Self-adaptive cutting system of three-axis linkage bus fillet processing machine

Abstract

The invention discloses a self-adaptive cutting system of a three-axis linkage bus fillet processing machine, which comprises a working condition sensing module, an intelligent decision module, a numerical control execution module and a data storage module, and is characterized in that the working condition sensing module is used for acquiring working condition data of cutting force, vibration, temperature and main shaft current in real time in a bus fillet milling process; the intelligent decision-making module is used for receiving the data transmitted and collected by the working condition sensing module, judging whether the working condition is abnormal or not in combination with a pre-stored parameter reference and an intelligent algorithm and generating an optimal parameter adjustment scheme; and the numerical control execution module is used for receiving the adjustment instruction of the intelligent decision module and correcting the parameters of the main shaft rotating speed, the shaft feeding rate, the milling depth and the cooling liquid flow in real time. The invention relates to the technical field of busbar machining equipment, and the system integrates closed-loop control of working condition sensing, parameter decision and dynamic adjustment, and can improve the consistency of the machining precision of a busbar fillet, prolong the service life of a cutter, improve the machining efficiency and guarantee the production safety of the busbar.

Description

Technical Field

[0001] This invention relates to the field of busbar processing equipment technology, specifically to an adaptive cutting system for a three-axis linkage busbar fillet machining machine. Background Technology

[0002] Busbars, also known as busbar bars or busbars, are usually made of copper and aluminum. As an important connecting component for current transmission, busbars are widely used in power equipment such as high-voltage switchgear and transformers. Since the busbar is the core conductor for current transmission in power equipment, the quality of the rounding of its ends and edges directly affects electrical safety and equipment stability. Therefore, during processing and installation, it is necessary to process its edges and corners using a rounding machine.

[0003] Existing busbar fillet machining machines mostly use fixed cutting parameters, such as preset cutting speed, feed rate, and milling depth. These have the following technical drawbacks: Due to differences in busbar materials, such as fluctuations in hardness of copper busbars, uneven impurity distribution in aluminum busbars, batch variations, and tool wear, actual cutting conditions can change. Fixed parameters are prone to overcutting or undercutting, making it difficult to meet machining accuracy requirements. When the material hardness increases locally or the tool edge wears, the fixed cutting force can easily lead to tool overload, causing edge breakage, resulting in a short average tool life and frequent replacements, increasing production costs. To avoid overload risks, traditional equipment needs to reduce cutting parameters to leave a safety margin, leading to lower throughput. Furthermore, cutting vibration cannot be monitored in real time, easily causing tool breakage and spatter, posing a safety hazard. Traditional equipment relies heavily on manual experience to adjust parameters, making it unable to adapt to rapid switching between different busbar specifications and unable to automatically record machining data, hindering process traceability and optimization. Therefore, improvements are needed to address these issues. Summary of the Invention

[0004] In response to the above situation and to overcome the current technical defects, this invention provides an adaptive cutting system for a three-axis linkage busbar fillet machining machine. This system integrates closed-loop control with working condition perception, parameter decision-making, and dynamic adjustment, which can improve the consistency of busbar fillet machining accuracy, extend tool life, improve machining efficiency, and ensure the production safety of busbars.

[0005] The technical solution adopted by this invention is as follows: This solution provides an adaptive cutting system for a three-axis linkage busbar fillet milling machine, including a working condition sensing module, an intelligent decision-making module, a CNC execution module, and a data storage module. The working condition sensing module is used to collect working condition data such as cutting force, vibration, temperature, and spindle current in real time during busbar fillet milling. The intelligent decision-making module is used to receive the data collected by the working condition sensing module, combine it with pre-stored parameter benchmarks and intelligent algorithms to determine whether the working condition is abnormal, and generate the optimal parameter adjustment scheme. The CNC execution module is used to receive adjustment instructions from the intelligent decision-making module and correct the cutting parameters such as spindle speed, axis feed rate, milling depth, and coolant flow rate in real time. The data storage module is used to record machining basic data, working condition data, parameter adjustment data, and tool data throughout the process, and supports data export to achieve process traceability and optimization. The working condition sensing module, intelligent decision-making module, CNC execution module, and data storage module achieve bidirectional communication through industrial Ethernet, forming a complete adaptive control closed loop.

[0006] Preferably, the working condition sensing module includes a force sensor, a vibration sensor, a temperature sensor, and a spindle current monitoring unit. The force sensor is installed at the milling spindle tool holder of the busbar fillet machining machine to collect the cutting radial and axial forces in real time. The vibration sensor is fixed to the side of the machining table to monitor the cutting vibration acceleration in the X, Y, and Z axes of the busbar fillet machining machine. The temperature sensor uses an infrared temperature probe and is installed above the milling area of ​​the busbar fillet machining machine to collect the temperature of the tool edge and the busbar machining surface. The spindle current monitoring unit is connected in series with the power supply circuit of the spindle drive motor and infers the cutting load change by the change in current.

[0007] Preferably, the intelligent decision-making module is built on an embedded processor and has a built-in parameter database and intelligent algorithm unit: the parameter database is used to pre-store the optimal cutting parameter benchmark values ​​of busbars of different material specifications, as well as the tool wear threshold; the intelligent algorithm unit adopts a hybrid algorithm of deep reinforcement learning and expert rules to compare the actual parameters collected by the perception module with the database benchmark values ​​in real time.

[0008] Preferably, the CNC execution module is used to be deeply integrated with the CNC system of the three-axis linkage busbar fillet machining machine, and to receive parameter adjustment instructions from the intelligent decision module.

[0009] Preferably, the data storage module uses a storage unit and a cloud storage system to record the basic processing data and parameters of the busbar in real time.

[0010] Preferably, the data storage module has a data export function for subsequent process traceability and optimization.

[0011] The beneficial effects achieved by the present invention using the above structure are as follows:

[0012] 1. The working condition perception module can capture cutting anomalies in real time through high-precision sensors, and the intelligent decision-making module dynamically generates adjustment plans to avoid overcutting and undercutting caused by busbar material fluctuations and tool wear. At the same time, the system automatically calls the optimal cutting parameters adapted to the busbar material to replace manual experience adjustment, reduce operation differences, ensure that the fillet radius and surface quality meet the processing standards, and guarantee the consistency of accuracy of different batches of busbars.

[0013] 2. The spindle current monitoring unit calculates the cutting load in real time, and the temperature sensor monitors the cutting edge temperature of the tool. When the current exceeds the limit or the temperature is too high, the system automatically adjusts the parameters to avoid tool overload and breakage and thermal damage. In addition, the system compares the tool usage time with the database life data to generate a replacement warning in advance to prevent excessive wear from increasing the scrap rate, so as to extend the tool life and reduce the tool replacement and rework costs.

[0014] 3. This system achieves simultaneous processing and adjustment through adaptive adjustment without interrupting the process; industrial Ethernet ensures rapid response from each module, and parameter adjustment commands are quickly implemented, avoiding delays and waste; at the same time, the data storage module automatically records processing data, reducing manual statistics time, improving efficiency from three aspects: process continuity, module collaboration, and data automation, thereby increasing batch processing efficiency.

[0015] 4. When the system starts up, it can automatically detect the communication status of each module and troubleshoot faults in advance; during processing, the vibration sensor and current monitoring unit capture abnormalities in real time, and trigger a shutdown alarm when the parameter deviation is too large, reducing the risk of tool breakage and equipment overload; and the operator only needs to input the processing requirements, and the system will automatically complete the parameter calling, monitoring and adjustment, greatly reducing manual intervention and reducing safety accidents caused by misoperation.

[0016] 5. The data storage module can record basic data of busbar processing, operating condition curves, and parameter adjustment records in real time, and supports data export, which facilitates process traceability and meets the needs of modern production digital management and control. Attached Figure Description

[0017] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0018] Figure 1 This is a schematic diagram of the adaptive cutting system of the three-axis linkage busbar fillet machining machine of the present invention;

[0019] Figure 2 This is a schematic diagram of the working process of the adaptive cutting system of the three-axis linkage busbar fillet machining machine of the present invention; Detailed Implementation

[0020] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0021] It should be noted that the terms “front,” “back,” “left,” “right,” “up,” and “down” used in the following description refer to the directions shown in the attached diagram, while the terms “inside” and “outside” refer to the directions toward or away from the geometric center of a specific component, respectively.

[0022] As per the instruction manual Figure 1-2 As shown, the technical solution adopted by the present invention is as follows:

[0023] The adaptive cutting system of the three-axis linkage busbar fillet machining machine provided by the present invention includes a working condition sensing module, an intelligent decision-making module, a numerical control execution module and a data storage module, and each module communicates bidirectionally via industrial Ethernet.

[0024] The working condition sensing module includes a force sensor, a vibration sensor, a temperature sensor, and a spindle current monitoring unit: the force sensor is installed at the milling spindle tool holder, with a range of 0-5000N and a sampling frequency of 1000Hz, used to collect the cutting radial and axial forces in real time; the vibration sensor is fixed to the side of the machining table, with a measurement range of 0-500Hz and a resolution of 0.1Hz, monitoring the cutting vibration acceleration in the X, Y, and Z axes; the temperature sensor uses an infrared temperature probe, installed 50-80mm above the milling area, with a temperature measurement range of -20℃ to 500℃, collecting the temperature of the tool edge and the machined surface of the busbar; the spindle current monitoring unit is connected in series in the spindle drive motor power supply circuit, with a sampling accuracy of 0.01A, and infers the cutting load change by the current change.

[0025] The intelligent decision-making module is built on an embedded processor and has a built-in parameter database and intelligent algorithm unit: the parameter database pre-stores the specification parameters of copper and aluminum busbars of different materials, the optimal cutting parameter reference values ​​of the busbars, and the wear thresholds of different types of tools;

[0026] The intelligent algorithm unit employs a hybrid algorithm combining deep reinforcement learning and expert rules to compare real-time parameters collected by the sensing module, such as cutting force, vibration, temperature, and current, with database benchmark values. When the actual cutting force or vibration acceleration exceeds the benchmark range, the feed rate or cutting speed is automatically adjusted. When the actual temperature exceeds the reasonable threshold for the corresponding material busbar, the cooling system flow rate is increased, and the cutting speed is adjusted simultaneously. When the spindle current continuously exceeds the rated range, tool wear is determined, wear compensation is calculated, and the Z-axis milling depth is adjusted to compensate for wear. When the parameter deviation is too large and cannot be recovered after adjustment, a shutdown alarm is triggered, and a fault diagnosis report is generated.

[0027] The CNC execution module is deeply integrated with the CNC system of the three-axis linkage busbar fillet machining machine, and is used to receive parameter adjustment instructions from the intelligent decision module: the cutting speed is adjusted by controlling the spindle servo motor speed; the feed rate is adjusted by controlling the feed rate of the X, Y, and Z axis servo motors; the milling depth is adjusted by compensating for tool wear by the Z axis servo motor; and the cooling system is regulated and controlled by adjusting the coolant flow rate by the solenoid valve.

[0028] The data storage module uses SD cards and cloud storage units to record relevant data in real time. The data includes: basic machining data such as busbar material, specifications, fillet radius requirements, and machining time; working condition data such as real-time curves of cutting force, vibration, temperature, and spindle current; parameter adjustment data such as cutting speed, feed rate, milling depth, and adjustment trigger reasons before and after adjustment; tool data such as tool model, usage time, wear, and replacement records; and supports data export for easy process traceability and optimization in the later stages.

[0029] In practical use, the system automatically detects the communication status of the working condition sensing module, intelligent decision-making module, CNC execution module, and data storage module. It verifies the normal bidirectional communication of each module via industrial Ethernet to ensure no communication interruptions or module failures, providing a stable hardware and communication foundation for subsequent processing. Operators input the processing requirements for the busbars, including the busbar material, specifications, and fillet radius requirements, through the human-machine interface. After receiving the instructions, the intelligent decision-making module retrieves the corresponding reference parameters for that type of busbar from its built-in parameter database.

[0030] Cutting parameters: Optimal cutting speed, feed rate, and depth of cut reference values ​​that match the current busbar material;

[0031] Tool parameters: Automatically select the appropriate tool type based on the busbar material and call the wear threshold of that tool type;

[0032] Operating condition thresholds: Preset reasonable reference ranges for cutting force, vibration acceleration, tool edge temperature, and spindle current during the machining of this type of busbar.

[0033] The busbar to be processed is fixed on the machining table. The system drives the X and Y axes to precisely feed the end of the busbar to the milling area. The spindle drives the matching tool to start rotating, entering the rounded corner milling process of the busbar. The force sensor installed at the milling spindle tool holder collects the cutting radial and axial forces in real time. The vibration sensor fixed on the side of the machining table monitors the cutting vibration acceleration in the X, Y, and Z axes. The temperature sensor and infrared temperature probe installed above the milling area collect the temperature of the tool edge and the machined surface of the busbar. The spindle current monitoring unit connected in series in the spindle drive motor power supply circuit infers the cutting load through current changes. After receiving the working condition data transmitted by each sensor, the intelligent decision module performs comparative analysis through a hybrid algorithm of deep reinforcement learning and expert rules.

[0034] The abnormal cutting force and vibration acceleration were determined to be caused by local material hardness fluctuations in the busbar.

[0035] The abnormal temperature and current were determined to be caused by slight tool wear leading to heat accumulation during cutting.

[0036] Based on the above judgment results, the algorithm, combined with the compensation rules in the parameter database, generates a parameter adjustment scheme for the mother row:

[0037] To address abnormal cutting forces and vibrations, adjust the feed rate and cutting speed while maintaining a constant milling depth and coolant flow rate.

[0038] For abnormal temperature and current: reduce cutting speed, increase cooling system flow, and compensate for tool wear by Z-axis milling depth to ensure that fillet radius meets design requirements; during busbar machining, the system synchronously compares the actual tool usage time with the corresponding tool life data in the parameter database and automatically generates tool replacement warning information.

[0039] The intelligent decision-making module sends parameter adjustment commands to the CNC execution module via industrial Ethernet. The CNC execution module and the CNC system of the machining center respond in concert: controlling the spindle servo motor speed to adjust the cutting speed; controlling the feed rate of the X-axis and Y-axis servo motors to adjust the feed amount; synchronously adjusting the spindle speed to match the cutting speed; regulating the coolant flow rate through the solenoid valve; and compensating for the milling depth through the Z-axis servo motor.

[0040] Within a short period after adjustment: cutting force and vibration acceleration return to the reference range, the system maintains stable parameters until the busbar milling is completed, and the X and Y axes drive the busbar out of the machining area; if it is batch processing, the tool edge temperature and spindle current quickly drop back to the normal range after adjustment, and the remaining busbars are processed according to the adjusted parameters; the data storage module automatically records the machining data of all busbars, including busbar material, specifications, machining time, real-time working condition curves, comparison of parameters before and after adjustment, and reasons for adjustment triggering; and supports data export for subsequent process traceability and optimization.

[0041] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, material, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, material, or apparatus.

[0042] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An adaptive cutting system for a three-axis gang bus fillet machining machine, characterized by: It comprises a working condition sensing module, an intelligent decision module, a numerical control execution module and a data storage module, the working condition sensing module is used for collecting working condition data of cutting force, vibration, temperature and spindle current in real time during busbar fillet milling, the intelligent decision module is used for receiving the data collected by the working condition sensing module, combining the pre-stored parameter benchmark and intelligent algorithm to determine whether the working condition is abnormal and generate an optimal parameter adjustment scheme; The numerical control execution module is used for receiving the adjustment instruction of the intelligent decision module to correct the cutting parameters of spindle speed, axis feed rate, milling depth and cooling liquid flow in real time; the data storage module is used for recording the processing basic data, working condition data, parameter adjustment data and tool data throughout the process, supporting data export to realize process traceability and optimization; the working condition sensing module, the intelligent decision module, the numerical control execution module and the data storage module realize bidirectional communication through industrial Ethernet to form a complete adaptive control closed loop.

2. The adaptive cutting system of a three-axis linkage bus corner rounding machine of claim 1, wherein: The working condition sensing module comprises a force sensor, a vibration sensor, a temperature sensor and a spindle current monitoring unit, the force sensor is installed at the milling spindle handle of the busbar fillet processing machine to collect cutting radial force and axial force in real time; the vibration sensor is fixed on the side of the processing workbench to monitor the cutting vibration acceleration in X, Y and Z three-axis directions of the busbar fillet processing machine; the temperature sensor adopts an infrared temperature measurement probe and is installed above the milling area of the busbar fillet processing machine to collect the temperature of the tool edge and the busbar processing surface; the spindle current monitoring unit is connected in series in the power supply circuit of the spindle driving motor to inversely deduce the cutting load change through the current change.

3. The adaptive cutting system of a three-axis linkage bus corner rounding machine of claim 1, wherein: The intelligent decision module is based on an embedded processor and has a built-in parameter database and an intelligent algorithm unit: the parameter database is used for pre-storing optimal cutting parameter benchmark values of different material specifications of busbars and wear threshold values of tools, the intelligent algorithm unit adopts a hybrid algorithm of deep reinforcement learning and expert rules to compare the actual parameters collected by the sensing module with the database benchmark values in real time.

4. The adaptive cutting system of a three-axis linkage bus corner rounding machine of claim 1, wherein: The numerical control execution module is used for deep integration with the numerical control system of the three-axis linkage busbar fillet processing machine to receive the parameter adjustment instruction of the intelligent decision module.

5. The adaptive cutting system of a three-axis linkage bus corner rounding machine of claim 1, wherein: The data storage module adopts a storage unit and a cloud storage system to record the processing basic data and parameters of the busbar in real time.

6. The adaptive cutting system of a three-axis linkage bus corner rounding machine of claim 5, wherein: The data storage module has a data export function to realize process traceability and optimization in later period.

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