CN114969140A - Detection and analysis method for product performance data of fluency strip - Google Patents
Detection and analysis method for product performance data of fluency strip Download PDFInfo
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Abstract
The invention discloses a method for detecting and analyzing product performance data of a fluency strip, which relates to the technical field of product performance data detection and analysis, solves the technical problem that the product performance of the fluency strip cannot be accurately detected and analyzed in the prior art, and accurately judges the qualified interval of the production data of the fluency strip, thereby improving the supervision of the fluency strip, effectively and accurately judging the product performance of the fluency strip and improving the production quality of the fluency strip; abnormal feature analysis is carried out on the unqualified fluency strips, and the abnormal features of the fluency strips are analyzed, so that the influence degree of the fluency strip faults is reasonably controlled, the rectification timeliness of the fault fluency strips is improved, and meanwhile the fluency strip faults are effectively prevented; and analyzing the influence factors of the main fault characteristics of the historical unqualified fluency strips, judging the influence factors of the main fault characteristics, controlling the influence of the influence factors on the main fault characteristics, improving the production efficiency of the fluency strips and reducing the fault frequency of the fluency strips.
Description
Technical Field
The invention relates to the technical field of product performance data detection and analysis, in particular to a method for detecting and analyzing product performance data of fluency strips.
Background
The fluency strip is a short name of an aluminum alloy sliding rail, is convenient and quick to install, can be used for smoothly and conveniently running objects placed above the sliding strip, is called the fluency strip as the name implies, is mainly used for a workshop material rack and the like, and is developed into a plastic product fluency strip for reducing the cost along with the deepening of lean production modes in recent years, wherein a smooth cylinder is called a second generation fluency strip, a fast sliding strip is called a third generation fluency strip, and the product performance detection of the fluency strip is particularly important along with the increasing of the using amount of the fluency strip;
however, in the prior art, the qualified interval of the production data of the qualified fluency strip cannot be obtained through historical production data analysis, so that the accuracy of quality detection is reduced, meanwhile, the influence factors of the unqualified fluency strip cannot be analyzed, the production efficiency of the fluency strip cannot be improved, and the fault frequency of the fluency strip can be reduced;
in view of the above technical drawbacks, a solution is proposed.
Disclosure of Invention
The invention aims to solve the problems, and provides a method for detecting and analyzing the product performance data of the fluency strip, which is used for analyzing the data of the fluency strip produced in history and accurately judging the qualified interval of the production data of the fluency strip, thereby improving the supervision of the fluency strip, effectively and accurately judging the product performance of the fluency strip and improving the production quality of the fluency strip; abnormal feature analysis is carried out on unqualified fluency strips, and the faulted fluency strips are analyzed to analyze the abnormal features of the fluency strips, so that the influence degree of the fluency strip faults is reasonably controlled, the rectification timeliness of the faulted fluency strips is improved, meanwhile, the fluency strip faults are effectively prevented, and the fault rate of the fluency strips is reduced; and analyzing the influence factors of the main fault characteristics of the historical unqualified fluency strips, and judging the influence factors of the main fault characteristics, thereby controlling the influence brought by the main fault characteristics, controlling the influence of the influence factors on the main fault characteristics, improving the production efficiency of the fluency strips, and reducing the fault frequency of the fluency strips.
The purpose of the invention can be realized by the following technical scheme:
a method for detecting and analyzing product performance data of a fluency strip comprises the following steps:
step one, historical data analysis, namely, judging a qualified interval of the production data of the fluency strip by carrying out data analysis on the fluency strip produced in history;
analyzing abnormal characteristics, namely analyzing the failed fluency strip and judging the abnormal characteristics of the fluency strip;
analyzing influence factors, namely acquiring the influence factors of the fluency strip according to the abnormal characteristics of the fluency strip so as to predict the abnormity of the fluency strip;
and step four, real-time detection, namely performing quality analysis detection on the fluent strip which is produced in real time.
As a preferred embodiment of the present invention, the historical data analysis process in the step one is as follows:
marking the historical produced fluent strips as finished fluent strips, setting a mark i, wherein the mark i is a natural number greater than 1, acquiring the failure times and the use frequency of the finished fluent strips, and if the failure times of the finished fluent strips do not exceed a failure time threshold and the use frequency exceeds a use frequency threshold, marking the corresponding finished fluent strips as qualified fluent strips; if the failure times of the finished fluent strips exceed the failure time threshold and the use frequency does not exceed the use frequency threshold, marking the corresponding finished fluent strips as unqualified fluent strips;
analyzing the qualified fluency strips, acquiring environmental data and equipment data of the qualified fluency strips, wherein the environmental data comprises environmental temperature and environmental humidity, the equipment data comprises equipment operation time and equipment operation frequency, acquiring the environmental data and the equipment data of the production process of the qualified fluency strips, carrying out numerical statistics on the environmental temperature and the environmental humidity in the environmental data, acquiring the highest numerical value and the lowest numerical value of the environmental temperature, and acquiring an environmental temperature interval through the highest numerical value and the lowest numerical value of the environmental temperature; acquiring a highest value and a lowest value of the environmental humidity, and acquiring an environmental humidity interval through the highest value and the lowest value of the environmental humidity;
carrying out numerical statistics on equipment operation duration and equipment operation frequency in the equipment data, collecting the highest numerical value of the equipment operation duration and the lowest numerical value of the equipment operation duration, and acquiring an equipment operation duration interval through the highest numerical value of the equipment operation duration and the lowest numerical value of the equipment operation duration; acquiring the highest numerical value of the equipment operating frequency and the lowest numerical value of the equipment operating frequency, and acquiring an equipment operating frequency interval through the highest numerical value of the equipment operating frequency and the lowest numerical value of the equipment operating frequency; and storing the environment temperature interval, the environment humidity interval, the equipment operation time interval and the equipment operation frequency interval of the qualified fluency strips.
As a preferred embodiment of the present invention, the abnormal feature analysis process in step two is as follows:
marking the historical unqualified fluency strips as feature analysis objects, acquiring fault features of the feature analysis objects, and setting the fault features of the feature analysis objects to be marked o, wherein o is a natural number greater than 1; acquiring the occurrence frequency and the total maintenance time consumption of the fault characteristics of the characteristic analysis object, and respectively marking the occurrence frequency and the total maintenance time consumption of the fault characteristics of the characteristic analysis object as PLo and SCo; acquiring the growth speed of the fault feature occurrence frequency of the feature analysis object, and marking the growth speed of the fault feature occurrence frequency of the feature analysis object as SDo;
analyzing the analysis coefficient Xo of the obtained fault characteristics, and comparing the analysis coefficient of the fault characteristics with an analysis coefficient threshold value:
if the analysis coefficient of the fault characteristic exceeds the analysis coefficient threshold, marking the corresponding fault characteristic as a main fault characteristic; if the analysis coefficient of the fault characteristic does not exceed the analysis coefficient threshold, marking the corresponding fault characteristic as a secondary fault characteristic;
and updating and storing the main fault characteristics in real time, and immediately finishing the production line of the fluency strip if the main fault characteristics of the fluency strip appear in the production process.
As a preferred embodiment of the present invention, the influencing factor analysis process of the third step is as follows:
setting an influence factor acquisition time period, wherein the occurrence time of the main fault characteristics of the historical unqualified fluency strips is the middle time of the influence factor acquisition time period; the occurrence time of the main fault characteristics divides the time period of the acquisition of the influencing factors into a front time period and a rear time period; collecting numerical data produced by the fluency strip, and analyzing the numerical data;
acquiring a floating value of the numerical data in the front time period, and if the floating value of the numerical data exceeds a corresponding floating value threshold, marking the corresponding numerical data as a factor causing influence; if the floating value of the numerical data does not exceed the corresponding floating value threshold, marking the corresponding numerical data as an irrelevant influence factor; acquiring a floating value of the numerical data in the rear time period, and if the floating value of the numerical data is changed from not exceeding a corresponding floating value threshold value to exceeding the corresponding floating value threshold value, marking the corresponding data numerical value as a factor of influence; if the floating value of the numerical data does not exceed the corresponding floating value threshold value and the floating amplitude does not exceed the corresponding floating amplitude threshold value, representing the corresponding numerical data as an irrelevant influence factor;
the influencing factors and the dependent influencing factors are stored, the influencing factors are monitored in real time when the main fault characteristics do not appear, and the factors absorbed by the factors are regulated and controlled in time when the main fault characteristics appear.
As a preferred embodiment of the present invention, the real-time detection process of step four is as follows:
marking the fluent strip which completes survival in real time as a real-time detection fluent strip, collecting the random inspection qualification rate of the real-time detection fluent strip and the longest qualification time of frequent use, and respectively comparing the random inspection qualification rate of the real-time detection fluent strip and the longest qualification time of the frequent use with a qualification rate threshold value and a qualification time threshold value:
if the random inspection qualification rate of the real-time detection fluency strips exceeds the qualification rate threshold and the longest frequently used qualification time exceeds the qualification time threshold, judging that the quality of the corresponding real-time detection fluency strips is qualified, and marking the quality as the real-time qualification fluency strips; and if the random inspection qualification rate of the real-time detection fluency strips does not exceed the qualification rate threshold or the longest frequently-used qualified time does not exceed the qualified time threshold, judging that the quality of the corresponding real-time detection fluency strips is unqualified, and marking the corresponding real-time detection fluency strips as real-time unqualified fluency strips.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the method, the data analysis is carried out on the fluency strip produced in history, and the qualified interval of the production data of the fluency strip is accurately judged, so that the supervision on the fluency strip is improved, the product performance of the fluency strip is effectively and accurately judged, and the production quality of the fluency strip is improved; abnormal feature analysis is carried out on unqualified fluency strips, and the faulted fluency strips are analyzed to analyze the abnormal features of the fluency strips, so that the influence degree of the fluency strip faults is reasonably controlled, the rectification timeliness of the faulted fluency strips is improved, meanwhile, the fluency strip faults are effectively prevented, and the fault rate of the fluency strips is reduced;
2. according to the method, the influence factors of the main fault characteristics of the historical unqualified fluency strips are analyzed, and the influence factors of the main fault characteristics are judged, so that the influence caused by the main fault characteristics is controlled, meanwhile, the influence of the influence factors on the main fault characteristics can be controlled, the production efficiency of the fluency strips is improved, and meanwhile, the fault frequency of the fluency strips can be reduced; the quality analysis and detection are carried out on the fluent strip which completes the production in real time, whether the data analysis is qualified or not can be judged while the production quality of the fluent strip is controlled, and the reduction of the quality monitoring efficiency of the fluent strip caused by the abnormal analysis steps is prevented, so that the risk of the fluent strip breaking down is increased.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic block diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, a method for detecting and analyzing product performance data of a fluency strip includes the following steps:
step one, historical data analysis, namely, judging a qualified interval of the production data of the fluency strip by carrying out data analysis on the fluency strip produced in history;
analyzing abnormal characteristics, namely analyzing the failed fluency strip and judging the abnormal characteristics of the fluency strip;
analyzing influence factors, namely acquiring the influence factors of the fluency strip according to the abnormal characteristics of the fluency strip so as to predict the abnormity of the fluency strip;
step four, real-time detection, namely performing quality analysis detection on the fluent strips which are produced in real time;
the method comprises the following steps of analyzing data of the fluency strip produced in history, and accurately judging the qualified interval of the production data of the fluency strip, thereby improving the supervision of the fluency strip, effectively and accurately judging the product performance of the fluency strip, and improving the production quality of the fluency strip, wherein the specific historical data analysis process comprises the following steps:
marking the historical produced fluent strips as finished fluent strips, setting a mark i, wherein the mark i is a natural number greater than 1, acquiring the failure times and the use frequency of the finished fluent strips, and if the failure times of the finished fluent strips do not exceed a failure time threshold and the use frequency exceeds a use frequency threshold, marking the corresponding finished fluent strips as qualified fluent strips; if the failure times of the finished fluent strips exceed the failure time threshold and the use frequency does not exceed the use frequency threshold, marking the corresponding finished fluent strips as unqualified fluent strips;
analyzing the qualified fluency strips, acquiring environmental data and equipment data of the qualified fluency strips, wherein the environmental data comprises environmental temperature and environmental humidity, the equipment data comprises equipment operation time and equipment operation frequency, acquiring the environmental data and the equipment data of the production process of the qualified fluency strips, carrying out numerical statistics on the environmental temperature and the environmental humidity in the environmental data, acquiring the highest numerical value and the lowest numerical value of the environmental temperature, and acquiring an environmental temperature interval through the highest numerical value and the lowest numerical value of the environmental temperature; acquiring a highest value and a lowest value of the environmental humidity, and acquiring an environmental humidity interval through the highest value and the lowest value of the environmental humidity;
carrying out numerical value statistics on equipment operation time and equipment operation frequency in the equipment data, acquiring the highest numerical value of the equipment operation time and the lowest numerical value of the equipment operation time, and acquiring an equipment operation time interval through the highest numerical value of the equipment operation time and the lowest numerical value of the equipment operation time; acquiring the highest numerical value of the equipment operating frequency and the lowest numerical value of the equipment operating frequency, and acquiring an equipment operating frequency interval through the highest numerical value of the equipment operating frequency and the lowest numerical value of the equipment operating frequency;
storing an environment temperature interval, an environment humidity interval, an equipment operation time interval and an equipment operation frequency interval of the qualified fluency strips;
and step two, abnormal feature analysis is carried out on the unqualified fluency strips, the faulted fluency strips are analyzed, and the abnormal features of the fluency strips are analyzed, so that the influence degree of the fluency strip faults is reasonably controlled, the rectification timeliness of the faulted fluency strips is improved, meanwhile, the fluency strip faults are effectively prevented, the fault rate of the fluency strips is reduced, and the specific abnormal feature analysis process is as follows:
marking the historical unqualified fluency strips as feature analysis objects, and acquiring fault features of the feature analysis objects, wherein the fault features are expressed as abnormal faults, stuck faults and other related faults when the fluency strips have faults in the summary of the application; setting a mark o for the fault characteristics of the characteristic analysis object, wherein the mark o is a natural number greater than 1; acquiring the occurrence frequency and the total maintenance time consumption of the fault characteristics of the characteristic analysis object, and respectively marking the occurrence frequency and the total maintenance time consumption of the fault characteristics of the characteristic analysis object as PLo and SCo; acquiring the increase speed of the fault feature occurrence frequency of the feature analysis object, and marking the increase speed of the fault feature occurrence frequency of the feature analysis object as SDo;
by the formula
Acquiring an analysis coefficient Xo of fault characteristics, wherein a1, a2 and a3 are all preset proportionality coefficients, and a1 is larger than a2 and is larger than a 3;
comparing the analysis coefficient of the fault feature to an analysis coefficient threshold:
if the analysis coefficient of the fault characteristic exceeds the analysis coefficient threshold, marking the corresponding fault characteristic as a main fault characteristic; if the analysis coefficient of the fault feature does not exceed the analysis coefficient threshold, marking the corresponding fault feature as a secondary fault feature;
updating and storing the main fault characteristics in real time, and immediately finishing the production line of the fluency strip if the main fault characteristics of the fluency strip appear in the production process;
and in the third step, analyzing influence factors of the main fault characteristics of the historical unqualified fluency strips, and judging the influence factors of the main fault characteristics, thereby controlling the influence brought by the main fault characteristics, simultaneously controlling the influence of the influence factors on the main fault characteristics, improving the production efficiency of the fluency strips, reducing the fault frequency of the fluency strips, and analyzing the specific influence factors as follows:
setting an influence factor acquisition time period, wherein the occurrence time of the main fault characteristics of the historical unqualified fluency strips is the middle time of the influence factor acquisition time period; the occurrence time of the main fault characteristics divides the time period of the acquisition of the influencing factors into a front time period and a rear time period; collecting numerical data produced by the fluency strip, and analyzing the numerical data, wherein the numerical data is expressed as related numerical data in the production process of the fluency strip, such as production related data of environmental data, equipment data and the like;
acquiring a floating value of the numerical data in the front time period, and if the floating value of the numerical data exceeds a corresponding floating value threshold value, marking the corresponding numerical data as a factor causing influence; if the floating value of the numerical data does not exceed the corresponding floating value threshold, marking the corresponding numerical data as an irrelevant influence factor; acquiring a floating value of the numerical data in the rear time period, and if the floating value of the numerical data is changed from not exceeding a corresponding floating value threshold value to exceeding the corresponding floating value threshold value, marking the corresponding data numerical value as a factor of influence; if the floating value of the numerical data does not exceed the corresponding floating value threshold value and the floating amplitude does not exceed the corresponding floating amplitude threshold value, representing the corresponding numerical data as an irrelevant influence factor;
storing the influencing factors and the dependent influencing factors, monitoring the influencing factors in real time when the main fault characteristics do not appear, and performing timely inching control on the factors absorbed by the dependent factors when the main fault characteristics appear;
the quality analysis and detection are carried out on the fluency strip which is produced in real time in the fourth step, whether the data analysis is qualified or not can be judged when the production quality of the fluency strip is controlled, the reduction of the quality monitoring efficiency of the fluency strip caused by the abnormity of the analysis step is prevented, thereby increasing the risk of the fluency strip breaking down, and the specific real-time detection process is as follows:
marking the fluency strip for completing the survival in real time as a real-time detection fluency strip, acquiring the random access qualification rate of the real-time detection fluency strip and the longest qualified time of frequent use, and respectively comparing the random access qualification rate of the real-time detection fluency strip and the longest qualified time of frequent use with a qualification rate threshold value and a qualified time threshold value:
if the random inspection qualification rate of the real-time detection fluency strips exceeds the qualification rate threshold and the longest frequently used qualification time exceeds the qualification time threshold, judging that the quality of the corresponding real-time detection fluency strips is qualified, and marking the quality as the real-time qualification fluency strips; and if the random inspection qualification rate of the real-time detection fluency strips does not exceed the qualification rate threshold or the longest frequently-used qualified time does not exceed the qualified time threshold, judging that the quality of the corresponding real-time detection fluency strips is unqualified, and marking the corresponding real-time detection fluency strips as real-time unqualified fluency strips.
The formulas are obtained by acquiring a large amount of data and performing software simulation, and the coefficients in the formulas are set by the technicians in the field according to actual conditions;
when the system is used, historical data is analyzed, and qualified intervals of the production data of the fluency strips are judged by analyzing the data of the fluency strips produced in the historical way, so that supervision on the fluency strips is improved, the product performance of the fluency strips is effectively and accurately judged, and the production quality of the fluency strips is improved; analyzing abnormal characteristics, namely analyzing the failed fluency strip and judging the abnormal characteristics of the fluency strip; abnormal characteristics of the fluency strip are analyzed, so that the influence degree of the fluency strip fault is reasonably controlled, the rectification timeliness of the fault fluency strip is improved, meanwhile, the occurrence of the fluency strip fault is effectively prevented, and the fault rate of the fluency strip is reduced; analyzing influence factors, namely acquiring the influence factors of the fluency strip according to the abnormal characteristics of the fluency strip, predicting the abnormity of the fluency strip, and judging the influence factors of the main fault characteristics, so that the influence caused by the main fault characteristics is controlled, meanwhile, the influence of the influence factors on the main fault characteristics can be controlled, the production efficiency of the fluency strip is improved, and meanwhile, the fault frequency of the fluency strip can be reduced; and the real-time detection is carried out, the quality analysis detection is carried out on the fluent strip which is produced in real time, whether the data analysis is qualified or not can be judged while the production quality of the fluent strip is controlled, and the reduction of the quality monitoring efficiency of the fluent strip caused by the abnormal analysis step is prevented, so that the risk of the fluent strip breaking down is increased.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (5)
1. A method for detecting and analyzing the performance data of a fluency strip product is characterized by comprising the following steps of:
step one, historical data analysis, namely, judging a qualified interval of the production data of the fluency strip by carrying out data analysis on the fluency strip produced in history;
analyzing abnormal characteristics, namely analyzing the failed fluency strip and judging the abnormal characteristics of the fluency strip;
analyzing influence factors, namely acquiring the influence factors of the fluency strip according to the abnormal characteristics of the fluency strip so as to predict the abnormity of the fluency strip;
and step four, real-time detection, namely performing quality analysis detection on the fluent strip which is produced in real time.
2. The method for detecting and analyzing fluency strip product performance data according to claim 1, wherein the historical data analysis process in the first step is as follows:
marking the historical produced fluent strips as finished fluent strips, setting a mark i, wherein the mark i is a natural number greater than 1, acquiring the failure times and the use frequency of the finished fluent strips, and if the failure times of the finished fluent strips do not exceed a failure time threshold and the use frequency exceeds a use frequency threshold, marking the corresponding finished fluent strips as qualified fluent strips; if the failure times of the finished fluent strips exceed the failure time threshold and the use frequency does not exceed the use frequency threshold, marking the corresponding finished fluent strips as unqualified fluent strips;
analyzing the qualified fluency strips, acquiring environmental data and equipment data of the qualified fluency strips, wherein the environmental data comprises environmental temperature and environmental humidity, the equipment data comprises equipment operation time and equipment operation frequency, acquiring the environmental data and the equipment data of the production process of the qualified fluency strips, carrying out numerical statistics on the environmental temperature and the environmental humidity in the environmental data, acquiring the highest numerical value and the lowest numerical value of the environmental temperature, and acquiring an environmental temperature interval through the highest numerical value and the lowest numerical value of the environmental temperature; acquiring a highest value and a lowest value of the environmental humidity, and acquiring an environmental humidity interval through the highest value and the lowest value of the environmental humidity;
carrying out numerical value statistics on equipment operation time and equipment operation frequency in the equipment data, acquiring the highest numerical value of the equipment operation time and the lowest numerical value of the equipment operation time, and acquiring an equipment operation time interval through the highest numerical value of the equipment operation time and the lowest numerical value of the equipment operation time; acquiring the highest numerical value of the equipment operating frequency and the lowest numerical value of the equipment operating frequency, and acquiring an equipment operating frequency interval through the highest numerical value of the equipment operating frequency and the lowest numerical value of the equipment operating frequency; and storing the environment temperature interval, the environment humidity interval, the equipment operation time interval and the equipment operation frequency interval of the qualified fluency strips.
3. The method for detecting and analyzing fluency strip product performance data according to claim 1, wherein the abnormal feature analysis process of the second step is as follows:
marking the historical unqualified fluency strips as feature analysis objects, acquiring fault features of the feature analysis objects, and setting the fault features of the feature analysis objects to be marked o, wherein o is a natural number greater than 1; acquiring the occurrence frequency and the total maintenance time consumption of the fault characteristics of the characteristic analysis object, and respectively marking the occurrence frequency and the total maintenance time consumption of the fault characteristics of the characteristic analysis object as PLo and SCo; acquiring the increase speed of the fault feature occurrence frequency of the feature analysis object, and marking the increase speed of the fault feature occurrence frequency of the feature analysis object as SDo;
analyzing the analysis coefficient Xo of the obtained fault characteristics, and comparing the analysis coefficient of the fault characteristics with an analysis coefficient threshold value:
if the analysis coefficient of the fault characteristic exceeds the analysis coefficient threshold, marking the corresponding fault characteristic as a main fault characteristic; if the analysis coefficient of the fault characteristic does not exceed the analysis coefficient threshold, marking the corresponding fault characteristic as a secondary fault characteristic;
and updating and storing the main fault characteristics in real time, and immediately finishing the production line of the fluency strip if the main fault characteristics of the fluency strip appear in the production process.
4. The method for detecting and analyzing the product performance data of the fluency strip according to claim 1, wherein the influence factor analysis process of the third step is as follows:
setting an influence factor acquisition time period, wherein the occurrence time of the main fault characteristics of the historical unqualified fluency strips is the middle time of the influence factor acquisition time period; the occurrence time of the main fault characteristics divides the time period of the acquisition of the influencing factors into a front time period and a rear time period; collecting numerical data produced by the fluency strip, and analyzing the numerical data;
acquiring a floating value of the numerical data in the front time period, and if the floating value of the numerical data exceeds a corresponding floating value threshold, marking the corresponding numerical data as a factor causing influence; if the floating value of the numerical data does not exceed the corresponding floating value threshold, marking the corresponding numerical data as an irrelevant influence factor; acquiring a floating value of the numerical data in the rear time period, and if the floating value of the numerical data is changed from not exceeding a corresponding floating value threshold value to exceeding the corresponding floating value threshold value, marking the corresponding data numerical value as a factor of influence; if the floating value of the numerical data does not exceed the corresponding floating value threshold value and the floating amplitude does not exceed the corresponding floating amplitude threshold value, representing the corresponding numerical data as an irrelevant influence factor;
the influence factors and the change influence factors are stored, the influence factors are monitored in real time when the main fault characteristics do not appear, and the factors absorbed by the patient due to the allergy are subjected to timely inching control when the main fault characteristics appear.
5. The method for detecting and analyzing the product performance data of the fluency strip according to claim 1, wherein the real-time detection process of the fourth step is as follows:
marking the fluent strip which completes survival in real time as a real-time detection fluent strip, collecting the random inspection qualification rate of the real-time detection fluent strip and the longest qualification time of frequent use, and respectively comparing the random inspection qualification rate of the real-time detection fluent strip and the longest qualification time of the frequent use with a qualification rate threshold value and a qualification time threshold value:
if the random inspection qualification rate of the real-time detection fluency strips exceeds the qualification rate threshold and the longest frequently used qualification time exceeds the qualification time threshold, judging that the quality of the corresponding real-time detection fluency strips is qualified, and marking the quality as the real-time qualification fluency strips; and if the random inspection qualification rate of the real-time detection fluency strips does not exceed the qualification rate threshold or the longest frequently-used qualified time does not exceed the qualified time threshold, judging that the quality of the corresponding real-time detection fluency strips is unqualified, and marking the corresponding real-time detection fluency strips as real-time unqualified fluency strips.
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