Intelligent drill bit application management system

Abstract

The invention relates to the technical field of drill bit management, and discloses an intelligent drill bit application management system, which comprises a data acquisition module for acquiring operation state data, including rotating speed, temperature and vibration parameters, of a machine tool drill bit in real time, and ensuring the accuracy and real-time performance of the data by adopting a high-precision sensor and a data transmission technology. The system can monitor the state of a machine tool and predict potential faults in real time by collecting and analyzing the operation data of the drill bit of the machine tool in real time, so that the reliability and stability of equipment are improved, data are deeply analyzed and mined by using a big data technology and a machine learning algorithm, rules and trends are found, and the working efficiency is improved. And the production efficiency is improved, the energy consumption is reduced, and the machining process is optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of drill bit management, and in particular to an intelligent drill bit application management system. Background Art

[0002] The intelligent machine tool drill application management system is a management tool based on modern information technology. It aims to improve the efficiency of machine tool drill bit use, reduce production costs, and enhance the overall intelligence level of the production line. The system integrates the Internet of Things, big data, and artificial intelligence advanced technologies to achieve refined management of the entire life cycle of machine tool drill bits.

[0003] The machine tool drill bit management system in the prior art generally has the following shortcomings:

[0004] 1. Drilling rig motors require the coordinated cooperation of a series of products. When a certain parameter or part is adjusted, it often affects the application of other parts of the equipment. At present, the customized development of motors is insufficient to meet the special needs of different application scenarios, which makes it impossible to achieve mass production of equipment, seriously affecting the cost-effectiveness of the equipment;

[0005] 2. Although some systems can collect the operating data of machine tool drills in real time, they have limited functions in data management and analysis. They cannot deeply explore the value behind the data and cannot provide strong data support for production decisions. At the same time, the degree of data visualization is not high enough, and it is difficult for users to intuitively understand the operating status of machine tool drills;

[0006] 3. The existing systems still need to be improved in terms of intelligent decision-making and automation. Some systems still rely on manual operation and experience-based judgment and cannot achieve truly intelligent management. Especially in terms of fault prediction and preventive maintenance, the intelligence level of the system is far from meeting the needs of enterprises.

[0007] Therefore, it is necessary to design an intelligent drill application management system to solve the above problems. Summary of the invention

[0008] The purpose of the present invention is to solve the shortcomings of the prior art and to propose an intelligent drill application management system.

[0009] In order to achieve the above object, the present invention adopts the following technical solutions:

[0010] An intelligent drill bit application management system includes the following modules:

[0011] Data acquisition module: real-time acquisition of machine tool drill bit operating status data, including speed, temperature, vibration parameters, using high-precision sensors and data transmission technology to ensure data accuracy and real-time performance;

[0012] Data management and analysis module: stores, manages and analyzes the collected data, extracts drill bit parameter information, uses big data technology and data analysis algorithms, and provides data visualization tools to help users intuitively understand the operating status of machine tool drill bits;

[0013] Intelligent decision-making and optimization module: Based on data analysis results, it automatically adjusts the operating parameters of machine tool drill bits, optimizes the production process, performs fault prediction and preventive maintenance, reduces the failure rate, and uses artificial intelligence technology, combined with expert experience and machine learning algorithms, to conduct intelligent management and decision-making;

[0014] Motor customized development module: Provide motor customized development services based on user needs and application scenarios to ensure that the equipment meets specific needs and expand the versatility of the product;

[0015] System security and stability module: adopts multiple security protection measures, including data encryption, access control, backup and recovery, real-time monitoring of system operation status, and timely detection and handling of potential security risks.

[0016] As a preferred technical solution of the present invention, in the data acquisition module, the collected raw data is preprocessed, including data cleaning, data conversion and data standardization steps to remove outliers and noise data, and the data collected by different sensors are converted into a unified format and standard to facilitate subsequent data management and analysis. A data verification mechanism is introduced to verify and check the collected data. The accuracy and reliability of the data are ensured by comparing historical data, preset thresholds or cross-verifying with other sensor data. When abnormal data is found during the data verification process, an alarm can be automatically triggered or data correction can be performed. The frequency and accuracy of data acquisition can be dynamically adjusted according to the operating status and working mode of the machine tool drill bit. When the machine tool drill bit is running stably, the data acquisition frequency can be reduced to reduce the amount of data transmission.

[0017] As a preferred technical solution of the present invention, in the data management and analysis module, data mining and machine learning technologies are introduced to conduct in-depth analysis and mining of the data, discover the rules and trends behind the data, support multiple data analysis methods such as association analysis, cluster analysis, and regression analysis, provide the function of customizing data analysis models, allow users to build data analysis models according to their own needs, and visualize the analysis results in the form of charts and images. It provides rich visualization tools and templates, supports users to customize visualization interfaces and interaction methods, supports real-time data updates and dynamic visualization, ensures that users can grasp the latest data dynamics in a timely manner, predicts the operating status, life, and failures of machine tool drill bits based on historical data and machine learning algorithms, provides prediction model construction, training, and verification functions, ensures the accuracy and reliability of prediction results, and supports the display and application of prediction results.

[0018] As a preferred technical solution of the present invention, in the intelligent decision-making and optimization module, the hierarchical analysis method is introduced to provide decision support for the selection and parameter setting of machine tool drill bits by establishing a hierarchical structure, pairwise comparison, weight calculation, consistency test and comprehensive decision-making steps. The machine learning algorithms, including decision trees and reinforcement learning, are integrated to build a prediction model by combining historical data and real-time data. The module supports customized decision rules and strategies, allowing users to set specific decision conditions and thresholds according to their own needs and experience. The module introduces optimization algorithms, including genetic algorithms and particle swarm algorithms, to automatically optimize the operating parameters of machine tool drill bits, support the optimization of processing paths, cutting parameters and lubrication methods to adapt to different materials and processing requirements, provide a visual display of optimization results, help users intuitively understand the optimization effect and potential improvement space, monitor the operating status and processing environment of machine tool drill bits in real time, dynamically adjust the decision and optimization strategies according to real-time data, and support adaptive learning.

[0019] As a preferred technical solution of the present invention, in the motor customization development module, a modular design concept is introduced, and the motor is divided into multiple functional modules, including a power module, a sensor module, and a control module. Each module has a standardized interface, allowing the user to select modules with different functions for combination according to needs, so as to realize rapid customization of the motor, and provide a wealth of motor parameter setting options, including power, speed, torque, efficiency, and size. Users can select appropriate parameter values ​​according to specific application scenarios. Customized settings of parameter ranges are supported, and high-performance semiconductor technology is introduced, including IGBT power switches and gate drivers, to provide higher control accuracy and stability, support multiple communication protocols, realize efficient communication and data interaction between motors and other devices, provide firmware customization and logic circuit customization services, and allow users to customize the control algorithm and Ethernet field bus type of the motor according to needs.

[0020] As a preferred technical solution of the present invention, in the system security and stability module, the data in the system is encrypted, stored and transmitted, the system data is automatically backed up regularly, and a complete data recovery mechanism is established to implement strict data access permission control to ensure that only authorized users can access and modify data. Vulnerability scans of the application system are performed regularly, and discovered vulnerabilities are repaired in a timely manner to reduce potential security risks. Security audits are performed on system applications to ensure that the applications comply with security standards and best practices. Security updates for systems and applications are pushed and installed in a timely manner to respond to emerging security threats. Physical isolation is implemented for key equipment and systems to prevent external physical attacks and interference. Access control mechanisms are implemented, including access control systems and identity authentication, to ensure that only authorized personnel can enter key areas.

[0021] The present invention has the following beneficial effects:

[0022] 1. Real-time monitoring and prediction: By collecting and analyzing the operating data of the machine tool drill bit in real time, the system can monitor the machine tool status in real time and predict potential failures, thereby improving the reliability and stability of the equipment.

[0023] 2. Data analysis and optimization: Use big data technology and machine learning algorithms to conduct in-depth analysis and mining of data to discover patterns and trends in order to improve production efficiency, reduce energy consumption, and optimize processing processes.

[0024] 3. Intelligent decision support: Based on the data analysis results, the system can automatically adjust the operating parameters of the machine tool, optimize the production process, reduce the failure rate, provide intelligent management and decision support, and improve production efficiency and product quality.

[0025] 4. Customized motor development: Provide customized motor development services. According to user needs and application scenarios, quickly customize motors that meet specific needs, expand the versatility of products, and improve the applicability and flexibility of equipment.

[0026] 5. System security and stability: Multiple security protection measures are adopted to ensure the security and stability of system data, including data encryption, access control, backup and recovery, etc., to improve the reliability and security of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a structural schematic diagram of an intelligent drill bit application management system proposed by the present invention. DETAILED DESCRIPTION

[0028] The technical solutions in the embodiments of the present invention will be described clearly and completely 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, rather than all the embodiments.

[0029] Reference Figure 1 , an intelligent drill bit application management system, including the following modules:

[0030] Data acquisition module: real-time acquisition of machine tool drill bit operating status data, including speed, temperature, and vibration parameters. High-precision sensors and data transmission technology are used to ensure data accuracy and real-time performance. In the data acquisition module, the collected raw data is preprocessed, including data cleaning, data conversion, and data standardization steps to remove abnormal values ​​and noise data. The data collected by different sensors are converted into a unified format and standard to facilitate subsequent data management and analysis. A data verification mechanism is introduced to verify and check the collected data. The accuracy and reliability of the data are ensured by comparing historical data, preset thresholds, or cross-verifying with other sensor data. When abnormal data is found during the data verification process, an alarm can be automatically triggered or data correction can be performed. The frequency and accuracy of data collection can be dynamically adjusted according to the operating status and working mode of the machine tool drill bit. When the machine tool drill bit is running stably, the data collection frequency can be reduced to reduce the amount of data transmission.

[0031] Data management and analysis module: store, manage and analyze the collected data, extract drill bit parameter information, use big data technology and data analysis algorithms, provide data visualization tools, and help users intuitively understand the operating status of machine tool drill bits. In the data management and analysis module, data mining and machine learning technologies are introduced to conduct in-depth analysis and mining of data to discover the laws and trends behind the data. It supports multiple data analysis methods such as association analysis, cluster analysis, and regression analysis. It provides the function of customizing data analysis models, allowing users to build data analysis models according to their own needs, and visualize the analysis results in the form of charts and images. It provides a wealth of visualization tools and templates, supports user-defined visualization interfaces and interactive methods, supports real-time data updates and dynamic visualization, and ensures that users can keep up with the latest data dynamics. Based on historical data and machine learning algorithms, it predicts the operating status, life, and failures of machine tool drill bits. It provides the functions of building, training, and verifying prediction models to ensure the accuracy and reliability of prediction results, and supports the display and application of prediction results.

[0032] Intelligent decision-making and optimization module: Based on the results of data analysis, the operating parameters of machine tool drills are automatically adjusted to optimize the production process, fault prediction and preventive maintenance are carried out to reduce the failure rate. Artificial intelligence technology is used, combined with expert experience and machine learning algorithms, to carry out intelligent management and decision-making. In the intelligent decision-making and optimization module, the hierarchical analysis method is introduced to provide decision support for the selection and parameter setting of machine tool drills by establishing a hierarchical structure, pairwise comparison, weight calculation, consistency test and comprehensive decision-making steps. Machine learning algorithms, including decision trees and reinforcement learning, are integrated to build prediction models by combining historical data and real-time data. Customized decision rules and strategies are supported, allowing users to set specific decision conditions and thresholds according to their own needs and experience. Optimization algorithms, including genetic algorithms and particle swarm algorithms, are introduced to automatically optimize the operating parameters of machine tool drills. The optimization of processing paths, cutting parameters and lubrication methods is supported to adapt to different materials and processing requirements. Visual optimization result display is provided to help users intuitively understand the optimization effect and potential improvement space. The operating status and processing environment of machine tool drills are monitored in real time, and decision-making and optimization strategies are dynamically adjusted according to real-time data to support adaptive learning.

[0033] Motor customized development module: Provide motor customized development services according to user needs and application scenarios to ensure that the equipment meets specific needs and expand the versatility of the product. In the motor customized development module, the modular design concept is introduced to divide the motor into multiple functional modules, including power module, sensor module, and control module. Each module has a standardized interface, allowing users to select modules with different functions for combination according to needs to achieve rapid customization of the motor. Provide a wealth of motor parameter setting options, including power, speed, torque, efficiency, and size. Users can select appropriate parameter values ​​according to specific application scenarios. Support custom settings of parameter ranges. Introduce high-performance semiconductor technology, including IGBT power switches and gate drivers, to provide higher control accuracy and stability, support multiple communication protocols, and achieve efficient communication and data interaction between motors and other devices. Provide firmware customization and logic circuit customization services, allowing users to customize the motor's control algorithm and Ethernet field bus type according to needs;

[0034] System security and stability module: adopt multiple security protection measures, including data encryption, access control, backup and recovery, real-time monitoring of system operation status, timely detection and handling of potential security risks. In the system security and stability module, the data in the system is encrypted, stored and transmitted, the system data is automatically backed up regularly, and a complete data recovery mechanism is established to implement strict data access permission control to ensure that only authorized users can access and modify data. Regular vulnerability scans of application systems are carried out, and discovered vulnerabilities are repaired in a timely manner to reduce potential security risks. Security audits are conducted on system applications to ensure that applications comply with security standards and best practices. Security updates for systems and applications are pushed and installed in a timely manner to respond to emerging security threats. Physical isolation is implemented for key equipment and systems to prevent external physical attacks and interference. Access control mechanisms are implemented, including access control systems and identity authentication, to ensure that only authorized personnel can enter key areas.

[0035] The specific working principle of the present invention includes the following:

[0036] First, the data acquisition module is responsible for real-time collection of the operating status data of the machine tool drill, including speed, temperature, vibration parameters, etc., and uses high-precision sensors and data transmission technology to ensure the accuracy and real-time nature of the data. The collected raw data is preprocessed, including data cleaning, conversion and standardization, to remove outliers and noise data, and convert the data collected by different sensors into a unified format and standard for subsequent data management and analysis. At the same time, a data verification mechanism is introduced to verify and check the collected data to ensure the accuracy and reliability of the data. When abnormal data is found, it can automatically trigger an alarm or perform data correction. According to the operating status and working mode of the machine tool drill, the frequency and accuracy of data acquisition are dynamically adjusted. When stable, the data acquisition frequency is reduced to reduce the amount of data transmission.

[0037] Secondly, the data management and analysis module stores, manages and analyzes the collected data, extracts drill bit parameter information, adopts big data technology and data analysis algorithms, and provides data visualization tools to help users understand the operating status of machine tool drill bits. It introduces data mining and machine learning technologies to conduct in-depth analysis and mining of the data, discover the patterns and trends behind the data, support multiple data analysis methods, and provide the function of customizing data analysis models, which are visualized in the form of charts and images. Based on historical data and machine learning algorithms, it predicts the operating status, lifespan, and failures of machine tool drill bits, provides the functions of building, training, and verifying prediction models, and ensures the accuracy and reliability of the prediction results.

[0038] Furthermore, the intelligent decision-making and optimization module automatically adjusts the operating parameters of the machine tool drill bit according to the data analysis results, optimizes the production process, performs fault prediction and preventive maintenance, and reduces the failure rate. It uses artificial intelligence technology, combined with expert experience and machine learning algorithms, to perform intelligent management and decision-making. It provides decision support for the selection and parameter setting of machine tool drill bits through multi-attribute decision-making methods such as hierarchical analysis method, integrates machine learning algorithms, including decision trees and reinforcement learning, combines historical data and real-time data, builds prediction models, supports custom decision rules and strategies, introduces optimization algorithms, and automatically optimizes the operating parameters of machine tool drill bits to adapt to different materials and processing requirements. It provides a visual display of optimization results to help users understand the optimization effect.

[0039] Finally, the system security and stability module adopts multiple security protection measures, including data encryption, access control, backup and recovery, real-time monitoring of system operation status, timely detection and handling of potential security risks, encrypted storage and transmission of data in the system, regular and automatic backup of system data, and establishment of a complete data recovery mechanism to implement strict data access permission control, conduct vulnerability scans on application systems, and promptly repair discovered vulnerabilities to reduce potential security risks, implement physical isolation of key equipment and systems to prevent external physical attacks and interference, and implement access control mechanisms to ensure that only authorized personnel can enter key areas.

[0040] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can replace or change the technical solution and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. An intelligent drill bit application management system, characterized in that: Includes the following modules: Data acquisition module: real-time acquisition of machine tool drill bit operating status data, including speed, temperature, vibration parameters, using high-precision sensors and data transmission technology to ensure data accuracy and real-time performance; Data management and analysis module: stores, manages and analyzes the collected data, extracts drill bit parameter information, uses big data technology and data analysis algorithms, and provides data visualization tools to help users intuitively understand the operating status of machine tool drill bits; Intelligent decision-making and optimization module: Based on data analysis results, it automatically adjusts the operating parameters of machine tool drill bits, optimizes the production process, performs fault prediction and preventive maintenance, reduces the failure rate, and uses artificial intelligence technology, combined with expert experience and machine learning algorithms, to conduct intelligent management and decision-making; Motor customized development module: Provide motor customized development services based on user needs and application scenarios to ensure that the equipment meets specific needs and expand the versatility of the product; System security and stability module: adopts multiple security protection measures, including data encryption, access control, backup and recovery, real-time monitoring of system operation status, and timely detection and handling of potential security risks.

2. The intelligent drill bit application management system according to claim 1, characterized in that: In the data acquisition module, the collected raw data is preprocessed, including data cleaning, data conversion and data standardization steps to remove outliers and noise data, and the data collected by different sensors are converted into a unified format and standard to facilitate subsequent data management and analysis. A data verification mechanism is introduced to verify and check the collected data. The accuracy and reliability of the data are ensured by comparing historical data, preset thresholds or cross-verifying with other sensor data. When abnormal data is found during the data verification process, an alarm can be automatically triggered or data correction can be performed. The frequency and accuracy of data acquisition can be dynamically adjusted according to the operating status and working mode of the machine tool drill bit. When the machine tool drill bit is running stably, the data acquisition frequency can be reduced to reduce the amount of data transmission.

3. The intelligent drill bit application management system according to claim 1, characterized in that: In the data management and analysis module, data mining and machine learning technologies are introduced to conduct in-depth analysis and mining of data, discover the rules and trends behind the data, support multiple data analysis methods such as association analysis, cluster analysis, and regression analysis, provide the function of customizing data analysis models, allow users to build data analysis models according to their own needs, and visualize the analysis results in the form of charts and images. It provides rich visualization tools and templates, supports users to customize visualization interfaces and interaction methods, supports real-time data updates and dynamic visualization, ensures that users can keep abreast of the latest data dynamics, and predicts the operating status, life, and failures of machine tool drill bits based on historical data and machine learning algorithms. It provides the functions of building, training, and verifying prediction models to ensure the accuracy and reliability of prediction results and support the display and application of prediction results.

4. The intelligent drill bit application management system according to claim 1, characterized in that: In the intelligent decision-making and optimization module, the hierarchical analysis method is introduced to provide decision support for the selection and parameter setting of machine tool drill bits by establishing a hierarchical structure, pairwise comparison, weight calculation, consistency test and comprehensive decision-making steps. Machine learning algorithms, including decision trees and reinforcement learning, are integrated to build a prediction model by combining historical data and real-time data. Customized decision rules and strategies are supported, allowing users to set specific decision conditions and thresholds according to their own needs and experience. Optimization algorithms, including genetic algorithms and particle swarm algorithms, are introduced to automatically optimize the operating parameters of machine tool drill bits. The optimization of processing paths, cutting parameters and lubrication methods is supported to adapt to different materials and processing requirements. A visual display of optimization results is provided to help users intuitively understand the optimization effect and potential improvement space. The operating status and processing environment of machine tool drill bits are monitored in real time, and decisions and optimization strategies are dynamically adjusted according to real-time data to support adaptive learning.

5. The intelligent drill bit application management system according to claim 1, characterized in that: In the motor customization development module, the concept of modular design is introduced, and the motor is divided into multiple functional modules, including a power module, a sensor module, and a control module. Each module has a standardized interface, allowing users to select modules with different functions for combination according to their needs, so as to realize rapid customization of the motor and provide a wealth of motor parameter setting options, including power, speed, torque, efficiency, and size. Users can select appropriate parameter values ​​according to specific application scenarios. Custom settings of parameter ranges are supported, and high-performance semiconductor technology is introduced, including IGBT power switches and gate drivers, to provide higher control accuracy and stability, support multiple communication protocols, realize efficient communication and data interaction between motors and other devices, provide firmware customization and logic circuit customization services, and allow users to customize the control algorithm and Ethernet field bus type of the motor according to their needs.

6. The intelligent drill bit application management system according to claim 1, characterized in that: In the system security and stability module, the data in the system is encrypted, stored and transmitted, the system data is automatically backed up regularly, and a complete data recovery mechanism is established to implement strict data access permission control to ensure that only authorized users can access and modify data. Vulnerability scans of the application system are performed regularly, and discovered vulnerabilities are repaired in a timely manner to reduce potential security risks. Security audits are performed on system applications to ensure that the applications comply with security standards and best practices. Security updates for the system and applications are pushed and installed in a timely manner to respond to emerging security threats. Physical isolation is implemented for key equipment and systems to prevent external physical attacks and interference. Access control mechanisms are implemented, including access control systems and identity authentication, to ensure that only authorized personnel can enter key areas.

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