An automated grinding control system and method

Abstract

This invention relates to the field of automated grinding technology, and discloses an automated grinding control system and method, comprising: a monitoring unit for acquiring the state information of the material to be ground and the operating status information of the equipment; and a central control unit comprising: a first control module for generating state characteristic parameters of the material to be ground based on the acquired state information of the material to be ground; a second control module for constructing a grinding model library based on historical grinding data; a third control module for generating corresponding control commands for the equipment by combining the state characteristic parameters of the material to be ground and the grinding model library; and a fourth control module for determining whether to generate a warning command based on the operating status information of the equipment. This invention achieves coordinated control of material state and equipment operation by acquiring the state information of the material to be ground and the operating status information of the equipment through the monitoring unit, and generating control commands for the equipment based on these two types of information through the central control unit.

Description

Technical Field

[0001] This invention relates to the field of automated grinding technology, and in particular to an automated grinding control system and method. Background Technology

[0002] In the workpiece grinding process, grinding equipment is typically used to grind the surface of the workpiece to ensure that the amount of material removed meets relevant requirements, thereby achieving the desired gloss and flatness. The grinding equipment mainly includes a grinding table and a grinding disc positioned above the grinding table. During grinding, the grinding disc descends to the workpiece surface and grinds it until grinding is complete.

[0003] Grinding, as a key process in precision machining, has long faced the dilemma of balancing efficiency and precision. However, during the grinding process, grinding equipment is susceptible to random factors such as inconsistent grinding fluid concentration and uneven mixing, which can lead to variations in the amount of material removed from the workpiece, consequently causing the workpiece's gloss or flatness to fail to meet relevant requirements. Summary of the Invention

[0004] The purpose of this invention is to acquire the state information of the material to be ground (such as hardness, humidity, and particle size) and the operating status information of the equipment through a monitoring unit. The central control unit generates control commands for the equipment based on these two types of information, achieving coordinated control of the material state and equipment operation. For example, when grinding materials with different hardness, humidity, and particle size, the equipment can adjust the grinding parameters according to the specific state of the material, thereby improving the grinding accuracy.

[0005] To achieve the above objectives, the present invention provides an automated grinding control system, comprising:

[0006] Monitoring unit: Acquires the status information of the material to be ground and the operating status information of the equipment;

[0007] Central control unit: Generates control commands for the equipment based on the status information of the material to be ground and the operating status information of the equipment;

[0008] The central control unit includes:

[0009] First control module: Generates state characteristic parameters of the material to be ground based on the acquired state information of the material to be ground;

[0010] Second control module: Constructs a grinding model library based on historical grinding data;

[0011] The third control module: combines the state characteristic parameters of the material to be ground with the grinding model library to generate corresponding control commands for the equipment;

[0012] The fourth control module determines whether to generate an early warning command based on the equipment's operating status information.

[0013] In some embodiments of the present invention, the first control module is further configured to:

[0014] The acquired state information of the material to be ground is classified to generate multiple types of material state information, including: hardness information value Sa, moisture information value Sb, and particle size information value Sc.

[0015] Based on the historical state information of the material to be ground, the value range of the state information of each type of material is determined as [ai,bi], (i=1, 2, 3);

[0016] Combine the current material state information and the corresponding value range [ai, bi] of the material state information to generate the state characteristic parameters of the material to be ground;

[0017] Among them, hardness characteristic parameter :

[0018] ;

[0019] Humidity characteristic parameters :

[0020] ;

[0021] Particle size characteristic parameters :

[0022] ;

[0023] Where a1 is the left endpoint of the range of hardness information value Sa, b1 is the right endpoint of the range of hardness information value Sa, a2 is the left endpoint of the range of humidity information value Sb, b2 is the right endpoint of the range of humidity information value Sb, a3 is the left endpoint of the range of particle size information value Sc, and b3 is the right endpoint of the range of particle size information value Sc. This represents the historical average hardness value.

[0024] In some embodiments of the present invention, the second control module is further configured to:

[0025] Obtain the state characteristic parameters of historical grinding materials;

[0026] The state characteristic parameters of historical grinding materials are obtained to classify the grinding materials and generate multiple types of grinding materials.

[0027] Obtain equipment operation data for the grinding process of the current type of abrasive material;

[0028] A sample of the current type of abrasive material is generated by combining the state characteristic parameters of the current type of abrasive material with the equipment operation data of the corresponding grinding process.

[0029] A grinding model library was constructed by combining samples of all types of grinding materials.

[0030] In some embodiments of the present invention, the third control module is further configured to:

[0031] The type of grinding material is determined based on the acquired state characteristic parameters of the material to be ground;

[0032] Select a sample of the corresponding type of grinding material based on the grinding material type and the grinding model library;

[0033] And based on the equipment operation data in the samples of the corresponding type of grinding material, control instructions for the corresponding equipment are generated;

[0034] When generating the corresponding control commands for the device, the method further includes:

[0035] Multiple grinding sub-stages are set based on the equipment operation data in the samples of corresponding types of grinding materials, and multiple monitoring cycles are set for each grinding stage;

[0036] Set corresponding grinding control instructions for each grinding sub-stage;

[0037] During the operation of the grinding control command, the state characteristic parameters of the material to be ground and the operating status information of the equipment are acquired based on the monitoring cycle.

[0038] Based on the state characteristic parameters of the material to be ground and the operating status information of the equipment during the current monitoring period, a grinding status evaluation value p1 is generated for the current monitoring period.

[0039] The state prediction value of the current grinding state sub-stage is generated based on the grinding state evaluation value p1 within multiple monitoring cycles in the current grinding sub-stage.

[0040] In some embodiments of the present invention, generating the grinding status evaluation value p1 for the current monitoring period further includes:

[0041] Based on historical grinding process data, obtain a set of standard characteristics of the state of grinding materials and a set of standard characteristics of the operating state of the equipment;

[0042] The average standard value of the material state information of various types of grinding materials in the current grinding sub-stage is calculated based on the standard set of state characteristics of the grinding materials.

[0043] The average standard value of various types of equipment status information for the grinding material in the current grinding sub-stage is calculated based on the standard set of equipment operating status.

[0044] The state evaluation value pa of the material to be ground is generated by combining the state characteristic parameters of the material to be ground with the average of the material state information of various types in the current grinding sub-stage.

[0045] A status evaluation value pb is generated by combining the current equipment operating status information and the average of various types of equipment status information in the current grinding sub-stage;

[0046] The grinding status evaluation value p1 for the current monitoring period is generated by combining the status evaluation value pa of the material to be ground and the status evaluation value pb of the equipment status information.

[0047] p1 = w1 * c1 * pa + w2 * c2 * pb;

[0048] Where w1 is the weight of the state evaluation value pa of the material to be ground, w2 is the weight of the state evaluation value pb of the equipment state information; c1 is the fixed coefficient of the state evaluation value pa of the material to be ground, c2 is the fixed coefficient of the state evaluation value pb of the equipment state information, and c1 and c2 are used to make pa and pb be in the same value range.

[0049] In some embodiments of the present invention, the process of generating the state evaluation value pa of the material to be ground further includes:

[0050] ;

[0051] Where w3 is the hardness feature weight. w4 represents the humidity feature weight. 5 represents the granularity feature weight. This represents the standard mean value of the hardness characteristic parameter. The standard mean value of the humidity characteristic parameter. This represents the standard mean value of the particle size characteristic parameter.

[0052] In some embodiments of the present invention, when generating the state evaluation value pb of the device state information, the method further includes:

[0053] Obtain the current operating status information of the device and generate a set of operating status feature parameters D, D={d1, d2…d… j …d n};

[0054] ;

[0055] Where, d j Let be the feature parameter value of the j-th type of equipment operating status information, and n be the total number of types of equipment operating status information. The weights corresponding to the feature parameter values ​​of the j-th type of equipment operating status information. The standard mean of the characteristic parameter values ​​of the j-th type of equipment operating status information.

[0056] In some embodiments of the present invention, generating the state prediction value of the current grinding state sub-stage further includes:

[0057] Obtain the grinding status evaluation value p1 within the monitoring cycle of the current grinding sub-stage n1 times; n1≤N; N is the total number of monitoring cycles in the current grinding sub-stage;

[0058] Obtain the change curves of n1 grinding state evaluation values ​​p1, and calculate the slope of the change curves to generate the first reference value;

[0059] Multiple first reference value scoring intervals are set based on historical first reference values, and each first reference value scoring interval corresponds to a state prediction value;

[0060] The state prediction value of the current grinding sub-stage is obtained by comparing the first reference value with the first reference value scoring range.

[0061] In some embodiments of the present invention, the fourth control module is further configured to:

[0062] Whether to generate an early warning instruction is determined by comparing the predicted state value of the current grinding sub-stage with the preset value;

[0063] The type of warning instruction determines whether to modify the control instructions for the current grinding sub-stage.

[0064] An automated grinding control method, applied to an automated grinding control system as described in any one of the above claims, comprising:

[0065] Acquire the status information of the material to be ground and the operating status information of the equipment;

[0066] Control commands for the equipment are generated based on the state information of the material to be ground and the operating status information of the equipment.

[0067] The control commands for the generating device include:

[0068] Based on the acquired state information of the material to be ground, generate state characteristic parameters of the material to be ground;

[0069] A grinding model library was built based on historical grinding data;

[0070] The control commands for the corresponding equipment are generated by combining the state characteristic parameters of the material to be ground with the grinding model library.

[0071] Whether to generate a warning command is determined based on the device's operating status information.

[0072] The automated grinding control system and method provided in this invention have the following advantages compared with the prior art:

[0073] Coordinated control of material condition and equipment operation can better adapt to the grinding requirements of different materials and reduce problems such as poor grinding effect or equipment wear caused by changes in material properties.

[0074] The second control module fully considers the multi-factor influence of material state characteristic parameters and equipment operation data by constructing a grinding model library. Different types of grinding materials may require different equipment operation parameters during the grinding process. The construction of the grinding model library can provide targeted grinding solutions for different types of materials, thereby improving grinding efficiency and product quality.

[0075] Since the grinding model library covers samples of various types of grinding materials, its state characteristic parameters can be identified by the system, and a suitable grinding model can be found in the grinding model library, thereby realizing an automated and efficient grinding process.

[0076] When generating control commands for the equipment, the third control module sets up multiple grinding sub-stages based on the equipment operation data in the samples of the corresponding type of grinding material. Each grinding sub-stage is set with multiple monitoring cycles. This fine division allows the grinding process to be controlled more precisely.

[0077] In each grinding sub-stage, the grinding control command can be adjusted according to the changes in the material's characteristics at that stage. In the initial stage of grinding, a larger grinding force can be used for materials with larger particle sizes. As grinding progresses, in sub-stages where the particle size gradually decreases, the grinding force can be reduced accordingly to avoid over-grinding or damaging the material.

[0078] Real-time condition assessment and prediction can promptly detect anomalies during the grinding process. Predicted condition values ​​can provide forward-looking guidance for subsequent grinding processes, allowing for adjustments to equipment parameters in advance to adapt to changes in material condition.

[0079] The fourth control module compares the predicted state value of the current grinding sub-stage with the preset value to determine whether to generate an early warning command. This allows for the timely detection of potential problems, and the accuracy of the early warning is improved by using the quantitative standard of comparing with the preset value.

[0080] The system determines whether to modify the control command for the current grinding sub-stage based on the type of warning command, enabling the system to adjust the control strategy in a timely manner according to the actual situation during the grinding process.

[0081] If the warning is due to a sudden increase in material humidity leading to a decrease in grinding efficiency, the system can correct the control commands, such as adjusting the grinding temperature or ventilation conditions, to restore normal grinding efficiency and ensure the stability of the grinding process and product quality. Attached Figure Description

[0082] Figure 1 This is a structural diagram of an automated grinding control system provided in an embodiment of the present invention. Detailed Implementation

[0083] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0084] In the description of this invention, it should be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0085] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0086] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0087] Example 1:

[0088] An automated grinding control system provided in this embodiment of the invention, such as... Figure 1 As shown, it includes:

[0089] Monitoring unit: Acquires the status information of the material to be ground and the operating status information of the equipment;

[0090] Central control unit: Generates control commands for the equipment based on the status information of the material to be ground and the operating status information of the equipment;

[0091] The central control unit includes:

[0092] First control module: Generates state characteristic parameters of the material to be ground based on the acquired state information of the material to be ground;

[0093] Second control module: Constructs a grinding model library based on historical grinding data;

[0094] The third control module: combines the state characteristic parameters of the material to be ground with the grinding model library to generate corresponding control commands for the equipment;

[0095] The fourth control module determines whether to generate an early warning command based on the equipment's operating status information.

[0096] Example 2: The first control module is also used for:

[0097] The acquired state information of the material to be ground is classified to generate multiple types of material state information, including: hardness information value Sa, moisture information value Sb, and particle size information value Sc.

[0098] Based on the historical state information of the material to be ground, the value range of the state information of each type of material is determined as [ai,bi], (i=1, 2, 3);

[0099] Combine the current material state information and the corresponding value range [ai, bi] of the material state information to generate the state characteristic parameters of the material to be ground;

[0100] Among them, hardness characteristic parameter :

[0101] ;

[0102] Humidity characteristic parameters :

[0103] ;

[0104] Particle size characteristic parameters :

[0105] ;

[0106] Where a1 is the left endpoint of the range of hardness information value Sa, b1 is the right endpoint of the range of hardness information value Sa, a2 is the left endpoint of the range of humidity information value Sb, b2 is the right endpoint of the range of humidity information value Sb, a3 is the left endpoint of the range of particle size information value Sc, and b3 is the right endpoint of the range of particle size information value Sc. This represents the historical average hardness value.

[0107] Example 3: The second control module is also used for:

[0108] Obtain the state characteristic parameters of historical grinding materials;

[0109] The state characteristic parameters of historical grinding materials are obtained to classify the grinding materials and generate multiple types of grinding materials.

[0110] Obtain equipment operation data for the grinding process of the current type of abrasive material;

[0111] A sample of the current type of abrasive material is generated by combining the state characteristic parameters of the current type of abrasive material with the equipment operation data of the corresponding grinding process.

[0112] A grinding model library was constructed by combining samples of all types of grinding materials.

[0113] In this embodiment, records of historical grinding tasks are retrieved from a database. These records contain detailed information about various grinding materials during past grinding processes, such as material hardness, moisture content, particle size, and other state characteristics.

[0114] Sensor data is also an important source. In the past, various sensors installed on the grinding equipment (such as hardness sensors, humidity sensors, particle size analyzers, etc.) would collect material state characteristic data in real time. This data was stored and could be used to obtain historical state characteristic parameters of the ground materials.

[0115] The acquired raw data is cleaned. Outliers are removed, such as obviously unreasonable values ​​caused by sensor malfunction or operational errors.

[0116] Data standardization is performed to transform state characteristic parameters of different units and magnitudes into a unified standard form for subsequent analysis and calculation. For example, hardness values ​​and humidity values ​​are converted into values ​​within the range [0, 1] according to a certain proportional relationship.

[0117] Cluster analysis methods, such as the K-Means clustering algorithm, can be used. Based on the state characteristics of historical grinding materials, grinding materials with similar state characteristics are grouped into one category. For example, materials with higher hardness, lower moisture content, and larger particle size can be grouped into one category, while materials with lower hardness, higher moisture content, and smaller particle size can be grouped into another.

[0118] Decision tree classification algorithms can also be applied. By constructing a decision tree, abrasive materials are classified into different categories based on different ranges of values ​​for state feature parameters. For example, if the hardness of a material is greater than a certain threshold and its moisture content is less than another threshold, it is classified as a specific type of abrasive material.

[0119] The reasonableness of the classification results is evaluated using metrics such as the silhouette coefficient. A silhouette coefficient close to 1 indicates a good classification effect, meaning that the state characteristic parameters of grinding materials within the same class are relatively similar, while there are significant differences between different classes.

[0120] Visualization techniques, such as scatter plots or tree diagrams, can be used to visually represent the classification results, enabling further analysis and adjustment of classification strategies.

[0121] Based on the categorized types of grinding materials, the corresponding equipment operation data is extracted from the database. This data includes operating parameters such as rotational speed, pressure, and temperature of the grinding equipment during the grinding process of the current type of grinding material.

[0122] Ensure an accurate correspondence between equipment operating data and grinding material types. For example, establish an index relationship between grinding material types and equipment operating data in the database to quickly and accurately retrieve the required data.

[0123] Check the completeness of the acquired equipment operation data. For missing data points, fill them in appropriately based on the time series characteristics of the data or other relevant data. For example, if temperature data for a certain moment is missing, the average of temperature data from before and after that moment can be used to fill in the missing data.

[0124] Samples are constructed by combining the state characteristic parameters of the current type of grinding material with the equipment operation data of the corresponding grinding process. For example, a sample can be represented in the form of {material hardness value, material moisture value, material particle size value, equipment rotation speed, equipment pressure, equipment temperature}.

[0125] Ensure the data in the sample is representative. Avoid over-reliance on data from individual specific grinding tasks; instead, construct the sample by comprehensively considering grinding process data under various conditions.

[0126] Feature selection is performed on the constructed samples. Features that have little impact on the grinding results or are highly correlated are removed to simplify the sample structure and improve the efficiency and accuracy of the model. For example, if a high correlation is found between material moisture and particle size, and particle size has a more critical impact on the grinding results, moisture features can be considered for removal.

[0127] Choose an appropriate model construction method based on the characteristics of the grinding material samples. For example, for sample data with strong linear relationships, a linear regression model can be used; for complex nonlinear relationships, a neural network model or a support vector machine model can be selected.

[0128] The model is trained using sample data from all types of abrasive materials, and an abrasive model library is built. For example, for different types of abrasive materials, corresponding linear regression models or neural network models are built, and these models are stored in the abrasive model library.

[0129] Example 4: The third control module is also used for:

[0130] The type of grinding material is determined based on the acquired state characteristic parameters of the material to be ground;

[0131] Select a sample of the corresponding type of grinding material based on the grinding material type and the grinding model library;

[0132] And based on the equipment operation data in the samples of the corresponding type of grinding material, control instructions for the corresponding equipment are generated;

[0133] When generating the corresponding control commands for the device, the method further includes:

[0134] Multiple grinding sub-stages are set based on the equipment operation data in the samples of corresponding types of grinding materials, and multiple monitoring cycles are set for each grinding stage;

[0135] Set corresponding grinding control instructions for each grinding sub-stage;

[0136] During the operation of the grinding control command, the state characteristic parameters of the material to be ground and the operating status information of the equipment are acquired based on the monitoring cycle.

[0137] Based on the state characteristic parameters of the material to be ground and the operating status information of the equipment during the current monitoring period, a grinding status evaluation value p1 is generated for the current monitoring period.

[0138] The state prediction value of the current grinding state sub-stage is generated based on the grinding state evaluation value p1 within multiple monitoring cycles in the current grinding sub-stage.

[0139] Example 5: When generating the grinding status evaluation value p1 for the current monitoring period, the method further includes:

[0140] Based on historical grinding process data, obtain a set of standard characteristics of the state of grinding materials and a set of standard characteristics of the operating state of the equipment;

[0141] The average standard value of the material state information of various types of grinding materials in the current grinding sub-stage is calculated based on the standard set of state characteristics of the grinding materials.

[0142] The average standard value of various types of equipment status information for the grinding material in the current grinding sub-stage is calculated based on the standard set of equipment operating status.

[0143] The state evaluation value pa of the material to be ground is generated by combining the state characteristic parameters of the material to be ground with the average of the material state information of various types in the current grinding sub-stage.

[0144] A status evaluation value pb is generated by combining the current equipment operating status information and the average of various types of equipment status information in the current grinding sub-stage;

[0145] The grinding status evaluation value p1 for the current monitoring period is generated by combining the status evaluation value pa of the material to be ground and the status evaluation value pb of the equipment status information.

[0146] p1 = w1 * c1 * pa + w2 * c2 * pb;

[0147] Where w1 is the weight of the state evaluation value pa of the material to be ground, w2 is the weight of the state evaluation value pb of the equipment state information; c1 is the fixed coefficient of the state evaluation value pa of the material to be ground, c2 is the fixed coefficient of the state evaluation value pb of the equipment state information, and c1 and c2 are used to make pa and pb be in the same value range.

[0148] In this embodiment, a large amount of historical grinding process data is extracted from the database. This data contains detailed information about previous grinding of different materials, such as various state information of the materials (hardness, humidity, particle size, etc.) and operating status information of the equipment (speed, temperature, pressure, etc.).

[0149] Historical data is filtered and organized to ensure its accuracy and completeness. For example, data points lost due to equipment malfunction or abnormal operation are removed, retaining only data from the normal grinding process.

[0150] Based on historical grinding process data, a set of standard characteristics for the grinding materials' state is determined. For each type of material state information (such as hardness, moisture content, particle size, etc.), its normal value range in different grinding tasks is statistically analyzed.

[0151] For example, when analyzing historical data, it can be found that the hardness values ​​of a certain metal material during normal grinding are mostly distributed within a specific range, and this range constitutes part of the standard set of hardness state characteristics.

[0152] Similarly, based on historical grinding process data, a set of standard operating conditions for the equipment is determined. For various operating condition information of the equipment (such as speed, temperature, pressure, etc.), the reasonable value range of these values ​​under normal grinding operation is identified.

[0153] For example, the rotational speed of a grinding equipment is determined based on historical data to determine its normal operating speed range. This range is the part of the equipment operating status standard set related to rotational speed.

[0154] Example 6: When generating the state evaluation value pa of the material to be ground, the method further includes:

[0155] ;

[0156] Where w3 is the hardness feature weight. w4 represents the humidity feature weight. 5 represents the granularity feature weight. This represents the standard mean value of the hardness characteristic parameter. The standard mean value of the humidity characteristic parameter. This represents the standard mean value of the particle size characteristic parameter.

[0157] Example 7: When generating the status evaluation value pb of the device status information, the method further includes:

[0158] Obtain the current operating status information of the device and generate a set of operating status feature parameters D, D={d1, d2…d… j …d n};

[0159] ;

[0160] Where, d j Let be the feature parameter value of the j-th type of equipment operating status information, and n be the total number of types of equipment operating status information. The weights corresponding to the feature parameter values ​​of the j-th type of equipment operating status information. The standard mean of the characteristic parameter values ​​of the j-th type of equipment operating status information.

[0161] In this embodiment, the current operating status information of the equipment is acquired through various sensors and monitoring devices. This information covers multiple aspects, such as the equipment's rotational speed, temperature, pressure, and vibration amplitude. Different grinding equipment may require the collection of different key operating status information, depending on the equipment's type, structure, and function.

[0162] For a high-precision grinding machine, the stability of the rotation speed and the control of the temperature are crucial, so the focus is on collecting operational status information in these aspects; while for large grinding equipment, information such as pressure and vibration amplitude may be more important, as they are directly related to the safety of the equipment and the grinding effect.

[0163] The collected operational status information of different types of equipment is transformed into operational status feature parameters, forming a set D = {d1, d2…dj…dn}. Each feature parameter dj represents a specific aspect of the equipment's operational status.

[0164] For example, d1 can represent the rotational speed characteristic parameter of the equipment, the value of which may be the actual rotational speed value obtained by collecting data from the rotational speed sensor and performing certain calculations; d2 can represent the temperature characteristic parameter of the equipment, reflecting the real-time temperature of the equipment during the grinding process.

[0165] Example 8: When generating the state prediction value of the current grinding state sub-stage, the method further includes:

[0166] Obtain the grinding status evaluation value p1 within the monitoring cycle of the current grinding sub-stage n1 times; n1≤N; N is the total number of monitoring cycles in the current grinding sub-stage;

[0167] Obtain the change curves of n1 grinding state evaluation values ​​p1, and calculate the slope of the change curves to generate the first reference value;

[0168] Multiple first reference value scoring intervals are set based on historical first reference values, and each first reference value scoring interval corresponds to a state prediction value;

[0169] The state prediction value of the current grinding sub-stage is obtained by comparing the first reference value with the first reference value scoring range.

[0170] In this embodiment, the n1 obtained grinding state evaluation values ​​p1 are arranged in the order of the monitoring cycle, and a change curve is plotted with the monitoring cycle number as the horizontal axis and the grinding state evaluation value p1 as the vertical axis. This curve intuitively shows the trend of grinding state change over time (in units of monitoring cycle) within the current grinding sub-stage.

[0171] For example, if the grinding status evaluation value p1 gradually increases with the increase of the monitoring period, it indicates that the grinding process is developing in the expected direction, such as the particle size of the material is gradually decreasing to the target value, and the operating efficiency of the equipment is gradually improving. If p1 fluctuates or shows a downward trend, it may indicate that there are some problems in the grinding process, such as uneven material hardness leading to unstable grinding effect or equipment failure affecting grinding efficiency.

[0172] The slope of the plotted change curve is calculated. The slope can be calculated using the slope formula between two points or a more complex method for calculating the slope of a fitted curve, depending on the shape of the curve and the characteristics of the data. The slope reflects the rate of change of the grinding state evaluation value p1.

[0173] The generated slope value serves as the primary reference value, and this value is of great significance. It can quantify the dynamic characteristics of the grinding process. For example, a larger positive slope may indicate that the grinding process is progressing rapidly and effectively, while a smaller positive or negative slope may indicate obstacles or abnormalities in the grinding process, requiring further analysis.

[0174] The system sets multiple scoring intervals based on historical primary reference values. These historical primary reference values ​​are extracted from data accumulated during past grinding processes. This historical data covers different types of materials, different grinding equipment, and various grinding conditions.

[0175] For example, in the grinding process of a certain type of material on a specific device, by analyzing a large amount of historical data, several typical slope ranges were determined, each corresponding to a different grinding state. These slope ranges were set as different first reference value scoring intervals. For instance, a slope within the interval [a, b] indicates that the grinding process is normal and efficient; a slope within the interval [c, d] indicates that the grinding process may have some minor problems but is still within a controllable range; and a slope outside the interval [e, f] indicates that the grinding process has serious problems.

[0176] The first reference value calculated in the current grinding sub-stage is compared with the set first reference value scoring interval. The state prediction value of the current grinding sub-stage is determined based on the scoring interval in which the first reference value falls.

[0177] If the first reference value falls within the scoring range indicating a normal and efficient grinding process, the status prediction value can be set to "Good," indicating that the grinding process can continue according to the current control instructions. If the first reference value falls within the scoring range indicating a possible minor problem, the status prediction value can be set to "Needs Attention," prompting the system or operator to perform appropriate checks and adjustments to the grinding process. If the first reference value falls outside the scoring range indicating a serious problem, the status prediction value is set to "Abnormal," requiring immediate measures to correct the problem in the grinding process, such as adjusting equipment parameters or replacing grinding tools.

[0178] Example 9: The fourth control module is also used for:

[0179] Whether to generate an early warning instruction is determined by comparing the predicted state value of the current grinding sub-stage with the preset value;

[0180] The type of warning instruction determines whether to modify the control instructions for the current grinding sub-stage.

[0181] In this embodiment, when a warning command is triggered because equipment operating parameters (such as excessively high equipment temperature or excessively high pressure) exceed preset values, such a warning command indicates that the equipment may face the risk of damage or is already in an unstable operating state. For example, a warning for excessively high grinding head temperature may be caused by excessive grinding pressure or poor heat dissipation.

[0182] If a warning is issued because the material's condition (such as abnormal changes in material hardness or unsuitable humidity) does not match the preset value, it means that the material did not change as expected during the grinding process. For example, a sudden increase in material hardness may be due to unsuitable grinding process parameters or changes in the material's internal structure.

[0183] Some warning commands are caused by a combination of factors related to equipment and materials. For example, when equipment is grinding a high-hardness material, the interaction between the grinding force and the material causes the equipment to vibrate beyond the normal range, while the particle size uniformity of the material is also affected. In this case, the warning command generated is a comprehensive warning.

[0184] For equipment-related warnings, such as overheating warnings, when correcting the control commands for the current grinding sub-stage, the first consideration should be reducing the equipment's operating parameters. For example, the grinding speed or grinding pressure can be reduced to decrease the equipment load and thus lower the equipment temperature. Simultaneously, the equipment's cooling system should be checked for proper functioning, such as increasing the coolant flow rate or adjusting the cooling fan speed.

[0185] When material-related warnings are issued, such as when material humidity does not meet requirements, the grinding process should be adjusted accordingly. If the material humidity is too high, drying measures during the grinding process can be increased, such as increasing ventilation or increasing the power of the heating device. If there is an abnormal change in material hardness, it may be necessary to adjust the type of grinding tools or the grinding pressure to accommodate the change in material hardness.

[0186] For comprehensive early warning systems, control commands need to be modified based on a comprehensive consideration of both equipment and material conditions. For example, if both equipment vibration and material particle size uniformity issues occur simultaneously, the equipment's balance parameters should be adjusted to reduce vibration.

[0187] An automated grinding control method, applied to any of the above-mentioned automated grinding control systems, includes:

[0188] Acquire the status information of the material to be ground and the operating status information of the equipment;

[0189] Control commands for the equipment are generated based on the state information of the material to be ground and the operating status information of the equipment.

[0190] The control commands for the generating device include:

[0191] Based on the acquired state information of the material to be ground, generate state characteristic parameters of the material to be ground;

[0192] A grinding model library was built based on historical grinding data;

[0193] The control commands for the corresponding equipment are generated by combining the state characteristic parameters of the material to be ground with the grinding model library.

[0194] Whether to generate a warning command is determined based on the device's operating status information.

[0195] Finally, it should be noted that those skilled in the art can obviously make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims and their equivalents, this invention also intends to include these modifications and variations.

[0196] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention.

Claims

1. An automated grinding control system, characterized in that, include: Monitoring unit: Acquires the status information of the material to be ground and the operating status information of the equipment; Central control unit: Generates control commands for the equipment based on the status information of the material to be ground and the operating status information of the equipment; The central control unit includes: First control module: Generates state characteristic parameters of the material to be ground based on the acquired state information of the material to be ground; Second control module: Constructs a grinding model library based on historical grinding data; The third control module: combines the state characteristic parameters of the material to be ground with the grinding model library to generate corresponding control commands for the equipment; The fourth control module determines whether to generate an early warning command based on the equipment's operating status information; The first control module is also used for: The acquired state information of the material to be ground is classified to generate multiple types of material state information, including: hardness information value Sa, moisture information value Sb, and particle size information value Sc. Based on the historical state information of the material to be ground, the value range of the state information of each type of material is determined as [ai,bi], (i=1, 2, 3); Combine the current material state information and the corresponding value range [ai, bi] of the material state information to generate the state characteristic parameters of the material to be ground; Among them, hardness characteristic parameter : ； Humidity characteristic parameters : ； Particle size characteristic parameters : ； Where a1 is the left endpoint of the range of hardness information value Sa, b1 is the right endpoint of the range of hardness information value Sa, a2 is the left endpoint of the range of humidity information value Sb, b2 is the right endpoint of the range of humidity information value Sb, a3 is the left endpoint of the range of particle size information value Sc, and b3 is the right endpoint of the range of particle size information value Sc. This represents the historical average hardness value.

2. The automated grinding control system as described in claim 1, characterized in that, The second control module is also used for: Obtain the state characteristic parameters of historical grinding materials; The state characteristic parameters of historical grinding materials are obtained to classify the grinding materials and generate multiple types of grinding materials. Obtain equipment operation data for the grinding process of the current type of abrasive material; A sample of the current type of abrasive material is generated by combining the state characteristic parameters of the current type of abrasive material with the equipment operation data of the corresponding grinding process. A grinding model library was constructed by combining samples of all types of grinding materials.

3. An automated grinding control system as described in claim 2, characterized in that, The third control module is also used for: The type of grinding material is determined based on the acquired state characteristic parameters of the material to be ground; Select a sample of the corresponding type of grinding material based on the grinding material type and the grinding model library; And based on the equipment operation data in the samples of the corresponding type of grinding material, control instructions for the corresponding equipment are generated; When generating the corresponding control commands for the device, the method further includes: Multiple grinding sub-stages are set based on the equipment operation data in the samples of corresponding types of grinding materials, and multiple monitoring cycles are set for each grinding stage; Set corresponding grinding control instructions for each grinding sub-stage; During the operation of the grinding control command, the state characteristic parameters of the material to be ground and the operating status information of the equipment are acquired based on the monitoring cycle. Based on the state characteristic parameters of the material to be ground and the operating status information of the equipment during the current monitoring period, a grinding status evaluation value p1 is generated for the current monitoring period. The state prediction value of the current grinding state sub-stage is generated based on the grinding state evaluation value p1 within multiple monitoring cycles in the current grinding sub-stage.

4. An automated grinding control system as described in claim 3, characterized in that, When generating the grinding status evaluation value p1 for the current monitoring period, the method further includes: Based on historical grinding process data, obtain a set of standard characteristics of the state of grinding materials and a set of standard characteristics of the operating state of the equipment; The average standard value of the material state information of various types of grinding materials in the current grinding sub-stage is calculated based on the standard set of state characteristics of the grinding materials. The average standard value of various types of equipment status information for the grinding material in the current grinding sub-stage is calculated based on the standard set of equipment operating status. The state evaluation value pa of the material to be ground is generated by combining the state characteristic parameters of the material to be ground with the average of the material state information of various types in the current grinding sub-stage. A status evaluation value pb is generated by combining the current equipment operating status information and the average of various types of equipment status information in the current grinding sub-stage; The grinding status evaluation value p1 for the current monitoring period is generated by combining the status evaluation value pa of the material to be ground and the status evaluation value pb of the equipment status information. p1 = w1 * c1 * pa + w2 * c2 * pb; Where w1 is the weight of the state evaluation value pa of the material to be ground, w2 is the weight of the state evaluation value pb of the equipment state information; c1 is the fixed coefficient of the state evaluation value pa of the material to be ground, c2 is the fixed coefficient of the state evaluation value pb of the equipment state information, and c1 and c2 are used to make pa and pb be in the same value range.

5. An automated grinding control system as described in claim 4, characterized in that, When generating the state evaluation value pa of the material to be ground, the method further includes: ； Where w3 is the hardness feature weight, w4 is the moisture feature weight, and w5 is the particle size feature weight. This represents the standard mean value of the hardness characteristic parameter. The standard mean value of the humidity characteristic parameter. This represents the standard mean value of the particle size characteristic parameter.

6. An automated grinding control system as described in claim 5, characterized in that, When generating the status evaluation value pb of the device status information, it also includes: Obtain the current operating status information of the device and generate a set of operating status feature parameters D, D={d1, d2…dj…dn}; ； Where dj is the feature parameter value of the j-th type of equipment operating status information, and n is the total number of types of equipment operating status information. The weights corresponding to the feature parameter values ​​of the j-th type of equipment operating status information. The standard mean of the characteristic parameter values ​​of the j-th type of equipment operating status information.

7. An automated grinding control system as described in claim 6, characterized in that, When generating the state prediction value for the current grinding state sub-stage, the method further includes: Obtain the grinding status evaluation value p1 within the monitoring cycle of the current grinding sub-stage n1 times; n1≤N; N is the total number of monitoring cycles in the current grinding sub-stage; Obtain the change curves of n1 grinding state evaluation values ​​p1, and calculate the slope of the change curves to generate the first reference value; Multiple first reference value scoring intervals are set based on historical first reference values, and each first reference value scoring interval corresponds to a state prediction value; The state prediction value of the current grinding sub-stage is obtained by comparing the first reference value with the first reference value scoring range.

8. An automated grinding control system as described in claim 7, characterized in that, The fourth control module is also used for: Whether to generate an early warning instruction is determined by comparing the predicted state value of the current grinding sub-stage with the preset value; The type of warning instruction determines whether to modify the control instructions for the current grinding sub-stage.

9. An automated grinding control method, applied to an automated grinding control system according to any one of claims 1-8, characterized in that, include: Acquire the status information of the material to be ground and the operating status information of the equipment; Control commands for the equipment are generated based on the state information of the material to be ground and the operating status information of the equipment. The control commands for the generating device include: Based on the acquired state information of the material to be ground, generate state characteristic parameters of the material to be ground; A grinding model library was built based on historical grinding data; The control commands for the corresponding equipment are generated by combining the state characteristic parameters of the material to be ground with the grinding model library. Whether to generate a warning command is determined based on the device's operating status information.

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