Multi-dimensional data analysis platform based on product quality sampling detection

Abstract

The invention belongs to the technical field of product quality sampling detection, and particularly discloses and provides a multi-dimensional data analysis platform based on product quality sampling detection, which comprises a gasoline sample sampling module, a gasoline sampling detection module, a gasoline component correction module, a gasoline quality analysis module and a gasoline quality feedback terminal, according to the invention, the sampling surface is divided at equal intervals based on the height of the gasoline liquid level, and then the annular areas are divided based on the projection points of the central axis of the tank body on the sampling surface, so that a preset number of sampling points are randomly arranged in each annular area, and the defects of traditional single-point or uniform sampling are overcome; spatial representativeness and distribution rationality of sampling points are remarkably improved, meanwhile, multi-dimensional coupling correction is performed on octane number, sulfur content and water content based on detection interval duration, environment temperature and environment humidity, systematic errors caused by environment and time factors are eliminated, and high-credibility basic data are provided for subsequent quality analysis.

Description

Technical Field

[0001] The present invention belongs to the technical field of product quality sampling detection, and relates to a multidimensional data analysis platform based on product quality sampling detection. Background Art

[0002] In the petrochemical industry, gasoline product quality testing is a core component of ensuring energy security, stable equipment operation, and environmental protection. With the increasing complexity of refining processes, rising environmental standards, and the growing demand for intelligent management and control, gasoline quality testing requires precise quantification and comprehensive assessment of multiple metrics, including octane number, sulfur content, and water content. However, traditional testing technologies suffer from significant deficiencies in sampling strategies, data correction mechanisms, and analytical models, making them incapable of meeting the demands of modern, refined quality management.

[0003] The main defects of existing technologies are as follows: 1. Traditional gasoline quality testing usually adopts single-point sampling or uniform distribution method, which does not fully consider the composition heterogeneity of oil in the storage tank due to factors such as gravity stratification and temperature gradient. Single-point sampling or simple equal sampling can only obtain local data and cannot cover the spatial distribution characteristics of the oil in the entire tank, resulting in significant deviations between the test results and the actual quality.

[0004] 2. Existing gasoline quality assessments are mostly based on single indicator thresholds, without building a coupled analysis of multi-dimensional indicators. This leads to one-sided assessment results and makes it impossible to locate the specific causes of multi-dimensional quality defects, which in turn increases the difficulty of subsequent quality tracing and improvement. Summary of the Invention

[0005] In view of this, in order to solve the problems raised in the above background technology, a multidimensional data analysis platform based on product quality sampling detection is proposed.

[0006] The objectives of the present invention can be achieved through the following technical solutions: The present invention provides a multidimensional data analysis platform based on product quality sampling detection, including: a gasoline sample sampling module, which is used to scan the three-dimensional image of the gasoline storage tank and arrange sampling points based on the three-dimensional image, and then collect samples at each sampling point to obtain each gasoline sample.

[0007] Gasoline sampling and testing module, used to detect the octane number, sulfur content and water content of each gasoline sample.

[0008] The gasoline composition correction module is used to correct the gasoline composition based on the octane number, sulfur content and water content of each gasoline sample, combined with the detection interval, ambient temperature and ambient humidity, to obtain the corrected octane number, corrected sulfur content and corrected water content of each gasoline sample.

[0009] The gasoline quality analysis module is used to perform quality analysis based on the corrected octane number, corrected sulfur content, and corrected water content of the gasoline sample, and generate a quality assessment result for each gasoline sample.

[0010] The gasoline quality feedback terminal is used to synchronize the quality qualification assessment results to the quality feedback cloud platform for corresponding feedback.

[0011] Compared with the prior art, the present invention has the following beneficial effects: (1) The present invention divides the sampling surface into equally spaced areas based on the gasoline liquid level, and then divides the annular areas based on the projection points of the tank centerline on the sampling surface, thereby randomly arranging a preset number of sampling points in each annular area. This overcomes the defects of traditional single-point or uniform sampling and significantly improves the spatial representativeness and distribution rationality of the sampling points.

[0012] (2) The present invention performs multi-dimensional coupled correction on octane number, sulfur content and water content based on the detection interval, ambient temperature and ambient humidity, thereby eliminating the systematic errors caused by environmental and time factors and providing high-reliability basic data for subsequent quality analysis.

[0013] (3) The present invention breaks through the limitation of traditional single indicator threshold judgment by conducting quality assessment based on the corrected octane number qualification, corrected sulfur content qualification, corrected water content qualification and quality qualification. The assessment results comprehensively reflect the multi-dimensional quality status of gasoline, accurately locate the causes of defects, and provide a clear direction for subsequent quality tracing and process improvement.

[0014] (4) The present invention obtains the corrected octane number by analyzing the detection interval correction coefficient of the gasoline sample in the short-term volatilization and long-term oxidation based on the critical time, and performing deviation analysis in combination with the ambient temperature and the preset value, thereby avoiding the system deviation caused by the passage of time and ambient temperature, thereby significantly improving the accuracy and reliability of octane number evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0016] Figure 1 This is a schematic diagram of the connection of each module of the present invention.

[0017] Figure 2 This is a connection diagram of the sampling point layout steps of the present invention.

[0018] Figure 3 A schematic diagram showing the connection steps for generating quality assessment results of the present invention. DETAILED DESCRIPTION

[0019] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0020] See also Figure 1 As shown, the present invention provides a multi-dimensional data analysis platform based on product quality sampling detection, including: a gasoline sample sampling module, a gasoline sampling detection module, a gasoline component correction module, a gasoline quality analysis module and a gasoline quality feedback terminal.

[0021] In the above, the gasoline sampling detection module is connected to the gasoline sample sampling module and the gasoline component correction module respectively, and the gasoline quality analysis module is also connected to the gasoline component correction module and the gasoline quality feedback terminal respectively.

[0022] The gasoline sample sampling module is used to scan the three-dimensional image of the gasoline storage tank, and arrange sampling points based on the three-dimensional image, and then collect samples at each sampling point to obtain each gasoline sample.

[0023] See also Figure 2 As shown, exemplarily, the gasoline sample sampling module includes: A1, extracting the gasoline liquid level from the stereoscopic image, dividing it into three intervals with equal spacing along the vertical direction based on the gasoline liquid level, and using the middle plane of each interval as the sampling surface.

[0024] It should be added that by determining the sampling surface through vertical stratification, it is ensured that the sampling points cover the upper, middle and lower height areas of the tank body, and gasoline samples at different liquid levels can be effectively collected.

[0025] A2. Extract the central axis of the gasoline storage tank from the stereoscopic image, and divide the sampling surface into three annular regions of equal area by spreading outward along the projection point of the central axis of the tank on the sampling surface as the center of the circle.

[0026] It should be noted that each sampling surface is divided into three concentric annular regions of equal area, centered on the projection of the tank's central axis onto the sampling surface. From the center outward, these three sampling ranges are formed: inner, middle, and outer circles, thus accounting for the horizontal distribution differences of gasoline within the storage tank.

[0027] A3. Randomly arrange a preset number of sampling points in each annular area to obtain each sampling point.

[0028] The gasoline sampling detection module is used to detect the octane number, sulfur content and water content of each gasoline sample.

[0029] It should be added that the octane number is obtained by detecting with a near-infrared spectrometer, the sulfur content is obtained by detecting with an X-ray fluorescence method, and the water content is obtained by detecting with a capacitive moisture sensor.

[0030] The embodiment of the present invention divides the sampling surface into evenly spaced areas based on the gasoline liquid level, and then divides the annular areas based on the projection points of the tank centerline on the sampling surface. A preset number of sampling points are randomly arranged in each annular area, thereby overcoming the shortcomings of traditional single-point or uniform sampling and significantly improving the spatial representativeness and distribution rationality of the sampling points.

[0031] The gasoline composition correction module is used to correct the gasoline composition based on the octane number, sulfur content and water content of each gasoline sample in combination with the detection interval, ambient temperature and ambient humidity, to obtain the corrected octane number, corrected sulfur content and corrected water content of each gasoline sample.

[0032] It should be added that the detection interval refers to the difference between the sampling time and the detection time, and the ambient temperature and ambient humidity are detected by a temperature sensor and a humidity sensor respectively.

[0033] Exemplarily, the analysis of the corrected octane number of each gasoline sample includes: B1, determining the correction type based on the gasoline sample detection interval duration and a preset critical duration, obtaining the duration correction type of the gasoline sample, and analyzing the detection interval duration correction coefficient of each gasoline sample accordingly.

[0034] It should be added that the correction type determination process is as follows: when the gasoline sample detection interval is less than the preset critical time, its time correction type is determined to be short-term volatilization; otherwise, its time correction type is determined to be long-term oxidation.

[0035] It should be added that the preset critical time is a time threshold used to distinguish the type of impact of the gasoline sample detection interval on the octane number. Its main core function is to distinguish between short-term volatilization and long-term oxidation stages. When the detection interval is ≤ the preset critical time, the gasoline sample mainly suffers from short-term volatilization loss. For example, the volatilization of low-boiling point components causes a decrease in octane number, which is compensated by the short-term volatilization correction coefficient. When the detection interval is greater than the preset critical time, the gasoline sample enters the long-term oxidation stage. For example, the generation of peroxides causes octane number deterioration, which needs to be corrected by the long-term oxidation correction coefficient. Among them, the time it takes for the gasoline sample to transition from short-term volatilization to long-term oxidation during each gasoline sampling test is obtained from historical data, and the median is extracted as the preset critical time.

[0036] Furthermore, the analysis of the detection interval time correction coefficient of each gasoline sample includes: B1-1, when the time correction type is short-term volatility, the product of the gasoline sample detection interval time and the preset short-term volatility correction coefficient is calculated as the detection interval time correction coefficient of the gasoline sample.

[0037] It should be added that the calculation formula for the detection interval correction coefficient is: , where is the detection interval correction coefficient, To preset the short-term volatility correction factor, The detection interval duration.

[0038] It should be added that the preset short-term volatility correction factor is the volatility loss rate of the octane number per unit time, unit: 1 / day, such as 0.01 / day means a loss of 1% per day.

[0039] It should be added that the preset short-term volatility correction factor is obtained through experimental verification. The specific process is: obtain the initial octane number and the measured octane number of each gasoline test sample whose detection interval is less than the preset critical time, as well as the detection interval, and use the formula Calculating octane number degradation rate , is the initial octane number, The actual octane number.

[0040] The octane number degradation rate and the detection interval duration of each gasoline test sample are summed up to obtain the total octane number degradation rate and the total detection interval duration, and then the ratio of the two is calculated to obtain the preset short-term volatility correction factor.

[0041] B1-2. When the duration correction type is long-term oxidation, the product of the detection interval duration and the preset long-term oxidation correction coefficient is calculated as the detection interval duration correction coefficient of each gasoline sample.

[0042] It should be added that the method for obtaining the preset long-term oxidation correction coefficient is similar to the method for obtaining the preset short-term volatilization correction coefficient, and will not be repeated here.

[0043] B2. Perform relative deviation analysis on the ambient temperature of the gasoline sample and the preset octane number correction temperature to obtain the ambient temperature correction coefficient of the gasoline sample.

[0044] B3. merging the detection interval correction coefficient, the ambient temperature correction coefficient, and the octane number to obtain a corrected octane number for each gasoline sample.

[0045] It should be added that the light hydrocarbons in gasoline will volatilize within a short period of time after sampling and undergo oxidation reactions over a long period of time, which will lead to a decrease in the octane number. At the same time, the increase in temperature will accelerate the movement of hydrocarbon molecules, resulting in an increase in the volatilization rate. Therefore, the detection interval and ambient temperature are selected for the correction analysis of the octane number.

[0046] The embodiment of the present invention analyzes the detection interval correction coefficient of the gasoline sample in the short-term volatilization and long-term oxidation based on the critical duration, and performs deviation analysis in combination with the ambient temperature and preset values to obtain a corrected octane number. This avoids system deviations caused by the passage of time and ambient temperature, thereby significantly improving the accuracy and reliability of octane number assessment.

[0047] Illustratively, the analysis of the corrected water content of each gasoline sample includes: E1, using the relative deviation between the ambient humidity and the preset standard humidity as the humidity compensation coefficient of the gasoline sample.

[0048] It should be added that the analytical formula for the humidity compensation coefficient is , where is the humidity compensation coefficient, is the ambient humidity, The preset standard humidity is obtained by obtaining the ambient temperature of each gasoline sampling test from historical data, performing average calculation, and using the calculation result as the preset standard humidity.

[0049] E2. Analyze the temperature compensation coefficient of the gasoline sample in the same way as the analysis of the humidity compensation coefficient.

[0050] E3. Compare the gasoline sample detection interval time with the preset moisture migration critical time to obtain the gasoline sample detection interval time compensation coefficient.

[0051] It should be added that the preset critical time for moisture migration is obtained by extracting the time when the moisture in gasoline begins to migrate during each gasoline sampling test from historical data and calculating the average value. The preset critical time for moisture migration is used to determine whether significant moisture migration has occurred in the gasoline sample during the test interval. When the test interval is less than or equal to the critical value, it indicates that the moisture in the gasoline has not yet undergone significant migration, so there is no need to make time-related corrections to the test results. When the test interval is greater than the critical value, it indicates that significant moisture migration has occurred, and the interval correction coefficient needs to be further calculated.

[0052] Furthermore, the analysis of the gasoline sample detection interval compensation coefficient includes: E3-1. If the gasoline sample detection interval is less than or equal to the preset moisture migration critical time, the preset minimum compensation coefficient is used as the gasoline sample detection interval compensation coefficient.

[0053] It should be added that the preset minimum compensation coefficient can specifically be set to 0.

[0054] E3-2. If the gasoline sample detection interval is longer than the preset critical time for moisture migration, the interval is subtracted from the preset critical time for moisture migration to obtain the migration time difference.

[0055] E3-3. If the migration time difference is less than the preset moisture migration critical time, the ratio of the two is used as the detection interval compensation coefficient of the gasoline sample. Otherwise, the preset maximum compensation coefficient is used as the detection interval compensation coefficient of the gasoline sample.

[0056] It should be added that the preset maximum compensation coefficient can specifically be set to 1.

[0057] E4. Couple the water content of the gasoline sample with the humidity compensation coefficient, the detection interval compensation coefficient, and the temperature compensation coefficient to obtain the corrected water content of each gasoline sample.

[0058] It should be added that the calculation formula for the corrected water content is: , where To correct for water content, is the water content, is the humidity compensation coefficient, is the detection interval compensation coefficient, is the temperature compensation coefficient.

[0059] It should be added that the humidity compensation coefficient reflects the proportion of the influence of the difference between ambient humidity and standard humidity on the water absorption of gasoline samples. The detection interval compensation coefficient quantifies the influence of the detection interval on the internal water migration of gasoline samples, and distinguishes the influence of short-term stable period and long-term diffusion period on water content. The temperature compensation coefficient reflects the influence of ambient temperature on the evaporation rate of water in gasoline samples. This formula couples the influencing factors of humidity, time and temperature in the form of product, reflecting the synergistic effect of various factors on the water content of gasoline samples.

[0060] It should be added that gasoline is hygroscopic. The water content in gasoline samples will increase with the ambient humidity. The water distribution of gasoline samples is stable in a short period of time, but the water in gasoline samples will diffuse to the oil-gas interface over a long period of time. At the same time, the increase in temperature will increase the evaporation rate of water molecules. Therefore, the ambient humidity, detection interval and ambient temperature are selected for the correction analysis of water content.

[0061] Exemplarily, the analysis of the corrected sulfur content of each gasoline sample includes: performing a deviation analysis on the ambient temperature of the gasoline sample and a preset value to obtain a temperature adjustment coefficient of the gasoline sample.

[0062] It should be added that the analytical formula for the temperature adjustment coefficient is , where is the temperature adjustment coefficient, is the ambient temperature, and are the preset lowest temperature where sulfur content has no effect and the preset highest temperature where sulfur content has an effect, respectively. The method of obtaining the sulfur content is as follows: obtain the lowest temperature range where the sulfur content is stable and has no obvious changes from the historical data, and then take the highest temperature value in the range as the preset lowest temperature where the sulfur content has no effect. How to obtain Similar, no repetition will be given here.

[0063] Dilution effect deviation analysis was performed based on the corrected water content of gasoline samples to obtain the water content correction coefficient of gasoline samples.

[0064] It should be added that the analytical formula for the water content correction factor is: , where is the water content correction factor, is the preset baseline water content, The method for obtaining is: extracting the average water content of gasoline samples at each sampling test from historical data as the preset benchmark water content.

[0065] The sulfur content of the gasoline samples was coupled with the temperature adjustment coefficient and the water content correction coefficient to obtain the corrected sulfur content of each gasoline sample.

[0066] It should be added that the analytical formula for correcting sulfur content is: , where To correct for sulfur content, The sulfur content.

[0067] It should be added that sulfur content is usually detected using the X-ray fluorescence method, and its concentration reading is related to the density of the gasoline sample. The increase in temperature will cause the volume of gasoline to expand, thereby diluting the apparent sulfur concentration. The water content in gasoline will dilute the sulfide distribution, and water molecules have an absorption effect on X-rays. Therefore, the ambient temperature is selected to correct the water content for the octane number correction analysis.

[0068] The embodiment of the present invention performs multi-dimensional coupled correction on octane number, sulfur content, and water content based on the detection interval duration, ambient temperature, and ambient humidity, thereby eliminating systematic errors caused by environmental and time factors and providing highly reliable basic data for subsequent quality analysis.

[0069] The gasoline quality analysis module is used to perform quality analysis based on the corrected octane number, corrected sulfur content, and corrected water content of each gasoline sample to generate a quality assessment result for each gasoline sample.

[0070] See also Figure 3 As shown, illustratively, the generating of the quality assessment results of each gasoline sample includes: Y1, comparing the corrected octane number of each gasoline sample with a preset standard corrected octane number to obtain the corrected octane number qualification of each gasoline sample.

[0071] It should be noted that the standard corrected octane number (SCON) is the acceptable octane number threshold specified in the quality standards for gasoline samples and is used to determine whether the corrected octane number meets usage requirements. For example, the SCON of a 92-octane gasoline sample is typically 92, while the SCON of a 95-octane gasoline sample is 95.

[0072] Furthermore, the analysis of the corrected octane number qualification of the gasoline sample includes: Y1-1. If the corrected octane number of the gasoline sample is greater than or equal to a preset standard corrected octane number, the preset qualification is used as the corrected octane number qualification of the gasoline sample.

[0073] It should be added that the preset qualification degree can specifically be set to 1.

[0074] Y1-2. If the corrected octane number of the gasoline sample is less than the preset standard corrected octane number, the ratio of the corrected octane number of the gasoline sample to the preset standard corrected octane number is used as the corrected octane number qualification of the gasoline sample, thereby obtaining the corrected octane number qualification of each gasoline sample.

[0075] Y2. Analyze the corrected sulfur content and water content of each gasoline sample in the same manner as the corrected octane number qualification.

[0076] Y3. Perform weighted fusion calculation on the corrected octane number qualification, corrected sulfur content qualification and corrected water content qualification of each gasoline sample to obtain the quality qualification of each gasoline sample.

[0077] It should be added that the calculation formula for quality compliance is , where For quality compliance, 、 and They are the corrected octane number qualification, corrected sulfur content qualification and corrected water content qualification, 、 and are the weights of the corrected octane number qualification, the corrected sulfur content qualification and the corrected water content qualification, respectively. , .

[0078] It should be added that the octane number is the core indicator for measuring the anti-knock performance of gasoline samples, which directly affects the power output, fuel consumption and service life of the engine. For example, insufficient octane number will cause engine knock, and in severe cases it can damage components such as pistons and cylinders, leading to safety accidents. Therefore, the weight of correcting the octane number qualification is the largest. Excessive sulfur content will cause pollutants to be generated after gasoline combustion, aggravating acid rain and air pollution, and sulfides will corrode the engine fuel system, shorten equipment life, and increase maintenance costs. Therefore, the weight of correcting the sulfur content qualification is second. Excessive water content will cause gasoline samples to stratify and emulsify, affecting combustion efficiency. For example, water molecules absorb heat and reduce calorific value, but usually do not cause serious safety accidents immediately, but affect equipment performance through long-term accumulation. Therefore, the weight of correcting the water content qualification is the smallest, so it is set. , in order to facilitate analysis, The specific value can be 0.5. The specific value can be 0.3, The specific value can be 0.2.

[0079] Y4. Perform a quality assessment on the corrected octane number qualification, corrected sulfur content qualification, corrected water content qualification, and quality qualification of each gasoline sample to obtain a quality assessment result of each gasoline sample.

[0080] Furthermore, the determination of the quality qualification evaluation results of each gasoline sample includes: Y4-1, comparing the corrected octane number qualification, corrected sulfur content qualification, corrected water content qualification and quality qualification of each gasoline sample with their preset thresholds respectively.

[0081] Y4-2. The qualified degree of the corrected octane number being greater than the preset threshold is used as condition 1, the qualified degree of the corrected sulfur content being greater than the preset threshold is used as condition 2, the qualified degree of the corrected water content being greater than the preset threshold is used as condition 3, and the qualified degree of the quality being greater than the preset threshold is used as condition 4. Then, a qualified determination is performed according to the preset qualified determination rules to obtain the qualified determination results of each gasoline sample.

[0082] It should be added that the qualification determination process of each gasoline sample is as follows: when condition 4 is not met, the gasoline sample is determined to be unqualified.

[0083] When conditions 1, 2, 3 and 4 are all met, the gasoline sample is judged to be of qualified quality.

[0084] When condition 4 is met and only one of conditions 1, 2, and 3 is not met, the gasoline sample is judged to be of qualified quality.

[0085] When condition 4 is met and at least two of conditions 1, 2, and 3 are not met, the gasoline sample is judged to be unqualified.

[0086] Y4-3. Count the number of gasoline samples with qualified quality and the total number of gasoline samples, and use the ratio of the two as the gasoline sample qualified ratio, and then compare it with the preset gasoline sample qualified ratio. When the gasoline sample qualified ratio is greater than or equal to the preset gasoline sample qualified ratio, the gasoline quality is regarded as qualified as the quality assessment result; otherwise, the gasoline quality is regarded as unqualified as the quality assessment result.

[0087] The embodiment of the present invention breaks through the limitations of traditional single-indicator threshold judgment by performing quality assessment based on the corrected octane number, corrected sulfur content, corrected water content, and quality. The assessment results comprehensively reflect the multi-dimensional quality status of gasoline, accurately locate the causes of defects, and provide a clear direction for subsequent quality tracing and process improvement.

[0088] The gasoline quality feedback terminal is used to synchronize the quality assessment results to the quality feedback cloud platform for corresponding feedback.

[0089] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0090] The above embodiments may be implemented in whole or in part through software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0091] Those skilled in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0092] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0093] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0094] Finally, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A multidimensional data analysis platform based on product quality sampling and testing, characterized by: include: A gasoline sampling module is used to scan a 3D image of the gasoline storage tank, arrange sampling points based on the 3D image, and collect samples at each sampling point to obtain gasoline samples; Gasoline sampling and testing module, used to test the octane number, sulfur content and water content of each gasoline sample; A gasoline composition correction module is used to correct the gasoline composition based on the octane number, sulfur content, and water content of each gasoline sample, combined with the detection interval, ambient temperature, and ambient humidity, to obtain the corrected octane number, corrected sulfur content, and corrected water content of each gasoline sample; A gasoline quality analysis module is used to perform quality analysis based on the corrected octane number, corrected sulfur content, and corrected water content of each gasoline sample and generate a quality assessment result for each gasoline sample; The gasoline quality feedback terminal is used to synchronize the quality assessment results to the quality feedback cloud platform for corresponding feedback.

2. The multidimensional data analysis platform based on product quality sampling detection according to claim 1, characterized in that: The gasoline sample sampling module comprises: A1, extracting the gasoline level from the stereo image, dividing the gasoline level into three intervals at equal intervals along the vertical direction based on the gasoline level, and using the middle plane of each interval as the sampling surface; A2. Extract the central axis of the gasoline storage tank from the stereoscopic image, and divide the sampling surface into three annular regions of equal area by spreading outward from the projection point of the central axis of the tank on the sampling surface as the center of the circle; A3. Randomly arrange a preset number of sampling points in each annular area to obtain each sampling point.

3. The multidimensional data analysis platform based on product quality sampling detection according to claim 1, characterized in that: The analysis of the corrected octane number of each gasoline sample includes: B1. Determine the correction type based on the gasoline sample detection interval duration and the preset critical duration, obtain the duration correction type of the gasoline sample, and analyze the detection interval duration correction coefficient of each gasoline sample accordingly; B2. Perform relative deviation analysis on the ambient temperature of the gasoline sample and the preset octane number correction temperature to obtain the ambient temperature correction coefficient of the gasoline sample; B3. merging the detection interval correction coefficient, the ambient temperature correction coefficient, and the octane number to obtain a corrected octane number for each gasoline sample.

4. The multidimensional data analysis platform based on product quality sampling detection according to claim 3, characterized in that: The correction coefficient for the detection interval of each gasoline sample is as follows: When the time correction type is short-term volatility, the product of the gasoline sample detection interval time and the preset short-term volatility correction coefficient is used as the gasoline sample detection interval time correction coefficient; When the duration correction type is long-term oxidation, the product of the detection interval duration and the preset long-term oxidation correction coefficient is calculated as the detection interval duration correction coefficient of each gasoline sample.

5. The multidimensional data analysis platform based on product quality sampling detection according to claim 1, characterized in that: The analysis of the corrected water content of each gasoline sample includes: E1. The relative deviation between the ambient humidity and the preset standard humidity is used as the humidity compensation coefficient of the gasoline sample; E2. Analyze the temperature compensation coefficient of the gasoline sample in the same way as the humidity compensation coefficient analysis method; E3. Compare the gasoline sample detection interval with the preset moisture migration critical time to obtain a gasoline sample detection interval compensation coefficient; E4. Couple the water content of the gasoline sample with the humidity compensation coefficient, the detection interval compensation coefficient, and the temperature compensation coefficient to obtain the corrected water content of each gasoline sample.

6. The multidimensional data analysis platform based on product quality sampling detection according to claim 5, characterized in that: The analysis of the gasoline sample detection interval compensation coefficient includes: If the gasoline sample detection interval is less than or equal to the preset moisture migration critical time, the preset minimum compensation coefficient is used as the gasoline sample detection interval compensation coefficient; If the gasoline sample detection interval is longer than the preset water migration critical time, the interval is subtracted from the preset water migration critical time to obtain the migration time difference; If the migration time difference is less than the preset moisture migration critical time, the ratio of the two will be used as the detection interval compensation coefficient of the gasoline sample. Otherwise, the preset maximum compensation coefficient will be used as the detection interval compensation coefficient of the gasoline sample.

7. The multidimensional data analysis platform based on product quality sampling detection according to claim 1, characterized in that: The analysis of the corrected sulfur content of each gasoline sample includes: Perform deviation analysis on the ambient temperature of the gasoline sample and the preset value to obtain the temperature adjustment coefficient of the gasoline sample; Dilution effect deviation analysis is performed based on the corrected water content of gasoline samples to obtain the water content correction factor of gasoline samples; The sulfur content of the gasoline samples was coupled with the temperature adjustment coefficient and the water content correction coefficient to obtain the corrected sulfur content of each gasoline sample.

8. The multidimensional data analysis platform based on product quality sampling detection according to claim 1, characterized in that: Generating the quality assessment results of each gasoline sample includes: Y1. Compare the corrected octane number of each gasoline sample with a preset standard corrected octane number to obtain the corrected octane number qualification of each gasoline sample; Y2. Analyze the corrected sulfur content and water content of each gasoline sample in the same manner as described for the corrected octane number qualification; Y3. Perform a weighted fusion calculation on the corrected octane number qualification, corrected sulfur content qualification, and corrected water content qualification of each gasoline sample to obtain the quality qualification of each gasoline sample; Y4. Perform a quality assessment on the corrected octane number qualification, corrected sulfur content qualification, corrected water content qualification, and quality qualification of each gasoline sample to obtain a quality assessment result of each gasoline sample.

9. The multidimensional data analysis platform based on product quality sampling detection according to claim 8, characterized in that: The analysis of the corrected octane number qualification of each gasoline sample includes: If the corrected octane number of the gasoline sample is greater than or equal to the preset standard corrected octane number, the preset qualification level is used as the corrected octane number qualification level of the gasoline sample; If the corrected octane number of the gasoline sample is less than the preset standard corrected octane number, the ratio of the corrected octane number of the gasoline sample to the preset standard corrected octane number is used as the corrected octane number qualification of the gasoline sample, thereby obtaining the corrected octane number qualification of each gasoline sample.

10. The multidimensional data analysis platform based on product quality sampling detection according to claim 8, characterized in that: The determination of the quality acceptance evaluation results of each gasoline sample includes: Compare the corrected octane number qualification, corrected sulfur content qualification, corrected water content qualification and quality qualification of each gasoline sample with their preset thresholds respectively; The qualified degree of the corrected octane number being greater than the preset threshold is used as condition 1, the qualified degree of the corrected sulfur content being greater than the preset threshold is used as condition 2, the qualified degree of the corrected water content being greater than the preset threshold is used as condition 3, and the qualified degree of the quality being greater than the preset threshold is used as condition 4. A qualified determination is then performed according to the preset qualified determination rules to obtain a qualified determination result for each gasoline sample; The number of gasoline samples with qualified quality and the total number of gasoline samples are counted, and the ratio of the two is used as the gasoline sample qualified ratio, which is then compared with the preset gasoline sample qualified ratio. When the gasoline sample qualified ratio is greater than or equal to the preset gasoline sample qualified ratio, the gasoline quality is regarded as qualified as the quality assessment result; otherwise, the gasoline quality is regarded as unqualified as the quality assessment result.

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