Sapphire processing pressure detection system

Abstract

The invention discloses a pressure detection system during sapphire processing, and relates to the technical field of sapphire processing systems, the system comprises the following components: a wireless pressure sensor, a wireless communication module, a remote monitoring center and an intelligent management system, through the intelligent management system, a real-time optimization algorithm and a big data analysis technology can be utilized, and the wireless communication module is connected with the wireless pressure sensor; pressure data are deeply processed and analyzed, valuable information and rules are extracted, the pressure state in the machining process can be known in real time through an intelligent system, an operator and a management layer, targeted optimization suggestions and decision support can be obtained, the suggestions are based on a large amount of historical data and real-time data, and the processing efficiency is improved. Through deep analysis of an intelligent algorithm, the method has very high accuracy and practicability, and can help operators to adjust machining parameters and optimize the technological process, thereby improving the product quality and the production efficiency.

Description

Technical Field

[0001] The invention relates to the technical field of sapphire processing systems, in particular to a pressure detection system during sapphire processing. Background Art

[0002] Sapphire is the general name for corundum gemstones other than ruby, and its main component is aluminum oxide (Al2O3). Sapphire can be pink, yellow, green, white, and even in the same stone. The blue sapphire is due to the presence of a small amount of titanium (Ti) and iron (Fe) impurities. As a precious material with high hardness and high melting point, sapphire's processing often requires extremely strict control, especially the monitoring of pressure parameters, which is directly related to product quality and the stable operation of processing equipment. In the traditional sapphire processing, pressure detection has always been an important link. In the field of sapphire processing, traditional pressure detection technology mainly relies on wired sensors for data collection, and displays and alarms through simple data monitoring systems. However, with the continuous development of processing technology and the improvement of intelligent demand, this traditional pressure detection method can no longer meet the complexity and high precision requirements of modern processing.

[0003] Traditional data monitoring systems have a single function and can only provide simple data display and alarm functions. They lack the ability to deeply analyze and process data and cannot provide valuable decision support for operators. During the processing, operators can only rely on experience and intuition to make adjustments, which makes it difficult to ensure processing efficiency and product quality.

[0004] However, the existing wireless pressure detection systems are still insufficient in terms of intelligence and application effects. Although some systems have basic intelligent functions, their algorithms and models are relatively simple and cannot accurately identify and process complex processing situations. In addition, some systems still have problems in stability, real-time performance and security in practical applications, which need further improvement and optimization. Summary of the invention

[0005] The purpose of the present invention is to make up for the shortcomings of the prior art and provide a pressure detection system for sapphire processing. Through an intelligent system, it enables operators and management to not only understand the pressure status of the processing process in real time, but also obtain targeted optimization suggestions and decision support. These suggestions are based on a large amount of historical data and real-time data, and are obtained through in-depth analysis of real-time optimization algorithms. Therefore, they have high accuracy and practicality, and effectively help operators adjust processing parameters and optimize process flow, thereby improving product quality and production efficiency.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a pressure detection system for sapphire processing, characterized in that the system comprises the following components:

[0007] Wireless pressure sensor: It uses a high-sensitivity and high-precision pressure sensor to collect pressure data in real time during sapphire processing. The sensor has a built-in wireless communication module, which can transmit the collected pressure data to the remote monitoring center wirelessly.

[0008] Wireless communication module: Use wireless communication technology (such as Wi-Fi, ZigBee, LoRa) to build a stable wireless communication network to achieve data transmission between the pressure sensor and the remote monitoring center. The communication network is high-speed, stable, and has strong anti-interference capabilities, which can ensure the real-time and accuracy of the data.

[0009] Remote monitoring center: Set up a dedicated remote monitoring center to receive wireless data from pressure sensors for real-time display, storage and analysis. The monitoring center can be equipped with a professional software system to achieve data visualization, alarm prompts, and historical data query functions, making it convenient for operators to conduct remote monitoring and management;

[0010] Intelligent management system: Based on big data analysis technology, the collected pressure data is intelligently processed and analyzed to extract valuable information, providing data support for optimizing processing technology and improving product quality. At the same time, the system can automatically determine whether there is any abnormality in the processing process based on the preset threshold, and issue an alarm in time to ensure the safety and stability of the processing process.

[0011] Furthermore, the specific steps of the wireless pressure sensor are:

[0012] (1) According to the specific requirements of sapphire processing, select a suitable wireless pressure sensor, ensure that the sensor has sufficient accuracy, stability and durability to adapt to the various pressure and temperature changes that may be encountered during the processing, correctly connect the sensor to the processing equipment, and configure various parameters of the sensor, such as sampling frequency and range. The setting of these parameters will directly affect the accuracy and real-time performance of the pressure data. Configure the wireless communication module of the sensor to ensure that the sensor can establish a stable wireless connection with the remote monitoring center, which usually involves setting the communication protocol, frequency and encryption method;

[0013] (2) The wireless pressure sensor starts to collect pressure data in real time during the sapphire processing. The sensor converts the collected data into digital signals and sends them out through the wireless module. The sensor transmits the collected pressure data to the remote monitoring center through the wireless network. This process needs to ensure the real-time, stability and security of data transmission to prevent data loss or tampering. After receiving the pressure data, the remote monitoring center can display, store and analyze it in real time. Through the monitoring software, the operator can understand the pressure changes in the processing process in real time and adjust the processing parameters or take other measures as needed.

[0014] Furthermore, the specific steps of the wireless communication module are:

[0015] (1) According to the actual layout and communication requirements of the sapphire processing site, plan the coverage, number of nodes and topology of the wireless communication network, select suitable wireless communication equipment, such as wireless routers, repeaters or gateways, ensure the stability and reliability of the network, deploy wireless communication equipment at key locations on the processing site, and perform initial configuration of the equipment, which includes setting the IP address, wireless channel, encryption method parameters of the equipment, to ensure unimpeded communication between devices;

[0016] (2) After completing the equipment deployment and configuration, conduct a connectivity test on the wireless communication network. By sending test signals or data packets, verify whether the communication between each node is normal to ensure the stability and reliability of the network. Based on the test results, optimize and adjust the performance of the wireless communication network. This may include adjusting the allocation of wireless channels, adding repeaters to expand coverage, and optimizing data transmission rates. Through continuous optimization, ensure that the wireless communication network can meet the real-time and accuracy requirements of the pressure monitoring system during sapphire processing.

[0017] Furthermore, the specific steps of the remote monitoring center are:

[0018] (1) Establish a system platform for the remote monitoring center, select appropriate software and hardware, ensure that the platform can run stably and meet the needs of real-time data processing and monitoring, configure the network access equipment of the remote monitoring center, and ensure that it can achieve stable connection with the wireless communication network, which includes setting network parameters and firewall rules to ensure the security and reliability of data transmission;

[0019] (2) The remote monitoring center receives the pressure data transmitted from the wireless communication network in real time. Through the data analysis program, the received data is converted into a readable format to facilitate subsequent processing and analysis. The analyzed data is further processed, such as filtering and statistics, to extract useful information. Then, the processed data is displayed in real time on the monitoring interface in the form of charts and curves through the monitoring software. At the same time, an alarm mechanism can be set. When the pressure data exceeds the preset range, an alarm is issued in time to remind the operator to take corresponding measures.

[0020] Furthermore, the specific steps of the intelligent management system are:

[0021] (1) According to the pressure monitoring requirements of sapphire processing, the overall architecture of the intelligent management system is designed, which includes determining the system's functional modules, data flow, and interface methods with other systems. According to the architecture design, the various functional modules of the intelligent management system, such as data acquisition module, data processing module, and alarm module, are developed. At the same time, these modules are ensured to be seamlessly integrated to achieve data sharing and interaction;

[0022] (2) Use the pressure data collected by the intelligent management system to conduct in-depth analysis. By applying machine learning, the patterns, trends and anomalies in the data can be discovered to provide support for decision-making. Based on the results of data analysis, the intelligent management system can automatically generate decision support reports or optimization suggestions. These reports and suggestions can provide guidance on pressure control, equipment maintenance and production efficiency during the processing process, helping operators and management make more informed decisions.

[0023] Furthermore, the intelligent management system dynamically adjusts system parameters or operation strategies by adopting a real-time optimization algorithm to optimize system performance. In the pressure monitoring system for sapphire processing, the real-time optimization algorithm can dynamically adjust the processing parameters according to the real-time monitored pressure data to optimize the processing process. Assume that (P(t)) represents the real-time pressure data at time (t), (X(t)) represents the processing parameters (such as cutting speed and feed rate) at time (t), and (Y(t)) represents the optimization target (such as processing efficiency and material utilization rate). Initialize the initial setting. Processing parameters (X_0), set the initial value or range of the optimization target (Y_0), determine the step size (\alpha) of the optimization algorithm and other related parameters Real-time data collection, at each moment (t), collect real-time pressure data (P(t)), real-time optimization, construct an optimization function (f(X(t),P(t))), which measures the deviation between the current processing parameters (X(t)) and real-time pressure data (P(t)) and the optimization target (Y(t)), use the optimization algorithm (such as gradient descent, genetic algorithm) to update the processing parameters (X(t)), the update formula is as follows; Where, \(\Deltat\) is the time step, \(\alpha\) is the learning rate or step size, \(\frac{\partialf}{\partialX}\) is the partial derivative of the optimization function with respect to the processing parameters, feedback and adjustment; apply the updated processing parameters (X(t+\Deltat)) to the processing process, monitor the pressure data (P(t+\Deltat)) and optimization target (Y(t+\Deltat)) after applying the new parameters in real time, and repeat step three for the next round of optimization according to the new feedback data, termination condition; when the optimization target (Y(t)) reaches the preset threshold or meets other termination conditions, stop the optimization process.

[0024] Furthermore, the wireless pressure sensor, as a core component of the system, is specially designed for pressure monitoring during sapphire processing. The sensor adopts advanced silicon-sapphire semiconductor sensitive elements, which not only has extremely high reliability and accuracy, but also can maintain stable performance under the worst working conditions. A miniature wireless communication module is integrated inside the sensor, which can wirelessly transmit the collected pressure data to the system in real time. This wireless transmission method not only avoids the cumbersome wiring problems of traditional wired transmission, but also improves the efficiency and flexibility of data transmission. In addition, the wireless pressure sensor also has the characteristics of extremely small temperature error and high cost performance. It can work stably for a long time, providing reliable guarantee for pressure monitoring in the sapphire processing process.

[0025] Furthermore, the wireless communication network is the key link in realizing data transmission between the wireless pressure sensor and the remote monitoring center. The network adopts advanced wireless communication technologies, such as Wi-Fi, ZigBee or 4G / 5G, to ensure real-time and accurate transmission of data. The wireless communication network has the advantages of wide coverage, fast transmission speed and high stability. It can adapt to the complex and changeable environmental conditions of the sapphire processing site. At the same time, the network also has automatic reconnection and data encryption functions to ensure the security and reliability of data transmission.

[0026] Furthermore, the remote monitoring center is the hub of the entire system, responsible for receiving, processing and analyzing data from wireless pressure sensors. The center is equipped with high-performance computers and professional monitoring software, which can display the pressure change curve during sapphire processing in real time and provide alarm and recording functions. Through the remote monitoring center, operators can understand the pressure conditions at the processing site anytime and anywhere, and promptly discover and deal with abnormal problems. At the same time, the monitoring center can also perform statistical analysis on the data to provide data support for optimizing the processing technology.

[0027] Furthermore, the intelligent management system is the core software part of the system, which is responsible for the intelligent management and control of the entire system. The system adopts real-time optimization algorithms and models, which can automatically identify the pressure change patterns in the processing process and make intelligent adjustments according to preset rules. The intelligent management system also has a learning function, which can continuously optimize its own control strategy and improve processing efficiency and quality. In addition, the system can also be integrated with other management systems to realize data sharing and collaborative work.

[0028] Compared with the prior art, the pressure detection system for sapphire processing has the following beneficial effects:

[0029] 1. The present invention, through an intelligent system, can utilize real-time optimization algorithms and big data analysis technology to deeply process and analyze pressure data and extract valuable information and rules. Through the intelligent system, operators and management can not only understand the pressure status of the processing process in real time, but also obtain targeted optimization suggestions and decision support. These suggestions are based on a large amount of historical data and real-time data, and are obtained through in-depth analysis of intelligent algorithms. Therefore, they have high accuracy and practicality. They can help operators adjust processing parameters and optimize process flow, thereby improving product quality and production efficiency.

[0030] 2. The present invention simplifies the installation and configuration process of the sensor by adopting an integrated design of the wireless pressure sensor and the communication module, and also greatly improves the stability and real-time performance of data transmission. Traditional pressure detection systems usually require cumbersome wiring work, but the integrated design of the present invention eliminates this requirement, allowing the sensor to be more flexibly deployed at various key positions of the processing equipment. At the same time, the built-in communication module ensures real-time transmission of data, allowing operators to promptly understand the pressure changes during the processing process and make corresponding adjustments.

[0031] Other advantages, objectives and features of the present invention will be set forth in part in the following description and, in part, will be apparent to those skilled in the art based on an examination of the following or may be taught from the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0033] Figure 1 This is the flow chart of the pressure detection system during sapphire processing. DETAILED DESCRIPTION

[0034] The technical solutions in the embodiments of the present invention are described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0035] Example 1

[0036] Pressure detection system for sapphire processing, the system includes the following components:

[0037] Wireless pressure sensor: It uses a high-sensitivity and high-precision pressure sensor to collect pressure data in real time during sapphire processing. The sensor has a built-in wireless communication module, which can transmit the collected pressure data to the remote monitoring center wirelessly.

[0038] Wireless communication module: Use wireless communication technology (such as Wi-Fi, ZigBee, LoRa) to build a stable wireless communication network to achieve data transmission between the pressure sensor and the remote monitoring center. The communication network is high-speed, stable, and has strong anti-interference capabilities, which can ensure the real-time and accuracy of the data.

[0039] Remote monitoring center: Set up a dedicated remote monitoring center to receive wireless data from pressure sensors for real-time display, storage and analysis. The monitoring center can be equipped with a professional software system to achieve data visualization, alarm prompts, and historical data query functions, making it convenient for operators to conduct remote monitoring and management;

[0040] Intelligent management system: Based on big data analysis technology, the collected pressure data is intelligently processed and analyzed to extract valuable information, providing data support for optimizing processing technology and improving product quality. At the same time, the system can automatically determine whether there is any abnormality in the processing process based on the preset threshold, and issue an alarm in time to ensure the safety and stability of the processing process.

[0041] The intelligent management system dynamically adjusts the system parameters or operation strategies by adopting real-time optimization algorithms to optimize the system performance. In the pressure monitoring system of sapphire processing, the real-time optimization algorithm can dynamically adjust the processing parameters according to the real-time monitored pressure data to optimize the processing process. Assume that (P(t)) represents the real-time pressure data at time (t), (X(t)) represents the processing parameters (such as cutting speed and feed rate) at time (t), and (Y(t)) represents the optimization target (such as processing efficiency and material utilization rate). Initialize the initial processing parameters. (X_0), set the initial value or range of the optimization target (Y_0), determine the step size (\alpha) and other related parameters of the optimization algorithm. Real-time data collection, at each moment (t), collect real-time pressure data (P(t)), real-time optimization, construct an optimization function (f(X(t),P(t))), which measures the deviation between the current processing parameters (X(t)) and the real-time pressure data (P(t)) and the optimization target (Y(t)), use the optimization algorithm (such as gradient descent, genetic algorithm) to update the processing parameters (X(t)), the update formula is as follows; Where, \(\Deltat\) is the time step, \(\alpha\) is the learning rate or step size, \(\frac{\partialf}{\partialX}\) is the partial derivative of the optimization function with respect to the processing parameters, feedback and adjustment; apply the updated processing parameters (X(t+\Deltat)) to the processing process, monitor the pressure data (P(t+\Deltat)) and optimization target (Y(t+\Deltat)) after applying the new parameters in real time, and repeat step three for the next round of optimization according to the new feedback data, termination condition; when the optimization target (Y(t)) reaches the preset threshold or meets other termination conditions, stop the optimization process.

[0042] Through the intelligent system, real-time optimization algorithms and big data analysis technology can be used to deeply process and analyze pressure data and extract valuable information and rules. Through the intelligent system, operators and management can not only understand the pressure status of the processing process in real time, but also obtain targeted optimization suggestions and decision support. These suggestions are based on a large amount of historical data and real-time data, and are obtained through in-depth analysis of intelligent algorithms. Therefore, they are highly accurate and practical. They can help operators adjust processing parameters and optimize process flow, thereby improving product quality and production efficiency.

[0043] Example 2

[0044] The system consists of the following components:

[0045] Choose a wireless pressure sensor that uses LoRa wireless communication technology. LoRa technology has the advantages of long transmission distance, strong anti-interference ability, and low power consumption. It is very suitable for use in complex industrial environments. The sensor and processing equipment are connected by wire to ensure the stability of data transmission.

[0046] By building a wireless communication network based on LoRa and deploying LoRa gateways and repeaters, data transmission between the wireless pressure sensor and the remote monitoring center is realized. The network adopts an encrypted communication protocol to ensure data security. At the same time, we optimize the network topology to reduce data transmission delays and packet loss rates.

[0047] The remote monitoring center uses high-performance servers and professional software systems to receive, store and analyze data from wireless pressure sensors in real time. The system has powerful data processing capabilities and can filter, count and analyze data to extract valuable information. In addition, the system also has rich visualization functions, which can display pressure data in the form of charts and curves on the monitoring interface, making it convenient for operators to intuitively understand the processing status.

[0048] The intelligent management system plays an important role in this embodiment. The system uses big data analysis technology to deeply mine and analyze pressure data to discover potential problems and optimization space in the processing process. By applying real-time optimization algorithms and pattern recognition technology, the system can predict abnormal situations that may occur in the processing process and issue early warnings. At the same time, the system can also provide operators with personalized optimization suggestions based on historical data and real-time data to help improve processing efficiency and quality.

[0049] By adopting LoRa wireless communication technology and intelligent management system, the real-time, secure and intelligent analysis requirements of data transmission are achieved, providing strong technical support for quality control and process optimization in the sapphire processing industry.

[0050] Example 3

[0051] The steps of the system based on Example 1 and Example 2 are as follows:

[0052] (1) Preparation

[0053] Select a suitable wireless pressure sensor and determine the accuracy and range parameters of the sensor according to processing requirements;

[0054] Determine the installation position of the sensor to ensure accurate measurement of pressure changes during sapphire processing;

[0055] Configure sensor parameters, including sampling frequency and measuring range, to meet the requirements of machining accuracy;

[0056] Configure the wireless communication module, select the appropriate communication protocol, frequency and encryption method to ensure the security and stability of data transmission.

[0057] (2) Data collection and transmission stage

[0058] Wireless pressure sensors collect pressure data in real time during sapphire processing;

[0059] The sensor sends the collected data to the remote monitoring center through the wireless communication module;

[0060] Wireless communication networks ensure real-time transmission of data, avoiding data loss or delay.

[0061] (3) Data processing and analysis stage

[0062] After receiving the data from the sensor, the remote monitoring center performs analysis, filtering, and statistical processing to extract useful information;

[0063] Visualize the processed data and intuitively display the pressure change trend and abnormal conditions in the form of charts and curves;

[0064] Introducing intelligent management systems and using machine learning algorithms to conduct in-depth analysis of pressure data to identify potential problems and optimization space;

[0065] The intelligent management system generates decision support reports or optimization suggestions to provide decision-making basis for operators.

[0066] (4) Decision-making and Execution Stage

[0067] Operators and management make decisions based on reports and recommendations generated by intelligent management systems;

[0068] Adjust processing parameters and optimize process flow according to decision-making results to improve product quality and production efficiency;

[0069] Continuously monitor the adjusted processing to ensure that the pressure is within a reasonable range and handle any abnormal situations in a timely manner.

[0070] (5) Maintenance and upgrade stage

[0071] Regularly maintain and calibrate the wireless pressure sensor and wireless communication module to ensure their normal operation and accuracy;

[0072] Upgrade and improve the system according to actual needs and technological development to improve system performance and stability.

[0073] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A pressure detection system for sapphire processing, characterized in that: The system consists of the following components: Wireless pressure sensor: It uses a high-sensitivity and high-precision pressure sensor to collect pressure data in real time during sapphire processing. The sensor has a built-in wireless communication module, which can transmit the collected pressure data to the remote monitoring center wirelessly. Wireless communication module: Use wireless communication technology (such as Wi-Fi, ZigBee, LoRa) to build a stable wireless communication network to achieve data transmission between the pressure sensor and the remote monitoring center. The communication network is high-speed, stable, and has strong anti-interference capabilities, which can ensure the real-time and accuracy of the data. Remote monitoring center: Set up a dedicated remote monitoring center to receive wireless data from pressure sensors for real-time display, storage and analysis. The monitoring center can be equipped with a professional software system to achieve data visualization, alarm prompts, and historical data query functions, making it convenient for operators to conduct remote monitoring and management; Intelligent management system; Based on big data analysis technology, the collected pressure data is intelligently processed and analyzed to extract valuable information, providing data support for optimizing processing technology and improving product quality. At the same time, the system can automatically determine whether there is any abnormality in the processing process based on preset thresholds, and issue alarm prompts in time to ensure the safety and stability of the processing process.

2. The sapphire processing pressure detection system according to claim 1, characterized in that: The specific steps of the wireless pressure sensor; (1) According to the specific requirements of sapphire processing, select a suitable wireless pressure sensor, ensure that the sensor has sufficient accuracy, stability and durability to adapt to the various pressure and temperature changes that may be encountered during the processing, correctly connect the sensor to the processing equipment, and configure various parameters of the sensor, such as sampling frequency and range. The setting of these parameters will directly affect the accuracy and real-time performance of the pressure data. Configure the wireless communication module of the sensor to ensure that the sensor can establish a stable wireless connection with the remote monitoring center, which usually involves setting the communication protocol, frequency and encryption method; (2) The wireless pressure sensor starts to collect pressure data in real time during the sapphire processing. The sensor converts the collected data into digital signals and sends them out through the wireless module. The sensor transmits the collected pressure data to the remote monitoring center through the wireless network. This process needs to ensure the real-time, stability and security of data transmission to prevent data loss or tampering. After receiving the pressure data, the remote monitoring center can display, store and analyze it in real time. Through the monitoring software, the operator can understand the pressure changes in the processing process in real time and adjust the processing parameters or take other measures as needed.

3. The sapphire processing pressure detection system according to claim 1, characterized in that: Specific steps of the wireless communication module; (1) According to the actual layout and communication requirements of the sapphire processing site, plan the coverage, number of nodes and topology of the wireless communication network, select suitable wireless communication equipment, such as wireless routers, repeaters or gateways, ensure the stability and reliability of the network, deploy wireless communication equipment at key locations on the processing site, and perform initial configuration of the equipment, which includes setting the IP address, wireless channel, encryption method parameters of the equipment, to ensure unimpeded communication between devices; (2) After completing the equipment deployment and configuration, conduct a connectivity test on the wireless communication network. By sending test signals or data packets, verify whether the communication between each node is normal to ensure the stability and reliability of the network. Based on the test results, optimize and adjust the performance of the wireless communication network. This may include adjusting the allocation of wireless channels, adding repeaters to expand coverage, and optimizing data transmission rates. Through continuous optimization, ensure that the wireless communication network can meet the real-time and accuracy requirements of the pressure monitoring system during sapphire processing.

4. The sapphire processing pressure detection system according to claim 1, characterized in that: Specific steps of the remote monitoring center; (1) Establish a system platform for the remote monitoring center, select appropriate software and hardware, ensure that the platform can run stably and meet the needs of real-time data processing and monitoring, configure the network access equipment of the remote monitoring center, and ensure that it can achieve stable connection with the wireless communication network, which includes setting network parameters and firewall rules to ensure the security and reliability of data transmission; (2) The remote monitoring center receives the pressure data transmitted from the wireless communication network in real time. Through the data analysis program, the received data is converted into a readable format to facilitate subsequent processing and analysis. The analyzed data is further processed, such as filtering and statistics, to extract useful information. Then, the processed data is displayed in real time on the monitoring interface in the form of charts and curves through the monitoring software. At the same time, an alarm mechanism can be set. When the pressure data exceeds the preset range, an alarm is issued in time to remind the operator to take corresponding measures.

5. The sapphire processing pressure detection system according to claim 1, characterized in that: Specific steps of the intelligent management system; (1) According to the pressure monitoring requirements of sapphire processing, the overall architecture of the intelligent management system is designed, which includes determining the system's functional modules, data flow, and interface methods with other systems. According to the architecture design, the various functional modules of the intelligent management system, such as data acquisition module, data processing module, and alarm module, are developed. At the same time, these modules are ensured to be seamlessly integrated to achieve data sharing and interaction; (2) Use the pressure data collected by the intelligent management system to conduct in-depth analysis. By applying machine learning, the patterns, trends and anomalies in the data can be discovered to provide support for decision-making. Based on the results of data analysis, the intelligent management system can automatically generate decision support reports or optimization suggestions. These reports and suggestions can provide guidance on pressure control, equipment maintenance and production efficiency during the processing process, helping operators and management make more informed decisions.

6. The sapphire processing pressure detection system according to claim 5, characterized in that The intelligent management system adopts a real-time optimization algorithm to dynamically adjust the system parameters or operation strategies to optimize the system performance. In the pressure monitoring system of sapphire processing, the real-time optimization algorithm can dynamically adjust the processing parameters according to the real-time monitored pressure data to optimize the processing process. Assume that (P(t)) represents the real-time pressure data at time (t), (X(t)) represents the processing parameters (such as cutting speed and feed rate) at time (t), and (Y(t)) represents the optimization target (such as processing efficiency and material utilization rate). Initialize the initial processing parameters. number (X_0), set the initial value or range of the optimization target (Y_0), determine the step size (\alpha) and other related parameters of the optimization algorithm. Real-time data collection, at each moment (t), collect real-time pressure data (P(t)), real-time optimization, construct an optimization function (f(X(t), P(t))), which measures the deviation between the current processing parameters (X(t)) and the real-time pressure data (P(t)) and the optimization target (Y(t)), use the optimization algorithm (such as gradient descent, genetic algorithm) to update the processing parameters (X(t)), the update formula is as follows; Where, \(\Deltat\) is the time step, \(\alpha\) is the learning rate or step size, \(\frac{\partialf}{\partialX}\) is the partial derivative of the optimization function with respect to the processing parameters, feedback and adjustment; apply the updated processing parameters (X(t+\Deltat)) to the processing process, monitor the pressure data (P(t+\Deltat)) and optimization target (Y(t+\Deltat)) after applying the new parameters in real time, and repeat step three for the next round of optimization according to the new feedback data, termination condition; when the optimization target (Y(t)) reaches the preset threshold or meets other termination conditions, stop the optimization process.

7. The sapphire processing pressure detection system according to claim 2, characterized in that ,The wireless pressure sensor as the core component of the system is specially designed for pressure monitoring in the sapphire processing process. ,The sensor adopts advanced silicon-sapphire semiconductor sensitive elements, which not only has extremely high reliability and accuracy, but can also maintain stable performance under the worst working conditions. ,A miniature wireless communication module is integrated inside the sensor, which can wirelessly transmit the collected pressure data to the system in real time. ,This wireless transmission method not only avoids the cumbersome wiring problems of traditional wired transmission, but also improves the efficiency and flexibility of data transmission. ,In addition, the wireless pressure sensor also has the characteristics of extremely small temperature error and high cost performance. ,It can work stably for a long time, providing reliable guarantee for the pressure monitoring in the sapphire processing process.

8. The sapphire processing pressure detection system according to claim 3, characterized in that ,The wireless communication network is the key link to realize data transmission between the wireless pressure sensor and the remote monitoring center. The network adopts advanced wireless communication technologies, such as Wi-Fi, ZigBee or 4G / 5G, to ensure real-time and accurate transmission of data. The wireless communication network has the advantages of wide coverage, fast transmission speed and high stability. It can adapt to the complex and changeable environmental conditions of the sapphire processing site. At the same time, the network also has automatic reconnection and data encryption functions, ensuring the security and reliability of data transmission.

9. The sapphire processing pressure detection system according to claim 4, characterized in that The remote monitoring center is the hub of the entire system, responsible for receiving, processing and analyzing data from wireless pressure sensors. The center is equipped with high-performance computers and professional monitoring software, which can display the pressure change curve during sapphire processing in real time and provide alarm and recording functions. Through the remote monitoring center, operators can understand the pressure conditions at the processing site anytime and anywhere, and promptly discover and deal with abnormal problems. At the same time, the monitoring center can also perform statistical analysis on the data to provide data support for optimizing the processing technology.

10. The sapphire processing pressure detection system according to claim 6, characterized in that ,The intelligent management system is the core software part of the system, which is responsible for ,intelligent management and control of the entire system. ,The system adopts real-time optimization algorithms and models, which can ,automatically identify the pressure change patterns during the processing process and ,make intelligent adjustments according to preset rules. ,The intelligent management system also has a learning function, which can ,continuously optimize its own control strategy and improve the processing efficiency and ,quality. In addition, the system can also be integrated with other ,management systems to realize data sharing and collaborative work.

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