Grinding fluid performance automatic evaluation method and system based on data analysis

Abstract

The invention relates to the technical field of performance evaluation, in particular to a grinding fluid performance automatic evaluation method and system based on data analysis, and the method comprises the following steps: monitoring the temperature, pressure and grinding speed in a grinding fluid use environment, recording environment parameter data, carrying out the statistical analysis of the collected data, and calculating the performance of the grinding fluid. Comprising calculating a mean value, a standard deviation and a data change trend. According to the method, the performance evaluation threshold value is dynamically adjusted by monitoring and carrying out real-time statistical analysis on environment parameters such as temperature and pressure, so that the evaluation accuracy and the real-time environment adaptation capability are improved, physicochemical indexes and environment data are integrated, an operation performance base line is set, the use effect of the grinding fluid is optimized through an environment adaptation adjustment value, and the grinding fluid quality is improved. Performance deviation is recognized in time by comparing actual operation data with expected performance, and the overall performance of the grinding fluid is evaluated by analyzing the deviation in detail, so that the evaluation process better fits the actual production condition.

Description

Technical Field

[0001] The present invention relates to the technical field of performance evaluation, and in particular to a method and system for automatically evaluating the performance of a polishing liquid based on data analysis. Background Art

[0002] The field of performance evaluation technology involves the use of various methods and systems to determine and analyze the function, efficiency or quality of materials, products or systems. This field generally includes data collection, processing and analysis to determine whether a specific object meets the predetermined performance standards or user needs. Performance evaluation technology is used in many industries, such as engineering, manufacturing, software development and medical. This technology not only helps to improve product quality and reliability, but also supports continuous improvement and innovation. In addition, performance evaluation also focuses on the setting of the test environment, experimental design, and the interpretation and application of results.

[0003] Among them, the automatic evaluation method of grinding fluid performance based on data analysis refers to the use of algorithms and statistical techniques to automatically analyze the performance of grinding fluid in actual applications to predict its grinding and processing effects on workpiece materials. This method usually involves collecting data on the grinding fluid during use, such as temperature, viscosity, and concentration of wear particles, and then evaluating its performance through a data analysis model. The uses of this technology include improving production efficiency, reducing costs, and optimizing grinding fluid formulations, and is particularly suitable for industrial applications with precision manufacturing and high quality requirements.

[0004] Existing technologies are clearly insufficient in adapting to rapidly changing production conditions. They are often based on fixed standards and assumptions, ignoring the impact of environmental changes, resulting in deviations between evaluation results and actual application scenarios. The lack of real-time data analysis and feedback mechanisms limits the ability to make effective adjustments under changing production conditions. For example, sudden changes in ambient temperature or pressure may directly affect the performance of the grinding fluid, thereby reducing product quality and production efficiency. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a method and system for automatically evaluating the performance of a grinding fluid based on data analysis.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: a method for automatically evaluating the performance of a grinding liquid based on data analysis, comprising the following steps:

[0007] S1: Monitor the temperature, pressure and grinding speed in the environment where the grinding fluid is used, record the environmental parameter data, perform statistical analysis on the collected data, including calculating the mean, standard deviation and data change trend, adjust the performance evaluation threshold according to the statistical results, and generate a dynamic environmental threshold;

[0008] S2: Analyze the physical and chemical indicators of the grinding fluid under the current grinding conditions, perform indicator matching, calculate the average value and variability of the current indicators, set the performance benchmark of the current operation according to the calculation results, and generate the operation performance baseline;

[0009] S3: using the dynamic environment threshold and the operation performance baseline, calculating the environment adaptability adjustment value, performing performance expectation adjustment, verifying whether the adjustment value meets the current environment conditions, and generating the adjusted expected performance;

[0010] S4: collecting actual operating data of the current grinding liquid, including actual operating temperature and pressure, comparing the data with the expected performance after adjustment, analyzing the deviation between the actual operating data and the expected performance, and obtaining an actual performance deviation value;

[0011] S5: Compare the actual performance deviation value with the preset performance standard range, sort out the comparison between the actual values ​​and expected values ​​of multiple performance indicators, analyze the size and frequency of the deviation, and generate a comprehensive performance evaluation value.

[0012] The dynamic environment threshold specifically includes a temperature threshold, a pressure threshold, and a speed threshold; the operating performance baseline specifically includes the mean of physical and chemical indicators and the variability of physical and chemical indicators; the adjusted expected performance includes the environmental adaptability adjustment result and the expected performance adjustment value; the actual performance deviation value specifically includes the temperature deviation and the pressure deviation; the comprehensive performance evaluation value includes the deviation size and the deviation frequency.

[0013] As a further solution of the present invention, the step of obtaining the dynamic environment threshold is specifically:

[0014] S111: collecting environmental parameter data, including temperature, pressure and grinding speed, calculating the mean and standard deviation of the data, performing data normalization processing, and obtaining statistical results;

[0015] S112: Based on the statistical results, a linear regression model is used to perform trend line fitting on the data set, and the accuracy of the model fitting is verified by residual analysis to generate data trend analysis results;

[0016] S113: Analyze the output of the linear model in the data trend analysis result, evaluate the deviation and error range of the model prediction, adjust the performance evaluation threshold, and use the formula:

[0017] T new =T avg +k·σ

[0018] Calculate a new threshold value to generate a new performance evaluation threshold value;

[0019] Among them, T new represents the new threshold, T avgrepresents the mean value of the data, σ represents the standard deviation, and k is a coefficient adjusted according to performance requirements;

[0020] S114: Integrate the new performance evaluation threshold, dynamically adjust the real-time environmental parameter data, update the environmental threshold in real time, and generate a dynamic environmental threshold.

[0021] As a further solution of the present invention, the steps of obtaining the operating performance baseline are specifically as follows:

[0022] S211: Collect physical and chemical data on viscosity, temperature, pH, and particle size of the grinding fluid, perform data quality review, screen data for iterative analysis, and generate a validated data set;

[0023] S212: Calculate the mean value and standard deviation of each physical and chemical index from the verified data set, evaluate the statistical distribution and variability of the data through the calculation results, and generate data statistical analysis results;

[0024] S213: Using the data statistical analysis results, a matching analysis of the performance benchmark is performed using the formula:

[0025]

[0026] Perform performance evaluation calculations and generate adjusted performance evaluation results;

[0027] Among them, x i represents the actual measured value of the physical and chemical index, μ represents the average value, and w i represents the weights assigned to multiple indicators, and n represents the number of samples;

[0028] S214: According to the adjusted performance evaluation result, a performance benchmark for the current operation is set to generate an operation performance baseline.

[0029] As a further solution of the present invention, the step of obtaining the adjusted expected performance is specifically:

[0030] S311: According to the dynamic environment threshold and the operation performance baseline, a comparative analysis is performed based on the real-time monitored environment data and the baseline data, and an environmental adaptability adjustment value is calculated to generate an environmental adaptability preliminary evaluation result;

[0031] S312: using the preliminary evaluation result of environmental adaptability, comprehensively referring to the influence of multiple environmental factors on performance by applying a weighted model, and adjusting the performance expectation to generate a performance expectation adjustment result;

[0032] S313: Using the expected performance adjustment result, perform performance verification in an actual scenario, using the formula:

[0033] Padjusted =P baseline ×(1+α·ΔE

[0034] Calculate the adjusted performance value to determine whether the performance adjustment matches the current environment;

[0035] Among them, P baseline represents the baseline performance, ΔE represents the deviation caused by environmental changes, and α is the adjustment coefficient;

[0036] S314: According to the verification result, verify that the adjusted performance meets the requirements of the current environment, and set the performance to the adjusted expected performance.

[0037] As a further solution of the present invention, the step of obtaining the actual performance deviation value is specifically as follows:

[0038] S411: monitor the current operating status of the grinding fluid in real time through sensors, measure key operating parameters of temperature and pressure, and generate actual operating data records;

[0039] S412: Compare the actual operation data with the adjusted expected performance standard, apply a numerical analysis method to quantitatively calculate the deviation between the two, and generate a preliminary performance deviation result;

[0040] S413: Analyze the preliminary performance deviation results using the formula:

[0041]

[0042] The calculated percentage represents the deviation of the actual performance from the expected performance, generating an actual performance deviation value;

[0043] Among them, P actual represents the actual performance data obtained from the equipment monitoring system, P expected Represents performance data based on expected target setting. ΔP represents the percentage deviation between actual performance and expected performance, which is used to indicate whether the performance meets the expected standard and the degree of deviation.

[0044] As a further solution of the present invention, the step of obtaining the comprehensive performance evaluation value is specifically as follows:

[0045] S511: Analyze the actual performance deviation value and the preset performance standard range, systematically classify the actual performance data, calculate the difference between the actual value and the expected value of each performance indicator, and generate performance difference data results;

[0046] S512: Perform frequency analysis on the performance difference data results, use statistical analysis methods to determine the frequency and pattern of deviations, and generate deviation frequency analysis results;

[0047] S513: Compare the deviation frequency analysis result with the industry standard using the formula:

[0048]

[0049] Calculate and generate comprehensive performance evaluation values;

[0050] Among them, P actual,i represents the actual value of the i-th performance indicator, P expected,i represents the expected value of the i-th performance indicator, w i represents the weight of each indicator, reflecting the criticality of the differentiation indicator in the overall evaluation, and E represents the comprehensive performance evaluation value, which quantifies the deviation between the overall performance and expectations through the weighted sum of squared differences.

[0051] A system for automatically evaluating the performance of a grinding liquid based on data analysis, the system for automatically evaluating the performance of a grinding liquid based on data analysis is used to execute the above-mentioned method for automatically evaluating the performance of a grinding liquid based on data analysis, and the system comprises:

[0052] The environmental parameter monitoring module monitors the temperature, pressure and grinding speed in the grinding fluid use environment, records the environmental parameter data, calculates the mean and standard deviation of temperature, pressure and speed, analyzes the change trend, and generates dynamic environmental thresholds based on the statistical analysis results;

[0053] The performance benchmark setting module analyzes the physical and chemical indicators of the grinding fluid under the current grinding conditions, calculates the average and variability of the physical and chemical indicators, and generates an operating performance baseline based on the physical and chemical indicator data;

[0054] The environmental adaptability adjustment module calculates the environmental adaptability adjustment value by using the dynamic environmental threshold and the operating performance baseline, performs performance expectation adjustment, verifies whether the adjustment value meets the current environmental conditions, and generates the expected performance after adjustment;

[0055] The performance deviation analysis module collects the actual operating data of the current grinding fluid, including the actual working temperature and pressure, compares the data with the expected performance after adjustment, analyzes the deviation between the actual operating data and the expectation, obtains the actual performance deviation value, and compares the actual performance deviation value with the preset performance standard range to generate a comprehensive performance evaluation value.

[0056] Compared with the prior art, the advantages and positive effects of the present invention are:

[0057] In the present invention, by monitoring and real-time statistical analysis of environmental parameters, such as temperature and pressure, the performance evaluation threshold is dynamically adjusted, which improves the accuracy of the evaluation and the ability to adapt to the environment in real time. By integrating physical and chemical indicators and environmental data, the operating performance baseline is set, and the use effect of the grinding liquid is optimized through the environmental adaptability adjustment value, thereby enhancing the personalization and accuracy of the operation. By comparing the actual operating data with the expected performance, the performance deviation is identified in time, and by analyzing these deviations in detail, the overall performance of the grinding liquid is evaluated, so that the evaluation process is more in line with the actual production situation. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 It is a schematic diagram of the workflow of the present invention;

[0059] Figure 2 A flowchart of the steps for obtaining the dynamic environment threshold of the present invention;

[0060] Figure 3 A flow chart of the steps for obtaining the operating performance baseline of the present invention;

[0061] Figure 4 A flow chart of the steps for obtaining the expected performance after adjustment of the present invention;

[0062] Figure 5 A flowchart of the steps for obtaining the actual performance deviation value of the present invention;

[0063] Figure 6 The figure is a flow chart of the steps for obtaining the comprehensive performance evaluation value of the present invention. DETAILED DESCRIPTION

[0064] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0065] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0066] Embodiment 1

[0067] See also Figure 1The present invention provides a technical solution: a method for automatically evaluating the performance of a grinding fluid based on data analysis, comprising the following steps:

[0068] S1: Monitor the temperature, pressure and grinding speed in the environment where the grinding fluid is used, record the environmental parameter data, perform statistical analysis on the collected data, including calculating the mean, standard deviation and data change trend, adjust the performance evaluation threshold according to the statistical results, and generate a dynamic environmental threshold;

[0069] S2: Analyze the physical and chemical indicators of the grinding fluid under the current grinding conditions, perform indicator matching, calculate the average value and variability of the current indicators, set the performance benchmark of the current operation according to the calculation results, and generate the operation performance baseline;

[0070] S3: Calculate the environmental adaptability adjustment value using the dynamic environmental threshold and the operating performance baseline, make performance expectation adjustments, verify whether the adjustment value meets the current environmental conditions, and generate the expected performance after adjustment;

[0071] S4: Collect the actual operating data of the current grinding fluid, including the actual operating temperature and pressure, compare the data with the expected performance after adjustment, analyze the deviation between the actual operating data and the expected data, and obtain the actual performance deviation value;

[0072] S5: Compare the actual performance deviation value with the preset performance standard range, collate the comparison between the actual values ​​and expected values ​​of multiple performance indicators, analyze the size and frequency of the deviation, and generate a comprehensive performance evaluation value.

[0073] The dynamic environmental thresholds specifically include temperature thresholds, pressure thresholds, and speed thresholds. The operating performance baseline specifically includes the mean of physical and chemical indicators and the variability of physical and chemical indicators. The adjusted expected performance includes the environmental adaptability adjustment results and the expected performance adjustment value. The actual performance deviation values ​​specifically include temperature deviation and pressure deviation. The comprehensive performance evaluation value includes deviation size and deviation frequency.

[0074] See also Figure 2 , the specific steps for obtaining the dynamic environment threshold are:

[0075] S111: collecting environmental parameter data, including temperature, pressure and grinding speed, calculating the mean and standard deviation of the data, performing data normalization processing, and obtaining statistical results;

[0076] The real-time data of variables is continuously recorded by sensors, and the data acquisition system is used to organize and transmit the data to the central processing unit. On the basis of ensuring the integrity and accuracy of the data, preliminary data cleaning is carried out to eliminate obvious errors and outliers. The mean and standard deviation of multiple parameters are obtained through statistical calculations, and data normalization is performed to ensure that the data is suitable for iterative analysis and obtain statistical results.

[0077] S112: Based on the statistical results, a linear regression model is used to fit the trend line of the data set, and the accuracy of the model fitting is verified through residual analysis to generate data trend analysis results;

[0078] A prediction model is constructed based on previous data. The input data include temperature, pressure and grinding speed. The regression coefficient is calculated using the least squares method. The accuracy of the model fitting is verified through residual analysis. The reliability and deviation of the model are evaluated to verify the feasibility and reliability of the data trend analysis and generate data trend analysis results.

[0079] S113: Analyze the output of the linear model in the data trend analysis results, evaluate the deviation and error range of the model prediction, and adjust the performance evaluation threshold using the formula:

[0080] T new =T avg +k·σ

[0081] Calculate a new threshold value to generate a new performance evaluation threshold value;

[0082] Among them, T new represents the new threshold, T avg represents the mean value of the data, σ represents the standard deviation, and k is a coefficient adjusted according to performance requirements;

[0083] formula:

[0084] T new =T avg +k·σ

[0085] The benefit of the formula is that, by introducing the adjustment coefficient k, a flexible way is provided to adjust the threshold according to differentiated operating conditions, so that the performance evaluation is more accurate and more matched.

[0086] Detailed explanation of the formula and the process of formula calculation and derivation:

[0087] Setting T avg =50℃,σ=10, adjustment coefficient k=0.5According to the actual operating conditions, T new The calculation is as follows:

[0088] 1. Calculate k (σ = 0.5 10 = 5

[0089] 2. Calculate T new =50+5=55℃

[0090] The results show that the new performance evaluation threshold is 55°C, which means that under the current operating conditions, the ambient temperature threshold needs to be adjusted to 55°C to match the performance requirements and ensure the safe operation and stable performance of the system.

[0091] S114: Integrate the new performance evaluation threshold, dynamically adjust the real-time environmental parameter data, update the environmental threshold in real time, and generate a dynamic environmental threshold.

[0092] By continuously monitoring changes in environmental parameters including temperature, pressure and grinding speed, and comparing them with new thresholds in real time, it is determined whether the threshold needs to be adjusted to match environmental changes. In this process, the automated control system is used to adjust the settings of associated equipment to ensure that the threshold matches the current operating environment and generate a dynamic environmental threshold.

[0093] See also Figure 3 ,The specific steps for obtaining the operation performance baseline are:

[0094] S211: Collect physical and chemical data on viscosity, temperature, pH, and particle size of the grinding fluid, perform data quality review, screen data for iterative analysis, and generate a validated data set;

[0095] The physical and chemical index data after data quality review include viscosity, temperature, pH value and particle size. The data are obtained in a laboratory environment by using high-precision instruments. The data of each sample are collected from the actual working grinder within three consecutive working days, three times a day to ensure the reliability and representativeness of the data. The collected data are preliminarily analyzed through statistics, outliers are excluded, and the mean and standard deviation of each indicator are calculated. This process ensures the high quality of the data set and the accuracy of the analysis, thereby generating a verified data set, laying a solid foundation for the next step of data statistical analysis.

[0096] S212: Calculate the mean and standard deviation of each physical and chemical index from the verified data set, evaluate the statistical distribution and variability of the data through the calculation results, and generate statistical analysis results of the data;

[0097] The mean and standard deviation of each physical and chemical index calculated from the verified data set are completed by specialized data processing software, which can effectively process batch data and output statistical results. These statistical results include not only basic descriptive statistics, but also skewness and kurtosis, which help to understand the statistical distribution characteristics and variability of the data set. These statistical analysis results provide a multi-dimensional assessment of data quality and consistency, which is the key basis for the next step of performance benchmark matching analysis.

[0098] S213: Using the statistical analysis results of the data, a matching analysis of the performance benchmark is performed using the formula:

[0099]

[0100] Perform performance evaluation calculations and generate adjusted performance evaluation results;

[0101] Among them, x i represents the actual measured value of the physical and chemical index, μ represents the average value, and w i represents the weights assigned to multiple indicators, and n represents the number of samples;

[0102] formula:

[0103]

[0104] The benefit of the formula is that by introducing the weight parameter w i , it is possible to perform differentiated calculations based on the impact of each physical and chemical index on the grinding effect, so that the performance evaluation can more accurately reflect the actual grinding conditions.

[0105] Detailed explanation of the formula and the process of formula calculation and derivation:

[0106] Set the average value of viscosity μ viscosity =35cP, the average temperature μ temperature =300K, average pH value μ pH =7.0, the average particle size μ size =0.5mm. Set the corresponding weight factors to 0.4, 0.3, 0.2, and 0.1 respectively. The number of samples n = 50. The calculation process is as follows:

[0107]

[0108] The results show that the current physical and chemical indicators are fully consistent with the preset average values, showing excellent consistency and stability, so there is no need to adjust the performance baseline.

[0109] S214: According to the adjusted performance evaluation result, a performance benchmark for the current operation is set to generate an operation performance baseline.

[0110] The adjusted performance evaluation results are set as the performance baseline for the current operation. This is a conclusion drawn based on the analysis of data collected under actual working conditions. The performance baseline is set with reference to the combined impact of multiple physical and chemical indicators on the grinding effect, ensuring the optimal performance of the grinding process. This setting method is not only scientific and reasonable, but also can effectively match any minor changes in the production process, thereby ensuring that the grinding quality is always in the optimal state.

[0111] See also Figure 4 , the specific steps to obtain the expected performance after adjustment are:

[0112] S311: Based on the dynamic environment threshold and the operation performance baseline, the real-time monitored environment data is compared and analyzed with the baseline data, and the environment adaptability adjustment value is calculated to generate the preliminary evaluation result of the environment adaptability;

[0113] Based on the integration of dynamic environmental thresholds and operational performance baselines, the calculation process of environmental adaptability adjustment values ​​is analyzed. First, based on the dynamic environmental thresholds and operational performance baselines, environmental data including temperature and humidity are monitored in real time, compared with the baseline data, and the difference analysis method is used to calculate the preliminary adaptability assessment results. The adaptability assessment results are determined by comparing the deviations between real-time data and baseline data. The deviation values ​​are obtained through the statistical methods of standard deviation and mean difference to ensure the accuracy and reliability of the results. Through real-time data updates, the environmental adaptability values ​​are dynamically adjusted to match the current environmental changes and generate preliminary environmental adaptability assessment results.

[0114] S312: using the preliminary evaluation results of environmental adaptability, comprehensively referring to the impact of multiple environmental factors on performance by applying a weighted model, and adjusting performance expectations to generate performance expectation adjustment results;

[0115] Based on the initial evaluation results of environmental adaptability, performance expectation adjustments are performed. During the adjustment process, a linear weighted model is used to calculate the performance expectation adjustment value. This model comprehensively refers to the impact of multiple environmental factors including real-time changes in temperature and pressure on performance. The weighting factors are derived from previous data analysis to ensure the scientific nature and adaptability of the weighted adjustment. Through model calculations, the real-time data of environmental factors are substituted to calculate the performance expectation adjustment results to ensure that the adjustment results meet actual operational needs.

[0116] S313: Use the expected performance adjustment results to perform performance verification in actual scenarios using the formula:

[0117] P adjusted =P baseline ×(1+α·ΔE)

[0118] Calculate the adjusted performance value to determine whether the performance adjustment matches the current environment;

[0119] Among them, P baseline represents the baseline performance, ΔE represents the deviation caused by environmental changes, and α is the adjustment coefficient;

[0120] formula:

[0121] P adjusted =P baseline ×(1+α·ΔE)

[0122] The benefit of the formula is that it can reflect the impact of environmental changes on expected performance through real-time calculation of the dynamic adjustment coefficient α and the environmental deviation ΔE, thereby achieving optimal performance matching.

[0123] Detailed explanation of the formula and the process of formula calculation and derivation:

[0124] Setting baseline performance P baseline=100 units, environmental deviation ΔE=0.05 (i.e., environmental changes cause the performance to be adjusted by 5%), adjustment coefficient α=0.3, the calculation process is:

[0125] P adjusted =100×(1+0.3×0.05)=100×1.015=101.5

[0126] The results show that the performance after adjustment increased by 1.5 units, from 100 units to 101.5 units, which shows the impact of environmental changes on performance and the necessity of adjustment.

[0127] S314: According to the verification result, verify that the adjusted performance meets the requirements of the current environment, and set the performance to the adjusted expected performance.

[0128] In the process of verifying whether the adjusted performance meets expectations, the actual operating conditions are used to match the adjusted performance values. The test is carried out by simulating actual working conditions to evaluate whether the adjusted performance meets work requirements. Through data comparison and analysis, it is verified whether the performance indicators meet the predetermined operating standards, ensuring that each performance adjustment is based on actual work requirements and environmental conditions, verifying that the adjusted performance meets expectations, and generating adjusted expected performance.

[0129] See also Figure 5 , the specific steps for obtaining the actual performance deviation value are:

[0130] S411: monitor the current operating status of the grinding fluid in real time through sensors, measure key operating parameters of temperature and pressure, and generate actual operating data records;

[0131] The current operating status of the grinding fluid is monitored in real time through sensors, and working parameters including temperature and pressure are measured to ensure accurate data collection. These data will be directly obtained from the equipment sensors and recorded as actual operating data records. Real-time monitoring not only provides accurate operating data, but also assists in maintaining the stable operation of the equipment. The collection of actual operating data depends on the collaborative work of high-precision sensors and real-time data processing systems to extract key operating parameters, including temperature fluctuations and pressure changes. Accurate recording of these data is crucial for data comparison in subsequent steps.

[0132] S412: Compare the actual operation data with the adjusted expected performance standard, apply numerical analysis methods to quantitatively calculate the deviation between the two, and generate preliminary performance deviation results;

[0133] Compare the collected real-time operating data with the preset performance standards. This step uses data analysis technology to determine the deviation between the actual operating data and the expected performance. The key to comparative analysis is statistical execution, which involves data standardization, deviation analysis and result interpretation. Through these data processing, the manifestation of performance deviation can be located. In this process, data comparison not only includes simple numerical comparison, but also includes analysis of data trends and fluctuation patterns, thereby ensuring the accuracy and practicality of the analysis results.

[0134] S413: Analyze the preliminary performance deviation results using the formula:

[0135]

[0136] The calculated percentage represents the deviation of the actual performance from the expected performance, generating an actual performance deviation value;

[0137] Among them, P actual represents the actual performance data obtained from the equipment monitoring system, P expected Represents performance data based on expected target setting. ΔP represents the percentage deviation between actual performance and expected performance, which is used to indicate whether the performance meets the expected standard and the degree of deviation.

[0138] formula:

[0139]

[0140] The benefit of the formula is that it provides a percentage that shows the degree of deviation between actual performance and expected performance, helping engineers and maintenance teams assess the performance status of the equipment and make timely adjustments.

[0141] Detailed explanation of the formula and the process of formula calculation and derivation:

[0142] Referring to an example, in which the actual performance data P actual is 98 units, while the expected performance P expected Set it to 100 units and substitute it into the formula to calculate the process as follows:

[0143]

[0144] The results show that the actual performance is 2% lower than the expected performance, which reflects the space that needs iterative optimization or adjustment.

[0145] See also Figure 6 , the steps for obtaining the comprehensive performance evaluation value are as follows:

[0146] S511: Analyze the actual performance deviation value and the preset performance standard range, systematically classify the actual performance data, calculate the difference between the actual value and the expected value of each performance indicator, and generate performance difference data results;

[0147] The actual performance data is systematically classified and the frequency and pattern of deviations are determined through statistical analysis methods. These data are obtained from sensors and real-time monitoring systems. Each monitoring point records temperature and pressure, and the data is updated every five minutes. Analysis of this data can help identify equipment operating trends and potential performance degradation issues. These analysis results are used to check whether the equipment is operating within the preset performance range. If any parameter is found to be outside the preset range, the corresponding early warning system will be triggered and engineers will be notified to conduct inspections and maintenance.

[0148] S512: Perform frequency analysis on the performance difference data results, use statistical analysis methods to determine the frequency and pattern of deviations, and generate deviation frequency analysis results;

[0149] The collected data is subjected to frequency analysis and the analysis results are compared with industry standards. This process involves batch data processing and calculation. It can automatically extract data from the database and process it using advanced mathematical models to calculate the difference between the actual value and the expected value of each performance indicator. Through these calculations, it is possible to quickly identify which performance indicators fail to meet expectations and adjust the production process accordingly.

[0150] S513: Compare the deviation frequency analysis results with the industry standard using the formula:

[0151]

[0152] Calculate and generate comprehensive performance evaluation values;

[0153] Among them, P actual,i represents the actual value of the i-th performance indicator, P expected,i represents the expected value of the i-th performance indicator, w i represents the weight of each indicator, reflecting the criticality of the differentiation indicator in the overall evaluation, and E represents the comprehensive performance evaluation value, which quantifies the deviation between the overall performance and expectations through the weighted sum of squared differences.

[0154] formula:

[0155]

[0156] The benefit of the formula is that it provides a comprehensive performance evaluation index by quantifying the deviation between each performance indicator and the expected value, which helps to quickly evaluate the overall performance of the equipment.

[0157] Detailed explanation of the formula and the process of formula calculation and derivation:

[0158] There are three performance indicators, whose actual values ​​are 100℃, 50bar, 1200rpm, and expected values ​​are 95℃, 55bar, 1250rpm, respectively. The weights are 0.3, 0.4, and 0.3, respectively.

[0159] 1. Calculation of temperature:

[0160] 2. Calculation of pressure:

[0161] 3. Calculation of speed:

[0162] Comprehensive performance evaluation value E = 0.0016 + 0.0033 + 0.0018 = 0.0067

[0163] The results show that the overall performance of the equipment is slightly lower than expected, mainly due to the large deviations in pressure and speed. It is necessary to adjust the parameters to improve the overall efficiency of the equipment.

[0164] A system for automatically evaluating the performance of a grinding fluid based on data analysis, the system for automatically evaluating the performance of a grinding fluid based on data analysis is used to execute the above-mentioned method for automatically evaluating the performance of a grinding fluid based on data analysis, and the system comprises:

[0165] The environmental parameter monitoring module monitors the temperature, pressure and grinding speed in the grinding fluid use environment, records the environmental parameter data, calculates the mean and standard deviation of temperature, pressure and speed, analyzes the change trend, and generates dynamic environmental thresholds based on the statistical analysis results;

[0166] The performance benchmark setting module analyzes the physical and chemical indicators of the grinding fluid under the current grinding conditions, calculates the average and variability of the physical and chemical indicators, and generates an operating performance baseline based on the physical and chemical indicator data;

[0167] The environmental adaptability adjustment module uses the dynamic environmental threshold and the operating performance baseline to calculate the environmental adaptability adjustment value, make performance expectation adjustments, verify whether the adjustment value meets the current environmental conditions, and generate the expected performance after adjustment;

[0168] The performance deviation analysis module collects the actual operating data of the current grinding fluid, including the actual working temperature and pressure, compares the data with the expected performance after adjustment, analyzes the deviation between the actual operating data and the expectation, obtains the actual performance deviation value, and compares the actual performance deviation value with the preset performance standard range to generate a comprehensive performance evaluation value.

[0169] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A method for automatically evaluating the performance of a grinding fluid based on data analysis, characterized in that: The following steps are involved: Monitor the temperature, pressure and grinding speed in the environment where the grinding fluid is used, record environmental parameter data, and perform statistical analysis on the collected data, including calculating the mean, standard deviation and data change trend, adjusting the performance evaluation threshold according to the statistical results, and generating a dynamic environmental threshold; Analyze the physical and chemical indicators of the grinding fluid under the current grinding conditions, perform indicator matching, calculate the average value and variability of the current indicators, set the performance benchmark of the current operation based on the calculation results, and generate the operating performance baseline; Calculate the environmental adaptability adjustment value by using the dynamic environmental threshold and the operational performance baseline, make performance expectation adjustment, verify whether the adjustment value meets the current environmental conditions, and generate the adjusted expected performance; Collecting actual operating data of the current grinding fluid, including actual operating temperature and pressure, comparing the data with the expected performance after adjustment, analyzing the deviation between the actual operating data and the expected performance, and obtaining an actual performance deviation value; The actual performance deviation value is compared with the preset performance standard range, the actual values ​​of multiple performance indicators are compared with the expected values, the size and frequency of the deviation are analyzed, and a comprehensive performance evaluation value is generated.

2. The method for automatically evaluating the performance of abrasive liquid based on data analysis according to claim 1, characterized in that: The dynamic environment threshold specifically includes a temperature threshold, a pressure threshold, and a speed threshold; the operating performance baseline specifically includes the mean of physical and chemical indicators and the variability of physical and chemical indicators; the adjusted expected performance includes the environmental adaptability adjustment result and the expected performance adjustment value; the actual performance deviation value specifically includes the temperature deviation and the pressure deviation; the comprehensive performance evaluation value includes the deviation size and the deviation frequency.

3. The method for automatically evaluating the performance of abrasive liquid based on data analysis according to claim 2, characterized in that: The steps for obtaining the dynamic environment threshold are specifically as follows: Collect environmental parameter data, including temperature, pressure and grinding speed, calculate the mean and standard deviation of the data, perform data normalization, and obtain statistical results; Based on the statistical results, a linear regression model is used to fit the trend line of the data set, the accuracy of the model fitting is verified through residual analysis, and the data trend analysis results are generated; Analyze the output of the linear model in the data trend analysis results, evaluate the deviation and error range of the model prediction, adjust the performance evaluation threshold, and use the formula: T new =T avg +k·σ Calculate a new threshold value to generate a new performance evaluation threshold value; Among them, T new represents the new threshold, T avg represents the mean value of the data, σ represents the standard deviation, and k is a coefficient adjusted according to performance requirements; The new performance evaluation threshold is integrated, the real-time environmental parameter data is dynamically adjusted, the environmental threshold is updated in real time, and a dynamic environmental threshold is generated.

4. The method for automatically evaluating the performance of abrasive liquid based on data analysis according to claim 3, characterized in that: The steps for obtaining the operation performance baseline are specifically as follows: Collect physicochemical data on viscosity, temperature, pH and particle size of the grinding fluid, perform data quality audits, screen data for iterative analysis, and generate validated data sets; From the validated data set, calculate the mean value and standard deviation of each physical and chemical index, evaluate the statistical distribution and variability of the data through the calculation results, and generate statistical analysis results of the data; Using the statistical analysis results of the data, a matching analysis of the performance benchmark is performed using the formula: Perform performance evaluation calculations and generate adjusted performance evaluation results; Among them, x i represents the actual measured value of the physical and chemical index, μ represents the average value, and w i represents the weights assigned to multiple indicators, and n represents the number of samples; According to the adjusted performance evaluation result, a performance benchmark for the current operation is set to generate an operation performance baseline.

5. The method for automatically evaluating the performance of abrasive liquid based on data analysis according to claim 4, characterized in that: The steps for obtaining the adjusted expected performance are specifically as follows: According to the dynamic environment threshold and the operating performance baseline, a comparative analysis is performed based on the real-time monitored environment data and the baseline data, and an environmental adaptability adjustment value is calculated to generate an environmental adaptability preliminary evaluation result; Using the preliminary evaluation results of environmental adaptability, a weighted model is applied to comprehensively refer to the impact of multiple environmental factors on performance, and performance expectation adjustments are made to generate performance expectation adjustment results; The expected performance adjustment results are used to verify the performance in actual scenarios using the formula: P adjusted =P baseline ×(1+α·ΔE) Calculate the adjusted performance value to determine whether the performance adjustment matches the current environment; Among them, P baseline represents the baseline performance, ΔE represents the deviation caused by environmental changes, and α is the adjustment coefficient; Based on the verification result, verify that the adjusted performance meets the requirements of the current environment and set the performance to the adjusted expected performance.

6. The method for automatically evaluating the performance of abrasive liquid based on data analysis according to claim 5, characterized in that: The steps for obtaining the actual performance deviation value are specifically as follows: The sensor monitors the current operating status of the grinding fluid in real time, measures the key operating parameters of temperature and pressure, and generates actual operating data records; Comparing the actual operating data with the adjusted expected performance standard, applying numerical analysis methods to quantitatively calculate the deviation between the two, and generating preliminary performance deviation results; The preliminary performance deviation results are analyzed using the formula: The calculated percentage represents the deviation of the actual performance from the expected performance, generating an actual performance deviation value; Among them, P actual represents the actual performance data obtained from the equipment monitoring system, P expected Represents performance data based on expected target setting. ΔP represents the percentage deviation between actual performance and expected performance, which is used to indicate whether the performance meets the expected standard and the degree of deviation.

7. The method for automatically evaluating the performance of abrasive liquid based on data analysis according to claim 6, characterized in that: The steps for obtaining the comprehensive performance evaluation value are specifically as follows: Analyze the actual performance deviation value and the preset performance standard range, systematically classify the actual performance data, calculate the difference between the actual value and the expected value of each performance indicator, and generate performance difference data results; Performing frequency analysis on the performance difference data results, using statistical analysis methods to determine the frequency and pattern of deviations, and generating deviation frequency analysis results; The deviation frequency analysis results were compared to the industry standard using the formula: Calculate and generate comprehensive performance evaluation values; Among them, P actual,i represents the actual value of the i-th performance indicator, P expected,i represents the expected value of the i-th performance indicator, w i represents the weight of each indicator, reflecting the criticality of the differentiation indicator in the overall evaluation, and E represents the comprehensive performance evaluation value, which quantifies the deviation between the overall performance and expectations through the weighted sum of squared differences.

8. A system for automatically evaluating the performance of a grinding fluid based on data analysis, characterized in that: According to the method for automatic evaluation of grinding fluid performance based on data analysis according to any one of claims 1 to 7, the system comprises: The environmental parameter monitoring module monitors the temperature, pressure and grinding speed in the grinding fluid use environment, records the environmental parameter data, calculates the mean and standard deviation of temperature, pressure and speed, analyzes the change trend, and generates dynamic environmental thresholds based on the statistical analysis results; The performance benchmark setting module analyzes the physical and chemical indicators of the grinding fluid under the current grinding conditions, calculates the average and variability of the physical and chemical indicators, and generates an operating performance baseline based on the physical and chemical indicator data; The environmental adaptability adjustment module calculates the environmental adaptability adjustment value by using the dynamic environmental threshold and the operating performance baseline, performs performance expectation adjustment, verifies whether the adjustment value meets the current environmental conditions, and generates the expected performance after adjustment; The performance deviation analysis module collects the actual operating data of the current grinding fluid, including the actual working temperature and pressure, compares the data with the expected performance after adjustment, analyzes the deviation between the actual operating data and the expectation, obtains the actual performance deviation value, and compares the actual performance deviation value with the preset performance standard range to generate a comprehensive performance evaluation value.

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