Method and system for testing washing performance of electric washing machine

Abstract

The invention discloses a method and system for testing the cleaning performance of an electric washing machine, and relates to the field of washing machine tests.The main scheme is that the method comprises the steps that standard original cloth made of different materials is selected to prepare polluted cloth, and original data are collected; washing the polluted cloth by using different washing modes of the washing machine, and collecting washing data; respectively inputting data in the operation data and the washing data into corresponding intelligent calculation models, and obtaining a cleaning rate set, a wear rate set and a comprehensive energy efficiency ratio set of different washing modes through the intelligent calculation models; evaluating evaluation grades of different washing modes, and calculating to obtain a comprehensive score of the washing machine; generating a comprehensive evaluation report; the wide applicability of the test result is ensured, the multi-dimensional quantitative evaluation of the washing machine cleaning performance is realized, the scientificity and credibility of the test result are improved, and comprehensive performance reference information is provided for users.

Description

Technical Field

[0001] The present invention relates to the technical field of washing machine testing, and in particular to a method and system for testing the cleaning performance of an electric washing machine. Background Art

[0002] As an indispensable household appliance in modern homes, electric washing machines have become widely popular and have profoundly changed the way people wash their clothes. With the continuous advancement of technology and the increasing diversification of consumer demands, electric washing machines have achieved significant developments in functionality, performance, and intelligence.

[0003] In household use, electric washing machines improve laundry efficiency and save manpower. As consumers' environmental awareness increases, energy-saving and water-saving washing machines are becoming more and more popular, becoming a new trend in market development. The promotion of environmental protection policies and the increasing tension of energy resources will prompt the washing machine industry to further develop energy-saving and water-saving technologies. In order to meet these requirements, the testing methods for washing machines are becoming more mature.

[0004] However, there are still some defects in the existing testing methods, such as:

[0005] Test samples are often relatively simple and lack comprehensive coverage of clothes of different materials, resulting in the test results not accurately reflecting the cleaning effect of the washing machine on clothes of various materials.

[0006] The data collection is not comprehensive enough, ignoring the operating data of the washing machine in different modes and the actual washing data of the clothes after washing, which limits the accuracy and reliability of the test results.

[0007] Insufficient data processing and analysis, usually lack of data standardization and outlier removal, leads to uneven data quality, affects the accuracy of subsequent analysis, and makes it difficult to conduct a comprehensive and in-depth evaluation of the washing machine's cleaning performance.

[0008] The washing machine cleaning performance test lacks systematic evaluation and analysis of different washing modes, making it impossible to comprehensively compare and evaluate the advantages and disadvantages of washing machines in various modes, making it difficult to provide comprehensive performance evaluations and improvement suggestions; it is not conducive to users making reasonable purchasing decisions. Summary of the Invention

[0009] (1) Technical problems solved

[0010] In response to the shortcomings of the existing technology, the present invention provides a method for testing the cleaning performance of an electric washing machine, which at least solves the problem in the existing technology that there is a lack of systematic evaluation and analysis of different washing modes, and it is impossible to comprehensively compare and evaluate the advantages and disadvantages of washing machines in various modes.

[0011] (2) Technical solution

[0012] To achieve the above objectives, the present invention is implemented through the following technical solutions: A method for testing the cleaning performance of an electric washing machine, comprising:

[0013] Step 1: Select standard original fabrics of different materials, contaminate them with contaminated liquid to prepare contaminated fabrics, and collect the original data of the contaminated fabrics;

[0014] Step 2: In a test environment, use different washing modes of a washing machine to wash the contaminated cloth, and collect the operating data of the washing machine in different washing modes and the washing data of the contaminated cloth after washing;

[0015] Step 3: Standardize the collected data, remove abnormal data, and perform preprocessing;

[0016] Step 4: Input the pre-processed operation data and washing data into the corresponding intelligent calculation model respectively, and obtain the cleaning rate set, wear rate set and comprehensive energy efficiency ratio set of different washing modes through the intelligent calculation model;

[0017] Step 5: Input the cleaning rate set, wear rate set, and comprehensive energy efficiency ratio set of different washing modes into the mode evaluation model, and output the evaluation level of different washing modes of the washing machine;

[0018] Step 6: Perform a comprehensive analysis of the cleaning rate set, wear rate set, and comprehensive energy efficiency ratio set of different washing modes to obtain a comprehensive score for the washing machine;

[0019] Step 7: Generate a comprehensive evaluation report of the washing machine based on the analysis results of steps 5 and 6.

[0020] In the preferred embodiment of the above-mentioned method for testing the cleaning performance of an electric washing machine, in step one, the types of contaminated liquid include at least carbon black oil contaminated liquid, protein contaminated liquid and sebum contaminated liquid; the standard original cloth of each material needs to be prepared into contaminated cloth of corresponding contamination type using different types of contaminated liquids, and the corresponding original data is collected.

[0021] In the preferred embodiment of the above-mentioned method for testing the cleaning performance of an electric washing machine, after multiple washing operations are performed on contaminated cloths contaminated with different types of contaminated liquids under the same mode, the obtained data are analyzed and calculated by an intelligent computing model to obtain corresponding multiple cleaning rates, wear rates and comprehensive energy efficiency ratios, which constitute a cleaning rate set, a wear rate set and a comprehensive energy efficiency ratio set respectively.

[0022] In the preferred embodiment of the above-mentioned method for testing the cleaning performance of an electric washing machine, in step five, the mode evaluation model can respectively calculate the average values of multiple parameters in the cleaning rate set, the wear rate set and the comprehensive energy efficiency ratio set, and the calculation results are respectively used as the cleaning rate evaluation value, the fabric wear evaluation value and the comprehensive energy efficiency ratio evaluation value; and compare the cleaning rate evaluation value, the fabric wear evaluation value and the comprehensive energy efficiency ratio evaluation value with the corresponding evaluation threshold value to determine the evaluation level of different indicators in each washing mode.

[0023] In the preferred embodiment of the above-mentioned method for testing the cleaning performance of an electric washing machine, the method for determining the evaluation level of different indicators in each washing mode is as follows:

[0024] Preset the cleaning rate interval threshold, wear rate interval threshold and comprehensive energy efficiency ratio interval threshold for different washing modes;

[0025] The cleaning rate evaluation values of different washing modes are compared with the cleaning rate interval thresholds of the corresponding modes. If the cleaning rate evaluation value is lower than the minimum value of the cleaning rate interval threshold, it means that the cleaning rate of the corresponding mode is unqualified; if the cleaning rate evaluation value is within the value range of the cleaning rate interval threshold, it means that the cleaning rate of the corresponding mode is qualified; if the cleaning rate evaluation value is greater than the maximum value of the cleaning rate interval threshold, it means that the cleaning rate of the corresponding mode is excellent;

[0026] The fabric wear evaluation values of different washing modes are compared with the wear rate interval thresholds of the corresponding modes. If the fabric wear evaluation value is lower than the minimum value of the wear rate interval threshold, it means that the fabric wear of the corresponding mode is unqualified; if the fabric wear evaluation value is within the value range of the wear rate interval threshold, it means that the wear rate of the corresponding mode is qualified; if the fabric wear evaluation value is greater than the maximum value of the wear rate interval threshold, it means that the wear rate of the corresponding mode is excellent;

[0027] The comprehensive energy efficiency ratio evaluation values of different washing modes are compared with the comprehensive energy efficiency ratio interval thresholds of the corresponding modes. If the comprehensive energy efficiency ratio evaluation value is lower than the minimum value of the comprehensive energy efficiency ratio interval threshold, it means that the comprehensive energy efficiency ratio of the corresponding mode is unqualified; if the comprehensive energy efficiency ratio evaluation value is within the value range of the comprehensive energy efficiency ratio interval threshold, it means that the comprehensive energy efficiency ratio of the corresponding mode is qualified; if the comprehensive energy efficiency ratio evaluation value is greater than the maximum value of the comprehensive energy efficiency ratio interval threshold, it means that the comprehensive energy efficiency ratio of the corresponding mode is excellent.

[0028] In the preferred embodiment of the above-mentioned method for testing the cleaning performance of an electric washing machine, the method for obtaining the comprehensive score of the washing machine is:

[0029] By inputting the cleaning rate evaluation value, fabric wear evaluation value and comprehensive energy efficiency ratio evaluation value of different washing modes into the comprehensive scoring model for analysis, the comprehensive scoring model can output a comprehensive score of the washing machine.

[0030] In the preferred embodiment of the above-mentioned method for testing the cleaning performance of an electric washing machine, the cleaning rate can be output by inputting the data in the operation data and the washing data into the cleaning rate intelligent calculation model, and the formula based on it is as follows:

[0031]

[0032] Among them, η1 represents the cleaning rate; R fi Indicates the reflectivity of the contaminated cloth after washing; R in Indicates the reflectivity of the contaminated cloth before washing; R max represents the theoretical maximum reflectivity; T represents the washing time; W represents the water temperature; M represents the mechanical index of the washing machine; C represents the pollutant type coefficient; C represents the water temperature; ref represents the reference pollutant coefficient; б represents the experimental fitting attenuation coefficient; β represents the mechanical inhibition coefficient; γ represents the smoothing coefficient; k represents the synergy coefficient;

[0033] By inputting the data from the operating data and the washing data into the wear rate intelligent calculation model, the wear rate can be output based on the following formula:

[0034]

[0035] Wherein, η2 represents the wear rate in the corresponding mode; CI and DI represent the mass of fluff and fiber separated during the washing process in the corresponding mode, respectively; PI represents the sum of the masses of all contaminated cloths in the corresponding mode; N represents the number of contaminated cloths in the corresponding mode; RI represents the sum of the reflectivities of all contaminated cloths before washing in the corresponding mode; RL represents the sum of the reflectivities of all contaminated cloths after washing in the corresponding mode; T represents the washing time; FI represents the washing water volume; W represents the water temperature; and JI represents the friction coefficient during the washing process.

[0036] In the preferred embodiment of the above-mentioned method for testing the cleaning performance of an electric washing machine, the comprehensive energy efficiency ratio can be output by inputting the operating data and the washing data into the comprehensive energy efficiency ratio intelligent calculation model. The method is as follows:

[0037] The dynamic wash gain coefficient of the washing machine in the corresponding mode is calculated through the comprehensive energy efficiency ratio intelligent calculation model. The formula is as follows:

[0038]

[0039] Wherein, DS represents the dynamic washing gain coefficient in the corresponding mode; DR represents the mean reflectivity of the contaminated cloth after washing; DI represents the mean reflectivity of the contaminated cloth before washing; DO represents the baseline reflectivity of the contaminated cloth; ε represents the contamination residual correction factor;

[0040] The time efficiency factor of the washing machine in the corresponding mode is calculated using the comprehensive energy efficiency ratio intelligent calculation model. The formula is as follows:

[0041]

[0042] Where TX represents the time efficiency factor of the corresponding mode, t0 represents the standard mode duration of the corresponding mode; ta represents the actual mode duration; t max Indicates the longest allowed duration for similar models;

[0043] The energy consumption density index of the washing machine in the corresponding mode is calculated using the comprehensive energy efficiency ratio intelligent calculation model. The formula is as follows:

[0044]

[0045] Where E represents the energy consumption density index of the corresponding mode; wc represents the driving energy consumption of the corresponding mode; wh represents the heating energy consumption of the corresponding mode; m represents the washing capacity of the corresponding mode; Ψ represents the heating efficiency coefficient;

[0046] The water resource utilization rate of the washing machine in the corresponding mode is calculated using the comprehensive energy efficiency ratio intelligent calculation model. The formula is as follows:

[0047]

[0048] Among them, Q represents the water resource utilization rate of the corresponding mode; Qa represents the actual water consumption of the corresponding mode; Qs represents the standard water consumption of the corresponding mode; ρ represents the water hardness correction index;

[0049] The washing stability coefficient of the washing machine in the corresponding mode is calculated using the comprehensive energy efficiency ratio intelligent calculation model based on the following formula:

[0050]

[0051] Where S represents the cleaning stability coefficient of the corresponding mode; σ represents the standard deviation of the multiple cleaning rate of the corresponding mode; μ represents the average value of the multiple cleaning rate of the corresponding mode;

[0052] The environmental coupling coefficient of the washing machine in the corresponding mode is calculated using the comprehensive energy efficiency ratio intelligent calculation model. The formula is as follows:

[0053]

[0054] Where K is the environmental coupling coefficient; ΔT is the ambient temperature difference; RH is the relative humidity deviation; π is a constant;

[0055] The dynamic washing gain coefficient DS, time efficiency factor TX, energy consumption density index E, water resource utilization rate Q, washing stability coefficient S, and environmental coupling coefficient K of the same mode are input into the comprehensive energy efficiency ratio intelligent calculation model to calculate the comprehensive energy efficiency ratio of the washing machine in the corresponding mode. The formula is as follows:

[0056]

[0057] It should be noted that η3 represents the comprehensive energy efficiency ratio of the corresponding mode.

[0058] In the preferred embodiment of the above-mentioned method for testing the cleaning performance of an electric washing machine, the cleaning rate evaluation values, fabric wear evaluation values, and comprehensive energy efficiency ratio evaluation values of different washing modes are input into a comprehensive scoring model for analysis. The comprehensive scoring model can output a comprehensive score for the washing machine; the formula based on this is as follows:

[0059]

[0060] Among them, HR represents the comprehensive score; η1 i represents the cleaning rate of the i-th washing mode; η2 represents the wear rate of the i-th washing mode; η3 i represents the comprehensive energy efficiency ratio of the i-th washing mode; ω i represents the weight coefficient of the sum of the cleaning rate, wear rate and comprehensive energy efficiency ratio in the i-th washing mode, and i represents the serial number of the washing mode, and its value is a positive integer.

[0061] (3) Beneficial effects

[0062] The present invention provides a method for testing the cleaning performance of an electric washing machine, which has the following beneficial effects:

[0063] (1) By selecting raw fabrics of different materials and preparing contaminated fabrics, a variety of representative test samples are provided for testing, ensuring the wide applicability of the test results. At the same time, comprehensive collection of operation data and washing data provides rich and accurate data support for subsequent performance evaluation, which can more comprehensively and accurately reflect the cleaning performance of the washing machine in different washing modes. This solves the problems of insufficient samples and data in existing methods, a single test sample that cannot fully reflect the washing machine's cleaning ability for clothes of different materials, and incomplete data collection that cannot accurately evaluate the performance of the washing machine in various modes.

[0064] (2) Data standardization and outlier removal ensure the standardization and accuracy of the data, laying a reliable data foundation for subsequent analysis. The application of intelligent computing models can deeply explore the complex relationships between data, accurately calculate the key indicators such as the cleaning rate, wear rate and comprehensive energy efficiency ratio under different washing modes, realize the multi-dimensional quantitative evaluation of the washing machine's cleaning performance, improve the scientificity and credibility of the test results, and overcome the shortcomings of traditional data processing and analysis methods. The data processing method is relatively simple, ignoring the standardization and outlier processing of the data, resulting in limited accuracy of the test results, lack of effective data mining and analysis methods, and inability to fully utilize the collected data.

[0065] (3) The mode evaluation model can comprehensively consider and rate the different washing modes of washing machines based on multiple factors such as cleaning rate, wear rate and comprehensive energy efficiency ratio, and clearly point out the advantages and disadvantages of each mode. The comprehensive score quantifies the washing performance of the washing machine as a whole, providing users with an intuitive basis for performance comparison, making it easier for users to choose the appropriate washing machine product according to their needs. It makes up for the shortcomings of existing testing methods in systematic evaluation and comprehensive analysis, avoiding the situation where it is difficult to comprehensively compare and evaluate the advantages and disadvantages of washing machines in various modes and unable to provide users with a comprehensive performance reference.

[0066] (4) The comprehensive evaluation report integrates key information such as the evaluation level and comprehensive score of different washing modes, and presents it to users in a clear and intuitive manner, allowing users to quickly understand the performance characteristics of the washing machine, providing a strong basis for product improvement and consumer choice, and solving the problem of non-intuitive and incomplete test results. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Figure 1 The present invention is a schematic diagram of the steps of a method for testing the cleaning performance of an electric washing machine. DETAILED DESCRIPTION

[0068] The following will provide a clear and complete description of 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. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0069] Example 1

[0070] See also Figure 1 The present invention provides a method for testing the cleaning performance of an electric washing machine, comprising:

[0071] Step 1: Select standard original cloth of different materials, contaminate it with contaminated liquid to prepare contaminated cloth, and collect the original data of the contaminated cloth.

[0072] Step 101: Choose standard raw fabrics of various materials, such as cotton, silk, polyester, and commonly used blended fabrics on the market.

[0073] Step 102: Select different types of contamination liquids, such as carbon black oil contamination liquid, which is a mixture of hardened beef tallow oil, liquid paraffin and carbon black; protein contamination liquid, which is composed of fresh eggs, whole milk powder and gum arabic; sebum contamination liquid, which is composed of palmitic acid, coconut oil and liquid paraffin; in addition to the above contamination liquids, other types of contamination liquids can also be added to increase the test contamination categories and enhance the persuasiveness. The contamination liquid can be prepared by yourself according to the formula of existing data or purchased as a finished product on the market.

[0074] Step 103: Different types of standard original fabrics are contaminated with the above-mentioned contamination liquid respectively; the method of contaminating the standard original fabric can be coating-drying or soaking-drying under a constant environment. It should be noted that the constant environment selected for the contamination environment must remain unchanged, and the method of contaminating the original fabric must be consistent to reduce errors.

[0075] Step 104: After the contaminated original cloth is dried, it is cut and a serial number mark is made on the same position of each piece of contaminated cloth after cutting, such as by sewing the serial number cloth at the corners of the contaminated cloth. Then, it is ironed to keep it flat and matte, and then left to dry to form the contaminated cloth. The original data of each piece of contaminated cloth is collected. It should be noted that the contaminated cloth needs to be of different sizes to correspond to the different washing modes of the washing machine.

[0076] It should be noted that when marking the contaminated cloths with different pollutants with serial numbers, it is necessary to number the contaminated cloths of different materials and different types of contaminated liquids. For example, uppercase letters A, B, C, D, E, etc. can be used to indicate the material number of the contaminated cloth, such as A corresponds to cotton cloth, B corresponds to silk cloth, C corresponds to polyester fiber cloth, etc.; lowercase letters a, b, c, d, etc. are used to indicate the type of pollutant, such as a corresponds to carbon black oil contaminated liquid, b corresponds to protein contaminated liquid, c corresponds to sebum contaminated liquid, etc.; Arabic numerals 001, 002, 003, ..., 999, etc. can be used to indicate the digital number of the contaminated cloth, that is, contaminated cloth No. 001, etc.; for example, Aa001 can be represented as a contaminated cloth with the material being cotton cloth, the pollutant being carbon black oil contaminated liquid, and the digital number being 001.

[0077] In this step, by selecting standard original cloths of various materials and different types of contaminated liquids, the diversity and representativeness of the test samples are ensured, which can more comprehensively evaluate the cleaning performance of the washing machine on clothes of different materials under different pollutants, making the test results more universal and reliable, and avoiding the problem that the test samples in the existing test methods are single and cannot fully reflect the cleaning ability of the washing machine for clothes of different materials; by standardizing the contaminated cloth, the non-standard contamination process in the existing test methods is avoided, and the inconsistency of the environment and methods leads to differences in contaminated cloths in different batches, resulting in high test errors, thereby improving the accuracy and reliability of the test results.

[0078] Step 2: In a test environment, use different washing modes of a washing machine to wash the contaminated cloth, and collect the operation data of the washing machine in different washing modes and the washing data of the contaminated cloth after washing.

[0079] Step 201: Select a space as a test environment, monitor real-time data such as temperature, humidity, current, voltage, water quality, and water temperature in the test environment, and perform intelligent regulation to keep the errors of various environmental factors in the test environment within a certain range, such as temperature error not exceeding 1%, humidity error not exceeding 5%, voltage error not exceeding 1%, current error not exceeding 0.015%, water temperature error not exceeding 0.5%, and the content of each element in water not exceeding 0.5%. The regulation of temperature and humidity can be achieved through precise control of constant temperature and humidity equipment to ensure stable environmental conditions. The regulation of current and voltage can use high-precision power supply equipment combined with PID control algorithm to adjust the power output in real time. The regulation of water quality and water temperature can be achieved through a water tank circulation system and a constant temperature device to maintain the stability of water quality and water temperature.

[0080] Step 202: Select various washing modes of the washing machine in turn, such as quick wash mode, standard wash mode, silk wash mode and large piece washing mode, etc., and put in the corresponding material, size and quantity of contaminated cloths according to the instructions for use of the washing machine; for example, in quick wash mode, place 5-8 pieces of clothing and standard laundry detergent, etc., and compare the number of clothes with the contaminated cloths to ensure that the washing weight is less than or equal to the standard capacity, and then select quick wash mode for washing; other washing modes are based on the same principle, and you can select the appropriate material, quantity of contaminated cloths and the standard amount of laundry detergent to run.

[0081] Step 203: Collecting the operation data of the washing machine in each mode.

[0082] Step 204: Take out the contaminated cloth after washing, let it dry naturally, then lay it flat again, iron it until it is not shiny, and let it dry naturally, then collect the washing data of each contaminated cloth.

[0083] In this step, by precisely controlling the test environment, the washing machine is ensured to operate under stable and standard conditions, reducing the interference of environmental factors on the test results, improving the accuracy and reliability of the test results, making the test data more scientific and convincing, and able to truly reflect the performance of the washing machine in different washing modes; overcoming the fluctuations of various factors that affect the operating status and washing effect of the washing machine, leading to uncertainty and incomparability of the test results; through standardized processing and data collection of contaminated cloth after washing, the accuracy and consistency of the washing data are ensured, which can truly reflect the cleaning effect of the washing machine in different modes; and providing a reliable data basis for performance comparison between different washing machines.

[0084] Step 3: Standardize the collected data, remove abnormal data, and perform preprocessing.

[0085] Step 301: By using the Z-score standard deviation method to identify outliers that exceed the threshold, the mean μ and standard deviation σ of each factor parameter X are calculated, and extremely high energy consumption data points with Z = (x-μ) / σ>3 are eliminated. The factor parameter X can be the reflectivity of the contaminated cloth, the current during operation, the voltage value, etc.

[0086] Step 302: Perform normalization preprocessing on the collected data to eliminate the dimensions of different parameters and provide a basis for comprehensive calculation of parameters of different categories.

[0087] In this step, the Z-score standard deviation method is used to scientifically identify and eliminate outliers outside the normal range, ensuring the accuracy and reliability of the test data. This method, based on statistical principles, uses the mean and standard deviation of the data to determine whether a data point is abnormal. This method can effectively avoid the impact of individual extreme values on the overall test results, improving the credibility and stability of the test results. Normalization preprocessing then converts data of different dimensions and value ranges to the same scale, making the various parameters comparable and providing a reliable data foundation for subsequent comprehensive analysis and calculations. This helps to more accurately evaluate the performance of washing machines in different aspects, avoids errors caused by dimensional differences, and improves the scientific nature and accuracy of the test results.

[0088] Step 4: Input the pre-processed operation data and washing data into the corresponding intelligent calculation model respectively, and obtain the cleaning rate set, wear rate set and comprehensive energy efficiency ratio set of different washing modes through the intelligent calculation model.

[0089] Step 401: The raw data includes the reflectivity, theoretical maximum reflectivity, pollutant type coefficient, and reference pollutant coefficient of each contaminated cloth in different modes; the washing data includes the reflectivity of the contaminated cloth after washing in different modes; the operation data includes the washing time, water temperature, and mechanical force index of different modes; the data is input into the cleaning rate intelligent calculation model to calculate the cleaning rate of each contaminated cloth in the corresponding mode of the washing machine, and then the cleaning rates of all contaminated cloths in each mode are averaged as the average cleaning rate of the washing machine in the corresponding mode as the final mode cleaning rate of the corresponding mode, or multiple experiments are conducted in the same mode, and the average of the average cleaning rates is taken as the final mode cleaning rate of the corresponding mode; the formula for calculating the cleaning rate of each contaminated cloth is as follows:

[0090]

[0091] Among them, η1 represents the cleaning rate; R fi Indicates the reflectivity of the contaminated cloth after washing; R in Indicates the reflectivity of the contaminated cloth before washing; R max represents the theoretical maximum reflectivity; T represents the washing time; W represents the water temperature; M represents the mechanical index of the washing machine; C represents the pollutant type coefficient; C represents the water temperature; ref represents the reference pollutant coefficient; б represents the experimental fitting attenuation coefficient; β represents the mechanical inhibition coefficient; γ represents the smoothing coefficient; and k represents the synergy coefficient.

[0092] It should be noted that the reflectivity of the contaminated cloth before washing and the reflectivity of the contaminated cloth after washing can be measured by using a spectrophotometer; the theoretical maximum reflectivity can be measured multiple times using the same batch of cloth and the average value can be taken as the standard value, or the material standard value of the corresponding cloth can be obtained by looking up the table; the washing time can be recorded by a timer to record the actual running time; the vibration frequency and amplitude of the drum can be measured by an acceleration sensor, and the kinetic energy integral can be calculated using the formula As a mechanical force index; the pollutant type coefficient can be determined according to the type of polluted liquid, such as carbon black oil polluted liquid with a value of C = 1.3, sebum polluted liquid with a value of C = 1.5, protein polluted liquid with a value of C = 2.0, etc., and also refer to international standards; the reference pollutant coefficient can take a fixed value for standardized calculation, such as C ref =1; the attenuation coefficient, mechanical suppression coefficient, smoothing coefficient and synergy coefficient can be obtained by using nonlinear regression, such as the Levenberg-Marquardt algorithm, for example, б = 0.8, β = 0.02, γ = 0.1, k = 0.05.

[0093] It should be noted that in the above formula, Represents the reflectivity ratio term, which quantifies the pollutant removal effect through reflectivity. The power function б reflects the marginal decreasing effect, which is more in line with the actual physical laws and solves the problem that traditional linear ratios cannot describe the nonlinear washing process. It represents the synergistic term of time and water temperature. The synergistic effect of time and water temperature is described by logarithmic function. For example, high temperature shortens the effective reaction time. The square of mechanical force is introduced into the denominator. 2 Restrain the abuse of mechanical force, suppress energy waste caused by excessive vibration, and avoid the problem that traditional formulas ignore the negative impact of mechanical force on energy consumption; represents the pollutant correction term, limits the extreme influence of the pollutant coefficient through the quadratic term in the denominator, enhances robustness through the smoothing coefficient, and avoids the problem of poor accuracy caused by the simple weighting of pollutant types in traditional methods; this formula uses the power function (б), logarithmic function (ln) and quadratic term (γ·(CC ref ) 2 ) Accurately fit the actual physical process of washing, solve the problem that traditional technical linear models cannot describe marginal effects, and through multi-dimensional nonlinear coupling and dynamic correction mechanism, solve the core problem of traditional cleaning rate models ignoring mechanical energy consumption, pollutant specificity and synergistic effects.

[0094] Step 402: The raw data also includes the sum of the number and weight of contaminated cloths in different modes. The washing data also includes the mass of fluff and fiber separated during the washing process in the corresponding mode. The operation data also includes the washing time, washing water volume, water temperature, and friction coefficient during the washing process in the corresponding mode. The data is input into the wear rate intelligent calculation model to calculate the wear rate of each contaminated cloth in the corresponding mode of the washing machine as the mode wear rate of the washing machine in the corresponding mode. Alternatively, multiple experiments are conducted in the same mode and the average of the average wear rates is taken as the mode wear rate of the washing machine in the corresponding mode. The formula for calculating the wear rate is as follows:

[0095]

[0096] Wherein, η2 represents the average wear rate in the corresponding mode; CI and DI represent the mass of fluff and fiber separated during the washing process in the corresponding mode, respectively, which can be collected, dried and weighed by a filtering device and a screening device, respectively; PI represents the sum of the masses of all contaminated cloths in the corresponding mode; N represents the number of contaminated cloths in the corresponding mode; RI represents the sum of the reflectivity of all contaminated cloths before washing in the corresponding mode; RL represents the sum of the reflectivity of all contaminated cloths after washing in the corresponding mode; T represents the washing time; FI represents the washing water capacity, which can be obtained from the washing machine manual or actual measurement; W represents the water temperature; JI represents the friction coefficient during the washing process, which can be obtained from the washing machine manual or relevant standard documents.

[0097] It should be noted that in the above formula, The ratio of the mass of separated fluff and fiber to the mass of the contaminated cloth reflects the amount of fiber shed by the fabric during the washing process due to mechanical action. The sum of the mass of the contaminated cloth is used as a reference, so that this ratio can reflect the relative degree of mechanical damage. The larger the ratio, the more serious the mechanical damage to the fabric, and vice versa. This represents the washing conditions in different modes, reflecting their combined impact on the cleaning effect. By calculating the proportions of these conditions, their contribution to the cleaning effect can be comprehensively evaluated. For example, a longer wash time, a larger water volume, an appropriate wash mode, and a suitable temperature all improve cleaning results.

[0098] Step 403: The original data also includes the average reflectivity and baseline reflectivity of the contaminated cloth corresponding to different modes; the washing data also includes the average reflectivity of the contaminated cloth after washing corresponding to different modes; the operation data also includes the standard mode duration, actual mode duration, maximum allowed duration of similar models, mode driving energy consumption, mode heating energy consumption, mode washing capacity, mode standard water consumption and actual water consumption corresponding to different modes.

[0099] The data is input into the intelligent calculation model to calculate the dynamic wash gain coefficient of the washing machine in the corresponding mode. The formula is as follows:

[0100]

[0101] Among them, DS represents the dynamic cleaning gain coefficient in the corresponding mode; DR represents the mean reflectivity of the contaminated cloth after washing, which can be obtained by summing up the reflectivity of all contaminated cloths after washing in one washing mode and taking the average; DI represents the mean reflectivity of the contaminated cloth before washing, which can be obtained by summing up the reflectivity of all contaminated cloths before washing in one washing mode and taking the average; DO represents the baseline reflectivity of the contaminated cloth, which can be obtained by querying the data provided by the supplier; ε represents the contamination residual correction factor, which can be obtained through the data provided by the contaminated liquid supplier, or can be obtained by using nonlinear regression to distinguish the type of contaminated liquid, such as the Levenberg-Marquardt algorithm fitting. Here, the value can be 0.05-0.15, for example, ε = 0.12 is suitable for protein stains, and ε = 0.08 is suitable for carbon black stains.

[0102] It should be noted that in the above formula, Represents the reflectivity difference term, which is used to quantify the improvement in reflectivity of the contaminated cloth after washing; It represents the logarithmic correction term, which characterizes the difficulty of removing stubborn stains through a nonlinear function, and can solve the problem of insufficient sensitivity of traditional cleaning ratios for heavily contaminated cloths.

[0103] The data is input into the intelligent calculation model to calculate the time efficiency factor of the washing machine in the corresponding mode. The formula is as follows:

[0104]

[0105] Among them, TX represents the time efficiency factor of the corresponding mode, t0 represents the standard mode duration of the corresponding mode, which is read through the washing machine program setting value; ta represents the actual mode duration, which can be recorded by a high-precision timer; t max Indicates the longest allowed duration for similar models, which can be obtained from the manufacturer's production standard data.

[0106] It should be noted that in the above formula, the power function term and the exponential decay term e -0.01(ta-t0) , which can dynamically balance the relationship between washing speed and energy consumption, and solve the problem of inflated scores for short-term high-energy-consuming programs.

[0107] The data is input into the intelligent calculation model to calculate the energy consumption density index of the washing machine in the corresponding mode. The formula is as follows:

[0108]

[0109] Among them, E represents the energy consumption density index of the corresponding mode; wc represents the driving energy consumption of the corresponding mode, wh represents the heating energy consumption of the corresponding mode; m represents the washing capacity of the corresponding mode; Ψ represents the heating efficiency coefficient, which is obtained through the manufacturer's production standard data and can be taken as 0.85-0.93 here.

[0110] It should be noted that in the above formula, the motor energy consumption term It can be shown that the motor power consumption increases nonlinearly with the load, by introducing the heating energy consumption term Distinguish the energy efficiency characteristics of heating and non-heating models to avoid the "mixed energy consumption measurement distortion" problem in traditional solutions.

[0111] The data is input into the intelligent calculation model to calculate the water resource utilization rate of the washing machine in the corresponding mode. The formula is as follows:

[0112]

[0113] Among them, Q represents the water resource utilization rate of the corresponding mode; Qa represents the actual water consumption of the corresponding mode, which can be measured by an electromagnetic flowmeter; Qs represents the standard water consumption of the corresponding mode, which can be obtained by checking the national standard value; ρ represents the water hardness correction index, which is obtained by a TDS detector and generally ranges from 0.9 to 1.1.

[0114] The data is input into the intelligent calculation model to calculate the washing stability coefficient of the washing machine in the corresponding mode. The formula is as follows:

[0115]

[0116] Among them, S represents the cleaning stability coefficient of the corresponding mode; σ represents the standard deviation of the multiple cleaning rates of the corresponding mode, which can be obtained by calculating the standard deviation of the historical cleaning rates; μ represents the average value of the multiple cleaning rates of the corresponding mode, which can be obtained by calculating the average value of the historical cleaning rates.

[0117] The data is input into the intelligent calculation model to calculate the environmental coupling coefficient of the washing machine in the corresponding mode. The formula is as follows:

[0118]

[0119] Where K represents the environmental coupling coefficient; ΔT represents the ambient temperature difference, which can be obtained from the temperature control system records; RH represents the relative humidity deviation, which can be obtained by measuring the temperature sensor; and π represents a constant with a value of 3.14.

[0120] It should be noted that in the above formula, the cosine temperature change response is used to decay the coefficient from 1 to 0 when the temperature fluctuates by ±20°C. The linear humidity compensation is used to reduce the score by 1.5% for every 10% deviation of the humidity when it deviates from 65%, thereby realizing the equivalent mapping of laboratory data to actual usage scenarios and avoiding the problem of abnormal fluctuations in cleaning rate in high temperature and high humidity environments.

[0121] The dynamic washing gain coefficient DS, time efficiency factor TX, energy consumption density index E, water resource utilization rate Q, washing stability coefficient S, and environmental coupling coefficient K of the same mode are input into the intelligent calculation model to calculate the comprehensive energy efficiency ratio of the washing machine in the corresponding mode. The formula is as follows:

[0122]

[0123] It should be noted that η3 represents the comprehensive energy efficiency ratio of the corresponding mode. In the formula (Ds×TX), the cleaning effect is combined with the time efficiency to avoid the situation where only high cleaning rate is pursued while ignoring the time cost, or only shortening the time leads to insufficient cleaning, and the cleaning rate and time efficiency are balanced. For example, if the cleaning rate of a certain mode is increased by 20% but the time is extended by 30%, the score may be reduced through multiplication, solving the one-sided problems of "the cleaning rate is artificially high but the time is too long" or "the fast washing is not clean enough" in traditional tests. In the formula (E×Q), the consumption of comprehensive energy and water resources is considered. High energy consumption or high water consumption will reduce the overall score, promoting the coordinated optimization of water saving and energy saving. For example, if a certain mode saves water by 10% but increases energy consumption by 15%, the comprehensive score may decrease, avoiding the design of "taking money from Peter to pay Paul" in traditional technology; in the formula The sum of cleaning efficiency and time effectiveness is divided by the total resource consumption to measure the comprehensive performance output under unit resource input, which directly reflects "green performance". For example, if a certain mode has high cleaning efficiency but huge resource consumption, the ratio will be significantly reduced, guiding the design to optimize in the direction of "high output and low consumption". The formula (1+ln(S)) can compress the fluctuation range of S, improve the repeatability of test results, and prevent misjudgments caused by the accidental nature of a single test. The overall formula integrates six major factors: cleaning efficiency, time, energy consumption, water consumption, stability, and environment, breaking through the limitations of single parameter optimization. By dynamically balancing cleaning efficiency, resource consumption, and stability, and introducing environmental adaptive correction, it solves the problems of traditional testing methods that unilaterally pursue a single parameter while ignoring overall performance, disconnect between laboratory data and actual usage scenarios, large fluctuations in multiple test results leading to unreliable evaluation, and split optimization of energy and water resources. The conversion of multi-physical field parameters (mechanical, thermodynamic, and fluid) into quantifiable mathematical models provides a scientific basis for the green design and performance evaluation of washing machines.

[0124] Step 5: Input the cleaning rate set, wear rate set, and comprehensive energy efficiency ratio set of different washing modes into the mode evaluation model, and output the evaluation level of different washing modes of the washing machine.

[0125] Step 501: Calculate the average values of multiple parameters in the cleaning rate set, wear rate set and comprehensive energy efficiency ratio set respectively through the pattern evaluation model, and use the calculation results as the cleaning rate evaluation value, fabric wear evaluation value and comprehensive energy efficiency ratio evaluation value respectively.

[0126] Step 502: Preset the cleaning rate interval threshold, wear rate interval threshold, and comprehensive energy efficiency ratio interval threshold for different washing modes.

[0127] It should be noted that the cleaning rate interval threshold, wear rate interval threshold and comprehensive energy efficiency ratio interval threshold can refer to the existing national standards for washing machine performance testing. The standards may stipulate the minimum value and standard value that the cleaning rate of a certain level of washing machine should reach under specific test conditions. This value range can be used as the cleaning rate evaluation interval threshold.

[0128] Step 503: Compare the cleaning rate evaluation value, fabric wear evaluation value, and comprehensive energy efficiency ratio evaluation value with the corresponding evaluation thresholds to determine the evaluation level of different indicators in each washing mode, specifically:

[0129] The cleaning rate evaluation values of different washing modes are compared with the cleaning rate interval thresholds of the corresponding modes. If the cleaning rate evaluation value is lower than the minimum value of the cleaning rate interval threshold, it means that the cleaning rate of the corresponding mode is unqualified; if the cleaning rate evaluation value is within the value range of the cleaning rate interval threshold, it means that the cleaning rate of the corresponding mode is qualified; if the cleaning rate evaluation value is greater than the maximum value of the cleaning rate interval threshold, it means that the cleaning rate of the corresponding mode is excellent;

[0130] The fabric wear evaluation values of different washing modes are compared with the wear rate interval thresholds of the corresponding modes. If the fabric wear evaluation value is lower than the minimum value of the wear rate interval threshold, it means that the fabric wear of the corresponding mode is unqualified; if the fabric wear evaluation value is within the value range of the wear rate interval threshold, it means that the wear rate of the corresponding mode is qualified; if the fabric wear evaluation value is greater than the maximum value of the wear rate interval threshold, it means that the wear rate of the corresponding mode is excellent;

[0131] The comprehensive energy efficiency ratio evaluation values of different washing modes are compared with the comprehensive energy efficiency ratio interval thresholds of the corresponding modes. If the comprehensive energy efficiency ratio evaluation value is lower than the minimum value of the comprehensive energy efficiency ratio interval threshold, it means that the comprehensive energy efficiency ratio of the corresponding mode is unqualified; if the comprehensive energy efficiency ratio evaluation value is within the value range of the comprehensive energy efficiency ratio interval threshold, it means that the comprehensive energy efficiency ratio of the corresponding mode is qualified; if the comprehensive energy efficiency ratio evaluation value is greater than the maximum value of the comprehensive energy efficiency ratio interval threshold, it means that the comprehensive energy efficiency ratio of the corresponding mode is excellent.

[0132] In this step, through average value calculation, random fluctuations and outliers in the test data can be smoothed, so that the evaluation value can better reflect the actual performance level of the washing machine in different modes, improve the stability and credibility of the evaluation results, and avoid the problem that the evaluation results may be affected by accidental factors of a single test and are not stable and reliable based on the reference test results; the preset threshold provides a clear quantitative standard for the evaluation, so that the performance evaluation of different washing machines is comparable, and the washing rate, wear rate and comprehensive energy efficiency ratio of the washing machine can be accurately graded, ensuring the fairness and authority of the evaluation, and can intuitively reflect the performance of the washing machine in different modes, and intuitively show the advantages and disadvantages of the washing machine in different performance indicators, making it difficult for users to quickly understand the overall performance of the washing machine.

[0133] Step 6: Comprehensively analyze the cleaning rate set, wear rate set, and comprehensive energy efficiency ratio set of different washing modes to obtain a comprehensive score for the washing machine.

[0134] Step 601: Obtain the cleaning rate evaluation value, fabric wear evaluation value, and comprehensive energy efficiency ratio evaluation value from the calculation results of step 5, and input them as input parameters into a comprehensive scoring model for analysis; the comprehensive scoring model can output a comprehensive score for the washing machine based on the following formula:

[0135]

[0136] Among them, HR represents the comprehensive score; η1 i represents the cleaning rate of the i-th washing mode; η2 i represents the wear rate of the i-th washing mode; η3 i represents the comprehensive energy efficiency ratio of the i-th washing mode; ω i represents the weight coefficient of the sum of the cleaning rate, wear rate and comprehensive energy efficiency ratio in the i-th washing mode, and i represents the serial number of the washing mode, which is a positive integer and can be [1, n], where n is the total number of washing modes. For example, i=1 represents the quick wash mode, i=2 represents the standard wash mode, i=3 represents the large wash mode, and so on.

[0137] It should be noted that the weight coefficient ω under different washing modes i The value of can be adjusted according to the frequency of use of different washing modes. For example, if the washing is done 100 times, and the quick wash mode is 20 times, then the weight coefficient in the quick wash mode is 20 / 100*1=0.2. It can also be adjusted according to different test modes. i .

[0138] It should be noted that the comprehensive score is used to evaluate the comprehensive performance of the washing machine. The level of the washing machine can be evaluated by setting the comprehensive score standard threshold; the comprehensive scores of different washing machines can also be compared and ranked to generate a comprehensive ranking list of washing machines.

[0139] In this step, a comprehensive scoring model is used to integrate key performance indicators (KPIs) such as cleaning efficiency, wear rate, and overall energy efficiency ratio across different washing modes into a single, integrated score, comprehensively reflecting the overall performance of the washing machine across all modes. This scoring approach not only considers the performance of individual modes but also flexibly adjusts weighting factors based on wash mode frequency or other testing requirements, making the comprehensive score more tailored to actual usage scenarios and user priorities. For example, assigning a higher weight to a mode that is more frequently used in practice makes the evaluation results more representative and practical. This flexible weighting adjustment mechanism enhances the flexibility and targeting of the evaluation, better meeting the needs of different user groups and market segments, and strengthening the credibility and reference value of the evaluation results, making them more scientific and reasonable. Furthermore, the comprehensive score facilitates direct comparison and ranking of different washing machines, providing consumers with a clear basis for purchasing decisions and promoting technological advancement in comprehensive performance improvement within the washing machine industry. It also avoids the problem of a lack of unified and comprehensive washing machine performance evaluation standards, which hinders consumers' comprehensive understanding of product pros and cons and makes them easily influenced by single performance indicators or brand promotions when choosing a washing machine.

[0140] Step 7: Generate a comprehensive evaluation report of the washing machine based on the analysis results of steps 5 and 6.

[0141] Specifically, the specific contents of the comprehensive evaluation report mainly include: the cleaning rate evaluation value, fabric wear evaluation value and comprehensive energy efficiency ratio evaluation value under different modes; the evaluation level of different indicators under each washing mode and the comprehensive score of the washing machine.

[0142] In this step, the comprehensive evaluation report integrates the cleaning rate evaluation values, fabric wear evaluation values, comprehensive energy efficiency ratio evaluation values, and the evaluation grade and comprehensive score of each mode under different modes to form a comprehensive and systematic performance summary. This report format allows users to quickly and intuitively understand the advantages and disadvantages of the washing machine in various modes, providing consumers with a detailed purchase reference. It also provides washing machine manufacturers with clear directions for product improvement, promoting the overall improvement of product quality.

[0143] By listing the evaluation values and grades for each mode in detail, users can obtain comprehensive information on washing machine performance in a single report, eliminating the need to consult multiple sources. Furthermore, the report is highly targeted, focusing on core performance indicators that users care about, such as cleaning results, clothing wear, and energy efficiency. This allows users to quickly filter and compare the performance of different washing machines based on their needs, saving time and effort and improving the scientificity and accuracy of their decision-making.

[0144] For consumers, the comprehensive evaluation report provides authoritative and objective performance evaluations, helping them rationally choose washing machines that meet their needs and avoid blindly following trends or making incorrect purchases. For manufacturers, the detailed data and ratings in the report clearly point out the strengths and weaknesses of products in different modes and performance indicators, providing a clear direction for product research and development and improvement, promoting the overall technical level and service quality of the washing machine industry, and promoting the healthy development of the industry.

[0145] This will avoid the current problem of fragmented washing machine performance information on the market, forcing users to consult multiple sources to obtain product performance information, which consumes a lot of time and effort, and makes it difficult to directly compare washing machines of different brands and models. This also results in consumers lacking professional performance evaluation information when faced with a wide range of washing machine products, making them easily influenced by advertising and brand effects, leading to irrational purchasing decisions. At the same time, it will provide washing machine manufacturers with systematic and accurate performance feedback during the product improvement process, helping them determine the focus and direction of improvement.

[0146] Example 2

[0147] The present invention also discloses a cleaning performance testing system for an electric washing machine, which is used to implement the above-mentioned cleaning performance testing method for an electric washing machine.

[0148] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. Those skilled in the art will appreciate that the units and algorithm steps of the various examples 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.

[0149] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0150] The above is only a specific implementation method of the present application, but the scope of protection of the present application is not limited thereto. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed in this application, which should be covered by the scope of protection of the present application.

Claims

1. A method for testing the cleaning performance of an electric washing machine, characterized in that: include: Step 1: Select standard original fabrics of different materials, contaminate them with contaminated liquid to prepare contaminated fabrics, and collect the original data of the contaminated fabrics; Step 2: In a test environment, use different washing modes of a washing machine to wash the contaminated cloth, and collect the operating data of the washing machine in different washing modes and the washing data of the contaminated cloth after washing; Step 3: Standardize the collected data, remove abnormal data, and perform preprocessing; Step 4: Input the pre-processed operation data and washing data into the corresponding intelligent calculation model respectively, and obtain the cleaning rate set, wear rate set and comprehensive energy efficiency ratio set of different washing modes through the intelligent calculation model; Step 5: Input the cleaning rate set, wear rate set, and comprehensive energy efficiency ratio set of different washing modes into the mode evaluation model, and output the evaluation level of different washing modes of the washing machine; Step 6: Perform a comprehensive analysis of the cleaning rate set, wear rate set, and comprehensive energy efficiency ratio set of different washing modes to obtain a comprehensive score for the washing machine; Step 7: Generate a comprehensive evaluation report of the washing machine based on the analysis results of steps 5 and 6.

2. A method for testing the cleaning performance of an electric washing machine according to claim 1, characterized in that: In step one, the types of contaminated liquid include at least carbon black oil contaminated liquid, protein contaminated liquid, and sebum contaminated liquid; the standard original cloth of each material needs to be prepared into contaminated cloth of corresponding contamination type using different types of contaminated liquids, and the corresponding original data is collected.

3. A method for testing the cleaning performance of an electric washing machine according to claim 2, characterized in that: After multiple washing operations on contaminated cloths contaminated by different types of contaminated liquids under the same mode, the obtained data is analyzed and calculated by an intelligent computing model to obtain corresponding multiple cleaning rates, wear rates and comprehensive energy efficiency ratios, which constitute a cleaning rate set, a wear rate set and a comprehensive energy efficiency ratio set respectively.

4. A method for testing the cleaning performance of an electric washing machine according to claim 3, characterized in that: In step five, the mode evaluation model can calculate the average values of multiple parameters in the washing rate set, wear rate set and comprehensive energy efficiency ratio set respectively, and the calculation results are used as the washing rate evaluation value, fabric wear evaluation value and comprehensive energy efficiency ratio evaluation value respectively; and compare the washing rate evaluation value, fabric wear evaluation value and comprehensive energy efficiency ratio evaluation value with the corresponding evaluation threshold value to determine the evaluation level of different indicators in each washing mode.

5. A method for testing the cleaning performance of an electric washing machine according to claim 4, characterized in that: The method for determining the evaluation level of different indicators in each washing mode is as follows: Preset the cleaning rate interval threshold, wear rate interval threshold and comprehensive energy efficiency ratio interval threshold for different washing modes; The cleaning rate evaluation values of different washing modes are compared with the cleaning rate interval thresholds of the corresponding modes. If the cleaning rate evaluation value is lower than the minimum value of the cleaning rate interval threshold, it means that the cleaning rate of the corresponding mode is unqualified; if the cleaning rate evaluation value is within the value range of the cleaning rate interval threshold, it means that the cleaning rate of the corresponding mode is qualified; if the cleaning rate evaluation value is greater than the maximum value of the cleaning rate interval threshold, it means that the cleaning rate of the corresponding mode is excellent; The fabric wear evaluation values of different washing modes are compared with the wear rate interval thresholds of the corresponding modes. If the fabric wear evaluation value is lower than the minimum value of the wear rate interval threshold, it means that the fabric wear of the corresponding mode is unqualified; if the fabric wear evaluation value is within the value range of the wear rate interval threshold, it means that the wear rate of the corresponding mode is qualified; if the fabric wear evaluation value is greater than the maximum value of the wear rate interval threshold, it means that the wear rate of the corresponding mode is excellent; The comprehensive energy efficiency ratio evaluation values of different washing modes are compared with the comprehensive energy efficiency ratio interval thresholds of the corresponding modes. If the comprehensive energy efficiency ratio evaluation value is lower than the minimum value of the comprehensive energy efficiency ratio interval threshold, it means that the comprehensive energy efficiency ratio of the corresponding mode is unqualified; if the comprehensive energy efficiency ratio evaluation value is within the value range of the comprehensive energy efficiency ratio interval threshold, it means that the comprehensive energy efficiency ratio of the corresponding mode is qualified; if the comprehensive energy efficiency ratio evaluation value is greater than the maximum value of the comprehensive energy efficiency ratio interval threshold, it means that the comprehensive energy efficiency ratio of the corresponding mode is excellent.

6. A method for testing the cleaning performance of an electric washing machine according to claim 5, characterized in that: The method to obtain the comprehensive rating of the washing machine is as follows: By inputting the cleaning rate evaluation value, fabric wear evaluation value and comprehensive energy efficiency ratio evaluation value of different washing modes into the comprehensive scoring model for analysis, the comprehensive scoring model can output a comprehensive score of the washing machine.

7. A method for testing the cleaning performance of an electric washing machine according to claim 6, characterized in that: By inputting the data from the operation data and the washing data into the cleaning rate intelligent calculation model, the cleaning rate can be output. The formula is as follows: Among them, η1 represents the cleaning rate; R fi Indicates the reflectivity of the contaminated cloth after washing; R in Represents the reflectivity of the contaminated cloth before washing; R max represents the theoretical maximum reflectivity; T represents the washing time; W represents the water temperature; M represents the mechanical index of the washing machine; C represents the pollutant type coefficient; C represents the water temperature; ref represents the reference pollutant coefficient; б represents the experimental fitting attenuation coefficient; β represents the mechanical inhibition coefficient; γ represents the smoothing coefficient; k represents the synergy coefficient; By inputting the data from the operating data and the washing data into the wear rate intelligent calculation model, the wear rate can be output based on the following formula: Wherein, η2 represents the wear rate in the corresponding mode; CI and DI represent the mass of fluff and fiber separated during the washing process in the corresponding mode, respectively; PI represents the sum of the masses of all contaminated cloths in the corresponding mode; N represents the number of contaminated cloths in the corresponding mode; RI represents the sum of the reflectivities of all contaminated cloths before washing in the corresponding mode; RL represents the sum of the reflectivities of all contaminated cloths after washing in the corresponding mode; T represents the washing time; FI represents the washing water volume; W represents the water temperature; and JI represents the friction coefficient during the washing process.

8. A method for testing the cleaning performance of an electric washing machine according to claim 7, characterized in that: By inputting the data from the operation data and washing data into the comprehensive energy efficiency ratio intelligent calculation model, the comprehensive energy efficiency ratio can be output according to the following method: The dynamic wash gain coefficient of the washing machine in the corresponding mode is calculated through the comprehensive energy efficiency ratio intelligent calculation model. The formula is as follows: Wherein, DS represents the dynamic washing gain coefficient in the corresponding mode; DR represents the mean reflectivity of the contaminated cloth after washing; DI represents the mean reflectivity of the contaminated cloth before washing; DO represents the baseline reflectivity of the contaminated cloth; ε represents the contamination residual correction factor; The time efficiency factor of the washing machine in the corresponding mode is calculated using the comprehensive energy efficiency ratio intelligent calculation model. The formula is as follows: Where TX represents the time efficiency factor of the corresponding mode, t0 represents the standard mode duration of the corresponding mode; ta represents the actual mode duration; t max Indicates the longest allowed duration for similar models; The energy consumption density index of the washing machine in the corresponding mode is calculated using the comprehensive energy efficiency ratio intelligent calculation model. The formula is as follows: Where E represents the energy consumption density index of the corresponding mode; wc represents the driving energy consumption of the corresponding mode; wh represents the heating energy consumption of the corresponding mode; m represents the washing capacity of the corresponding mode; Ψ represents the heating efficiency coefficient; The water resource utilization rate of the washing machine in the corresponding mode is calculated using the comprehensive energy efficiency ratio intelligent calculation model. The formula is as follows: Among them, Q represents the water resource utilization rate of the corresponding mode; Qa represents the actual water consumption of the corresponding mode; Qs represents the standard water consumption of the corresponding mode; ρ represents the water hardness correction index; The washing stability coefficient of the washing machine in the corresponding mode is calculated using the comprehensive energy efficiency ratio intelligent calculation model based on the following formula: Where S represents the cleaning stability coefficient of the corresponding mode; σ represents the standard deviation of the multiple cleaning rate of the corresponding mode; μ represents the average value of the multiple cleaning rate of the corresponding mode; The environmental coupling coefficient of the washing machine in the corresponding mode is calculated using the comprehensive energy efficiency ratio intelligent calculation model. The formula is as follows: Where K is the environmental coupling coefficient; ΔT is the ambient temperature difference; RH is the relative humidity deviation; π is a constant; The dynamic washing gain coefficient DS, time efficiency factor TX, energy consumption density index E, water resource utilization rate Q, washing stability coefficient S, and environmental coupling coefficient K of the same mode are input into the comprehensive energy efficiency ratio intelligent calculation model to calculate the comprehensive energy efficiency ratio of the washing machine in the corresponding mode. The formula is as follows: It should be noted that η3 represents the comprehensive energy efficiency ratio of the corresponding mode.

9. A method for testing the cleaning performance of an electric washing machine according to claim 8, characterized in that: By inputting the cleaning rate evaluation values, fabric wear evaluation values, and comprehensive energy efficiency ratio evaluation values of different washing modes into the comprehensive scoring model for analysis, the comprehensive scoring model can output a comprehensive score for the washing machine based on the following formula: Among them, HR represents the comprehensive score; η1 i represents the cleaning rate of the i-th washing mode; η2 i represents the wear rate of the i-th washing mode; η3 i represents the comprehensive energy efficiency ratio of the i-th washing mode; ω i represents the weight coefficient of the sum of the cleaning rate, wear rate and comprehensive energy efficiency ratio in the i-th washing mode, and i represents the serial number of the washing mode, and its value is a positive integer.

10. A system for testing the cleaning performance of an electric washing machine, characterized by: A method for testing the cleaning performance of an electric washing machine according to any one of claims 1 to 9.

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