CN117933803A - Air conditioner hose product performance test data management system - Google Patents
Air conditioner hose product performance test data management system Download PDFInfo
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Abstract
The invention discloses an air conditioner hose product performance test data management system, which belongs to the technical field of air conditioner hose product performance test data management and comprises a data statistics module and a data analysis module; the data statistics module is used for butting a database for storing performance test data of the air conditioner hose product, identifying each performance test data, and carrying out classification statistics on each performance test data to form a test statistical chart of the air conditioner hose product; the data analysis module is used for carrying out performance analysis on the air conditioner hose product based on the test statistical graph, and acquiring batch analysis data from the test statistical graph according to the acquired product number table; setting a batch test value set according to batch analysis data; calculating a batch analysis value according to the batch test value set; generating a corresponding batch curve according to the batch test value and the number of the test batches; identifying vertexes in the batch curves in real time, and calculating curve difference values of all test batches based on the vertexes in real time; when the curve difference is greater than the threshold value X1, production optimization data is generated.
Description
Technical Field
The invention belongs to the technical field of performance test data management of air-conditioning hose products, and particularly relates to a performance test data management system of an air-conditioning hose product.
Background
An air conditioner hose is an important component in an air conditioner, and has certain performance indexes such as pressure resistance, heat resistance, corrosion resistance and the like in the use process; in order to ensure that the quality and performance of the product meet the requirements, comprehensive performance test and evaluation are required; performance testing of air conditioning hose products typically generates a large amount of data, including test parameters, test results, and the like. The traditional data management method may have problems of manual recording, paper files and the like, so that the efficiency is low, and data loss or errors are easy to occur. Therefore, in the current test of the air-conditioning hose, a corresponding data management system is basically introduced, but the existing data management system basically focuses on the test result of the air-conditioning hose, namely whether the test is qualified or not, has low utilization rate on other data, and cannot fully play the role of testing the data, especially for small and medium-sized micro-manufacturing enterprises; based on the data management system, the invention provides an air conditioner hose product performance test data management system.
Disclosure of Invention
In order to solve the problems of the scheme, the invention provides an air conditioner hose product performance test data management system.
The aim of the invention can be achieved by the following technical scheme:
The system comprises a data statistics module, a data management module and a data analysis module;
the data statistics module is used for butting a database for storing performance test data of the air-conditioning hose products, identifying each performance test data, and carrying out classified statistics on each performance test data to form a test statistical chart of each air-conditioning hose product.
Further, the method for generating the test statistical graph comprises the following steps:
Identifying each piece of performance test data, and converting each piece of performance test data into corresponding performance coordinates; inputting each performance coordinate into a corresponding coordinate space;
Classifying according to the distribution of each performance coordinate in the coordinate space to obtain a plurality of performance classifications; generating a corresponding spatial distribution diagram according to the performance classification; supplementing a classification list of each classification area in the spatial distribution diagram;
And identifying corresponding coordinate recording features in the classification area in real time, and recording the coordinate recording features in the classification list.
Further, the method for classifying the performance test data comprises the following steps:
step SA1: acquiring historical performance test data, and establishing a corresponding judgment model based on the historical performance test data;
Judging the expression of the model to be Wherein: c represents the combined performance coordinates;
Step SA2: determining initial coordinates in the coordinate space, and identifying performance coordinates adjacent to the initial coordinates, wherein the performance coordinates are marked as associated coordinates; forming a combined performance coordinate by the initial coordinate and the associated coordinate;
Step SA3: analyzing the combination performance coordinates through the judging model to judge whether the combination performance coordinates meet the combination requirements;
When the combination requirement is judged to be met, the associated coordinates and the initial coordinates are marked in the same type;
When the combination requirement is not met, canceling the associated coordinate mark;
Step SA4: marking performance coordinates adjacent to the associated coordinates as associated coordinates, and forming new combined performance coordinates by the initial coordinates and the associated coordinates; returning to the step SA3;
when there is no combined performance coordinate, go to step SA5;
Step SA5: classifying each performance coordinate with the same type of mark into one type, and marking the performance coordinate as performance classification;
step SA6: and (5) cycling the steps SA2 to SA5 until all the performance coordinates in the coordinate space are classified, and obtaining a plurality of performance classifications.
Further, the setting method of the spatial distribution map comprises the following steps:
Identifying region boundaries corresponding to the performance classifications according to the performance coordinates corresponding to the performance classifications, and forming corresponding classification regions in the coordinate space based on the region boundaries; marking corresponding initial coordinates in each classification area;
and mapping according to each classification region in the coordinate space to form a corresponding spatial distribution map.
Further, the test statistical diagram is correspondingly updated according to the updating condition of the performance test data stored in the database;
the updating method comprises the following steps:
identifying performance test data updated and stored in a database, converting the performance test data into performance coordinates and inputting the performance coordinates into a coordinate space;
When the performance coordinates are located in the corresponding classification areas, identifying performance classifications corresponding to the classification areas, and matching corresponding classification detail tables in the test statistical diagram according to the performance classifications; identifying the coordinate recording characteristics of the performance coordinates, and recording the coordinate recording characteristics in a classification list;
When the performance coordinates are not located in any classification area, the distances between the performance coordinates and the boundaries of all adjacent classification areas are identified, the performance coordinates are evaluated in sequence from small to large, and whether the initial coordinates corresponding to the performance coordinates and the classification areas meet the merging requirement is evaluated; when the combination requirement is judged to be met, combining the performance coordinates into the corresponding classification area, and adjusting the classification area; recording in a corresponding classification list according to the region classification and the coordinate recording characteristics of the performance coordinates; when the combination requirement is not met, evaluating the next classification area; and so on; and when no classification area meeting the merging requirement exists, generating a new performance classification and classification area by taking the performance coordinates as a reference, and adjusting the test statistical graph.
Further, the data management module is used for managing the stored performance test data and identifying a stored data management scheme preset by a user; acquiring a test statistical chart, identifying initial coordinates corresponding to each classification area in the test statistical chart, and storing and marking performance test data corresponding to the initial coordinates;
and managing the performance test data stored in the database according to the stored data management scheme and a preset stored mark processing scheme.
The data analysis module is used for carrying out performance analysis on air-conditioning hose products based on the test statistical graph, and obtaining an air-conditioning hose product numbering list of each production batch; acquiring a test statistical chart, and acquiring corresponding batch analysis data from the test statistical chart according to the product numbering table; setting a corresponding batch test value set according to the batch analysis data;
According to Calculating a corresponding batch analysis value;
wherein: FPZ is a batch analysis value; PCGi represents the corresponding batch test value in the batch test value set, i=1, 2, … …, n being a positive integer;
Generating a corresponding batch curve according to the batch test value and the corresponding test batch times;
identifying vertexes in the batch curves in real time, and calculating curve difference values of all test batches in real time based on the vertexes; when the curve difference value is larger than a threshold value X1, corresponding production optimization data are generated; when the curve difference is not greater than the threshold value X1, no corresponding operation is performed.
Further, the method for acquiring batch analysis data comprises the following steps:
Identifying the performance classification of each air-conditioning hose product in the test statistical chart according to the product number table, counting the number of products in each performance classification, and calculating the classification proportion of each performance classification according to the number of products; identifying performance test data corresponding to the initial coordinates of each performance class, and marking corresponding performance class labels, product quantity labels and class proportion labels on the performance test data; and integrating each performance test data into batch analysis data.
Further, the method for setting the batch test value set comprises the following steps:
Identifying each performance test data in the batch analysis data, converting the performance test data into performance coordinates, calculating corresponding positioning values based on the performance coordinates, and marking the positioning values as DP (DP)
Identifying the classification proportion corresponding to each performance test data, and marking the classification proportion as mu;
According to the formula Calculating a corresponding batch test value; wherein: PCG is a batch test value; d1 and D2 are respectively corresponding boundary locating values, and D1< D2; the range of the batch test value is [0, 10];
Integrating the batch test values of the performance test data into a batch test value set.
Further, the method for calculating the positioning value comprises the following steps:
Acquiring performance test data corresponding to the evaluation qualification standard, converting the performance test data into corresponding performance coordinates, marking the performance coordinates as standard coordinates, marking each element value in the standard coordinates as YSt, wherein t=1, 2, … … and v, v is a positive integer, and t represents a performance test item;
Marking each element value in the performance coordinates as YXt, wherein t=1, 2, … … and v, v is a positive integer, and t represents a performance test item;
presetting a weight coefficient of each performance test item, and marking the weight coefficient as sigma t;
Then according to the formula Calculating a corresponding positioning value, wherein: DW is a positioning value;
And for the two boundary positioning values, converting the boundary coordinates corresponding to the boundaries 0 and 10, and calculating.
Compared with the prior art, the invention has the beneficial effects that:
Through the mutual coordination between the data statistics module and the data management module, a large amount of performance test data stored in the database can be intelligently managed, if necessary, the performance test data of each performance classification only needs to retain performance test data corresponding to one initial coordinate, other performance test data in the performance classification can be deleted, and after the performance test data are deleted, the analysis results which are the same as those of the undeleted performance test data can be realized through combining with the test statistics graph; under the requirement of guaranteeing the subsequent data analysis, the storage space is utilized to the maximum extent; even if the user deletes all the performance test data in the performance class through the management authority, the corresponding data analysis can be realized when any performance test data in the performance class is stored later, so that the fault tolerance is very high, and the fault deletion of the performance test data is not worried.
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In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings can be obtained according to these drawings without inventive effort to a person skilled in the art.
Fig. 1 is a functional block diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in fig. 1, an air conditioner hose product performance test data management system comprises a data statistics module, a data management module and a data analysis module;
the data statistics module is used for butting a database for storing performance test data of each air-conditioning hose product, identifying the stored performance test data of each air-conditioning hose product, and carrying out classified statistics on each performance test data to form a test statistical chart of the air-conditioning hose product; the specific method comprises the following steps:
identifying performance test data of each air-conditioning hose product, wherein the performance test data can comprise pressure resistance data, temperature resistance data, corrosion resistance data, wear resistance data, sealing performance data, bending performance data, durability data and the like according to actual test requirements; setting performance coordinates of each piece of performance test data corresponding to the air conditioner hose product, wherein the performance coordinates are formed by converting and integrating each performance test item corresponding to the performance test data, each performance test item corresponds to one element item in the performance coordinates, and supplementing a numerical value corresponding to the performance test item data to a corresponding element position in the performance coordinates.
Because different test methods may cause a difference in the data units of the performance test items corresponding to the performance test items, a corresponding conversion mode needs to be set according to the test method applied by the user, and common data units of several performance test items are: pressure resistance in units of pressure (e.g., megapascals/hundred pascals) or pressure differential (e.g., bar/pascals); temperature resistance in degrees (e.g., celsius/fahrenheit); sealing performance: typically expressed in terms of leak rate (e.g., millimeters per minute) or pressure loss (e.g., pascals); bending properties: in degrees (e.g., degrees) or bend radius (e.g., millimeters/inch); durability performance: typically expressed in terms of life (e.g., hours/cycles) or failure rate (e.g., percent); for non-numerical performance test item data, a corresponding conversion mode can be preset according to an existing numerical conversion method, conversion can be carried out according to the preset conversion mode, and by way of example, a test data range which the performance test item data possibly has is obtained, two range boundaries are respectively marked as B1 and B2, B1> B2, then the converted numerical value is SZ= [ (100-60)/(B1-B2) ]× (Bz-B2), wherein SZ is the corresponding converted numerical value, and Bz is detected data; performing difference calculation according to the performance degree; other existing means for numerical conversion may also be used.
Inputting each performance coordinate corresponding to each air-conditioning hose product into a corresponding coordinate space, wherein one air-conditioning hose product has one or two coordinate spaces, and if the performance coordinates converted from the qualified performance test data and the unqualified performance test data are in one coordinate space, one air-conditioning hose product has one coordinate space, otherwise, two coordinate spaces are provided; classifying according to the distribution of each performance coordinate in the coordinate space to obtain a plurality of performance classifications; generating a corresponding classification area according to the position of each performance classification in the coordinate space, and generating by taking the performance coordinates of each boundary in the performance classification as an area boundary; and marking the initial coordinates in the classification region; and then, the performance test data can be rapidly classified according to the classification area, and for the condition that the performance test data is not directly positioned in the classification area, the performance test data is evaluated and matched with the initial coordinates corresponding to the near classification area, the corresponding classification area is determined, and the corresponding classification area is updated.
Generating a corresponding spatial distribution map according to each classification region in the coordinate space, namely, in the spatial distribution map, carrying out corresponding change according to the shape, the size and other changes of each classification region in the middle of the coordinates to form the spatial distribution map of the classification region; supplementing a classification list of each classification area in the spatial distribution diagram, wherein the classification list comprises data fields such as performance coordinate numbers, recording time, serial numbers and the like; the classification list can be folded; identifying coordinate recording features such as the number, the recording time and the like of the coordinates in the corresponding classification region in the coordinate space in real time, and recording in the corresponding classification detail table according to the obtained coordinate recording features;
The current spatial distribution map is marked as a test statistical map.
The method for classifying according to the distribution of each performance coordinate in the coordinate space comprises the following steps:
Step SA1: obtaining a large amount of historical performance test data, converting the historical performance test data into corresponding historical performance coordinates, setting equivalent deviation of each performance test item, namely, on the performance test item, the numerical deviation can be regarded as the same, namely, the subsequent data analysis effect brought by the performance test item is the same, setting can be carried out by combining corresponding allowable deviation, such as temperature resistance 60 ℃ and 60.1 ℃, 63 ℃, 62.5 ℃ and the like, the equivalent deviation brought by 60 ℃ is 3 ℃, the analysis effect brought by 60 ℃ and 60.1 ℃ and 62.5 ℃ is the same, and the performance test item can be regarded as meeting the requirement of the equivalent deviation, and the performance test item is specifically required to be set by professionals according to the actual conditions according to the historical performance test data; further, whether other historical performance coordinates meet the requirement of equivalent deviation is marked according to the historical performance coordinates in a simulation mode, namely all performance test items are met; establishing a judgment model for the training set according to the marked data integration, wherein the expression of the judgment model is as follows Wherein: c represents a combined performance coordinate, namely two performance coordinates which need to be evaluated whether the equivalent deviation requirement is met; if c is an anomaly indicates that the combined performance coordinates do not meet the requirement of equivalent deviation;
step SA2: determining initial coordinates in a coordinate space, identifying associated coordinates adjacent to the initial coordinates, and excluding adjacent performance coordinates with different test results, namely, failing test and test can not be used as associated coordinates, and directly taking the adjacent performance coordinates into consideration; the initial coordinates and each associated coordinate form a combined performance coordinate;
In one embodiment, one performance coordinate in the optional coordinate space may be the initial coordinate.
In another embodiment, the performance test data may be evaluated by using an existing evaluation method to obtain an evaluation value, where the evaluation value may be a priority value, a stored value, or other expression form in the prior art; if the priority deleting sequence of each stored data is evaluated, selecting the final screened initial coordinate; and the intelligent evaluation can be performed by establishing a corresponding intelligent model based on neural networks such as CNN networks and DNN networks.
Step SA3: analyzing the combination performance coordinates through a judgment model, and judging whether the combination performance coordinates meet the requirement of equivalent deviation, namely the combination requirement;
When judging that the combination requirements are met, carrying out similar marking on the corresponding associated coordinates and the initial coordinates;
When the combination requirement is not met, canceling the associated coordinate mark; i.e. the performance coordinates are not associated coordinates of the initial coordinates;
Step SA4: taking the performance coordinates adjacent to the associated coordinates with the same type marks as new associated coordinates, forming new combined performance coordinates by the initial coordinates and the associated coordinates, and returning to the step SA3 for analysis;
until no combined performance coordinates exist, entering step SA5;
step SA5: classifying each performance coordinate with the same type of mark into one type, and marking the performance coordinate as performance classification;
Step SA6: and (5) cycling the steps SA2 to SA5 until all the performance coordinates in the coordinate space are classified, and obtaining a plurality of performance classifications.
The data management module is used for managing the stored performance test data, and because a large amount of performance test data can be generated in actual production test, the conventional management method is to set a period, and delete the corresponding performance test data when the corresponding period is reached; leading to poor utilization and lower retention of performance test data; therefore, the invention manages by combining the test statistical diagram in the data statistical module, and even if the subsequent performance test data is deleted, the corresponding data analysis can be carried out by the test statistical diagram; because the analysis effect of the performance test data of each performance class is basically equivalent, the analysis can be performed according to the corresponding quantity and specific gravity.
The method comprises the following steps:
Acquiring a stored data management scheme set by a user, such as how long to store and delete data, which data marks can not be deleted and other related data set by the user;
acquiring a test statistical chart, identifying initial coordinates corresponding to each classification area in the test statistical chart, storing and marking performance test data corresponding to the initial coordinates, wherein the stored marks indicate that the performance test data are not deleted and can only be deleted by the authority of a user application manager;
And identifying a corresponding stored data management scheme, and managing the performance test data stored in the database according to the stored data management scheme and a preset stored mark processing scheme.
Through the mutual coordination between the data statistics module and the data management module, a large amount of performance test data stored in the database can be intelligently managed, if necessary, the performance test data of each performance classification only needs to retain performance test data corresponding to one initial coordinate, other performance test data in the performance classification can be deleted, and after the performance test data are deleted, the analysis results which are the same as those of the undeleted performance test data can be realized through combining with the test statistics graph; under the requirement of guaranteeing the subsequent data analysis, the storage space is utilized to the maximum extent; even if the user deletes all the performance test data in the performance class through the management authority, the corresponding data analysis can be realized when any performance test data in the performance class is stored later, so that the fault tolerance is very high, and the fault deletion of the performance test data is not worried.
The data analysis module is used for carrying out performance analysis on air-conditioning hose products based on the test statistical graph, and obtaining an air-conditioning hose product numbering table of each production batch, wherein the product numbering table comprises numbers of air-conditioning hose products in the production test batch;
Acquiring a test statistical chart, and acquiring corresponding batch analysis data from the test statistical chart according to a product numbering table; evaluating a corresponding batch test value set according to the obtained batch analysis data;
According to the batch test value set, calculating a corresponding batch analysis value, wherein the calculation formula is as follows:
wherein: FPZ is a batch analysis value, PCGi represents a corresponding batch test value in a batch test value set, and i=1, 2, … …, n is a positive integer;
Integrating the obtained batch analysis value and the corresponding test batch times into coordinates, inputting the coordinates into a coordinate system, wherein the horizontal axis represents the test batch times, and the vertical axis represents the batch analysis value; connecting the coordinates in the coordinate system into corresponding batch curves;
Identifying the vertex in the batch curve, namely the coordinate corresponding to the largest batch analysis value; identifying differences between batch analysis values corresponding to other curves and batch analysis values corresponding to the vertexes in real time, marking the differences as curve differences, and subtracting the batch analysis values corresponding to the other curves from the batch analysis values of the vertexes; when the curve difference value is larger than a threshold value X1, marking corresponding coordinates, and generating production optimization data according to the marked coordinates; the production data of the batch of air-conditioning hose products, the production data of the air-conditioning hose products corresponding to the vertexes and the corresponding performance test data are identified according to the mark coordinates, and a user is assisted to approach production parameters, management modes and the like to the vertexes; the production is convenient for the user to optimize.
The method for acquiring the batch analysis data comprises the following steps:
Identifying the performance classification of each air-conditioning hose product in the test statistical chart according to the product numbering table, counting the number of products in each performance classification, and calculating the classification proportion, namely the number share, of each performance classification according to the number of products; identifying performance test data corresponding to the initial coordinates of each performance class, and marking corresponding performance class labels, product quantity labels and class proportion labels on the obtained performance test data; each performance test data was integrated into batch analysis data.
The evaluation method of the batch test value set comprises the following steps:
Identifying each performance test data in the batch analysis data, and evaluating performance evaluation values corresponding to the performance test data, wherein the range of the performance evaluation values is [0, 10], and 10 and 0 respectively represent the best and worst states of the performance test data reaching the air-conditioning hose product at the user site; the method can be used for determining various performance test data by combining historical performance test data, acquiring performance test data corresponding to 10 and 0, converting the performance test data into corresponding performance coordinates, marking the corresponding performance coordinates as boundary coordinates, presetting the weight coefficient of each performance test item, setting by a user or setting whether the whole evaluation is qualified or not according to each performance test item, setting according to economic loss specific gravity caused by disqualification of each performance test item, and particularly adjusting according to actual conditions;
Acquiring performance test data corresponding to the evaluation qualification standard, converting the performance test data into corresponding performance coordinates, marking the performance coordinates as standard coordinates, subtracting corresponding element values in the standard coordinates from boundary coordinates, and subtracting the element values in the standard coordinates from the element values in the boundary coordinates; multiplying the corresponding weight coefficients to obtain corresponding single values, accumulating the single values to obtain corresponding boundary positioning values when the performance evaluation values are 0 and 10, and marking the boundary positioning values as D1 and D2, wherein D1 is smaller than D2;
Acquiring performance test data to be evaluated, converting the performance test data into corresponding performance coordinates, marking the performance coordinates as evaluation coordinates, calculating positioning values corresponding to the evaluation coordinates, and marking the positioning values as DP;
The performance evaluation value of the performance test data to be evaluated is xn= [10 ≡ (D2-D1) ]×dp, where: XN is a performance evaluation value;
Identifying the classification proportion corresponding to each performance test data, and marking as mu;
then the batch test value pcg=μ×xn; wherein: PCG is a batch test value.
The batch test values of the performance test data are integrated into a batch test value set.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas which are obtained by acquiring a large amount of data and performing software simulation to obtain the closest actual situation, and preset parameters and preset thresholds in the formulas are set by a person skilled in the art according to the actual situation or are obtained by simulating a large amount of data.
The above embodiments are only for illustrating the technical method of the present invention and not for limiting the same, and it should be understood by those skilled in the art that the technical method of the present invention may be modified or substituted without departing from the spirit and scope of the technical method of the present invention.
Claims (8)
1. The air conditioner hose product performance test data management system is characterized by comprising a data statistics module and a data analysis module;
The data statistics module is used for butting a database for storing performance test data of the air-conditioning hose products, identifying each performance test data, and carrying out classification statistics on each performance test data to form a test statistical chart of each air-conditioning hose product;
The data analysis module is used for carrying out performance analysis on air-conditioning hose products based on the test statistical graph, and obtaining an air-conditioning hose product numbering list of each production batch; acquiring a test statistical chart, and acquiring corresponding batch analysis data from the test statistical chart according to the product numbering table; setting a corresponding batch test value set according to the batch analysis data;
According to Calculating a corresponding batch analysis value;
wherein: FPZ is a batch analysis value; PCGi represents the corresponding batch test value in the batch test value set, i=1, 2, … …, n being a positive integer;
Generating a corresponding batch curve according to the batch test value and the corresponding test batch times;
identifying vertexes in the batch curves in real time, and calculating curve difference values of all test batches in real time based on the vertexes; when the curve difference value is larger than a threshold value X1, corresponding production optimization data are generated; when the curve difference is not greater than the threshold value X1, no corresponding operation is performed.
2. The air conditioner hose product performance test data management system of claim 1, wherein the method for generating the test statistical chart comprises:
Identifying each piece of performance test data, and converting each piece of performance test data into corresponding performance coordinates; inputting each performance coordinate into a corresponding coordinate space;
Classifying according to the distribution of each performance coordinate in the coordinate space to obtain a plurality of performance classifications; generating a corresponding spatial distribution diagram according to the performance classification; supplementing a classification list of each classification area in the spatial distribution diagram;
And identifying corresponding coordinate recording features in the classification area in real time, and recording the coordinate recording features in the classification list.
3. The air conditioning hose product performance test data management system of claim 2, wherein the method of classifying the performance test data comprises:
step SA1: acquiring historical performance test data, and establishing a corresponding judgment model based on the historical performance test data;
Judging the expression of the model to be Wherein: c represents the combined performance coordinates;
Step SA2: determining initial coordinates in the coordinate space, and identifying performance coordinates adjacent to the initial coordinates, wherein the performance coordinates are marked as associated coordinates; forming a combined performance coordinate by the initial coordinate and the associated coordinate;
Step SA3: analyzing the combination performance coordinates through the judging model to judge whether the combination performance coordinates meet the combination requirements;
When the combination requirement is judged to be met, the associated coordinates and the initial coordinates are marked in the same type;
When the combination requirement is not met, canceling the associated coordinate mark;
Step SA4: marking performance coordinates adjacent to the associated coordinates as associated coordinates, and forming new combined performance coordinates by the initial coordinates and the associated coordinates; returning to the step SA3;
when there is no combined performance coordinate, go to step SA5;
Step SA5: classifying each performance coordinate with the same type of mark into one type, and marking the performance coordinate as performance classification;
step SA6: and (5) cycling the steps SA2 to SA5 until all the performance coordinates in the coordinate space are classified, and obtaining a plurality of performance classifications.
4. A system for managing performance test data of an air conditioning hose product according to claim 3, wherein the method for setting the spatial distribution map comprises:
Identifying region boundaries corresponding to the performance classifications according to the performance coordinates corresponding to the performance classifications, and forming corresponding classification regions in the coordinate space based on the region boundaries; marking corresponding initial coordinates in each classification area;
and mapping according to each classification region in the coordinate space to form a corresponding spatial distribution map.
5. The system for managing performance test data of an air conditioner hose product according to claim 4, wherein the test statistical chart is updated accordingly according to the update condition of the performance test data stored in the database;
the updating method comprises the following steps:
identifying performance test data updated and stored in a database, converting the performance test data into performance coordinates and inputting the performance coordinates into a coordinate space;
When the performance coordinates are located in the corresponding classification areas, identifying performance classifications corresponding to the classification areas, and matching corresponding classification detail tables in the test statistical diagram according to the performance classifications; identifying the coordinate recording characteristics of the performance coordinates, and recording the coordinate recording characteristics in a classification list;
When the performance coordinates are not located in any classification area, the distances between the performance coordinates and the boundaries of all adjacent classification areas are identified, the performance coordinates are evaluated in sequence from small to large, and whether the initial coordinates corresponding to the performance coordinates and the classification areas meet the merging requirement is evaluated; when the combination requirement is judged to be met, combining the performance coordinates into the corresponding classification area, and adjusting the classification area; recording in a corresponding classification list according to the region classification and the coordinate recording characteristics of the performance coordinates; when the combination requirement is not met, evaluating the next classification area; and so on; and when no classification area meeting the merging requirement exists, generating a new performance classification and classification area by taking the performance coordinates as a reference, and adjusting the test statistical graph.
6. The air conditioning hose product performance test data management system of claim 1, wherein the method for obtaining batch analysis data comprises:
Identifying the performance classification of each air-conditioning hose product in the test statistical chart according to the product number table, counting the number of products in each performance classification, and calculating the classification proportion of each performance classification according to the number of products; identifying performance test data corresponding to the initial coordinates of each performance class, and marking corresponding performance class labels, product quantity labels and class proportion labels on the performance test data; and integrating each performance test data into batch analysis data.
7. The air conditioning hose product performance test data management system of claim 6, wherein the method for setting the batch test value set comprises:
Identifying each performance test data in the batch analysis data, converting the performance test data into performance coordinates, calculating corresponding positioning values based on the performance coordinates, and marking the positioning values as DP (DP)
Identifying the classification proportion corresponding to each performance test data, and marking the classification proportion as mu;
According to the formula Calculating a corresponding batch test value; wherein: PCG is a batch test value; d1 and D2 are respectively corresponding boundary locating values, and D1< D2; the range of the batch test value is [0, 10];
Integrating the batch test values of the performance test data into a batch test value set.
8. The system for managing performance test data of an air conditioner hose product according to claim 1, further comprising a data management module for managing the stored performance test data, and identifying a stored data management scheme preset by a user; acquiring a test statistical chart, identifying initial coordinates corresponding to each classification area in the test statistical chart, and storing and marking performance test data corresponding to the initial coordinates;
and managing the performance test data stored in the database according to the stored data management scheme and a preset stored mark processing scheme.
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