Adaptive control system and method for numerical control machine tool

Abstract

The invention discloses a self-adaptive control system and method for a numerical control machine tool. The system comprises a numerical control machine tool, a data processing module, a working condition judgment module, a self-adaptive control module and an output control module, the data processing module comprises a data acquisition unit and a preprocessing unit, and the data acquisition unit is composed of a plurality of sensors and is used for acquiring a plurality of operation parameters at regular time; wherein the numerical control machine tool is connected with the data acquisition unit in the data processing module, the data acquisition unit is connected with the preprocessing unit, the preprocessing unit is connected with the working condition judgment module, the working condition judgment module is connected with the self-adaptive control module, and the self-adaptive control module is connected with the output control module. According to the embodiment of the invention, by automatically adjusting the cutting parameters and controlling the axial movement, not only can unnecessary energy consumption and material waste be reduced, but also the system can adapt to complex geometrical shapes and machining requirements, and the flexibility enables the system to adapt to various complex and variable machining tasks.

Description

Technical Field

[0001] The present invention relates to the technical field of CNC machine tool processing monitoring and control, and in particular to a CNC machine tool adaptive control system and method. Background Art

[0002] In the manufacturing of aircraft parts, as aircraft structural parts become larger and more complex, the difficulty of processing parts continues to increase. Due to the low level of intelligence, existing processing machine tools are unable to perform adaptive processing of workpieces and still use fixed processes. Therefore, it is difficult to meet the complex and changeable working conditions during part processing.

[0003] Adaptive adjustment and compensation of the parts processing process is an effective means to solve the above problems. The adaptive control system can automatically adjust the processing parameters according to the equipment load, temperature changes and other conditions during the processing, so that the potential of the equipment can be fully utilized, improving the equipment production efficiency and the service life of the tool. Summary of the invention

[0004] Based on this, the present invention provides an adaptive control system and method for a CNC machine tool to solve the problem that traditional CNC machine tools cannot perform adaptive processing of workpieces.

[0005] In a first aspect, an embodiment of the present invention provides an adaptive control system for a numerically controlled machine tool, the system comprising: a numerically controlled machine tool, a data processing module, a working condition judgment module, an adaptive control module, and an output control module;

[0006] The data processing module includes a data acquisition unit and a preprocessing unit, wherein the data acquisition unit is composed of a plurality of sensors and is used to regularly acquire a plurality of operating parameters;

[0007] The CNC machine tool is connected to the data acquisition unit in the data processing module, the data acquisition unit is connected to the preprocessing unit, the preprocessing unit is connected to the working condition judgment module, the working condition judgment module is connected to the adaptive control module, and the adaptive control module is connected to the output control module;

[0008] The data processing unit is used to extract features of the collected multiple operating parameters in real time to obtain multiple machine tool features;

[0009] The working condition judgment module is used to receive multiple machine tool features from the data processing unit, and perform working condition judgment according to a pre-established working condition judgment strategy. If the working condition of the operating parameter is judged to be abnormal, the abnormal cutting parameter corresponding to the abnormal operating parameter is obtained, and the abnormal cutting parameter is sent to the adaptive control module;

[0010] The adaptive control module is used to receive the abnormal cutting parameters transmitted from the working condition judgment module, and adaptively adjust the abnormal cutting parameters according to a preset adaptive algorithm;

[0011] The output control module is used to receive the cutting parameters adjusted by the adaptive control module and control the axial movement of the machine tool according to the cutting parameters.

[0012] Further, the data acquisition unit includes a temperature sensor, a position sensor, a force sensor and a speed sensor, wherein the target CNC machine tool is respectively connected to each sensor of the data acquisition unit;

[0013] A temperature sensor is used to collect the machine temperature of the target CNC machine tool based on a time period and send it to the working condition judgment module;

[0014] A force sensor is used to collect the cutting load of the target CNC machine tool based on a time period and send it to the working condition judgment module;

[0015] A position sensor is used to receive a coordinate acquisition instruction from an output control module, collect the target position coordinates of each axis of the target CNC machine tool, and send them to the output control module;

[0016] The speed sensor is used to receive the data acquisition instruction issued by the working condition judgment module, collect the target cutting parameters of the target CNC machine tool, and send them to the adaptive control module.

[0017] Furthermore, the working condition judgment module also includes a temperature abnormality judgment unit and a cutting force abnormality judgment unit;

[0018] The temperature abnormality determination unit is used to compare the machine temperature of the target CNC machine tool with the temperature threshold, and when the machine temperature data is greater than the temperature threshold, obtain the abnormal cutting parameters under the current abnormal machine temperature through the speed sensor in the data acquisition unit;

[0019] The cutting force abnormality determination unit is used to compare the cutting load of the target CNC machine tool with a load threshold. When the cutting load is greater than the load threshold, the abnormal cutting parameters under the current abnormal cutting load are obtained through the speed sensor in the data acquisition unit.

[0020] Further, the adaptive control module includes an adaptive updating unit, an adaptive compensation unit and a cutting parameter adjustment unit;

[0021] The adaptive updating unit is used to receive the abnormal cutting parameters sent by the working condition judgment module, and substitute the abnormal cutting parameters into the pre-built adaptive updating algorithm to calculate the adaptive cutting parameters;

[0022] The adaptive compensation unit is used to receive the new cutting parameters sent by the cutting parameter adjustment unit, and substitute the new cutting parameters into the pre-built adaptive compensation algorithm to calculate the cutting compensation amount;

[0023] The cutting parameter adjustment unit is used to receive the adaptive cutting parameter in the adaptive updating unit and the cutting compensation amount in the adaptive compensation unit, and calculate the sum of the adaptive cutting parameter and the cutting compensation amount to obtain a new cutting parameter.

[0024] Furthermore, the output control module further includes a path planning unit and a servo unit;

[0025] The path planning unit is used to send a coordinate acquisition instruction to the position sensor after receiving the new cutting parameters obtained from the cutting parameter adjustment unit, and receive the original target position coordinates of each axis of the target CNC machine tool collected from the position sensor, and obtain the new target position coordinates of each axis of the target CNC machine tool according to a preset position coordinate and cutting parameter relationship library;

[0026] The servo unit is used to receive the new target position coordinates of each axis of the target CNC machine tool sent from the path planning unit, and drive each axis of the machine tool to move according to the new target position coordinates based on the original target position coordinates.

[0027] Furthermore, the system further comprises a reinforcement learning module, wherein the reinforcement learning module is respectively connected to the data processing module, the adaptive control module and the working condition judgment module;

[0028] The reinforcement learning module is used to obtain multiple operating parameters in the preprocessing unit according to a specified period; the multiple operating parameters are input into the original machine learning model to obtain a library of machine tool temperature and cutting parameter relationships, a library of cutting load and cutting parameter relationships, and a library of position coordinates and cutting parameter relationships respectively;

[0029] At the same time, it is also used to obtain abnormal cutting parameters in the working condition judgment module according to the specified period, and build an adaptive update algorithm and an adaptive compensation algorithm based on the abnormal cutting parameters and the preset original cutting parameters, and synchronize the adaptive update algorithm to the adaptive update unit, and synchronize the adaptive compensation algorithm to the adaptive compensation unit.

[0030] In a second aspect, an embodiment of the present invention provides a method for adaptive control of a CNC machine tool, the method comprising:

[0031] Through the data acquisition unit, multiple operating parameters are collected regularly;

[0032] Through the data processing unit, the collected multiple operating parameters are subjected to real-time feature extraction to obtain multiple machine tool features;

[0033] The working condition judgment module receives a plurality of machine tool features from the data processing unit, and judges the working condition according to a pre-established working condition judgment strategy. If the working condition of the operating parameter is judged to be abnormal, the abnormal cutting parameter corresponding to the abnormal operating parameter is obtained, and the abnormal cutting parameter is sent to the adaptive control module.

[0034] The adaptive control module receives the abnormal cutting parameters transmitted from the working condition judgment module, and adaptively adjusts the abnormal cutting parameters according to a preset adaptive algorithm;

[0035] The output control module receives the cutting parameters adjusted by the adaptive control module, and controls the axial movement of the machine tool according to the cutting parameters.

[0036] The technical solution of the embodiment of the present invention monitors the operating status of the target CNC machine tool by regularly collecting and processing the operating parameter data during the CNC machine tool processing. When the data is abnormal, the cutting parameters at the abnormal moment can be adaptively adjusted, and the motion displacement of each axial direction of the machine tool can be controlled according to the adjusted cutting parameters to achieve adaptive control. By automatically adjusting the cutting parameters and axial motion control, not only can unnecessary energy consumption and material waste be reduced, but also complex geometric shapes and processing requirements can be adapted. This flexibility enables the system to adapt to various complex and changeable processing tasks.

[0037] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0039] Figure 1 Schematic diagram of the overall connection relationship of a CNC machine tool adaptive control system provided according to the first embodiment of the present invention;

[0040] Figure 2 is a flow chart of a CNC machine tool adaptive control method provided according to Embodiment 2 of the present invention;

[0041] Figure 3 It is a schematic diagram of the connection relationship between a reinforcement learning module and other functional modules applicable to an embodiment of the present invention;

[0042] Figure 4Schematic diagram of the internal expansion of each functional module of a CNC machine tool adaptive control system applicable to an embodiment of the present invention

[0043] Figure 5 It is a schematic diagram of the connection relationship of internal subunits of an output control module applicable to an embodiment of the present invention. DETAILED DESCRIPTION

[0044] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0045] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0046] Embodiment 1

[0047] Figure 1 A schematic diagram of an adaptive control system for a CNC machine tool provided in Embodiment 1 of the present invention, the system comprising:

[0048] CNC machine tool (S1), data processing module (S2), working condition judgment module (S3), adaptive control module (S4) and output control module (S5);

[0049] The data processing module (S2) comprises a data acquisition unit (S21) and a preprocessing unit (S22), wherein the data acquisition unit is composed of a plurality of sensors and is used to regularly acquire a plurality of operating parameters;

[0050] The numerical control machine tool (S1) is connected to a data acquisition unit in a data processing module, the data acquisition unit is connected to a preprocessing unit, the preprocessing unit is connected to a working condition judgment module, the working condition judgment module is connected to an adaptive control module, and the adaptive control module is connected to an output control module;

[0051] The data processing unit is used to extract features of the collected multiple operating parameters in real time to obtain multiple machine tool features;

[0052] The working condition judgment module is used to receive multiple machine tool features from the data processing unit, and perform working condition judgment according to a pre-established working condition judgment strategy. If the working condition of the operating parameter is judged to be abnormal, the abnormal cutting parameter corresponding to the abnormal operating parameter is obtained, and the abnormal cutting parameter is sent to the adaptive control module;

[0053] The adaptive control module is used to receive the abnormal cutting parameters transmitted from the working condition judgment module, and adaptively adjust the abnormal cutting parameters according to a preset adaptive algorithm;

[0054] The output control module is used to receive the cutting parameters adjusted by the adaptive control module and control the axial movement of the machine tool according to the cutting parameters.

[0055] In the aircraft manufacturing process, most aircraft parts have complex structures, large outline dimensions, and high processing precision requirements, which put forward high requirements on the selection and use of CNC machine tools. With the rapid development of modern aviation manufacturing industry, CNC machine tools have initially formed key technical advantages represented by the manufacturing of large and complex aircraft structures in the aviation manufacturing industry. Especially in the processing and manufacturing of typical aircraft parts, adaptive processing control of CNC machine tools will help promote the development of CNC machine tools in terms of processing reliability and tool cutting efficiency.

[0056] Specifically, in the CNC machine tool adaptive control system designed in the embodiment of the present invention, the operation status of the CNC machine tool is monitored by regularly collecting multiple machine tool operation parameters of the CNC machine tool (S1). Each machine tool operation parameter is acquired by relying on a specific sensor, and multiple sensors constitute a data acquisition unit (S21). The collected different types of operation parameters are sent to a preprocessing unit (S22) for filtering, normalization and other processing to ensure the quality and consistency of the operation parameters, and then frequency domain features or time domain features are extracted to describe key information in the processing process, and multiple machine tool features are obtained.

[0057] In practical applications, the working condition determination strategy is to determine whether the current state of the target machine tool is normal based on the value of the operating parameter obtained based on prior knowledge. For example, when the value of a certain operating parameter exceeds the normal threshold specified in the working condition determination strategy, the machine tool needs to be adaptively controlled. The cutting parameters can refer to the spindle speed and feed speed. When the operating parameters of the target machine tool are at different values, the corresponding spindle speed and feed speed are different. Therefore, when the operating parameters are determined to be abnormal, the cutting parameters under the abnormal operating parameters are also abnormal, that is, the speed and feed speed are abnormal.

[0058] The pre-set adaptive algorithm refers to adaptively adjusting the abnormal cutting parameters to restore the normal rotation speed and feed speed of the target machine tool. When the cutting parameters return to normal, the working state of the target machine tool returns to normal, that is, all operating parameters return to normal.

[0059] The embodiment of the present invention monitors the operating status of the target CNC machine tool by regularly collecting and processing the operating parameter data during the CNC machine tool processing. When the data is abnormal, the cutting parameters at the abnormal moment can be adaptively adjusted, and the motion displacement of each axial direction of the machine tool can be controlled according to the adjusted cutting parameters to achieve adaptive control. By automatically adjusting the cutting parameters and axial motion control, not only can unnecessary energy consumption and material waste be reduced, but also complex geometric shapes and processing requirements can be adapted. This flexibility enables the system to adapt to various complex and changeable processing tasks.

[0060] Optionally, the data acquisition unit includes a temperature sensor, a position sensor, a force sensor, and a speed sensor, wherein the target CNC machine tool is connected to each sensor of the data acquisition unit respectively;

[0061] A temperature sensor is used to collect the machine temperature of the target CNC machine tool based on a time period and send it to the working condition judgment module through a preprocessing unit;

[0062] A force sensor is used to collect the cutting load of the target CNC machine tool based on a time period and send it to the working condition judgment module through a preprocessing unit;

[0063] A position sensor is used to receive a coordinate acquisition instruction from the output control module, collect the target position coordinates of each axis of the target CNC machine tool, and send them to the output control module via a preprocessing unit;

[0064] The speed sensor is used to receive the data acquisition instruction issued by the working condition judgment module, collect the target cutting parameters of the target CNC machine tool, and send them to the adaptive control module through the preprocessing unit.

[0065] Temperature sensors can be used to measure the temperature of machine tools and cutting tools to avoid the influence of overheating and thermal deformation on processing accuracy; force sensors can be used to measure cutting loads in order to monitor the mechanical properties of the cutting process in real time; position sensors can be used to measure the position and motion status of each axis of the machine tool, such as grating scales and encoders; speed sensors can be used to collect, for example, the current spindle speed and feed speed of the target machine tool.

[0066] Optionally, the working condition judgment module further includes a temperature abnormality judgment unit and a cutting force abnormality judgment unit;

[0067] The temperature abnormality determination unit is used to compare the machine temperature of the target CNC machine tool with the temperature threshold, and when the machine temperature data is greater than the temperature threshold, obtain the abnormal cutting parameters under the current abnormal machine temperature through the speed sensor in the data acquisition unit;

[0068] The cutting force abnormality determination unit is used to compare the cutting load of the target CNC machine tool with a load threshold. When the cutting load is greater than the load threshold, the abnormal cutting parameters under the current abnormal cutting load are obtained through the speed sensor in the data acquisition unit.

[0069] In the working condition determination strategy, the basic threshold value of each operating parameter is pre-set. When the temperature operating parameter collected by the temperature sensor or the cutting load operating parameter collected by the force sensor exceeds the corresponding basic threshold value, the working condition determination module sends a data acquisition signal to the speed sensor. After receiving the data acquisition signal, the speed sensor collects the cutting parameters under the current working condition of the target machine tool and sends them to the adaptive update unit for adaptive adjustment.

[0070] Optionally, the adaptive control module includes an adaptive updating unit, an adaptive compensation unit and a cutting parameter adjustment unit;

[0071] The adaptive updating unit is used to receive the abnormal cutting parameters sent by the working condition judgment module, and substitute the abnormal cutting parameters into the pre-built adaptive updating algorithm to calculate the control error and the new cutting parameters;

[0072] The adaptive compensation unit is used to receive the control error sent by the cutting parameter adjustment unit, and substitute the control error into the pre-built adaptive compensation algorithm to calculate the cutting compensation amount; the cutting parameter adjustment unit is used to receive the new cutting parameters in the adaptive update unit and the cutting compensation amount in the adaptive compensation unit, and calculate the sum of the new cutting parameters and the cutting compensation amount to obtain the adaptive cutting parameters.

[0073] Specifically, in the adaptive update algorithm, the initial cutting parameter μ0 and the expected output r(k) are preset. The expected output r(k) is the standard operating parameters corresponding to the initial cutting parameter μ0. The abnormal operating parameters are used as the actual output y(k). The control error between the expected output and the actual output can be obtained. The specific calculation formula is: e(k) = r(k) - y(k);

[0074] Among them, e(k) represents the control error at time k. The cutting adjustment amount of the cutting parameters is calculated based on the control error. The algorithm formula is:

[0075] Δu(k)=K·e(k);

[0076] Wherein, K is a preset gain matrix, Δu(k) is a cutting parameter adjustment amount, and the cutting parameter adjustment amount is added to the initial cutting parameter to obtain a new cutting parameter u(k), that is: u(k)=u0+Δu(k).

[0077] In the adaptive compensation unit, the required cutting compensation is calculated by controlling the error to correct the error that occurs during the machining process. The specific algorithm formula is: C(k) = K c e(k);

[0078] Among them, C(k) represents the cutting compensation at time k, K c Represents the compensation factor.

[0079] Finally, in the cutting parameter adjustment unit, the new cutting parameter u(k) and the cutting compensation amount C(k) are obtained and summed to obtain the final adaptive cutting parameter, which is denoted as U k , the specific algorithm formula is: k =Δu(k)+C(k).

[0080] Optionally, the output control module further includes a path planning unit and a servo unit;

[0081] The path planning unit is used to send a coordinate acquisition instruction to the position sensor after receiving the adaptive cutting parameters obtained from the cutting parameter adjustment unit, and receive the original target position coordinates of each axis of the target CNC machine tool collected by the position sensor, and obtain the new target position coordinates of each axis of the target CNC machine tool according to a preset position coordinate and cutting parameter relationship library;

[0082] The servo unit is used to receive the new target position coordinates of each axis of the target CNC machine tool sent from the path planning unit, and drive each axis of the machine tool to move according to the new target position coordinates based on the original target position coordinates.

[0083] The servo unit is composed of a plurality of servo devices, which are used to drive the movement of each axis of the target machine tool according to the new target position coordinates, and perform position control and speed regulation.

[0084] Optionally, the system further includes a reinforcement learning module, wherein the reinforcement learning module is respectively connected to the data processing module, the adaptive control module and the working condition judgment module;

[0085] The reinforcement learning module is used to obtain multiple operating parameters in the preprocessing unit according to a specified period; the multiple operating parameters are input into the original machine learning model to obtain a library of machine tool temperature and cutting parameter relationships, a library of cutting load and cutting parameter relationships, and a library of position coordinates and cutting parameter relationships respectively;

[0086] At the same time, it is also used to obtain abnormal cutting parameters in the working condition judgment module according to the specified period, and build an adaptive update algorithm and an adaptive compensation algorithm based on the abnormal cutting parameters and the preset original cutting parameters, and synchronize the adaptive update algorithm to the adaptive update unit, and synchronize the adaptive compensation algorithm to the adaptive compensation unit.

[0087] The library of machine tool temperature and cutting parameter relationship includes the mapping relationship between machine tool temperature and cutting parameters. Based on this mapping relationship, the expected output value of machine tool temperature under the initial cutting parameter μ0 can be obtained in the adaptive update algorithm. Similarly, the library of cutting load and cutting parameter relationship includes the mapping relationship between cutting load and cutting parameters. In the adaptive update algorithm, the expected output value of cutting load under the initial cutting parameter μ0 can be obtained. The library of position coordinates and cutting parameter relationship includes the mapping relationship between the position of each axis of the target machine tool and the cutting parameters. In the path planning unit, the position of each axis of the current target machine tool can be obtained according to the abnormal cutting parameter μ0, and according to the adaptive cutting parameter U k The new target machine tool axis position coordinates are obtained, and the machine tool is driven from the current position to the new position based on the servo unit.

[0088] Embodiment 2

[0089] Figure 2 This is a flow chart of a CNC machine tool adaptive control method provided in the second embodiment of the present invention. This embodiment can be applied to the case of controlling a CNC machine tool to perform adaptive processing. The method can be executed by a CNC machine tool adaptive control system, which can be configured in a CNC machine tool for part processing. Figure 2 As shown, the method includes:

[0090] S210, regularly collecting multiple operating parameters through a data collection unit;

[0091] S220, extracting features of the collected multiple operating parameters in real time through a data processing unit to obtain multiple machine tool features;

[0092] S230, receiving multiple machine tool features from the data processing unit through the working condition judgment module, and performing working condition judgment according to a pre-established working condition judgment strategy, if the working condition of the operating parameter is determined to be abnormal, obtaining abnormal cutting parameters corresponding to the abnormal operating parameters, and sending the abnormal cutting parameters to the adaptive control module;

[0093] S240, receiving the abnormal cutting parameters transmitted from the working condition judgment module through the adaptive control module, and adaptively adjusting the abnormal cutting parameters according to a preset adaptive algorithm;

[0094] S250, receiving the cutting parameters adjusted by the adaptive control module through the output control module, and controlling the axial movement of the machine tool according to the cutting parameters.

[0095] Optionally, the method may further include:

[0096] Through the reinforcement learning module, multiple operating parameters in the preprocessing unit are obtained according to the specified cycle; the multiple operating parameters are input into the original machine learning model to obtain the relationship library between machine tool temperature and cutting parameters, the relationship library between cutting load and cutting parameters, and the relationship library between position coordinates and cutting parameters respectively;

[0097] At the same time, the abnormal cutting parameters in the working condition judgment module are obtained according to the specified period, and based on the abnormal cutting parameters and the preset original cutting parameters, an adaptive update algorithm and an adaptive compensation algorithm are constructed, and the adaptive update algorithm is synchronized to the adaptive update unit, and the adaptive compensation algorithm is synchronized to the adaptive compensation unit.

[0098] Among them, the reinforcement learning module is connected with the data processing module to obtain the mapping relationship between the operating parameters and the cutting parameters, and is synchronously updated to the adaptive update unit; at the same time, it is connected with the working condition judgment module to obtain two adaptive algorithms, which are synchronized to the adaptive update unit respectively. Figure 3 A schematic diagram showing the connection relationship between a reinforcement learning module and other functional modules in the system.

[0099] Furthermore, the adaptive control module receives the abnormal cutting parameters transmitted from the working condition judgment module, and adaptively adjusts the abnormal cutting parameters according to a preset adaptive algorithm, which may include:

[0100] The adaptive updating unit receives abnormal cutting parameters sent from the working condition judgment module, and substitutes the abnormal cutting parameters into a pre-built adaptive updating algorithm to calculate adaptive cutting parameters;

[0101] The adaptive compensation unit receives new cutting parameters sent by the cutting parameter adjustment unit, and substitutes the new cutting parameters into a pre-built adaptive compensation algorithm to calculate a cutting compensation amount;

[0102] The cutting parameter adjustment unit receives the adaptive cutting parameter in the adaptive updating unit and the cutting compensation amount in the adaptive compensation unit, and calculates the sum of the adaptive cutting parameter and the cutting compensation amount to obtain a new cutting parameter.

[0103] Easy to understand, Figure 4 FIG. 1 shows a schematic diagram of detailed connection relationships of each functional module in a CNC machine tool adaptive control system according to an embodiment of the present invention after expansion, wherein Figure 1 On this basis, the data flow of each sensor in the data acquisition unit, the abnormal judgment units contained in the operating condition judgment module, and the data processing sequence of each unit in the adaptive control module are demonstrated.

[0104] Optionally, receiving the cutting parameters adjusted by the adaptive control module through the output control module and controlling the axial movement of the machine tool according to the cutting parameters may include:

[0105] After receiving the new cutting parameters from the cutting parameter adjustment unit through the path planning unit, a coordinate acquisition instruction is sent to the position sensor, and the original target position coordinates of each axis of the target CNC machine tool collected by the position sensor are received, and the new target position coordinates of each axis of the target CNC machine tool are obtained according to the preset position coordinate and cutting parameter relationship library;

[0106] The servo unit is used to receive the new target position coordinates of each axis of the target CNC machine tool sent from the path planning unit, and drive each axis of the machine tool to move according to the new target position coordinates based on the original target position coordinates.

[0107] Easy to understand, Figure 5 The internal sub-unit connection diagram of the output control module is shown, and the data source of the output control unit and the specific application of the data are described.

[0108] The embodiment of the present invention proposes an adaptive control method for CNC machine tools. Specifically, the data stand-alone unit periodically collects the operating parameters of the target CNC machine tool and sends them to the working condition judgment unit after preprocessing. The working condition judgment unit judges whether the operating parameters are abnormal based on the working condition judgment strategy. If abnormal, the abnormal cutting parameters under the current abnormal operating parameters are obtained, and the abnormal cutting parameters are adaptively adjusted through the adaptive control module. The output control module controls the target CNC machine tool according to the adaptive adjustment result. Among them, the reinforcement learning module is used to regularly update the mapping relationship between the cutting parameters and the operating parameters and the adaptive algorithm, and synchronize them to the adaptive control module, which enhances the autonomous learning and optimization capabilities of the system and can ensure the efficient operation of the machine tool under different processing conditions. At the same time, the adjustment of the cutting parameters through the adaptive algorithm can compensate for the errors in the processing process, thereby improving the processing accuracy and stability.

[0109] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0110] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A CNC machine tool adaptive control system, characterized in that: include: CNC machine tools, data processing modules, working condition judgment modules, adaptive control modules and output control modules; The data processing module includes a data acquisition unit and a preprocessing unit, wherein the data acquisition unit is composed of a plurality of sensors and is used to regularly acquire a plurality of operating parameters; The CNC machine tool is connected to the data acquisition unit in the data processing module, the data acquisition unit is connected to the preprocessing unit, the preprocessing unit is connected to the working condition judgment module, the working condition judgment module is connected to the adaptive control module, and the adaptive control module is connected to the output control module; The data processing unit is used to extract features of the collected multiple operating parameters in real time to obtain multiple machine tool features; The working condition judgment module is used to receive multiple machine tool features from the data processing unit, and perform working condition judgment according to a pre-established working condition judgment strategy. If the working condition of the operating parameter is judged to be abnormal, the abnormal cutting parameter corresponding to the abnormal operating parameter is obtained, and the abnormal cutting parameter is sent to the adaptive control module; The adaptive control module is used to receive the abnormal cutting parameters transmitted from the working condition judgment module, and adaptively adjust the abnormal cutting parameters according to a preset adaptive algorithm; The output control module is used to receive the cutting parameters adjusted by the adaptive control module and control the axial movement of the machine tool according to the cutting parameters.

2. The system according to claim 1, characterized in that The data acquisition unit includes a temperature sensor, a position sensor, a force sensor and a speed sensor, wherein the target CNC machine tool is respectively connected to each sensor of the data acquisition unit; A temperature sensor is used to collect the machine temperature of the target CNC machine tool based on a time period and send it to the working condition judgment module through a preprocessing unit; A force sensor is used to collect the cutting load of the target CNC machine tool based on a time period and send it to the working condition judgment module through a preprocessing unit; A position sensor is used to receive a coordinate acquisition instruction from the output control module, collect the target position coordinates of each axis of the target CNC machine tool, and send them to the output control module via a preprocessing unit; The speed sensor is used to receive the data acquisition instruction issued by the working condition judgment module, collect the target cutting parameters of the target CNC machine tool, and send them to the adaptive control module through the preprocessing unit.

3. The system according to claim 1, characterized in that The working condition judgment module also includes a temperature abnormality judgment unit and a cutting force abnormality judgment unit; The temperature abnormality determination unit is used to compare the machine temperature of the target CNC machine tool with the temperature threshold, and when the machine temperature data is greater than the temperature threshold, obtain the abnormal cutting parameters under the current abnormal machine temperature through the speed sensor in the data acquisition unit; The cutting force abnormality determination unit is used to compare the cutting load of the target CNC machine tool with a load threshold. When the cutting load is greater than the load threshold, the abnormal cutting parameters under the current abnormal cutting load are obtained through the speed sensor in the data acquisition unit.

4. The system according to claim 1, characterized in that The adaptive control module includes an adaptive updating unit, an adaptive compensation unit and a cutting parameter adjustment unit; The adaptive updating unit is used to receive the abnormal cutting parameters sent by the working condition judgment module, and substitute the abnormal cutting parameters into the pre-built adaptive updating algorithm to calculate the control error and the new cutting parameters; The adaptive compensation unit is used to receive the control error sent by the cutting parameter adjustment unit, and substitute the control error into a pre-built adaptive compensation algorithm to calculate the cutting compensation amount; The cutting parameter adjustment unit is used to receive the new cutting parameter in the adaptive updating unit and the cutting compensation amount in the adaptive compensation unit, and calculate the sum of the new cutting parameter and the cutting compensation amount to obtain the adaptive cutting parameter.

5. The system according to claim 4, characterized in that The output control module also includes a path planning unit and a servo unit; The path planning unit is used to send a coordinate acquisition instruction to the position sensor after receiving the adaptive cutting parameters obtained from the cutting parameter adjustment unit, and receive the original target position coordinates of each axis of the target CNC machine tool collected by the position sensor, and obtain the new target position coordinates of each axis of the target CNC machine tool according to a preset position coordinate and cutting parameter relationship library; The servo unit is used to receive the new target position coordinates of each axis of the target CNC machine tool sent from the path planning unit, and drive each axis of the machine tool to move according to the new target position coordinates based on the original target position coordinates.

6. The system according to claim 1, characterized in that The system further includes a reinforcement learning module, wherein the reinforcement learning module is respectively connected to the data processing module, the adaptive control module and the working condition judgment module; The reinforcement learning module is used to obtain multiple operating parameters in the preprocessing unit according to a specified period; the multiple operating parameters are input into the original machine learning model to obtain a library of machine tool temperature and cutting parameter relationships, a library of cutting load and cutting parameter relationships, and a library of position coordinates and cutting parameter relationships respectively; At the same time, it is also used to obtain abnormal cutting parameters in the working condition judgment module according to the specified period, and build an adaptive update algorithm and an adaptive compensation algorithm based on the abnormal cutting parameters and the preset original cutting parameters, and synchronize the adaptive update algorithm to the adaptive update unit, and synchronize the adaptive compensation algorithm to the adaptive compensation unit.

7. A method for adaptive control of a numerically controlled machine tool, characterized in that: Applied to the adaptive control system of a CNC machine tool according to any one of claims 1 to 6, the method comprises: Through the data acquisition unit, multiple operating parameters are collected regularly; Through the data processing unit, the collected multiple operating parameters are subjected to real-time feature extraction to obtain multiple machine tool features; The working condition judgment module receives a plurality of machine tool features from the data processing unit, and judges the working condition according to a pre-established working condition judgment strategy. If the working condition of the operating parameter is judged to be abnormal, the abnormal cutting parameter corresponding to the abnormal operating parameter is obtained, and the abnormal cutting parameter is sent to the adaptive control module. The adaptive control module receives the abnormal cutting parameters transmitted from the working condition judgment module, and adaptively adjusts the abnormal cutting parameters according to a preset adaptive algorithm; The output control module receives the cutting parameters adjusted by the adaptive control module, and controls the axial movement of the machine tool according to the cutting parameters.

8. The method according to claim 7, characterized in that The method further comprises: Through the reinforcement learning module, multiple operating parameters in the preprocessing unit are obtained according to the specified cycle; the multiple operating parameters are input into the original machine learning model to obtain the relationship library between machine tool temperature and cutting parameters, the relationship library between cutting load and cutting parameters, and the relationship library between position coordinates and cutting parameters respectively; At the same time, the abnormal cutting parameters in the working condition judgment module are obtained according to the specified period, and based on the abnormal cutting parameters and the preset original cutting parameters, an adaptive update algorithm and an adaptive compensation algorithm are constructed, and the adaptive update algorithm is synchronized to the adaptive update unit, and the adaptive compensation algorithm is synchronized to the adaptive compensation unit.

9. The method according to claim 7, characterized in that: The adaptive control module receives the abnormal cutting parameters transmitted from the working condition judgment module, and adaptively adjusts the abnormal cutting parameters according to a preset adaptive algorithm, including: The abnormal cutting parameters sent by the working condition judgment module are received through the adaptive updating unit, and the abnormal cutting parameters are substituted into the pre-built adaptive updating algorithm to calculate the control error and the new cutting parameters; The control error sent by the cutting parameter adjustment unit is received by the adaptive compensation unit, and the control error is substituted into a pre-built adaptive compensation algorithm to calculate the cutting compensation amount; The cutting parameter adjustment unit receives the new cutting parameter in the adaptive updating unit and the cutting compensation amount in the adaptive compensation unit, and calculates the sum of the new cutting parameter and the cutting compensation amount to obtain the adaptive cutting parameter.

10. The method according to claim 7, characterized in that The output control module receives the cutting parameters adjusted by the adaptive control module, and controls the axial movement of the machine tool according to the cutting parameters, including: After receiving the adaptive cutting parameters obtained from the cutting parameter adjustment unit through the path planning unit, a coordinate acquisition instruction is sent to the position sensor, and the original target position coordinates of each axis of the target CNC machine tool collected by the position sensor are received, and the new target position coordinates of each axis of the target CNC machine tool are obtained according to the preset position coordinate and cutting parameter relationship library; The servo unit receives the new target position coordinates of each axis of the target CNC machine tool sent from the path planning unit, and drives each axis of the machine tool to move according to the new target position coordinates based on the original target position coordinates.

Images