Cleaning agent quality detection and analysis system based on artificial intelligence

Abstract

The invention relates to the technical field of cleaning agent quality detection, in particular to a cleaning agent quality detection and analysis system based on artificial intelligence, which comprises a quality detection and analysis platform, a database, a physical evaluation unit, a non-use evaluation unit, a chemical component quality unit, a use evaluation and analysis unit and a display response unit, according to the invention, quality analysis is carried out preliminarily from the perspective of physical detection and chemical detection of the detected sample, and physical quality evaluation interaction analysis is carried out in an information progressive manner, so that the physical quality detection accuracy and reliability of the detected sample can be improved; component deviation verification feedback analysis is performed on the basic component data from the perspective of chemical detection, so that whether the quality of the detected sample reaches the standard or not is judged in a non-use mode, quality detection analysis is performed from the perspective of the use effect, the quality analysis result of the detected sample can be further verified and fed back, and the detection accuracy is improved. The quality analysis error risk of the whole detection sample is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of cleaning agent quality detection, and in particular to a cleaning agent quality detection and analysis system based on artificial intelligence. Background Art

[0002] Cleaning agents are a very large category with many types, including inorganic cleaning and organic cleaning. The difference between organic cleaning agents and inorganic cleaning agents is simply that organic cleaning agents are cleaning agents made of carbon-containing compounds, while inorganic cleaning agents are cleaning agents made of carbon-free compounds, so they belong to inorganic substances. There are many brands of liquid cleaning agents on the market, and their quality varies greatly. Users often face difficulties in choosing. Traditional cleaning agent quality assessment methods usually rely on manual observation and empirical judgment, lack objective and accurate evaluation standards, and cannot conduct comprehensive evaluation from multiple perspectives such as physics, chemistry, and usage effects, thereby reducing the reliability and comprehensiveness of cleaning agent quality testing, and increasing the risk of errors in cleaning agent quality test results. In view of the above technical defects, a solution is now proposed. Summary of the invention

[0003] The purpose of the present invention is to provide a cleaning agent quality detection and analysis system based on artificial intelligence to solve the technical defects mentioned above. The present invention initially performs quality analysis from the physical detection perspective and the chemical detection perspective of the detection sample, and performs interactive analysis of physical quality evaluation in a progressive manner through information advancement, thereby helping to improve the accuracy and reliability of physical quality detection of the detection sample, and by performing component deviation verification and feedback analysis on the basic component data from the perspective of chemical detection, and analyzing the overall quality of the detection sample by integrating the physical and chemical detection results, so as to judge whether the quality of the detection sample meets the standard in a non-use manner, and in-depth quality detection and analysis from the perspective of usage effect, which helps to improve the comprehensiveness of the quality detection perspective of the detection sample, and helps to further verify and feedback the quality analysis results of the detection sample to reduce the error risk of the entire detection sample quality analysis.

[0004] The object of the present invention can be achieved by the following technical solutions: A cleaning agent quality detection and analysis system based on artificial intelligence, comprising a quality detection and analysis platform, a database, a physical evaluation unit, a non-use judgment unit, a chemical composition quality unit, a use evaluation and analysis unit, and a display response unit; The quality inspection and analysis platform is used to retrieve the physical appearance data and characteristic performance data of the cleaning agent to be inspected from the database, and send the physical appearance data and characteristic performance data to the physical evaluation unit and the non-use evaluation unit respectively; The physical evaluation unit is used to perform intuitive physical feature detection and analysis on the received physical appearance data, compare and analyze the obtained appearance difference value and physical flow coefficient, and obtain an intuitive normal signal or an intuitive deviation signal; The non-use evaluation unit is used to perform physical non-intuitive evaluation feedback analysis on the received characteristic performance data, perform discrimination processing on the obtained table characteristic value and the own characteristic index, obtain the evaluation normal signal or the evaluation abnormal signal, and perform physical quality evaluation interactive analysis on the intuitive normal signal, the intuitive deviation signal, the evaluation normal signal and the evaluation abnormal signal, and obtain the physical qualified signal or the physical unqualified signal; The chemical composition quality unit is used to retrieve basic composition data from the database, conduct composition deviation verification feedback analysis on the basic composition data, perform discrimination processing on the obtained chemical analysis index, and obtain a qualified component signal or a failed component signal; Interactively analyze physical qualified signals, physical unqualified signals, component qualified signals, and component unqualified signals to obtain quality stability signals or quality risk signals; When the usage evaluation and analysis unit is used to respond to the quality stability signal, it collects the usage effect data of the test samples for quality verification evaluation feedback analysis to obtain a usage compliance signal or a usage non-compliance signal.

[0005] Preferably, the intuitive physical feature detection and analysis process of the physical evaluation unit is as follows: The cleaning agent to be tested is set as a test sample, and physical appearance data of the test sample is collected, wherein the physical appearance data includes an appearance characteristic image and a physical flow coefficient; The appearance feature image is compared and analyzed with the standard appearance feature image corresponding to the test sample to obtain the difference value between the appearance feature image and the standard appearance feature image corresponding to the test sample, and the difference value between the appearance feature image and the standard appearance feature image corresponding to the test sample is set as the appearance difference value.

[0006] Preferably, the physical flow coefficient represents the time length corresponding to the deviation of the cleaning agent flow rate of the test sample at the set temperature and load from the set cleaning agent flow rate range; The appearance difference value and the physical flow coefficient are compared and analyzed with the preset appearance difference value threshold and the preset physical flow coefficient threshold that are internally recorded and stored, so as to obtain an intuitive normal signal or an intuitive deviation signal.

[0007] Preferably, the physical non-intuitive evaluation feedback analysis process of the non-use evaluation unit is as follows: Divide the test sample into i sub-samples, where i is a natural number greater than zero, and obtain characteristic performance data of each sub-sample, wherein the characteristic performance data represents a characteristic value and an own characteristic index; The surface tension of each sub-sample is obtained, the maximum value and the minimum value of the surface tension are obtained, and the difference between the maximum value and the minimum value of the surface tension is set as the surface tension characteristic value; The self-characteristic index indicates the number of sub-samples whose self-data deviate from the preset threshold. The self-data includes specific gravity, viscosity, and boiling point.

[0008] Preferably, the characteristic value of the table and the characteristic index of the self are discriminated: If the table feature value is less than the preset table feature value and threshold, and the own characteristic index is equal to zero, then a normal evaluation signal is generated; if the table feature value is greater than or equal to the preset table feature value and threshold, or the own characteristic index is not equal to zero, then an abnormal evaluation signal is generated; Perform physical quality evaluation interactive analysis on the intuitive normal signal, intuitive deviation signal, evaluation normal signal and evaluation abnormal signal: if the intuitive normal signal and the evaluation normal signal are generated, a physical qualified signal is obtained; if the intuitive normal signal and the evaluation abnormal signal or the intuitive deviation signal and the evaluation normal signal or the intuitive deviation signal and the evaluation abnormal signal are generated, a physical unqualified signal is obtained.

[0009] Preferably, the component deviation verification feedback analysis process of the chemical component mass unit is as follows: Obtain basic component data of the test sample, the basic component data including a component deviation value and a component contamination index, compare and analyze the component deviation value and the component contamination index with a preset component deviation value threshold and a preset component contamination index threshold, set the number of component deviation values ​​and component contamination indexes that are greater than or equal to the preset component deviation value threshold and the preset component contamination index threshold as a chemical analysis index, and perform discrimination processing on the chemical analysis index to obtain a component qualified signal or a component unqualified signal; Obtain the component type and content of the test sample, compare and analyze the content corresponding to the component type of the test sample with the preset content, and set the number of deviations of the content corresponding to the component type of the test sample from the preset content as the component deviation value; Obtaining the pH value of the test sample, comparing and analyzing the pH value of the test sample with a preset pH value range, and setting the portion of the pH value of the test sample that deviates from the preset pH value range as a component contamination index; Physical qualified signals, physical unqualified signals, component qualified signals, and component unqualified signals are obtained, and interactive analysis is performed to obtain quality stability signals or quality risk signals.

[0010] Preferably, the quality verification evaluation feedback analysis process using the evaluation analysis unit is as follows: Obtaining use effect data of the test sample, the use effect data including a decontamination deviation value and a use evaluation value, wherein the reflectivity change value of the stained cloth before and after washing is obtained by testing the sample based on the artificial cotton cloth detection method, the reflectivity change value of the stained cloth before and after washing is set as the decontamination floating value, and the part of the decontamination floating value that is less than a preset decontamination floating value threshold is set as the decontamination deviation value; Obtaining the residual area of ​​the stained cloth after washing, and comparing the residual area of ​​the stained cloth after washing with a preset residual area, and setting the portion of the residual area of ​​the stained cloth after washing that is larger than the preset residual area as a usage evaluation value; The decontamination deviation value and the usage evaluation value are compared and analyzed with the preset decontamination deviation value threshold and the preset usage evaluation value threshold to obtain a usage compliance signal or a usage non-compliance signal.

[0011] The beneficial effects of the present invention are as follows: The present invention preliminarily performs quality analysis from the perspective of physical detection and chemical detection of the test sample, that is, analyzes from two points of view, intuitive and non-intuitive, from the perspective of physical detection, that is, performs intuitive physical characteristic detection and analysis on the physical appearance data of the test sample, so as to preliminarily understand whether the physical quality of the test sample is qualified, and performs physical non-intuitive evaluation feedback analysis on the characteristic performance data from a non-intuitive perspective, so as to further judge the physical quality of the test sample, and performs interactive analysis of physical quality evaluation in a progressive manner of information, thereby helping to improve the accuracy and reliability of physical quality detection of the test sample; The present invention performs component deviation verification and feedback analysis on basic component data from the perspective of chemical testing to determine whether the chemical quality of the test sample is qualified. At the same time, the overall quality of the test sample is analyzed by fusing the physical and chemical test results, so as to determine whether the quality of the test sample is up to standard in a non-usage manner, and conducts in-depth quality testing and analysis from the perspective of usage effect, that is, performing quality verification, evaluation and feedback analysis on the usage effect data of the test sample, which helps to improve the comprehensiveness of the quality testing perspective of the test sample, and at the same time helps to improve the reliability and effectiveness of the quality testing of the test sample, and helps to further verify and feedback the quality analysis results of the test sample to reduce the error risk of the entire quality analysis of the test sample. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The present invention will be further described below in conjunction with the accompanying drawings; Figure 1 It is a flowchart of the system of the present invention; Figure 2 It is a local analysis reference diagram of the first embodiment of the present invention. DETAILED DESCRIPTION

[0013] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0014] Example 1: Please refer to Figure 1 to Figure 2 As shown, the present invention is a cleaning agent quality detection and analysis system based on artificial intelligence, including a quality detection and analysis platform, a database, a physical evaluation unit, a non-use judgment unit, a chemical composition quality unit, a use evaluation and analysis unit and a display response unit, the database is connected to the quality detection and analysis platform in a one-way communication, the quality detection and analysis platform is connected to the physical evaluation unit and the chemical composition quality unit in a one-way communication, the physical evaluation unit is connected to the non-use judgment unit in a one-way communication, the quality detection and analysis platform is connected to the non-use judgment unit in a two-way communication, the chemical composition quality unit is connected to the use evaluation and analysis unit and the display response unit in a one-way communication, and the use evaluation and analysis unit is connected to the display response unit in a one-way communication; The quality inspection and analysis platform is used to retrieve the physical appearance data and characteristic performance data of the cleaning agent to be inspected from the database, and send the physical appearance data and characteristic performance data to the physical evaluation unit and the non-use evaluation unit respectively; The physical evaluation unit is used to perform intuitive physical feature detection and analysis on the received physical appearance data, so as to directly determine whether the quality of the test sample is qualified from an intuitive perspective. The specific intuitive physical feature detection and analysis process is as follows: The cleaning agent to be tested is set as a test sample, and physical appearance data of the test sample is collected, wherein the physical appearance data includes an appearance characteristic image and a physical flow coefficient; In the embodiment of the present invention, the appearance feature image is compared and analyzed with the standard appearance feature image corresponding to the test sample, and the difference value between the appearance feature image and the standard appearance feature image corresponding to the test sample is obtained, and the difference value between the appearance feature image and the standard appearance feature image corresponding to the test sample is set as the appearance difference value. It should be noted that the larger the value of the appearance difference value, the greater the risk of abnormal appearance quality of the test sample; In the embodiment of the present invention, the physical flow coefficient indicates the time duration corresponding to the deviation of the cleaning agent flow rate of the test sample under the set temperature and load from the set cleaning agent flow rate range. It should be noted that the greater the value of the physical flow coefficient, the greater the risk of physical quality abnormality of the test sample; The appearance difference value and the physical flow coefficient are compared and analyzed with the preset appearance difference value threshold and the preset physical flow coefficient threshold that are stored internally: If the appearance difference value is less than the preset appearance difference value threshold, and the physical flow coefficient is less than the preset physical flow coefficient threshold, an intuitive normal signal is generated; If the appearance difference value is greater than or equal to a preset appearance difference value threshold, or the physical flow coefficient is greater than or equal to a preset physical flow coefficient threshold, an intuitive deviation signal is generated; The non-use evaluation unit is used to perform physical non-intuitive evaluation feedback analysis on the received characteristic performance data, accompanied by further physical quality evaluation interactive analysis of the test samples, thereby helping to improve the accuracy and reliability of the physical quality detection of the test samples. The specific physical non-intuitive evaluation feedback analysis process is as follows: Divide the test sample into i sub-samples, where i is a natural number greater than zero, and obtain characteristic performance data of each sub-sample, wherein the characteristic performance data represents a characteristic value and an own characteristic index; In the embodiment of the present invention, the surface tension of each sub-sample is obtained, the maximum value and the minimum value of the surface tension are obtained, and the difference between the maximum value and the minimum value of the surface tension is set as the surface tension characteristic value. It should be noted that the larger the value of the surface tension characteristic value is, the greater the risk of non-intuitive characteristic abnormality of the detected sample is; In the embodiment of the present invention, the self-characteristic index indicates the number of sub-samples whose self-data deviate from the preset threshold, and the self-data includes specific gravity, viscosity, boiling point, etc. It should be noted that the self-characteristic index is an influencing parameter reflecting the risk of abnormal non-intuitive characteristics of the test sample; Discriminate the characteristic value of the table and the characteristic index of the self: If the table characteristic value is less than the preset table characteristic value and threshold, and the self-characteristic index is equal to zero, a normal evaluation signal is generated; If the table feature value is greater than or equal to the preset table feature value and threshold, or the self-characteristic index is not equal to zero, an evaluation abnormal signal is generated; Obtain intuitive normal signals, intuitive deviation signals, normal evaluation signals, and abnormal evaluation signals, and perform physical quality evaluation interactive analysis on the intuitive normal signals, intuitive deviation signals, normal evaluation signals, and abnormal evaluation signals: If an intuitive normal signal and an evaluation normal signal are generated, a physical qualified signal is obtained; If an intuitive normal signal and an abnormal evaluation signal or an intuitive deviation signal and a normal evaluation signal or an intuitive deviation signal and an abnormal evaluation signal are generated, a physical unqualified signal is obtained, and the physical qualified signal or the physical unqualified signal is sent to the quality inspection and analysis platform.

[0015] Embodiment 2: The chemical composition quality unit is used to retrieve basic composition data from the database and perform composition deviation verification feedback analysis on the basic composition data to determine whether the chemical quality of the test sample is qualified, so as to provide data support for subsequent analysis. The specific composition deviation verification feedback analysis process is as follows: The basic component data of the test sample is obtained, and the basic component data includes a component deviation value and a component pollution index. The component deviation value and the component pollution index are compared and analyzed with a preset component deviation value threshold and a preset component pollution index threshold. The number of component deviation values ​​and component pollution indexes that are greater than or equal to the preset component deviation value threshold and the preset component pollution index threshold is set as a chemical analysis index, and the chemical analysis index is discriminated: If the chemical analysis index is equal to zero, a component acceptance signal is generated; If the chemical analysis index is not equal to zero, a component failure signal is generated; In the embodiment of the present invention, the components of the test sample are detected based on chemical analysis technology, which includes chromatography, gas chromatography, liquid chromatography, etc., to obtain the component type and content of the test sample, compare and analyze the content corresponding to the component type of the test sample with the preset content, and set the number of deviations of the content corresponding to the component type of the test sample from the preset content as the component deviation value. It should be noted that the larger the value of the component deviation value, the greater the risk of quality abnormality of the test sample; In the embodiment of the present invention, the pH value of the test sample is obtained, and the pH value of the test sample is compared and analyzed with the preset pH value range, and the portion of the pH value of the test sample that deviates from the preset pH value range is set as the component contamination index. It should be noted that the component contamination index is an influencing parameter that reflects the contamination risk of the test sample; Obtain physical qualified signals, physical unqualified signals, component qualified signals, and component unqualified signals, and perform interactive analysis: If a physical qualified signal and a component qualified signal are generated, a quality stable signal is obtained; If a physical qualified signal and a component unqualified signal or a physical unqualified signal and a component qualified signal or a physical unqualified signal and a component unqualified signal are generated, a quality risk signal is obtained, and a quality stability signal or a quality risk signal is sent to a display response unit. After receiving the quality stability signal or the quality risk signal, the display response unit immediately performs a preset warning operation corresponding to the quality stability signal or the quality risk signal, so as to intuitively understand the quality test result of the test sample; When the evaluation and analysis unit is used to respond to the quality stability signal, the use effect data of the test sample is collected for quality verification evaluation feedback analysis, which helps to improve the comprehensiveness of the quality detection angle of the test sample, and at the same time helps to improve the quality detection reliability and effectiveness of the test sample, and helps to further verify and feedback the quality analysis results of the test sample to reduce the error risk of the entire test sample quality analysis. The specific quality verification evaluation feedback analysis process is as follows: Obtaining use effect data of the test sample, the use effect data including a decontamination deviation value and a use evaluation value, wherein the reflectivity change value of the stained cloth before and after washing is obtained by testing the sample based on the artificial cotton cloth detection method, the reflectivity change value of the stained cloth before and after washing is set as the decontamination floating value, and the part of the decontamination floating value that is less than a preset decontamination floating value threshold is set as the decontamination deviation value; The residual area of ​​the stained cloth after washing is obtained, and the residual area of ​​the stained cloth after washing is compared with the preset residual area, and the portion of the residual area of ​​the stained cloth after washing that is larger than the preset residual area is set as the use evaluation value. It should be noted that the use evaluation value is an influencing parameter that reflects the use effect of the test sample; Compare and analyze the decontamination deviation value and the usage evaluation value with the preset decontamination deviation value threshold and the preset usage evaluation value threshold: If the decontamination deviation value is less than the preset decontamination deviation value threshold, and the usage evaluation value is less than the preset usage evaluation value threshold, a usage compliance signal is generated; If the decontamination deviation value is greater than or equal to the preset decontamination deviation value threshold, or the usage evaluation value is greater than or equal to the preset usage evaluation value threshold, a usage failure signal is generated, and the usage compliance signal or the usage failure signal is sent to the display response unit. After receiving the usage compliance signal or the usage failure signal, the display response unit immediately performs the preset warning operation corresponding to the usage compliance signal or the usage failure signal, which helps to improve the reliability and effectiveness of the quality detection of the test samples, and helps to further verify and feedback the quality analysis results of the test samples, so as to reduce the risk of error in the quality analysis of the entire test samples; In summary, the present invention preliminarily performs quality analysis from the perspectives of physical detection and chemical detection of the test sample, that is, performs analysis from two points of view, intuitive and non-intuitive, from the perspective of physical detection, that is, performs intuitive physical feature detection and analysis on the physical appearance data of the test sample, so as to preliminarily understand whether the physical quality of the test sample is qualified, and performs physical non-intuitive evaluation feedback analysis on the characteristic performance data from a non-intuitive perspective, so as to further judge the physical quality of the test sample, and performs interactive analysis of physical quality evaluation in a progressive manner of information, thereby helping to improve the accuracy and reliability of physical quality detection of the test sample; And by conducting component deviation verification and feedback analysis on the basic component data from the perspective of chemical testing, it is possible to determine whether the chemical quality of the test samples is qualified. At the same time, the overall quality of the test samples is analyzed by integrating the physical and chemical test results, so as to determine whether the quality of the test samples is up to standard by non-usage methods, and to conduct in-depth quality testing and analysis from the perspective of usage effects, that is, conducting quality verification, evaluation and feedback analysis on the usage effect data of the test samples, which helps to improve the comprehensiveness of the quality testing perspective of the test samples, and at the same time helps to improve the reliability and effectiveness of the quality testing of the test samples, and helps to further verify and feedback the quality analysis results of the test samples to reduce the risk of error in the quality analysis of the entire test samples.

[0016] The threshold is set to facilitate comparison. The threshold depends on the amount of sample data and the number of bases set by technicians in this field for each set of sample data. It does not affect the proportional relationship between the parameter and the quantized value. The size of the coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the coefficient depends on the amount of sample data and the preliminary setting of the corresponding operating coefficient for each set of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0017] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. The cleaning agent quality detection and analysis system based on artificial intelligence is characterized by: It includes a quality inspection and analysis platform, a database, a physical evaluation unit, a non-use evaluation unit, a chemical composition quality unit, a use evaluation and analysis unit, and a display response unit; The quality inspection and analysis platform is used to retrieve the physical appearance data and characteristic performance data of the cleaning agent to be inspected from the database, and send the physical appearance data and characteristic performance data to the physical evaluation unit and the non-use evaluation unit respectively; The physical evaluation unit is used to perform intuitive physical feature detection and analysis on the received physical appearance data, compare and analyze the obtained appearance difference value and physical flow coefficient, and obtain an intuitive normal signal or an intuitive deviation signal; The non-use evaluation unit is used to perform physical non-intuitive evaluation feedback analysis on the received characteristic performance data, perform discrimination processing on the obtained table characteristic value and the own characteristic index, obtain the evaluation normal signal or the evaluation abnormal signal, and perform physical quality evaluation interactive analysis on the intuitive normal signal, the intuitive deviation signal, the evaluation normal signal and the evaluation abnormal signal, and obtain the physical qualified signal or the physical unqualified signal; The chemical composition quality unit is used to retrieve basic composition data from the database, conduct composition deviation verification feedback analysis on the basic composition data, perform discrimination processing on the obtained chemical analysis index, and obtain a qualified component signal or a failed component signal; Interactively analyze physical qualified signals, physical unqualified signals, component qualified signals, and component unqualified signals to obtain quality stability signals or quality risk signals; When the usage evaluation and analysis unit is used to respond to the quality stability signal, it collects the usage effect data of the test samples for quality verification evaluation feedback analysis to obtain a usage compliance signal or a usage non-compliance signal.

2. The cleaning agent quality detection and analysis system based on artificial intelligence according to claim 1 is characterized in that: The intuitive physical feature detection and analysis process of the physical evaluation unit is as follows: The cleaning agent to be tested is set as a test sample, and physical appearance data of the test sample is collected, wherein the physical appearance data includes an appearance characteristic image and a physical flow coefficient; The appearance feature image is compared and analyzed with the standard appearance feature image corresponding to the test sample to obtain the difference value between the appearance feature image and the standard appearance feature image corresponding to the test sample, and the difference value between the appearance feature image and the standard appearance feature image corresponding to the test sample is set as the appearance difference value.

3. The cleaning agent quality detection and analysis system based on artificial intelligence according to claim 2 is characterized in that: The physical flow coefficient represents the time duration corresponding to the deviation of the cleaning agent flow rate of the test sample from the set cleaning agent flow rate range under the set temperature and load; The appearance difference value and the physical flow coefficient are compared and analyzed with the preset appearance difference value threshold and the preset physical flow coefficient threshold that are internally recorded and stored, so as to obtain an intuitive normal signal or an intuitive deviation signal.

4. The cleaning agent quality detection and analysis system based on artificial intelligence according to claim 1 is characterized in that: The physical non-intuitive evaluation feedback analysis process of the non-use evaluation unit is as follows: Divide the test sample into i sub-samples, where i is a natural number greater than zero, and obtain characteristic performance data of each sub-sample, wherein the characteristic performance data represents a characteristic value and an own characteristic index; The surface tension of each sub-sample is obtained, the maximum value and the minimum value of the surface tension are obtained, and the difference between the maximum value and the minimum value of the surface tension is set as the surface tension characteristic value; The self-characteristic index indicates the number of sub-samples whose self-data deviate from the preset threshold. The self-data includes specific gravity, viscosity, and boiling point.

5. The cleaning agent quality detection and analysis system based on artificial intelligence according to claim 4 is characterized in that: Discriminate the characteristic value of the table and the characteristic index of the self: If the table characteristic value is less than the preset table characteristic value and threshold, and the self-characteristic index is equal to zero, a normal evaluation signal is generated; If the table feature value is greater than or equal to the preset table feature value and threshold, or the self-characteristic index is not equal to zero, an evaluation abnormal signal is generated; Perform physical quality evaluation interactive analysis on the intuitive normal signal, intuitive deviation signal, evaluation normal signal and evaluation abnormal signal: if the intuitive normal signal and the evaluation normal signal are generated, a physical qualified signal is obtained; if the intuitive normal signal and the evaluation abnormal signal or the intuitive deviation signal and the evaluation normal signal or the intuitive deviation signal and the evaluation abnormal signal are generated, a physical unqualified signal is obtained.

6. The cleaning agent quality detection and analysis system based on artificial intelligence according to claim 1 is characterized in that: The component deviation verification feedback analysis process of the chemical component quality unit is as follows: Obtain basic component data of the test sample, the basic component data including a component deviation value and a component contamination index, compare and analyze the component deviation value and the component contamination index with a preset component deviation value threshold and a preset component contamination index threshold, set the number of component deviation values ​​and component contamination indexes that are greater than or equal to the preset component deviation value threshold and the preset component contamination index threshold as a chemical analysis index, and perform discrimination processing on the chemical analysis index to obtain a component qualified signal or a component unqualified signal; Obtain the component type and content of the test sample, compare and analyze the content corresponding to the component type of the test sample with the preset content, and set the number of deviations of the content corresponding to the component type of the test sample from the preset content as the component deviation value; Obtaining the pH value of the test sample, and comparing and analyzing the pH value of the test sample with a preset pH value range, and setting the portion of the pH value of the test sample that deviates from the preset pH value range as a component contamination index; Physical qualified signals, physical unqualified signals, component qualified signals, and component unqualified signals are obtained, and interactive analysis is performed to obtain quality stability signals or quality risk signals.

7. The cleaning agent quality detection and analysis system based on artificial intelligence according to claim 1 is characterized in that: The quality verification evaluation feedback analysis process using the evaluation analysis unit is as follows: Obtaining use effect data of the test sample, the use effect data including a decontamination deviation value and a use evaluation value, wherein the reflectivity change value of the stained cloth before and after washing is obtained by testing the sample based on the artificial cotton cloth detection method, the reflectivity change value of the stained cloth before and after washing is set as the decontamination floating value, and the part of the decontamination floating value that is less than a preset decontamination floating value threshold is set as the decontamination deviation value; Obtaining the residual area of ​​the stained cloth after washing, and comparing the residual area of ​​the stained cloth after washing with a preset residual area, and setting the portion of the residual area of ​​the stained cloth after washing that is larger than the preset residual area as a usage evaluation value; The decontamination deviation value and the usage evaluation value are compared and analyzed with the preset decontamination deviation value threshold and the preset usage evaluation value threshold to obtain a usage compliance signal or a usage non-compliance signal.

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