A method and device for analyzing test data of a vehicle-mounted telescopic tent

Abstract

The application discloses a kind of vehicle-mounted telescopic tent test data analysis method and device, the method includes: the performance index test data set of vehicle-mounted telescopic tent is measured to obtain corresponding test site set;The test site set includes the position information of test site;The performance index test data set includes rainproof performance test data sequence, snow load performance test data sequence, deployment time test data sequence, failure rate test data sequence, energy consumption test data sequence, storage time test data sequence;Each data in the test data sequence is tested in the test site set in test site;Same serial number data in all test data sequences correspond to the same test site;The performance index test data set is preprocessed to obtain preprocessed data set;The preprocessed data set is evaluated and calculated to obtain the performance comprehensive evaluation result value of the field tent.

Description

Technical Field

[0001] This invention relates to the fields of industrial data processing and data modeling, and specifically to a method and apparatus for analyzing test data of a vehicle-mounted telescopic tent. Background Technology

[0002] With the increasing popularity of outdoor travel and camping activities, vehicle-mounted telescopic tents, as a type of camping equipment that combines convenience and practicality, are gaining popularity among more and more users. However, there are still some issues that need to be addressed in the analysis of current performance test data for vehicle-mounted telescopic tents.

[0003] On the one hand, traditional performance testing methods usually only focus on a single performance indicator, such as rainproof performance or deployment time, lacking a comprehensive consideration of multiple performance indicators, and making it difficult to fully reflect the overall performance of the tent in actual use.

[0004] On the other hand, existing methods often neglect the integrity and consistency of test data during data processing, such as data differences between different test locations and interference from data noise, which may lead to bias in evaluation results.

[0005] Furthermore, existing technologies have not adequately considered the impact of test locations on tent performance, and environmental conditions (such as climate and terrain) at different locations significantly affect the actual performance of tents. These issues limit the accuracy and reliability of performance evaluation for vehicle-mounted telescopic tents, failing to provide strong technical support for product improvement and optimization, and making it difficult to meet users' demands for high-quality tents. Summary of the Invention

[0006] This invention primarily addresses the issues of accuracy and reliability in performance evaluation of vehicle-mounted telescopic tents. It discloses a method and apparatus for analyzing test data of vehicle-mounted telescopic tents.

[0007] In a first aspect, this invention discloses a method for analyzing test data of a vehicle-mounted telescopic tent, comprising:

[0008] S1, measure and obtain the performance index test data set and corresponding test location set of the vehicle-mounted telescopic tent; the test location set includes the location information of the test locations; the performance index test data set includes rainproof performance test data sequence, snow load performance test data sequence, deployment time test data sequence, failure rate test data sequence, energy consumption test data sequence, and storage time test data sequence; each data in the test data sequence is obtained by testing at a test location in the test location set; data with the same sequence number in all test data sequences correspond to the same test location;

[0009] S2, preprocess the performance index test data set to obtain a preprocessed data set;

[0010] S3, perform evaluation and calculation on the preprocessed data set to obtain the comprehensive performance evaluation result value of the outdoor tent.

[0011] The preprocessing of the performance index test data set to obtain a preprocessed data set includes:

[0012] S21, perform data cleaning on the performance index test data set to obtain the first dataset;

[0013] S22, Perform time registration processing on the first dataset to obtain the second dataset;

[0014] S23, perform data reduction processing on the second dataset to obtain a preprocessed data set.

[0015] The evaluation and calculation of the preprocessed data set to obtain the comprehensive performance evaluation result of the field tent includes:

[0016] S31, obtain the qualified values ​​for rainproof performance, snow load performance, deployment time, failure rate, energy consumption, and storage time.

[0017] S32, for each data sequence in the preprocessed data set, subtract the corresponding qualified value to obtain the corresponding difference sequence;

[0018] S33, using the difference sequence of rainproof performance and the difference sequence of snow load performance, a first difference matrix is ​​constructed;

[0019] S34, using the difference sequence of the unfolding time and the difference sequence of the storage time, a second difference matrix is ​​constructed;

[0020] S35, using the difference sequence of failure rate and the difference sequence of energy consumption, a third difference matrix is ​​constructed;

[0021] S36, perform fusion evaluation processing on each difference matrix to obtain the corresponding evaluation sequence;

[0022] S37, Perform performance evaluation processing on all evaluation sequences and test site sets to obtain the comprehensive performance evaluation result value of the outdoor tent.

[0023] The fusion evaluation process includes:

[0024] For each row vector of the difference matrix, calculate the weight value to obtain the corresponding weight value;

[0025] By using the weight value of each row vector, the row vectors of the difference matrix are summed in a weighted manner to obtain the corresponding evaluation sequence.

[0026] The performance evaluation process is performed on all evaluation sequences and test site sets to obtain the comprehensive performance evaluation result value of the field tent, including:

[0027] S371, Image modeling is performed on all evaluation sequences and test site sets to obtain image information to be evaluated;

[0028] S372, Perform corner detection processing on the image information to be evaluated to obtain a set of corner information;

[0029] S373, perform edge point detection processing on the image information to be evaluated to obtain an edge point information set;

[0030] S374, perform fusion feature calculation processing on the corner point information set and edge point information set to obtain the comprehensive performance evaluation result value of the outdoor tent.

[0031] The image modeling process, which involves performing image modeling on all evaluation sequences and test location sets to obtain image information to be evaluated, includes:

[0032] Each evaluation sequence is normalized to obtain the corresponding normalized evaluation sequence;

[0033] The normalized evaluation sequences corresponding to the first, second, and third difference matrices are used as the R, G, and B channel values ​​of the image pixels, respectively. The location information of the test location corresponding to each element of the normalized evaluation sequence is used as the two-dimensional image plane location coordinates of the image pixels to construct the image information to be evaluated.

[0034] The process of fusing the corner point information set and the edge point information set to obtain the comprehensive performance evaluation result of the outdoor tent includes:

[0035] Statistical processing is performed on the pixel values ​​of all pixels in the corner information set to obtain a first statistical information set; the first statistical information set includes the variance and mean of the pixel values ​​of all pixels in the corner information set.

[0036] Statistical processing is performed on the pixel values ​​of all pixels in the edge point information set to obtain a second statistical information set; the second statistical information set includes the median and mode values ​​of all pixel values ​​in the edge point information set.

[0037] Statistical calculations are performed on the first and second sets of statistical information to obtain the comprehensive performance evaluation result of the outdoor tent.

[0038] The expression for the statistical calculation is:

[0039]

[0040] Where zp is the comprehensive performance evaluation result of the outdoor tent, T2() is the second-order polynomial of the first-type Chebyshev polynomial, L2() is the second-order Legendre polynomial, μ and σ are the variance and mean in the first statistical information set, respectively, and ν and η are the median and mode in the second statistical information set, respectively.

[0041] According to a second aspect of the present invention, a test data analysis device for a vehicle-mounted telescopic tent is disclosed, the device comprising:

[0042] Memory containing executable program code;

[0043] A processor coupled to the memory;

[0044] The processor calls the executable program code stored in the memory to execute the test data analysis method for the vehicle-mounted telescopic tent.

[0045] In a third aspect, the present invention discloses a computer-storable medium storing computer instructions, which, when invoked by a computer, are used to execute the test data analysis method for the vehicle-mounted telescopic tent.

[0046] In a fourth aspect, the present invention discloses an information data processing terminal, which is used to implement the test data analysis method for the vehicle-mounted telescopic tent.

[0047] The beneficial effects of this invention are as follows:

[0048] This invention provides a test data analysis method for vehicle-mounted telescopic tents. By comprehensively considering various performance indicators and the influence of the test location, and combining systematic data preprocessing and evaluation calculation methods, a comprehensive and accurate analysis of the performance of vehicle-mounted telescopic tents is achieved. Specifically, this invention has the following beneficial effects:

[0049] 1. Comprehensive evaluation of multiple indicators: This invention covers multiple key performance indicators such as rainproof performance, snow load performance, deployment time, failure rate, energy consumption, and storage time. It can comprehensively reflect the overall performance of vehicle-mounted telescopic tents in different usage scenarios, overcome the limitations of traditional methods that only focus on a single indicator, and provide users with a comprehensive performance evaluation perspective.

[0050] 2. Test Location Correlation Analysis: This invention combines the location information of the test locations with performance index test data, fully considering the impact of different environmental conditions at different test locations on tent performance, making the evaluation results more targeted and practical. This correlation analysis helps users understand the tent's adaptability in different environments, providing a more scientific basis for product optimization and user selection.

[0051] 3. Efficient data preprocessing: Through preprocessing steps such as data cleaning, time registration, and data reduction, this invention can effectively solve problems such as noise, missing values, time inconsistencies, and data redundancy in test data, ensuring data quality and consistency, thereby providing a reliable data foundation for subsequent evaluation calculations and improving the accuracy of evaluation results.

[0052] 4. Scientific Evaluation and Calculation Method: This invention constructs a difference matrix and performs fusion evaluation processing to scientifically quantify the differences in various performance indicators and conducts a comprehensive evaluation in conjunction with test location information. This evaluation method not only highlights the impact of key performance indicators but also effectively reflects the actual impact of different test locations on tent performance, making the evaluation results more scientific and reliable. Attached Figure Description

[0053] Figure 1 This is a flowchart illustrating the implementation of the method of the present invention. Detailed Implementation

[0054] To better understand the content of this invention, an embodiment is provided here.

[0055] Figure 1 This is a flowchart illustrating the implementation of the method of the present invention.

[0056] In a first aspect, this invention discloses a method for analyzing test data of a vehicle-mounted telescopic tent, comprising:

[0057] S1, measure and obtain the performance index test data set and corresponding test location set of the vehicle-mounted telescopic tent; the test location set includes the location information of the test locations; the performance index test data set includes rainproof performance test data sequence, snow load performance test data sequence, deployment time test data sequence, failure rate test data sequence, energy consumption test data sequence, and storage time test data sequence; each data in the test data sequence is obtained by testing at a test location in the test location set; data with the same sequence number in all test data sequences correspond to the same test location;

[0058] S2, preprocess the performance index test data set to obtain a preprocessed data set;

[0059] S3, perform evaluation and calculation on the preprocessed data set to obtain the comprehensive performance evaluation result of the outdoor tent;

[0060] The preprocessing of the performance index test data set to obtain a preprocessed data set includes:

[0061] S21, perform data cleaning on the performance index test data set to obtain the first dataset;

[0062] S22, Perform time registration processing on the first dataset to obtain the second dataset;

[0063] S23, perform data reduction processing on the second dataset to obtain a preprocessed data set;

[0064] The evaluation and calculation of the preprocessed data set to obtain the comprehensive performance evaluation result of the field tent includes:

[0065] S31, obtain the qualified values ​​for rainproof performance, snow load performance, deployment time, failure rate, energy consumption, and storage time.

[0066] S32, for each data sequence in the preprocessed data set, subtract the corresponding qualified value to obtain the corresponding difference sequence;

[0067] S33, using the difference sequence of rainproof performance and the difference sequence of snow load performance, a first difference matrix is ​​constructed;

[0068] S34, using the difference sequence of the unfolding time and the difference sequence of the storage time, a second difference matrix is ​​constructed;

[0069] S35, using the difference sequence of failure rate and the difference sequence of energy consumption, a third difference matrix is ​​constructed;

[0070] S36, perform fusion evaluation processing on each difference matrix to obtain the corresponding evaluation sequence;

[0071] S37, Perform performance evaluation processing on all evaluation sequences and test site sets to obtain the comprehensive performance evaluation result value of the outdoor tent.

[0072] The row vectors of each difference matrix are the corresponding difference sequences;

[0073] The fusion evaluation process includes:

[0074] For each row vector of the difference matrix, calculate the weight value to obtain the corresponding weight value;

[0075] By using the weight value of each row vector, the row vectors of the difference matrix are weighted and summed to obtain the corresponding evaluation sequence;

[0076] Each element of the evaluation sequence corresponds to a test location in the test location set;

[0077] The performance evaluation process is performed on all evaluation sequences and test site sets to obtain the comprehensive performance evaluation result value of the field tent, including:

[0078] S371, Image modeling is performed on all evaluation sequences and test site sets to obtain image information to be evaluated;

[0079] S372, Perform corner detection processing on the image information to be evaluated to obtain a set of corner information;

[0080] S373, perform edge point detection processing on the image information to be evaluated to obtain an edge point information set;

[0081] S374, perform fusion feature calculation processing on the corner point information set and the edge point information set to obtain the comprehensive performance evaluation result of the outdoor tent;

[0082] The image modeling process, which involves performing image modeling on all evaluation sequences and test location sets to obtain image information to be evaluated, includes:

[0083] Each evaluation sequence is normalized to obtain the corresponding normalized evaluation sequence;

[0084] The normalized evaluation sequences corresponding to the first difference matrix, the second difference matrix, and the third difference matrix are used as the R channel value, G channel value, and B channel value of the image pixel, respectively. The location information of the test location corresponding to each element of the normalized evaluation sequence is used as the two-dimensional image plane location coordinates of the image pixel to construct the image information to be evaluated.

[0085] The process of fusing the corner point information set and the edge point information set to obtain the comprehensive performance evaluation result of the outdoor tent includes:

[0086] Statistical processing is performed on the pixel values ​​of all pixels in the corner information set to obtain a first statistical information set; the first statistical information set includes the variance and mean of the pixel values ​​of all pixels in the corner information set.

[0087] Statistical processing is performed on the pixel values ​​of all pixels in the edge point information set to obtain a second statistical information set; the second statistical information set includes the median and mode values ​​of all pixel values ​​in the edge point information set.

[0088] Statistical calculations are performed on the first and second sets of statistical information to obtain the comprehensive performance evaluation result of the outdoor tent.

[0089] The expression for the statistical calculation is:

[0090]

[0091] Where zp is the comprehensive performance evaluation result of the outdoor tent, T2() is the second-order polynomial of the first-type Chebyshev polynomial, L2() is the second-order Legendre polynomial, μ and σ are the variance and mean in the first statistical information set, respectively, and ν and η are the median and mode in the second statistical information set, respectively.

[0092] The row vectors in the difference matrix are difference sequences;

[0093] The step of calculating the weight value for each row vector of the difference matrix to obtain the corresponding weight value includes:

[0094]

[0095] Where, p ij ε is the element in the i-th row and j-th column of the difference matrix. i Let α be the weight value corresponding to the i-th row of the difference matrix. i and β i Let be the mean and variance of the i-th row of the difference matrix, respectively, and M be the column dimension of the difference matrix;

[0096] The step of performing fusion evaluation processing on each difference matrix to obtain the corresponding evaluation sequence also includes:

[0097] Perform cross-correlation calculation on all row vectors of the difference matrix to obtain a cross-correlation matrix; the elements of the i-th row and j-th column of the cross-correlation matrix are the cross-correlation values ​​of the i-th row vector and the j-th row vector of the difference matrix;

[0098] The cross-correlation matrix and difference matrix are evaluated and processed to obtain the evaluation sequence;

[0099] The expression for the evaluation calculation process is:

[0100]

[0101] Among them, h i To evaluate the i-th element in the sequence, Let A be the mean of the i-th row of the difference matrix A. ij Let B be the element in the i-th row and j-th column of the difference matrix A. ijLet N be the element in the i-th row and j-th column of the cross-correlation matrix B, and N be the column dimension of the difference matrix.

[0102] The rainproof performance test data can be obtained by testing with a tent rainproof testing device;

[0103] The snow load performance test data sequence can be obtained using a tent snow load detection device;

[0104] The time test data sequence can be obtained by measuring the tent's deployment and take-down times;

[0105] The data cleaning process includes filling in missing values, smoothing noisy data, and smoothing or deleting outlier points.

[0106] The time registration process can employ methods such as extrapolation / extrapolation and Lagrange three-point interpolation.

[0107] The data reduction processing includes:

[0108] For each data attribute in the second dataset, using the data collection information of the data as the independent variable and the data value of the data as the dependent variable, autoregressive-moving average modeling is performed to obtain the regression model of the data attribute.

[0109] Using the regression model, the independent variables are calculated and processed to obtain regression data values; it is determined whether the absolute value of the difference between the regression data value and the corresponding dependent variable value is greater than a set first regression discrimination threshold; if it is greater than the first regression discrimination threshold, the data is deleted from the second dataset; if it is less than or equal to the first regression discrimination threshold, the data is not processed.

[0110] The data after all execution modes in the second dataset are fused together to obtain a preprocessed dataset.

[0111] The data collection information may be collection time information;

[0112] According to a second aspect of the present invention, a test data analysis device for a vehicle-mounted telescopic tent is disclosed, the device comprising:

[0113] Memory containing executable program code;

[0114] A processor coupled to the memory;

[0115] The processor calls the executable program code stored in the memory to execute the test data analysis method for the vehicle-mounted telescopic tent.

[0116] In a third aspect, the present invention discloses a computer-storable medium storing computer instructions, which, when invoked by a computer, are used to execute the test data analysis method for the vehicle-mounted telescopic tent.

[0117] In a fourth aspect, the present invention discloses an information data processing terminal, which is used to implement the test data analysis method for the vehicle-mounted telescopic tent.

[0118] The above description is merely an embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of the present invention should be included within the scope of the claims of the present invention.

Claims

1. A method for analyzing test data of a vehicle-mounted telescopic tent, characterized in that, include: S1, the set of test data for the performance indicators of the vehicle-mounted telescopic tent and the corresponding set of test locations were obtained; The set of test locations includes the location information of the test locations; The performance index test data set includes rainproof performance test data sequence, snow load performance test data sequence, deployment time test data sequence, failure rate test data sequence, energy consumption test data sequence, and storage time test data sequence; each data point in the test data sequence is obtained from tests conducted at test locations in the test location set. Data with the same sequence number in all test data sequences correspond to the same test location; S2, preprocess the performance index test data set to obtain a preprocessed data set; S3, perform evaluation and calculation on the preprocessed data set to obtain the comprehensive performance evaluation result of the field tent; The evaluation and calculation of the preprocessed data set to obtain the comprehensive performance evaluation result of the field tent includes: S31, obtain the qualified values ​​for rainproof performance, snow load performance, deployment time, failure rate, energy consumption, and storage time. S32, for each data sequence in the preprocessed data set, subtract the corresponding qualified value to obtain the corresponding difference sequence; S33, using the difference sequence of rainproof performance and the difference sequence of snow load performance, a first difference matrix is ​​constructed; S34, using the difference sequence of the unfolding time and the difference sequence of the storage time, a second difference matrix is ​​constructed; S35, using the difference sequence of failure rate and the difference sequence of energy consumption, a third difference matrix is ​​constructed; S36, perform fusion evaluation processing on each difference matrix to obtain the corresponding evaluation sequence; S37, Perform performance evaluation processing on all evaluation sequences and test site sets to obtain the comprehensive performance evaluation result value of the outdoor tent.

2. The test data analysis method for the vehicle-mounted telescopic tent as described in claim 1, characterized in that, The preprocessing of the performance index test data set to obtain a preprocessed data set includes: S21, perform data cleaning on the performance index test data set to obtain the first dataset; S22, Perform time registration processing on the first dataset to obtain the second dataset; S23, perform data reduction processing on the second dataset to obtain a preprocessed data set.

3. The test data analysis method for the vehicle-mounted telescopic tent as described in claim 1, characterized in that, The fusion evaluation process includes: For each row vector of the difference matrix, calculate the weight value to obtain the corresponding weight value; By using the weight value of each row vector, the row vectors of the difference matrix are summed in a weighted manner to obtain the corresponding evaluation sequence.

4. The test data analysis method for the vehicle-mounted telescopic tent as described in claim 1, characterized in that, The performance evaluation process is performed on all evaluation sequences and test site sets to obtain the comprehensive performance evaluation result value of the field tent, including: S371, Image modeling is performed on all evaluation sequences and test site sets to obtain image information to be evaluated; S372, Perform corner detection processing on the image information to be evaluated to obtain a set of corner information; S373, perform edge point detection processing on the image information to be evaluated to obtain an edge point information set; S374, perform fusion feature calculation processing on the corner point information set and edge point information set to obtain the comprehensive performance evaluation result value of the outdoor tent.

5. The test data analysis method for the vehicle-mounted telescopic tent as described in claim 4, characterized in that, The image modeling process, which involves performing image modeling on all evaluation sequences and test location sets to obtain image information to be evaluated, includes: Each evaluation sequence is normalized to obtain the corresponding normalized evaluation sequence; The normalized evaluation sequences corresponding to the first, second, and third difference matrices are used as the R, G, and B channel values ​​of the image pixels, respectively. The location information of the test location corresponding to each element of the normalized evaluation sequence is used as the two-dimensional image plane location coordinates of the image pixels to construct the image information to be evaluated.

6. A test data analysis device for a vehicle-mounted telescopic tent, characterized in that, The device includes: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the test data analysis method for the vehicle-mounted telescopic tent as described in any one of claims 1 to 5.

7. A computer-storable medium, characterized in that, The computer storage medium stores computer instructions, which, when invoked by the computer, are used to execute the test data analysis method for the vehicle-mounted telescopic tent as described in any one of claims 1 to 5.

8. An information data processing terminal, characterized in that, The information data processing terminal is used to implement the test data analysis method for the vehicle-mounted telescopic tent as described in any one of claims 1 to 5.

Images