assembly quality abnormal parameters of each procedure and the subjective evaluation result of the blade assembly quality in the assembly process, generating a rule base, and forming the bulldozer blade assembly process quality evaluation system based on the fuzzy-association rule.
Bulldozer blade assembly process, its spare part includes: the device comprises a bolt, a gasket, a left integrated pipe seat, a right integrated pipe seat, a hose, a flange, an O-shaped pipe, an oil suction pipe (pump end), a T-shaped hose clamp, a flat key, a spacer bush, a locking block and the like.
The adopted equipment assembly process comprises the following steps: installing an upper hard tube of a working oil tank; installing a hose on the main frame; connecting a pipeline; installing a working pump; installing an upper pipeline of a working oil tank; connecting a pipeline; detecting bolt torque; hoisting the first-stage wheel, the second-stage wheel and the third-stage wheel; hoisting the outer shell; adjusting the bearing clearance; detecting a bearing clearance; reaming; installing a dust cover; hoisting a chain wheel; and detecting the pressure value of the chain wheel, and entering the next working procedure after the detection is finished.
And matching the bolt torque, the bearing clearance and the sprocket pressure value detected in the assembling process of the bulldozer blade with a rule base so as to evaluate the assembling quality of the blade.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (9)
1. The method for evaluating the quality of the bulldozer blade assembly process based on the fuzzy-association rule is characterized by comprising the following steps: the method comprises the following steps:
collecting assembly test parameters and constructing a test parameter database;
analyzing the parameter database to determine the distribution form of the test parameter data;
analyzing the test parameters by adopting a membership function in a fuzzy theory to obtain a maximum threshold and a minimum threshold of the test parameters, and determining a Boolean value of the test parameter data according to the maximum threshold and the minimum threshold;
the quality of the assembled assembly is subjectively evaluated and processed into a Boolean value;
constructing a quality evaluation Boolean database by using the evaluation result and the Boolean values of the test parameters;
analyzing the Boolean database by adopting an Apriori algorithm in the association rule to obtain the support degree, the promotion degree and the interest degree of the assembling quality abnormal parameters of each procedure and the subjective evaluation result of the assembling quality of the scraper knife in the assembling process, and generating a rule base;
collecting real-time assembly parameter data, performing fuzzification processing on the real-time assembly parameter data, and determining Boolean-type abnormal parameters of assembly quality of each process;
and evaluating the quality of the assembled assembly by using the constructed rule base.
2. The method for evaluating the quality of a bulldozer blade assembly process based on fuzzy-association rules according to claim 1, characterized in that: the test parameters include bolt torque, sprocket pressure values and bearing clearances.
3. The method for evaluating the quality of a bulldozer blade assembly process based on fuzzy-association rules according to claim 1, characterized in that: the distribution form is Weber distribution, chi-square distribution, normal distribution or F distribution, and the probability density function is calculated.
4. The method for evaluating the quality of a bulldozer blade assembly process based on fuzzy-association rules according to claim 1, characterized in that: and analyzing the test parameters by adopting a membership function in a fuzzy theory, wherein the minimum threshold value of the test parameters is 0.05, and the maximum threshold value of the test parameters is 0.97.
5. The method for evaluating the quality of a bulldozer blade assembly process according to claim 4, in which: data between the minimum threshold and the maximum threshold are normal values with a boolean value of 0, and data below the minimum threshold and above the maximum threshold are abnormal values with a boolean value of 1.
6. The method for evaluating the quality of a bulldozer blade assembly process based on fuzzy-association rules according to claim 1, characterized in that: the subjective evaluation method comprises the following steps: evaluating the assembling quality of the bulldozer blade by three to five experts, wherein the score range is 0-100 points, and the score is greater than or equal to 85 points and is marked as 0; score less than 85, 1.
7. A bulldozer blade assembly process quality evaluation system based on fuzzy-association rules is characterized in that: the method comprises the following steps:
the device is used for collecting assembly test parameters and constructing a test parameter database;
means for analyzing the parameter database to determine the distribution pattern of the test parameter data;
a device for analyzing the parameters by adopting a membership function in a fuzzy theory to obtain a maximum threshold and a minimum threshold of the tested parameters, processing the maximum threshold and the minimum threshold into Boolean values, subjectively evaluating the quality of the assembled assembly, processing the quality into Boolean values, and constructing a quality evaluation Boolean database;
a device for analyzing the Boolean database by adopting an Apriori algorithm in the association rule, and generating a rule base by using Boolean type data of a subjective evaluation result of the assembly quality of the scraper knife obtained by analysis and the support degree, the promotion degree and the interest degree of abnormal assembly quality parameters of each procedure in the assembly process;
the device is used for acquiring assembly parameters in real time and acquiring the assembly parameters of each process;
the device is used for fuzzifying the real-time data and determining Boolean-type abnormal parameters of the assembly quality of each process;
a device for evaluating the quality of the assembled assembly by big data analysis by utilizing the established rule base;
and forming a bulldozer blade assembly process quality evaluation system based on the fuzzy-association rule.
8. An electronic device, characterized in that: comprising a memory and a processor and computer instructions stored on the memory and executed on the processor, which when executed by the processor, perform the steps of the method of the first aspect.
9. A computer-readable storage medium characterized by: for storing computer instructions which, when executed by a processor, perform the steps of the method of the first aspect.
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