A control method and system applied to tool processing

Abstract

The present invention relates to the technical field of machining, and discloses a control method and system for tool machining. The method includes obtaining the actual machining data, expected motion trajectory, tool service life, and acoustic emission signal of the tool; comparing the actual machining data with preset expected machining data and adjusting the tool according to the comparison result; determining the remaining life cycle of the tool based on the actual machining data, expected motion trajectory, and tool service life, and dynamically adjusting the initial use instruction of the tool; dynamically generating an adjusted tool running route through a tool path optimization algorithm based on the expected motion trajectory; dynamically adjusting the tool maintenance instruction according to the actual machining data and acoustic emission signal; integrating the tool adjustment instruction, tool use instruction, tool motion instruction, and tool maintenance instruction as a tool control instruction, and controlling the machining process according to the tool control instruction. This method realizes maintaining high processing performance and high-precision product quality.

Description

Technical Field

[0001] The present invention relates to the technical field of machining, and particularly to a control method and system applied to tool machining. Background Art

[0002] At present, tool machining plays a crucial role in modern industry and is the core link to achieve high efficiency and high quality in mechanical manufacturing. As the "teeth" of the industrial mother machine, tools not only have a profound impact on the production efficiency and machining quality of cutting machine tools, but also are directly related to the technical level and economic benefits of the entire mechanical manufacturing industry. In machining, metal cutting machine tools and tools constitute the basic process equipment for cutting machining. With the continuous progress of manufacturing technology, the wide application of numerically controlled machine tools has greatly improved the flexibility, precision and efficiency of machining. However, no matter how advanced the numerically controlled machine tool is, its effectiveness depends on the support of high-efficiency and high-precision tools. Therefore, the selection, use and maintenance of tools have become key factors that cannot be ignored in modern manufacturing, and are of great significance for improving machining efficiency, reducing production costs and ensuring product quality. Especially in the field of high-end manufacturing, the application of high-performance tools has become one of the important means to improve the competitiveness of enterprises. With the continuous emergence of new materials and new technologies, the tool industry is also constantly innovating and developing to meet the increasingly complex machining requirements and promote the manufacturing industry to move towards a higher level.

[0003] Within the current technical framework, traditional tool machining methods often rely on a series of preset fixed parameters, covering aspects such as speed, position, acceleration and tool selection, and the goal is always to strive for the best machining quality. The selection of these key parameters is all based on the rich practical experience and profound professional qualities of the operators. Through repeated experiments and fine adjustment processes, the most suitable machining conditions are gradually explored and finally determined. In this process, every fine adjustment of a detail may have an important impact on the final machining result. Therefore, the accumulation of experience and technology is particularly important here. The operator not only needs to have an in-depth understanding of the characteristics of various tools, but also needs to be able to flexibly adjust various process parameters according to factors such as different material properties and machining requirements to ensure the smooth progress of the machining process and the stable and reliable product quality.

[0004] However, when the machining material or environment changes, the fixed machining parameters are difficult to automatically adapt, which may lead to a decrease in machining efficiency or unqualified quality; at the same time, in the face of emergencies such as tool wear or damage, the response speed of traditional methods is slow and unable to make adjustments in time, thus affecting the production progress. In summary, traditional methods cannot monitor and dynamically adjust the machining process in real time, so they cannot ensure high-efficiency machining performance and high-precision product quality under any circumstances. Summary of the Invention

[0005] The present invention provides a control method and system for tool processing to achieve efficient processing performance and high-precision product quality under any circumstances.

[0006] In a first aspect, to solve the above technical problems, the present invention provides a control method for tool processing, including:

[0007] Obtain the actual processing data, expected motion trajectory, tool service life, and acoustic emission signal of the tool, where the actual processing data includes actual position, actual speed, actual acceleration, and actual processing time;

[0008] Compare the actual processing data with preset expected processing data and adjust the tool according to the comparison result to obtain a tool adjustment instruction, where the expected processing data includes expected position, expected speed, expected acceleration, and expected processing time;

[0009] Determine the remaining life cycle of the tool based on the actual processing data, the expected motion trajectory, and the tool service life, and dynamically adjust the initial use instruction of the tool to obtain a tool use instruction;

[0010] Based on the expected motion trajectory, dynamically generate an adjusted tool running route through a tool path optimization algorithm to obtain a tool motion instruction;

[0011] Dynamically adjust the initial tool maintenance instruction according to the actual processing data and the acoustic emission signal to obtain a tool maintenance instruction;

[0012] Use the tool adjustment instruction, the tool use instruction, the tool motion instruction, and the tool maintenance instruction as tool control instructions, and control the processing process according to the tool control instructions.

[0013] In an optional implementation manner, the step of comparing the actual processing data with preset expected processing data and adjusting the tool according to the comparison result to obtain a tool adjustment instruction includes:

[0014] Take the absolute value of the difference between the actual processing data and the expected processing data to obtain error data;

[0015] If the error data does not exceed the preset error range, the tool adjustment ends;

[0016] If the error data exceeds the preset error range, calculate the remaining path length of the tool based on the actual processing data and the expected processing data;

[0017] If the remaining path length is less than zero, the tool adjustment ends;

[0018] If the remaining path length is greater than zero, calculate the mid-course adjustment position based on the actual machining data and the expected machining data;

[0019] Perform reasoning and integration based on the mid-course adjustment position, the actual machining data, and the expected machining data to obtain the following tool adjustment instructions:

[0020] Control the tool to move from the actual position to the mid-course adjustment position, and adjust the actual speed and the actual acceleration to the expected speed and the expected acceleration during the movement;

[0021] When the tool runs to the mid-course adjustment position, move at a constant speed at the expected speed until reaching the expected position;

[0022] Among them, calculate the remaining path length of the tool according to the following formula:

[0023] ;

[0024] Among them, solve for the expected acceleration and the mid-course adjustment position by simultaneously solving the following formulas:

[0025] ;

[0026] Among them, represents the remaining path length of the tool, represents the expected adjustment path length of the tool, represents the actual position of the tool, represents the expected position of the tool, represents the mid-course adjustment position reached in the next execution cycle, represents the actual speed of the tool, represents the expected acceleration of the tool, the expected speed of the tool, represents a preset execution cycle.

[0027] In an alternative embodiment, determining the remaining life cycle of the tool based on the actual machining data, the expected motion trajectory, and the tool service life, and dynamically adjusting the initial use instruction of the tool to obtain a tool use instruction, includes:

[0028] Calculate the remaining time for the tool to reach the expected position based on the expected motion trajectory of the tool;

[0029] Calculate the remaining life cycle of the tool based on a pre-calculated motion deviation index and the actual machining data;

[0030] Compare the remaining life cycle with the tool service life to obtain the following tool use instructions:

[0031] If the remaining service life reaches the tool service life, calculate the tool adjustment strategy for the expected position and adjust the expected motion trajectory;

[0032] If the remaining service life does not reach the tool service life, update the expected processing time corresponding to the expected motion trajectory according to the remaining time and preset process parameters;

[0033] Among them, the remaining time for the tool to reach the expected position is calculated by the following formula:

[0034] ;

[0035] Among them, the motion deviation index is calculated according to the following formula:

[0036] ;

[0037] Among them, the remaining service life of the tool is calculated according to the following formula:

[0038] ;

[0039] Among them, the expected processing time is calculated by the following formula:

[0040] ;

[0041] Among them, represents the remaining time, represents the distance from the expected motion trajectory to the next expected position, represents the expected motion speed, represents the motion deviation index, represents the upper threshold of the preset motion deviation index, represents the lower threshold of the preset motion deviation index, represents the actual processing error, represents the upper threshold of the preset actual processing error, represents the lower threshold of the preset actual processing error, represents the preset least squares optimization parameter, represents the preset execution cycle, represents the remaining service life, represents the actual speed, and represent the preset parameters in the tool service life model, represents the expected processing time, represents the cutting time, represents the cutting path length, represents the tool feed speed, represents the spindle speed.

[0042] In an alternative embodiment, the tool adjustment strategy for calculating the expected position and adjusting the expected motion trajectory includes:

[0043] Taking the expected motion trajectory as the initial state and the position corresponding to the remaining time as the desired state to obtain the initial state and the desired state;

[0044] Adjusting the expected speed and expected acceleration according to the initial state and the desired state;

[0045] Calculating the usage instruction of the tool motion trajectory according to the following minimization objective function:

[0046] ;

[0047] Wherein, represents the remaining time, the adjusted expected speed, represents the adjusted expected acceleration, and represent preset weight coefficients, represents the objective function;

[0048] Adjusting the expected motion trajectory according to the usage instruction to obtain a new expected motion trajectory.

[0049] In an alternative embodiment, the dynamically generating an adjusted tool running route based on the expected motion trajectory to obtain a tool motion instruction includes:

[0050] Dividing the expected motion trajectory into multiple path adjustment areas to obtain path adjustment regions;

[0051] Calculating the new expected acceleration and new expected speed for each path adjustment area based on the path adjustment regions to obtain the new expected speed and new expected acceleration;

[0052] Updating the expected acceleration and the expected speed in each of the path adjustment regions according to the new expected acceleration and the new expected speed and optimizing the tool path through a tool path optimization algorithm to obtain a tool motion instruction.

[0053] In an alternative embodiment, the tool path optimization algorithm includes:

[0054] Defining a machining model: represents the number of machining trajectory points in the machining area, represents the th machining trajectory point, represents the curvature of the machining trajectory point, Represents the distance between two adjacent machining trajectory points;

[0055] Calculate the weighted speed and weighted acceleration of the tool at the stage according to the following formula:

[0056] ;

[0057] Where, represents the weighted speed, represents the expected speed, represents the actual speed, represents the weighted acceleration, represents the expected acceleration, represents the actual acceleration, and represent the preset weighted factors;

[0058] Calculate the feed speed and cutting speed according to the following formula:

[0059] ;

[0060] Where, represents the feed speed, represents the cutting speed, represents the curvature of the current trajectory point, and represent the preset weighted factors;

[0061] Generate the tool optimization path through the following function:

[0062] ;

[0063] Where, represents the th machining trajectory point, represents the weighted speed of the th machining trajectory point, represents the weighted acceleration of the th machining trajectory point, represents the feed speed of the th machining trajectory point, represents the cutting speed of the th machining trajectory point, represents the th machining trajectory point to the -1th machining trajectory point distance.

[0064] In an alternative embodiment, the dynamically adjusting the tool maintenance instruction according to the actual machining data and the acoustic emission signal to obtain the tool maintenance instruction includes:

[0065] Perform a Fourier transform on the said acoustic emission signal to obtain a frequency-domain signal;

[0066] According to the said frequency-domain signal, calculate the power spectral density matrix through the following formula: ;

[0067] where, represents the power spectral density matrix, represents the frequency-domain signal, represents the acoustic emission signal;

[0068] According to the said power spectral density matrix, use the support vector machine algorithm to determine the working cutting time of the tool;

[0069] Subtract the said working cutting time from the expected cutting time to obtain deviation data;

[0070] Generate the following tool maintenance instructions according to the said deviation data, a preset deviation threshold, the actual machining time and the expected machining time:

[0071] Compare the said deviation data with the preset deviation threshold. If the said deviation data is greater than the preset deviation threshold, increase the cutting depth so that the remaining cutting area is equal to the current cutting area;

[0072] If the said deviation data is less than the preset deviation threshold, maintain the original cutting depth;

[0073] Compare the said actual machining time with the expected machining time. If the said actual machining time is greater than the expected machining time, return to compare the said deviation data with the preset deviation threshold;

[0074] If the said actual machining time is less than the expected machining time, the tool maintenance process ends.

[0075] In a second aspect, the present invention provides a control device applied to tool machining, including:

[0076] A data acquisition module for acquiring the actual machining data, expected motion trajectory, tool service life and acoustic emission signal of the tool, wherein the said actual machining data includes actual position, actual speed, actual acceleration and actual machining time;

[0077] A tool adjustment module for comparing the said actual machining data with preset expected machining data and adjusting the tool according to the comparison result to obtain a tool adjustment instruction, wherein the said expected machining data includes expected position, expected speed, expected acceleration and expected machining time;

[0078] Use an adjustment module to determine the remaining service life of the tool based on the actual machining data, the expected motion trajectory, and the tool service life, and dynamically adjust the initial tool usage instruction to obtain a tool usage instruction;

[0079] A motion adjustment module for dynamically generating an adjusted tool running route based on the expected motion trajectory through a tool path optimization algorithm to obtain a tool motion instruction;

[0080] A maintenance adjustment module for dynamically adjusting the initial tool maintenance instruction according to the actual machining data and the acoustic emission signal to obtain a tool maintenance instruction;

[0081] An output module for using the tool adjustment instruction, the tool usage instruction, the tool motion instruction, and the tool maintenance instruction as tool control instructions to obtain tool control instructions.

[0082] In a third aspect, the present invention also provides an electronic device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the control method for tool machining described in any one of the above.

[0083] In a fourth aspect, the present invention also provides a computer-readable storage medium. The computer-readable storage medium includes a stored computer program. When the computer program runs, it controls the device where the computer-readable storage medium is located to execute the control method for tool machining described in any one of the above.

[0084] Compared with the prior art, the present invention has the following beneficial effects:

[0085] The present invention discloses a control method applied to tool processing, including acquiring actual processing data of a tool, an expected motion trajectory, tool service life, and acoustic emission signals. Among them, the actual processing data includes actual position, actual speed, actual acceleration, and actual processing time; comparing the actual processing data with preset expected processing data and adjusting the tool according to the comparison result to obtain a tool adjustment instruction. Among them, the expected processing data includes expected position, expected speed, expected acceleration, and expected processing time; determining the remaining life cycle of the tool according to the actual processing data, the expected motion trajectory, and the tool service life, and dynamically adjusting the initial use instruction of the tool to obtain a tool use instruction; dynamically generating an adjusted tool running route through a tool path optimization algorithm based on the expected motion trajectory to obtain a tool motion instruction; dynamically adjusting the initial tool maintenance instruction according to the actual processing data and the acoustic emission signals to obtain a tool maintenance instruction; taking the tool adjustment instruction, the tool use instruction, the tool motion instruction, and the tool maintenance instruction as tool control instructions, and controlling the processing process according to the tool control instructions. By collecting the actual processing data, expected motion trajectory, tool service life, and acoustic emission signals of the tool, and comparing them with preset processing parameters, the present invention automatically adjusts the position and speed of the tool, generates a new running route, and at the same time adjusts the tool use and maintenance plans according to the actual processing conditions and acoustic emission signals, and finally integrates them into control instructions to guide the precise processing of the tool, so as to maintain high processing performance and high-precision product quality in any case. BRIEF DESCRIPTION OF THE DRAWINGS

[0086] Figure 1 is a schematic flowchart of a control method applied to tool processing provided by the first embodiment of the present invention;

[0087] Figure 2 is a schematic structural diagram of a control device applied to tool processing provided by the second embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0088] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0089] Referring to Figure 1 , the first embodiment of the present invention provides a control method applied to tool processing, including the following steps:

[0090] S11. Obtain the actual machining data, expected motion trajectory, tool service life, and acoustic emission signal of the tool. Among them, the actual machining data includes actual position, actual speed, actual acceleration, and actual machining time;

[0091] S12. Compare the actual machining data with the preset expected machining data and adjust the tool according to the comparison result to obtain a tool adjustment instruction. Among them, the expected machining data includes expected position, expected speed, expected acceleration, and expected machining time;

[0092] S13. Determine the remaining service life of the tool based on the actual machining data, the expected motion trajectory, and the tool service life, and dynamically adjust the initial use instruction of the tool to obtain a tool use instruction;

[0093] S14. Based on the expected motion trajectory, dynamically generate an adjusted tool running route through a tool path optimization algorithm to obtain a tool motion instruction;

[0094] S15. Dynamically adjust the initial tool maintenance instruction according to the actual machining data and the acoustic emission signal to obtain a tool maintenance instruction;

[0095] S16. Use the tool adjustment instruction, the tool use instruction, the tool motion instruction, and the tool maintenance instruction as tool control instructions, and control the machining process according to the tool control instructions.

[0096] In step S11, obtain the actual machining data, expected motion trajectory, tool service life, and acoustic emission signal of the tool. Among them, the actual machining data includes actual position, actual speed, actual acceleration, and actual machining time.

[0097] The actual machining data is monitored and recorded in real time by position sensors, speed sensors, acceleration sensors, and time counters installed on the machine tool; the expected motion trajectory data comes from machining programs or CAM software, which generate the motion path of the tool according to design requirements; the tool service life data can be obtained through life parameters provided by the manufacturer, historical maintenance records, or an online monitoring system; the acoustic emission signal is captured by acoustic emission sensors installed on the machine tool or the tool, reflecting the vibration of the tool during the cutting process.

[0098] In step S12, compare the actual machining data with the preset expected machining data and adjust the tool according to the comparison result to obtain a tool adjustment instruction. Among them, the expected machining data includes expected position, expected speed, expected acceleration, and expected machining time.

[0099] In a specific implementation manner, the process of comparing the actual machining data with the preset expected machining data and adjusting the tool according to the comparison result to obtain a tool adjustment instruction includes:

[0100] Subtract the expected machining data from the actual machining data and take the absolute value to obtain error data;

[0101] If the error data does not exceed the preset error range, the tool adjustment ends;

[0102] If the error data exceeds the preset error range, calculate the remaining path length of the tool based on the actual machining data and the expected machining data;

[0103] If the remaining path length is less than zero, the tool adjustment ends;

[0104] If the remaining path length is greater than zero, calculate the midway adjustment position based on the actual machining data and the expected machining data;

[0105] Perform reasoning and integration based on the midway adjustment position, actual machining data, and the expected machining data to obtain the following tool adjustment instruction:

[0106] Control the tool to move from the actual position to the midway adjustment position, and adjust the actual speed and actual acceleration to the expected speed and expected acceleration during the movement;

[0107] When the tool runs to the midway adjustment position, move at a constant speed with the expected speed until reaching the expected position;

[0108] Among them, the remaining path length of the tool is calculated according to the following formula:

[0109] ;

[0110] Among them, the expected acceleration and midway adjustment position are solved by simultaneously solving the following formulas:

[0111] ;

[0112] Among them, represents the remaining path length of the tool, represents the expected adjustment path length of the tool, represents the actual position of the tool, represents the expected position of the tool, represents the midway adjustment position reached in the next execution cycle, represents the actual speed of the tool, represents the expected acceleration of the tool, the expected speed of the tool Represents a preset execution cycle.

[0113] Specifically, the difference between the actual machining data and the expected machining data is quantified, that is, the error data is obtained by calculating the difference between the two and taking the absolute value. If these error data are all within the preset allowable error range, it indicates that the current machining state is good and there is no need to make additional adjustments to the tool, and the tool adjustment process ends.

[0114] If the error data exceeds the preset error range, it indicates that there is a significant deviation between the actual machining situation and the expectation. At this time, it is necessary to further calculate the remaining path length of the tool through the following formula:

[0115] ;

[0116] Wherein, Represents the remaining path length of the tool, Represents the expected adjustment path length of the tool, Represents the actual position of the tool, Represents the expected position of the tool;

[0117] If the calculation result shows that the remaining path length is less than zero, it means that the tool has exceeded the expected position and there is no need to make adjustments either, and the tool adjustment process ends. However, if the remaining path length is greater than zero, it indicates that the tool has not reached the expected position and it is necessary to calculate an intermediate adjustment position to adjust the tool in a timely manner.

[0118] Next, based on the actual machining data and the expected machining data, calculate the intermediate position to which the tool should be adjusted through the following formula. At the same time, determine how the speed of the tool should be smoothly transitioned from the actual speed to the expected speed during this process. ;

[0119] Wherein, Represents the intermediate adjustment position reached in the next execution cycle, Represents the actual position of the tool, Represents the actual speed of the tool, Represents the expected acceleration of the tool, The expected speed of the tool, Represents a preset execution cycle.

[0120] According to the calculation result, specific tool adjustment instructions can be formulated to instruct the tool to move from the current position to the calculated intermediate adjustment position and gradually adjust its speed and acceleration during the movement until the expected values are reached. The specific steps are as follows:

[0121] Control the tool to move from the actual position to the mid - adjustment position. During the movement, gradually adjust the actual speed and actual acceleration to the expected speed and expected acceleration. When the tool runs to the mid - adjustment position, move at a constant speed with the expected speed until reaching the expected position. By precisely controlling the movement parameters of the tool, machining errors can be effectively reduced, and machining accuracy and efficiency can be improved.

[0122] In step S13, determine the remaining life cycle of the tool according to the actual machining data, the expected motion trajectory, and the tool service life, and dynamically adjust the initial tool use instruction to obtain the tool use instruction.

[0123] In a specific implementation manner, the determining the remaining life cycle of the tool according to the actual machining data, the expected motion trajectory, and the tool service life, and dynamically adjusting the initial tool use instruction to obtain the tool use instruction includes:

[0124] Calculate the remaining time for the tool to reach the expected position based on the expected motion trajectory of the tool;

[0125] Calculate the remaining life cycle of the tool based on the pre - calculated motion deviation index and the actual machining data;

[0126] Compare the remaining life cycle with the tool service life to obtain the following tool use instruction:

[0127] If the remaining life cycle reaches the tool service life, calculate the tool adjustment strategy for the expected position and adjust the expected motion trajectory;

[0128] If the remaining life cycle does not reach the tool service life, update the expected machining time corresponding to the expected motion trajectory according to the remaining time and the preset process parameters;

[0129] Among them, the remaining time for the tool to reach the expected position is calculated by the following formula: ;

[0130] Among them, the motion deviation index is calculated according to the following formula: ;

[0131] Among them, the remaining life cycle of the tool is calculated according to the following formula: ;

[0132] Among them, the expected machining time is calculated by the following formula: ;

[0133] Among them, represents the remaining time, represents the distance from the expected motion trajectory to the next expected position, Represents the expected motion speed, Represents the motion deviation index, Represents the upper threshold of the preset motion deviation index, The lower threshold of the preset motion deviation index, Represents the actual machining error, Represents the upper threshold of the preset actual machining error, Represents the lower threshold of the preset actual machining error, Represents the preset least squares optimization parameter, Represents the preset execution cycle, Represents the remaining life cycle, Represents the actual speed, and Represents the preset parameter in the tool service life model, Represents the expected machining time, Represents the cutting time, Represents the cutting path length, Represents the tool feed speed, Represents the spindle speed.

[0134] In a specific implementation, calculating the tool adjustment strategy for the expected position and adjusting the expected motion trajectory includes:

[0135] Taking the expected motion trajectory as the initial state and the position corresponding to the remaining time as the desired state to obtain the initial state and the desired state;

[0136] Adjusting the expected speed and expected acceleration according to the initial state and the desired state;

[0137] Calculating the usage instruction of the tool motion trajectory according to the following minimization objective function:

[0138] ;

[0139] Wherein, Represents the remaining time, The adjusted expected speed, Represents the adjusted expected acceleration, and Represents the preset weight coefficient, Represents the objective function;

[0140] Adjusting the expected motion trajectory according to the usage instruction to obtain a new expected motion trajectory.

[0141] Specifically, first, based on the expected motion trajectory of the tool, calculate the remaining time for the tool to reach the expected position. This step is achieved through the following formula:

[0142] ;

[0143] Wherein, represents the remaining time, represents the distance from the expected motion trajectory to the next expected position, represents the expected motion speed;

[0144] Next, based on the pre-calculated motion deviation index and actual machining data, calculate the remaining life cycle of the tool. The motion deviation index reflects the impact of actual machining errors on tool life and is calculated by the following formula:

[0145] ;

[0146] Wherein, represents the motion deviation index, represents the upper threshold value of the preset motion deviation index, represents the lower threshold value of the preset motion deviation index, represents the actual machining error, represents the upper threshold value of the preset actual machining error, represents the lower threshold value of the preset actual machining error, represents the preset least squares optimization parameter, represents the preset execution cycle;

[0147] Then, according to the actual speed and the expected speed, combined with the preset parameters in the tool service life model, calculate the remaining life cycle of the tool, which is achieved by the following formula:

[0148] ;

[0149] Wherein, represents the remaining life cycle, represents the actual speed, and represent the preset parameters in the tool service life model;

[0150] Next, compare the calculated remaining life cycle with the service life of the tool. If the remaining life cycle reaches the service life of the tool, it means the tool is about to fail and it is necessary to immediately calculate the tool adjustment strategy for the expected position and adjust the expected motion trajectory to extend the service life of the tool. If the remaining life cycle does not reach the service life of the tool, it means the tool is still in a usable state and the expected machining time of the corresponding expected motion trajectory can be updated according to the remaining time and the preset process parameters.

[0151] Wherein, the expected machining time is calculated by the following formula:

[0152] ;

[0153] Among them, represents the expected processing time, represents the cutting time, represents the cutting path length, represents the tool feed rate, represents the spindle speed.

[0154] Specifically, calculate the tool adjustment strategy for the expected position and adjust the expected motion trajectory, including the following steps:

[0155] Take the expected motion trajectory as the initial state and the position corresponding to the remaining time as the desired state to obtain the initial state and the desired state. The initial state includes the current position, current speed, and current acceleration of the tool, and the desired state includes the target position, target speed, and target acceleration that the tool should reach within the remaining time. The purpose of this step is to clarify the motion target of the tool from the current position to the target position.

[0156] Adjust the expected speed and expected acceleration according to the initial state and the desired state. The adjustment target is to make the tool reach the target position smoothly and efficiently within the remaining time.

[0157] Calculate the usage instruction for the tool motion trajectory according to the following minimization objective function:

[0158] ;

[0159] Among them, represents the remaining time, the adjusted expected speed, represents the adjusted expected acceleration, and represents the preset weight coefficient, represents the objective function;

[0160] The purpose of this objective function is to minimize the changes in speed and acceleration within the remaining time, thereby reducing the energy consumption and wear of the tool and improving the machining quality and efficiency. According to the calculated usage instruction, the usage instruction is used to adjust the expected speed and expected acceleration, so as to achieve the adjustment of the expected motion trajectory and obtain a new expected motion trajectory. This step is realized through an optimization algorithm to ensure that the new expected motion trajectory can make the tool reach the target position efficiently and smoothly under the condition of meeting the minimization condition of the objective function.

[0161] The usage instruction provides a quantification metric for evaluating and optimizing the tool's motion trajectory. By minimizing it, it can be ensured that the tool can not only reach the target position quickly during movement, but also reduce unnecessary energy consumption and wear, improving the machining quality and efficiency. The finally generated tool motion instruction will guide the tool to move along the optimized path to ensure the smooth progress of the machining process.

[0162] In step S14, based on the expected motion trajectory, an adjusted tool running route is dynamically generated through a tool path optimization algorithm to obtain a tool motion instruction.

[0163] In a specific implementation manner, the generating an adjusted tool running route based on the expected motion trajectory through a tool path optimization algorithm to obtain a tool motion instruction includes:

[0164] Dividing the expected motion trajectory into multiple path adjustment zones to obtain path adjustment regions;

[0165] Calculating the new expected acceleration and new expected speed for each path adjustment zone based on the path adjustment regions to obtain the new expected speed and new expected acceleration;

[0166] According to the new expected acceleration and the new expected speed, updating the expected acceleration and the expected speed in each of the path adjustment regions and optimizing the tool path through the tool path optimization algorithm to obtain a tool motion instruction.

[0167] In a specific implementation manner, the tool path optimization algorithm includes:

[0168] Defining a machining model: represents the number of machining trajectory points in the machining area, represents the th machining trajectory point, represents the curvature of the machining trajectory point, represents the distance between two adjacent machining trajectory points;

[0169] Calculating the weighted speed and weighted acceleration of the tool in the th stage according to the following formula: ;

[0170] where, represents the weighted speed, represents the expected speed, represents the actual speed, represents the weighted acceleration, represents the expected acceleration, represents the actual acceleration, and represent preset weighted factors;

[0171] Calculate the feed rate and cutting speed according to the following formula: ;

[0172] wherein, represents the feed rate, represents the cutting speed, represents the curvature of the current trajectory point, and represents the preset weighting factor;

[0173] Generate the optimized tool path through the following function: ;

[0174] wherein, represents the th machining trajectory point, represents the weighted speed of the th machining trajectory point, represents the weighted acceleration of the th machining trajectory point, represents the feed rate of the th machining trajectory point, represents the cutting speed of the th machining trajectory point, represents the distance from the th machining trajectory point to the -1 th machining trajectory point.

[0175] Specifically, first, divide the expected motion trajectory into multiple path adjustment zones to obtain path adjustment regions. Each path adjustment zone represents a specific machining trajectory, facilitating independent optimization and adjustment for each section.

[0176] Next, apply the tool path optimization algorithm to generate the optimized tool running route. The specific steps are as follows:

[0177] Define the machining model: represents the number of machining trajectory points in the machining area, represents the th machining trajectory point, represents the curvature of the machining trajectory point, represents the distance between two adjacent machining trajectory points; the purpose of this step is to establish a detailed machining trajectory model to provide a basis for subsequent optimization calculations.

[0178] Calculate the weighted speed and weighted acceleration of the tool at the stage according to the following formula:

[0179] ;

[0180] wherein, represents the weighted speed, represents the expected speed, represents the actual speed, represents the weighted acceleration, represents the expected acceleration, represents the actual acceleration, and represents the preset weighting factor;

[0181] Through weighted calculation, the expected and actual motion parameters can be comprehensively considered to ensure that the optimized motion trajectory is more reasonable.

[0182] The feed speed and cutting speed are calculated according to the following formula:

[0183] ;

[0184] where, represents the feed speed, represents the cutting speed, represents the curvature of the current trajectory point, and represents the preset weighting factor;

[0185] Through these formulas, it can be ensured that the tool has appropriate feed speed and cutting speed at the trajectory points with different curvatures, thereby improving the machining efficiency and quality.

[0186] The tool optimization path is generated through the following function:

[0187] ;

[0188] where, represents the th machining trajectory point, represents the weighted speed of the th machining trajectory point, represents the weighted acceleration of the th machining trajectory point, represents the feed speed of the th machining trajectory point, represents the cutting speed of the th machining trajectory point, represents the distance to the -1th machining trajectory point.

[0189] Through this function, a tool running path containing all optimized parameters can be generated to guide the movement of the tool during machining and obtain the tool motion instruction.

[0190] Through the above steps, an adjusted tool running route can be dynamically generated to ensure that the tool can run efficiently and smoothly during the machining process. These optimization steps not only improve the machining efficiency, but also reduce the tool wear and enhance the machining quality. The finally generated tool motion instructions will guide the tool to move along the optimized path to ensure the smooth progress of the machining process.

[0191] In step S15, the initial tool maintenance instruction is dynamically adjusted according to the actual machining data and the acoustic emission signal to obtain the tool maintenance instruction.

[0192] In a specific implementation manner, the dynamically adjusting the tool maintenance instruction according to the actual machining data and the acoustic emission signal to obtain the tool maintenance instruction includes:

[0193] Performing Fourier transform on the acoustic emission signal to obtain a frequency-domain signal;

[0194] According to the frequency-domain signal, calculate the power spectral density matrix through the following formula: ;

[0195] where, represents the power spectral density matrix, represents the frequency-domain signal, represents the acoustic emission signal;

[0196] According to the power spectral density matrix, use the support vector machine algorithm to determine the working cutting time of the tool;

[0197] Subtract the working cutting time from the expected cutting time to obtain deviation data;

[0198] Generate the following tool maintenance instruction according to the deviation data, a preset deviation threshold, the actual machining time and the expected machining time:

[0199] Compare the deviation data with the preset deviation threshold. If the deviation data is greater than the preset deviation threshold, increase the cutting depth so that the remaining cutting area is equal to the current cutting area;

[0200] If the deviation data is less than the preset deviation threshold, maintain the original cutting depth;

[0201] Compare the actual machining time with the expected machining time. If the actual machining time is greater than the expected machining time, return to compare the deviation data with the preset deviation threshold;

[0202] If the actual machining time is less than the expected machining time, the tool maintenance process ends.

[0203] Specifically, first, perform a Fourier transform on the acoustic emission signal to convert the time-domain signal into a frequency-domain signal. The purpose of this step is to decompose the complex time-domain signal into frequency components for subsequent analysis and processing.

[0204] According to the obtained frequency-domain signal, calculate the power spectral density matrix through the following formula: ;

[0205] where, represents the power spectral density matrix, represents the frequency-domain signal, represents the acoustic emission signal.

[0206] For example, there is an acoustic emission signal in the form of a two-dimensional array (matrix), where each column represents an independent signal measurement. Perform a Fourier transform on each column separately, then calculate the square of the amplitude of each frequency-domain signal to obtain the corresponding power spectral density, and combine the power spectral densities of each signal column into a new matrix by columns, which is the power spectral density matrix.

[0207] The power spectral density matrix obtained by this method can not only reflect the energy distribution of different frequency components in the original signal, but also be used for further analysis, such as identifying abnormal conditions during the cutting process of the tool. For example, if the power spectral density of a certain frequency suddenly increases, this is an indicator of tool wear or damage.

[0208] Subtract the determined tool working cutting time from the expected cutting time to obtain deviation data. The purpose of this step is to quantify the difference between the actual cutting time and the expected cutting time, so as to judge whether the working state of the tool is normal.

[0209] Generate a tool maintenance instruction based on the calculated deviation data, a preset deviation threshold, the actual machining time, and the expected machining time. The specific steps are as follows:

[0210] Compare the deviation data with the preset deviation threshold. If the deviation data is greater than the preset deviation threshold, it means that there is a large deviation in the working state of the tool and adjustment is required. The specific adjustment method is to increase the cutting depth so that the remaining cutting area is equal to the current cutting area. This can ensure that the tool can return to a normal working state during subsequent machining. If the deviation data is less than the preset deviation threshold, it means that the working state of the tool is basically normal and the original cutting depth can be maintained to continue machining.

[0211] Compare the actual processing time with the expected processing time. If the actual processing time is greater than the expected processing time, it indicates that the processing efficiency is low, and it is necessary to re - compare the deviation data to further adjust the working state of the tool. The specific steps are to return to compare the deviation data with the preset deviation threshold. If the actual processing time is less than the expected processing time, it indicates that the processing efficiency is high, the working state of the tool is good, and the tool maintenance process ends.

[0212] Through the above steps, the maintenance instructions of the tool can be dynamically adjusted to ensure that the tool maintains the best working state during the processing. These steps not only improve the processing efficiency, but also reduce the wear of the tool and improve the processing quality. The finally generated tool maintenance instructions will guide the maintenance and adjustment of the tool during the processing to ensure the smooth progress of the processing.

[0213] In step S16, the tool adjustment instruction, the tool use instruction, the tool movement instruction and the tool maintenance instruction are used as tool control instructions, and the processing process is controlled according to the tool control instructions.

[0214] First, integrate the tool adjustment instruction, the tool use instruction, the tool movement instruction and the tool maintenance instruction generated in the previous steps into a unified tool control instruction. The purpose of this step is to organically combine each instruction to form a complete control strategy to ensure that every link of the tool during the processing can be effectively managed and adjusted. Analyze the integrated tool control instruction into specific control parameters. These control parameters include the position, speed, acceleration, cutting depth, cutting speed, and feed speed of the tool. The purpose of the analysis is to convert the high - level control instruction into specific control parameters so that the control system can understand and execute. Then, send the analyzed control parameters to the control system. The control system is responsible for receiving and executing the control instructions to ensure that the tool processes according to the predetermined path and parameters.

[0215] The working process of the present invention is described below by taking a relatively common scenario as an example. The specific implementation manner of the present invention refers to Figure 1 , a control method applied to tool processing, including the following steps:

[0216] First, position sensors, speed sensors and acceleration sensors are installed on the numerically controlled machine tool, and these sensors monitor the current position, speed and acceleration of the tool in real time. Assume that the actual position of the current tool is , the actual speed is , and the actual acceleration is . At the same time, the expected position , the expected speed , and the expected acceleration of the tool are preset.

[0217] Calculate the position deviation: , and check whether the position deviation exceeds the preset error range (e.g., ±2 mm). Since the position deviation exceeds the preset error range, it is determined that the tool needs to be position-adjusted.

[0218] Then, compare the actual speed with the expected speed and calculate the speed deviation: , and check whether the speed deviation exceeds the preset error range (e.g., ±5 mm / s). Since the speed deviation exceeds the preset error range, it is determined that the tool needs to be speed-adjusted.

[0219] Finally, compare the actual acceleration with the expected acceleration and calculate the acceleration deviation: , and check whether the acceleration deviation exceeds the preset error range (e.g., ±2 mm / s²). Since the acceleration deviation exceeds the preset error range, it is determined that the tool needs to be acceleration-adjusted.

[0220] Calculate the remaining service life of the tool based on the actual machining data and the expected motion trajectory. Assume that the tool life cycle is 1000 hours, the initialization time is 0 hour, the tool life percentage given by the system is 80%, the current time is 500 hours, the average tool usage time evaluated by the system is 500 hours, the current usage time is 500 hours, and the remaining service life is 300 hours.

[0221] Assume that the expected machining time is 10 hours, the current machining time is 5 hours, the feed speed and acceleration correction factor is 1.1, the cutting speed and acceleration correction factor is 1.2, the normal machining speed is 60 mm / s, the normal machining acceleration is 12 mm / s², the prediction time is 1 hour, the increased feed and cutting time caused by tool adjustment is 0.5 hour, and the estimated time for the machining stage is 10 hours.

[0222] The calculated new feed speed is 66 mm / s and the cutting speed is 14.4 mm / s²:

[0223] Divide the expected motion trajectory into multiple path adjustment zones. Assume that the number of path adjustment zones is 5, the distance of each path adjustment zone is 100 mm, the remaining adjustment time is 2 hours, the historical expected acceleration is 12 mm / s², and the historical expected speed is 60 mm / s.

[0224] The calculated new expected acceleration for each path adjustment zone is 3.78 mm / s² and the new expected speed is 66 mm / s.

[0225] Perform a Fourier transform on the acoustic emission signal to obtain a frequency-domain signal. Assume the amplitude of the frequency-domain signal is 100, and calculate the power spectral density matrix.

[0226] Use the support vector machine algorithm to determine the working cutting time of the tool. Assume the working cutting time is 8 hours and the expected cutting time is 10 hours, and calculate the deviation data as 2 hours:

[0227] Compare the deviation data with a preset deviation threshold (e.g., ±1 hour). Since the deviation data is less than the preset deviation threshold, maintain the original cutting depth.

[0228] Integrate the above-generated tool adjustment instructions, tool usage instructions, tool movement instructions, and tool maintenance instructions into a unified tool control instruction.

[0229] Send the integrated control parameters to the control system. The control system adjusts the position, speed, and acceleration of the tool to ensure that the tool processes according to the optimized path. At the same time, the control system dynamically adjusts the movement parameters of the tool based on the real-time feedback of the processing data and the acoustic emission signal to ensure the smoothness and efficiency of the processing process.

[0230] In summary, we can monitor in real time and dynamically adjust the processing parameters of the tool to ensure the efficient, smooth, and reliable operation of the tool during the processing process, improving the processing quality and efficiency. The finally generated tool control instructions will guide every link in the processing process to ensure the smooth progress of the processing process.

[0231] Refer to Figure 2 , the second embodiment of the present invention provides a control device applied to tool processing, including:

[0232] A data acquisition module for acquiring the actual processing data of the tool, the expected movement trajectory, the tool service life, and the acoustic emission signal, where the actual processing data includes the actual position, actual speed, actual acceleration, and actual processing time;

[0233] A tool adjustment module for comparing the actual processing data with preset expected processing data and adjusting the tool according to the comparison result to obtain a tool adjustment instruction, where the expected processing data includes the expected position, expected speed, expected acceleration, and expected processing time;

[0234] A usage adjustment module for determining the remaining life cycle of the tool based on the actual processing data, the expected movement trajectory, and the tool service life, and dynamically adjusting the initial usage instruction of the tool to obtain a tool usage instruction;

[0235] A motion adjustment module, configured to dynamically generate an adjusted tool running route based on the expected motion trajectory through a tool path optimization algorithm, and obtain a tool motion instruction;

[0236] A maintenance adjustment module, configured to dynamically adjust an initial tool maintenance instruction according to the actual machining data and the acoustic emission signal, and obtain a tool maintenance instruction;

[0237] An output module, configured to use the tool adjustment instruction, the tool usage instruction, the tool motion instruction, and the tool maintenance instruction as tool control instructions, and obtain tool control instructions.

[0238] It should be noted that a control device applied to tool machining provided in an embodiment of the present invention is used to execute all process steps of a control method applied to tool machining in the above embodiment. The working principles and beneficial effects of the two correspond one by one, and thus will not be elaborated here.

[0239] An embodiment of the present invention further provides an electronic device. The electronic device includes: a processor, a memory, and a computer program stored in the memory and executable on the processor, such as a control program applied to tool machining. When the processor executes the computer program, the steps in the above embodiments of the control method applied to tool machining are implemented, such as Figure 1 step S11 shown. Alternatively, when the processor executes the computer program, the functions of each module / unit in the above device embodiments are implemented, such as a control module applied to tool machining.

[0240] Exemplarily, the computer program can be divided into one or more modules / units. The one or more modules / units are stored in the memory and executed by the processor to complete the present invention. The one or more modules / units can be a series of computer program instruction segments capable of performing specific functions, and the instruction segments are used to describe the execution process of the computer program in the electronic device.

[0241] The electronic device can be a computing device such as a desktop computer, a notebook, a palm computer, and a smart tablet. The electronic device may include, but is not limited to, a processor and a memory. Those skilled in the art can understand that the above components are only examples of the electronic device, and do not constitute a limitation on the electronic device. It may include more or fewer components than the above, or combine some components, or different components. For example, the electronic device may further include input / output devices, network access devices, a bus, etc.

[0242] The so-called processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The processor is the control center of the electronic device and connects all parts of the entire electronic device through various interfaces and circuits.

[0243] The memory can be used to store the computer programs and / or modules. The processor realizes various functions of the electronic device by running or executing the computer programs and / or modules stored in the memory, and by calling the data stored in the memory. The memory may mainly include a program storage area and a data storage area. Among them, the program storage area can store an operating system, application programs required for at least one function (such as a sound playback function, an image playback function, etc.); the data storage area can store data created according to the use of the mobile phone (such as audio data, phone book, etc.). In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, at least one magnetic disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0244] Among them, if the modules / units integrated in the electronic device are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, to implement all or part of the processes in the above-described embodiment methods of the present invention, it can also be completed by a computer program instructing relevant hardware. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-described various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content included in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0245] It should be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. In addition, in the attached drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which can be specifically implemented as one or more communication buses or signal lines. Those of ordinary skill in the art can understand and implement it without creative work.

[0246] The specific embodiments described above further elaborate on the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only the specific embodiments of the present invention and is not used to limit the protection scope of the present invention. It is particularly pointed out that for those skilled in the art, any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A control method applied to tool processing, characterized in that, Executed by the controller, including: Acquire actual processing data, expected motion trajectory, tool life and acoustic emission signal of the tool, wherein the actual processing data includes actual position, actual speed, actual acceleration and actual processing time; Comparing the actual processing data with preset expected processing data and adjusting the tool according to the comparison result to obtain a tool adjustment instruction, wherein the expected processing data includes an expected position, an expected speed, an expected acceleration and an expected processing time; Determine the remaining life cycle of the tool according to the actual processing data, the expected motion trajectory and the tool service life, and dynamically adjust the initial use instruction of the tool to obtain the tool use instruction; Based on the expected motion trajectory, the adjusted tool movement path is dynamically generated through a tool path optimization algorithm to obtain a tool movement instruction, including: Dividing the expected motion trajectory into a plurality of path adjustment regions to obtain a path adjustment area; Calculating a new expected acceleration and a new expected speed of each path adjustment zone based on the path adjustment area to obtain a new expected speed and a new expected acceleration; According to the new expected acceleration and the new expected speed, updating the expected acceleration and the expected speed in each path adjustment area and obtaining a tool motion instruction by using a tool path optimization algorithm tool path; Dynamically adjust the initial tool maintenance instruction according to the actual processing data and the acoustic emission signal to obtain the tool maintenance instruction; Using the tool adjustment instruction, the tool use instruction, the tool movement instruction and the tool maintenance instruction as tool control instructions, and controlling the machining process according to the tool control instructions; The step of comparing the actual processing data with the preset expected processing data and adjusting the tool according to the comparison result to obtain the tool adjustment instruction includes: Subtract the actual processing data from the expected processing data and take an absolute value to obtain error data; If the error data does not exceed the preset error range, the tool adjustment is completed; If the error data exceeds a preset error range, the remaining path length of the tool is calculated based on the actual processing data and the expected processing data; If the remaining path length is less than zero, the tool adjustment is completed; If the remaining path length is greater than zero, a midway adjustment position is calculated according to the actual processing data and the expected processing data; According to the mid-course adjustment position, the actual processing data and the expected processing data, the following tool adjustment instructions are obtained by reasoning and integrating: Controlling the tool to move from the actual position to the midway adjustment position, and adjusting the actual speed and the actual acceleration to the expected speed and the expected acceleration during the movement; When the tool moves to the midway adjustment position, it moves at a constant speed at the expected speed until it reaches the expected position; The remaining path length of the tool is calculated according to the following formula: ； Among them, the expected acceleration and mid-course adjustment position are solved by the following formula: ； ； Among them, represents the remaining path length of the tool, represents the expected adjustment path length of the tool, represents the actual position of the tool, represents the expected position of the tool; represents the mid-course adjustment position reached in the next execution cycle, represents the actual speed of the tool, represents the expected acceleration of the tool, the expected speed of the tool, represents the preset execution cycle.

2. The control method applied to tool machining according to claim 1, wherein, Determining the remaining life cycle of the tool based on the actual machining data, the expected motion trajectory, and the tool service life, and dynamically adjusting the initial tool usage instruction to obtain a tool usage instruction, including: Calculating the remaining time for the tool to reach the expected position based on the expected motion trajectory of the tool; Calculating the remaining life cycle of the tool based on the pre-calculated motion deviation index and the actual machining data; Comparing the remaining life cycle with the tool service life to obtain the following tool usage instruction: If the remaining life cycle reaches the tool service life, calculating the tool adjustment strategy for the expected position and adjusting the expected motion trajectory; If the remaining life cycle does not reach the tool service life, updating the expected machining time corresponding to the expected motion trajectory according to the remaining time and the preset process parameters; Among them, the remaining time for the tool to reach the expected position is calculated by the following formula: ; Among them, the motion deviation index is calculated according to the following formula: ； Among them, the remaining life cycle of the tool is calculated according to the following formula: ； Among them, the expected machining time is calculated through the following formula: ； Among them, represents the remaining time, represents the distance from the expected motion trajectory to the next expected position, represents the expected motion speed, represents the motion deviation index, represents the upper threshold value of the preset motion deviation index, the lower threshold value of the preset motion deviation index, represents the actual machining error, represents the upper threshold value of the preset actual machining error, represents the lower threshold value of the preset actual machining error, represents the preset least squares optimization parameter, represents the preset execution cycle, represents the remaining life cycle, represents the actual speed, and represents the preset parameters in the tool service life model, represents the expected machining time, represents the cutting time, represents the cutting path length, represents the tool feed speed, represents the spindle speed.

3. The control method applied to tool processing according to claim 2, wherein The calculating the tool adjustment strategy for the expected position and adjusting the expected motion trajectory includes: Taking the expected motion trajectory as the initial state and the position corresponding to the remaining time as the desired state to obtain the initial state and the desired state; Adjusting the expected speed and expected acceleration according to the initial state and the desired state; Calculating the usage instruction of the tool motion trajectory according to the following minimization objective function: ； Among them, represents the remaining time, represents the expected acceleration of the tool, the expected speed of the tool, and represents the preset weight coefficient, represents the objective function; among them, the usage instruction includes the adjusted expected acceleration and expected speed; Adjusting the expected motion trajectory according to the usage instruction to obtain a new expected motion trajectory.

4. The control method applied to tool processing according to claim 1, wherein The tool path optimization algorithm includes: Define the machining model: Indicates the number of machining trajectory points in the machining area, Indicates the th machining trajectory point, Indicates the curvature of the machining trajectory point, Indicates the distance between two adjacent machining trajectory points; Calculate the weighted speed and weighted acceleration of the tool in the phase according to the following formula: ； Among them, represents the weighted speed, represents the expected speed, represents the actual speed, represents the weighted acceleration, represents the expected acceleration, represents the actual acceleration, and represents the preset weighted factor; Calculating the feed speed and cutting speed according to the following formula: ； Among them, represents the feed rate, represents the cutting speed, represents the curvature of the current trajectory point, and represents the preset weighting factor; Generating an optimized tool path through the following function: ； Among them, represents the th machining trajectory point, represents the weighted speed of the th machining trajectory point, represents the weighted acceleration of the th machining trajectory point, represents the feed speed of the th machining trajectory point, represents the cutting speed of the th machining trajectory point, represents the distance from the th machining trajectory point to the th - 1 machining trajectory point.

5. The control method applied to tool machining according to claim 2, wherein The dynamically adjusting the tool maintenance instruction according to the actual machining data and the acoustic emission signal to obtain a tool maintenance instruction includes: Performing Fourier transform on the acoustic emission signal to obtain a frequency domain signal; According to the frequency-domain signal, calculate the power spectral density matrix through the following formula: ; Among them, represents the power spectral density matrix, represents the frequency-domain signal, represents the acoustic emission signal; Determining the working cutting time of the tool using the support vector machine algorithm according to the power spectral density matrix; Taking the difference between the working cutting time and the expected cutting time to obtain deviation data; Generating the following tool maintenance instruction according to the deviation data, the preset deviation threshold, the actual machining time, and the expected machining time: Comparing the deviation data with the preset deviation threshold. If the deviation data is greater than the preset deviation threshold, increasing the cutting depth so that the remaining cutting area is equal to the current cutting area; If the deviation data is less than the preset deviation threshold, maintaining the original cutting depth; Comparing the actual machining time with the expected machining time. If the actual machining time is greater than the expected machining time, returning to compare the deviation data with the preset deviation threshold; If the actual machining time is less than the expected machining time, the tool maintenance process ends.

6. A control device applied to tool processing, characterized in that, For implementing a control method applied to tool machining as described in any one of claims 1 to 5, including: A data acquisition module for obtaining the actual machining data, expected motion trajectory, tool service life, and acoustic emission signal of a tool, where the actual machining data includes actual position, actual speed, actual acceleration, and actual machining time; A tool adjustment module for comparing the actual machining data with preset expected machining data and adjusting the tool according to the comparison result to obtain a tool adjustment instruction, where the expected machining data includes expected position, expected speed, expected acceleration, and expected machining time; A usage adjustment module for determining the remaining life cycle of the tool based on the actual machining data, the expected motion trajectory, and the tool service life, and dynamically adjusting the initial usage instruction of the tool to obtain a tool usage instruction; A motion adjustment module for dynamically generating an adjusted tool running route based on the expected motion trajectory through a tool path optimization algorithm to obtain a tool motion instruction; A maintenance adjustment module for dynamically adjusting the initial tool maintenance instruction according to the actual machining data and the acoustic emission signal to obtain a tool maintenance instruction; An output module for using the tool adjustment instruction, the tool usage instruction, the tool motion instruction, and the tool maintenance instruction as tool control instructions to obtain tool control instructions.

7. An electronic device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the control method for tool machining described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored computer program. When the computer program runs, it controls the device where the computer-readable storage medium is located to execute the control method for tool machining described in any one of claims 1 to 5.

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