A steep-pulse perforation ablation emergency stop energy release control system and method

Abstract

This invention discloses a steep-pulse perforation ablation emergency stop energy release control system and method, relating to the field of perforation manufacturing technology. The system, through a comprehensive energy release analysis module, calculates the energy diffusion rate Ks and the heat-affected zone area Ry, and combines this with the perforation temperature Ckwd to obtain the energy release control index Snkz, predicting the heat diffusion behavior and temperature change trend in the material. The system sets a pulse frequency threshold F2 and generates an optimized energy release strategy by comparing it with the energy release control index Snkz. When the energy release control index Snkz exceeds the pulse frequency threshold F2, the system reduces and adjusts the pulse energy E and pulse frequency f to reduce heat output and prevent material overheating; when the energy release control index Snkz is below the pulse frequency threshold F2, the system appropriately increases the pulse energy E and pulse frequency f to improve processing efficiency. The system can maximize processing efficiency and heat control effect while ensuring safety.

Description

Technical Field

[0001] This invention relates to the field of perforation manufacturing technology, specifically to a steep pulse perforation ablation emergency stop energy release control system and method. Background Technology

[0002] The steep-pulse perforation ablation emergency stop energy release control system belongs to the field of manufacturing technology, which encompasses everything from traditional metal processing to modern high-end manufacturing processes, with engine manufacturing being a particularly critical application. In these applications, the implementation of micro-hole machining processes is crucial, primarily used to improve the performance and efficiency of key components such as turbine blades. To achieve precise material removal, pulse perforation technology, as an innovative method, utilizes high-frequency, high-energy laser pulses to rapidly and accurately perforate materials, meeting the requirements of modern engineering for complex geometries and stringent tolerances.

[0003] While pulsed perforation technology is widely used in high-precision manufacturing, it still faces numerous challenges in actual processing. One of the most prominent issues is material overheating caused by heat accumulation, leading to decreased processing accuracy or even material damage. Traditional control systems typically rely on fixed processing parameters, lacking the ability to monitor and dynamically adjust the process in real time. Therefore, when excessive heat accumulates, existing systems often fail to react promptly, potentially causing micro-hole deformation or an excessively large heat-affected zone, thus impacting the quality of the final product. Furthermore, existing control schemes are inadequate in managing safety risks, failing to effectively prevent sudden malfunctions during processing and increasing the risk of equipment damage. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a steep pulse perforation ablation emergency stop energy release control system and method, which solves the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solution: including a data acquisition module, a data processing module, a preliminary emergency stop judgment module, a comprehensive energy release analysis module, and an energy release control module;

[0006] The data acquisition module is used to install an integrated sensor group around the micro-hole machining of engine turbine blades and on the pulse generator to collect material processing data and pulse data in real time.

[0007] The data processing module is used to upload the collected processing data and pulse data to the cloud platform for storage via wireless transmission, and to preprocess the processing data and pulse data.

[0008] The preliminary emergency stop judgment module is used to calculate the cumulative total heat Rl and temperature change rate ΔT based on the pre-processed processing data and pulse data, and to calculate the perforation temperature Ckwd in the same way. Then, it is used to compare and evaluate the preset safety threshold F1 to determine whether to trigger the emergency stop strategy.

[0009] The integrated energy release analysis module is used to calculate the energy diffusion rate Ks and the heat-affected zone area Ry based on the pre-processed processing data and pulse data, and to calculate the energy release control index Snkz in combination with the perforation temperature Ckwd.

[0010] The energy release control module is used to compare and evaluate the preset pulse frequency threshold F2 with the acquired energy release control index Snkz, analyze the pulse energy and frequency, and generate an energy release strategy.

[0011] Preferably, the data acquisition module includes a processing data acquisition unit and a pulse data acquisition unit;

[0012] The processing data acquisition unit acquires material processing data in real time by installing a first integrated sensor group around the micro-hole machining area of ​​the engine turbine blade. The first integrated sensor group includes a thermal conductivity meter, a laser thickness gauge, a thermal diffusivity meter, a differential thermal analyzer, and a high-temperature melting point meter. The material processing data includes the material's thermal conductivity K, material thickness d, and thermal diffusivity. Heat capacity C and melting point temperature Tm;

[0013] The pulse data acquisition unit is used to install a second integrated sensor group inside the pulse piercing device to collect the pulse data of the piercing pulse device in real time during the micro-hole processing of the turbine blade. The second integrated sensor group includes a pulse frequency meter and a laser energy meter, and the pulse data includes the pulse frequency f and the pulse energy E.

[0014] Preferably, the data processing module includes a data transmission unit, a cloud platform storage unit, and a data preprocessing unit;

[0015] The data transmission unit converts analog signals to digital signals by installing a built-in analog-to-digital converter (ADC) in the integrated sensor. After packaging the material processing data and pulse data according to the protocol, it connects to the local gateway via the WI-FI wireless communication protocol. The local gateway then transmits the packaged material processing data and pulse data to the cloud platform in real time via the Internet.

[0016] The cloud platform storage unit uses NoSQL big data technology to build a cloud platform database and stores the received material processing data and pulse data in real time. The cloud platform uses machine learning algorithms and big data analysis tools to process and analyze the real-time data, extract useful information and generate corresponding control commands. The analysis results are sent back to the local control system through the cloud platform to adjust equipment parameters and issue emergency stop commands.

[0017] The data preprocessing unit is used to remove noise and interference from the material processing data and pulse data stored in the cloud platform database using Kalman digital filtering technology, then to eliminate instantaneous abnormal data points using median filtering, and finally to correct measurement errors and equipment deviations using equipment calibration data.

[0018] Preferably, the preliminary emergency stop judgment module includes a heat accumulation calculation unit, a temperature change calculation unit, and an emergency stop control unit;

[0019] The heat accumulation calculation unit is used to construct a heat accumulation algorithm, and substitute the preprocessed pulse data into it to calculate and obtain the total accumulated heat Rl, and predict the heat accumulation within a unit time t.

[0020] The temperature change calculation unit is used to construct a heat change algorithm, which combines the preprocessed material processing data with the cumulative total heat Rl to calculate the temperature change rate ΔT, analyzes the thermal conduction response of the material during the micro-hole processing of engine turbine blades, and reflects the influence of time on temperature change.

[0021] Preferably, the emergency stop control unit includes a perforation temperature calculation unit and an emergency stop evaluation unit;

[0022] The perforation temperature calculation unit is used to perform dimensionless processing on the acquired cumulative total heat Rl and temperature change rate ΔT, and then combine the influence of temperature change to calculate the perforation temperature Ckwd, predicting the temperature change of engine turbine blade material caused by pulse energy input during micro-hole processing.

[0023] Preferably, the emergency stop assessment unit presets a safety threshold F1 based on material properties and process requirements, then compares and assesses it with the obtained perforation temperature Ckwd, and executes an emergency stop strategy based on the assessment results.

[0024] The specific assessment plan is as follows:

[0025] When the perforation temperature Ckwd(t) ≥ safety threshold F1, it indicates that the engine turbine blade material is overheating during the current micro-hole processing. At this time, an emergency stop strategy is executed. Control commands are sent to the pulse device through the cloud platform to immediately stop the pulse energy input and start the cooling system for cooling treatment. At the same time, an energy release control strategy is executed.

[0026] When the perforation temperature Ckwd(t) < the safety threshold F1, it indicates that the processing parameters are safe to continue processing during the current micro-hole processing.

[0027] Preferably, the integrated energy release analysis module includes an energy diffusion prediction unit, a thermally affected area prediction unit, and an integrated energy release calculation unit;

[0028] The energy diffusion prediction unit is used to construct an energy diffusion prediction algorithm, and to combine the acquired material processing data and pulse data to calculate the energy diffusion rate Ks, analyze the diffusion behavior of heat in the material, and predict the temperature change trend over time.

[0029] The heat-affected zone prediction unit constructs a heat-affected zone prediction algorithm, substitutes the acquired pulse data, calculates and obtains the area Ry of the heat-affected zone, determines the area of ​​the heat-affected zone, and predicts the size of the local heat-affected zone.

[0030] Preferably, the integrated energy release calculation unit is used to calculate and obtain the energy release control index Snkz based on the obtained energy diffusion rate Ks and heat-affected zone area Ry, and in combination with the perforation temperature Ckwd.

[0031] Preferably, the energy release control module performs average processing based on the pulse punching frequency of historical normal operation, sets a pulse frequency threshold F2, compares and evaluates it with the obtained energy release control index Snkz(t), and executes an energy release control strategy based on the evaluation result.

[0032] The specific assessment content is as follows:

[0033] When the energy release control index Snkz(t) > pulse frequency threshold F2, the first energy release control scheme is executed, the pulse energy E and pulse frequency f are adjusted, the heat output of the pulse device is optimized, the pulse energy E and pulse frequency f are reduced, and the heat output is reduced.

[0034] When the energy release control index Snkz(t) = pulse frequency threshold F2, there is no need to perform energy release control and the current heat output can continue to be maintained.

[0035] When the energy release control index Snkz(t) < pulse frequency threshold F2, the second energy release control scheme is executed. Compared with the first energy release control scheme, the pulse energy E and pulse frequency f are adjusted in reverse to optimize the heat output of the pulse equipment, appropriately increase the pulse energy and frequency, and improve the processing efficiency.

[0036] A method for controlling the emergency stop and energy release in steep pulse perforation ablation includes the following steps:

[0037] S1. First, an integrated sensor group is installed around the micro-hole machining of the engine turbine blades and on the pulse generator to collect material processing data and pulse data in real time.

[0038] S2. The collected processing data and pulse data are uploaded to the cloud platform for storage via wireless transmission, and the processing data and pulse data are preprocessed.

[0039] S3. Based on the preprocessed processing data and pulse data, the algorithm is constructed to calculate the cumulative total heat Rl and the temperature change rate ΔT, and the perforation temperature Ckwd is obtained by correlation calculation. Then, the safety threshold F1 is preset for comparison and evaluation to determine the triggering of the emergency stop strategy.

[0040] S4. Simultaneously, based on the pre-processed processing data and pulse data, calculate the energy diffusion rate Ks and the heat-affected zone area Ry, and combine them with the perforation temperature Ckwd to calculate the energy release control index Snkz.

[0041] S5. Finally, the preset pulse frequency threshold F2 is compared and evaluated with the obtained energy release control index Snkz to analyze the pulse energy and frequency, and generate an energy release strategy.

[0042] This invention provides a steep-pulse perforation ablation emergency stop energy release control system and method. It has the following beneficial effects:

[0043] (1) This system achieves comprehensive real-time monitoring of the micro-hole machining process of engine turbine blades through a data acquisition module and a data processing module. The data acquisition module includes a machining data acquisition unit and a pulse data acquisition unit, which can acquire material machining data and pulse data in real time through an integrated sensor group, and upload them to the cloud platform for storage and preprocessing via wireless transmission. The data processing module uses Kalman filtering technology to remove noise and interference, and eliminates instantaneous abnormal data points through median filtering. At the same time, it combines equipment calibration data to correct measurement errors and equipment deviations, ensuring the accuracy and real-time performance of the data.

[0044] (2) The system, through a preliminary emergency stop judgment module, constructs a heat accumulation algorithm and a temperature change algorithm to calculate the total accumulated heat Rl and the temperature change rate ΔT in real time, and obtains the perforation temperature Ckwd by combining dimensionless processing. It then performs a preliminary comparison and evaluation with the system's preset safety threshold F1 to promptly determine whether to trigger the emergency stop strategy. When the perforation temperature Ckwd exceeds the safety threshold F1, the system quickly executes the emergency stop strategy, stops the pulse energy input, and starts the cooling system for cooling treatment, thereby preventing material damage due to overheating. This mechanism significantly improves the safety of the processing, reduces material loss and equipment failure risks, and ensures high quality and high precision in micro-hole processing.

[0045] (3) The system calculates the energy diffusion rate Ks and the heat-affected zone area Ry through a comprehensive energy release analysis module, and calculates the energy release control index Snkz in conjunction with the perforation temperature Ckwd, predicting the heat diffusion behavior and temperature change trend in the material. The system sets a pulse frequency threshold F2 and generates an optimized energy release strategy by comparing and evaluating it with the energy release control index Snkz. When the energy release control index Snkz exceeds the pulse frequency threshold F2, the system reduces and adjusts the pulse energy E and pulse frequency f to reduce heat output and prevent the material from overheating; when the energy release control index Snkz is lower than the pulse frequency threshold F2, the system appropriately increases the pulse energy and frequency to improve processing efficiency. Through this mechanism, the system can maximize processing efficiency and heat control effect while ensuring safety, thereby improving overall production efficiency. Attached Figure Description

[0046] Figure 1 This is a schematic diagram of the steep pulse perforation ablation emergency stop energy release control system of the present invention;

[0047] Figure 2 This is a schematic diagram of the steps of a steep pulse perforation ablation emergency stop energy release control method according to the present invention. Detailed Implementation

[0048] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Example 1

[0049] Please see Figure 1 This invention provides a steep pulse perforation ablation emergency stop energy release control system. To achieve the above objectives, this invention is implemented through the following technical solution: including a data acquisition module, a data processing module, a preliminary emergency stop judgment module, a comprehensive energy release analysis module, and an energy release control module;

[0050] The data acquisition module is used to install an integrated sensor group around the micro-hole machining of engine turbine blades and on the pulse generator to collect material processing data and pulse data in real time;

[0051] The data processing module is used to upload the collected processing data and pulse data to the cloud platform for storage via wireless transmission, and to preprocess the processing data and pulse data.

[0052] The preliminary emergency stop judgment module is used to calculate the cumulative total heat Rl and temperature change rate ΔT based on the pre-processed processing data and pulse data, and to calculate the perforation temperature Ckwd in the same way. Then, it compares and evaluates the preset safety threshold F1 to determine whether to trigger the emergency stop strategy.

[0053] The integrated energy release analysis module is used to calculate the energy diffusion rate Ks and the heat-affected zone area Ry based on the pre-processed processing data and pulse data, and to calculate the energy release control index Snkz in combination with the perforation temperature Ckwd.

[0054] The energy release control module is used to compare and evaluate the preset pulse frequency threshold F2 with the acquired energy release control index Snkz, analyze the pulse energy and frequency, and generate an energy release strategy.

[0055] In this embodiment, the system integrates sensor groups on the processing equipment and pulse generator via a data acquisition module to collect material processing data and pulse data in real time. This data is then wirelessly transmitted to a cloud platform for storage and preprocessing. This process ensures the real-time nature and accuracy of the data, providing reliable data support for subsequent judgment and control. Through a preliminary emergency stop judgment module, the system constructs an algorithm formula based on the preprocessed data to calculate the accumulated total heat Rl and the temperature change rate ΔT, and further calculates the perforation temperature Ckwd. This is compared with a preset safety threshold F1, allowing the system to determine in real time whether to trigger an emergency stop strategy, ensuring the safety of the processing. This mechanism effectively prevents material overheating due to heat accumulation, improving the safety and reliability of the micro-hole processing process. The comprehensive energy release analysis module calculates the energy diffusion rate Ks and the heat-affected zone area Ry, and combines this with the perforation temperature Ckwd to generate an energy release control index Snkz, providing a decision-making basis for the energy release control module. The energy release control module optimizes the pulse energy and frequency by comparing the energy release control index Snkz with a preset pulse frequency threshold F2, thereby generating an effective energy release strategy. Compared to traditional technologies, this system offers greater precision and flexibility in heat management and energy release, significantly improving processing efficiency and finished product quality while reducing equipment wear and tear and the risk of failure, thus enhancing overall production efficiency. Example 2

[0056] This embodiment is an explanation based on Embodiment 1. Please refer to it. Figure 1 Specifically: the data acquisition module includes a processing data acquisition unit and a pulse data acquisition unit;

[0057] The processing data acquisition unit, by installing a first integrated sensor group around the micro-hole machining area of ​​the engine turbine blades, collects material processing data of the turbine blades in real time during the micro-hole machining process. The first integrated sensor group includes a thermal conductivity meter, a laser thickness gauge, a thermal diffusivity meter, a differential thermal analyzer, and a high-temperature melting point meter. The material processing data includes the material's thermal conductivity K, material thickness d, and thermal diffusivity. Heat capacity C and melting point temperature Tm;

[0058] The pulse data acquisition unit is used to install a second integrated sensor group inside the pulse piercing equipment to collect the pulse data of the piercing pulse equipment in real time during the micro-hole processing of turbine blades. The second integrated sensor group includes a pulse frequency meter and a laser energy meter, and the pulse data includes the pulse frequency f and the pulse energy E.

[0059] In this embodiment, the system uses an integrated sensor array, comprised of a processing data acquisition unit and a pulse data acquisition unit, to collect key data in real time during the micro-hole machining process, providing comprehensive data support for the micro-hole machining of turbine blades. The processing data acquisition unit, installed around the machining area, utilizes sensors such as a thermal conductivity meter, laser thickness gauge, thermal diffusivity meter, differential thermal analyzer, and high-temperature melting point meter to collect data in real time on the material's thermal conductivity K, thickness d, thermal diffusivity, heat capacity C, and melting point temperature Tm. This real-time acquisition and analysis of data helps to accurately control the thermodynamic changes of the material during machining, providing a solid foundation for optimizing machining parameters and improving product quality. The pulse data acquisition unit, installed inside the pulse piercing equipment, uses a pulse frequency meter and laser energy meter to collect pulse frequency f and pulse energy E in real time. This data acquisition enables the system to monitor the pulse energy input in real time and precisely control heat management during the piercing process. Through the integrated application of these two modules, the system can acquire and process key data during the micro-hole machining process in real time, optimize machining parameters, and improve machining quality. Compared with existing technologies, this system has significant advantages in terms of the comprehensiveness and real-time nature of data acquisition, improves the safety and stability of the processing, significantly enhances overall production efficiency and product quality, and reduces equipment wear and tear and failure risks. Example 3

[0060] This embodiment is an explanation based on Embodiment 2. Please refer to it. Figure 1 Specifically: the data processing module includes a data transmission unit, a cloud platform storage unit, and a data preprocessing unit;

[0061] The data transmission unit converts analog data into digital data by installing a built-in analog-to-digital converter (ADC) in the integrated sensor. After packaging the material processing data and pulse data according to the protocol, it connects to the local gateway via the WI-FI wireless communication protocol. The local gateway then transmits the packaged material processing data and pulse data to the cloud platform in real time via the Internet.

[0062] The cloud platform storage unit uses NoSQL big data technology to build a cloud platform database and stores the received material processing data and pulse data in real time. The cloud platform uses machine learning algorithms and big data analysis tools to process and analyze the real-time data, extract useful information and generate corresponding control commands. The analysis results are sent back to the local control system through the cloud platform to adjust equipment parameters and issue emergency stop commands.

[0063] The data preprocessing unit uses Kalman digital filtering to remove noise and interference from the material processing data and pulse data stored in the cloud platform database, then uses median filtering to eliminate instantaneous abnormal data points, and corrects measurement errors and equipment deviations using equipment calibration data.

[0064] In this embodiment, the system uses a built-in analog-to-digital converter (ADC) in the data transmission unit to convert the collected material processing data and pulse data into digital signals, which are then transmitted to the cloud platform via Wi-Fi wireless communication. This real-time and stable data transmission method ensures the continuity and integrity of the processing data, eliminating data loss and transmission delays. The cloud platform storage unit employs NoSQL database technology, combined with big data analytics and machine learning algorithms, to efficiently store and process the transmitted real-time data. By analyzing the processing and pulse data in real time, the cloud platform can quickly extract useful information and generate corresponding control commands, thereby optimizing equipment parameters and improving processing accuracy. Simultaneously, the cloud platform's real-time monitoring and analysis capabilities enable the system to promptly detect anomalies and issue emergency stop commands, preventing equipment failures and safety hazards. The data preprocessing unit uses Kalman digital filtering and median filtering techniques to remove noise and interference, eliminating transient abnormal data points, further improving data accuracy and reliability. Equipment calibration data is used to correct measurement errors and equipment deviations, ensuring high data precision. Compared to traditional technologies, the application of this module significantly improves the real-time performance and accuracy of data processing, enabling the system to maintain efficient and stable operation in complex processing environments, significantly improving overall production efficiency and product quality, and reducing equipment maintenance costs. Example 4

[0065] This embodiment is an explanation based on Embodiment 3. Please refer to it. Figure 1Specifically: the preliminary emergency stop judgment module includes a heat accumulation calculation unit, a temperature change calculation unit, and an emergency stop control unit;

[0066] The heat accumulation calculation unit is used to construct the heat accumulation algorithm formula, and substitute the preprocessed pulse data into it to calculate and obtain the total accumulated heat Rl, and predict the heat accumulation within a unit time t;

[0067] The total accumulated heat Rl is calculated using the following heat accumulation formula:

[0068] ;

[0069] In the formula, This represents the system efficiency factor, used to consider time-energy conversion efficiency.

[0070] The temperature change calculation unit is used to construct the heat change algorithm formula, combine the preprocessed material processing data with the cumulative total heat Rl, calculate the temperature change rate ΔT, and analyze the thermal conduction response of the material during the micro-hole processing of engine turbine blades, reflecting the influence of time on temperature change.

[0071] The rate of temperature change ΔT is obtained using the following formula:

[0072] ;

[0073] In the formula, m represents the mass of the material, k represents the thermal conductivity of the material, and e represents the first exponential function.

[0074] The emergency stop control unit includes a perforation temperature calculation unit and an emergency stop assessment unit;

[0075] The perforation temperature calculation unit is used to perform dimensionless processing on the acquired cumulative total heat Rl and temperature change rate ΔT, and then combine the influence of temperature change to calculate the perforation temperature Ckwd, predicting the temperature change of engine turbine blade material caused by pulse energy input during micro-hole processing.

[0076] The perforation temperature Ckwd is calculated using the following algorithm formula;

[0077] ;

[0078] In the formula, T0 represents the initial temperature, which serves as the reference value for temperature change of the engine turbine blade material during micro-hole machining, and Ckwd(t) represents the piercing temperature at time t. The term represents the exponential decay, which indicates the process of heat diffusion and decay in the material over time, reflecting the thermal diffusion characteristics of the material. Initially, the exponential decay term is close to 1, and the temperature change ΔT is close to its maximum value. As time t increases, the exponential decay term approaches zero, and the temperature change tends to stabilize.

[0079] The emergency stop assessment unit presets a safety threshold F1 based on material properties and process requirements, then compares and evaluates it with the obtained perforation temperature Ckwd, and executes an emergency stop strategy based on the assessment results.

[0080] The specific assessment plan is as follows:

[0081] When the perforation temperature Ckwd(t) ≥ safety threshold F1, it indicates that the engine turbine blade material is overheating during the current micro-hole processing. At this time, an emergency stop strategy is executed. Control commands are sent to the pulse device through the cloud platform to immediately stop the pulse energy input and start the cooling system for cooling treatment. At the same time, an energy release control strategy is executed.

[0082] When the perforation temperature Ckwd(t) < the safety threshold F1, it indicates that the processing parameters are safe to continue processing during the current micro-hole processing.

[0083] In this embodiment, the system uses a heat accumulation calculation unit to accurately calculate the total accumulated heat Rl by constructing a heat accumulation algorithm formula, thereby predicting the heat accumulation per unit time and ensuring accurate control of heat changes during processing. The temperature change calculation unit combines material processing data and the total accumulated heat to calculate the temperature change rate ΔT, thus analyzing the thermal conduction response of the material during micro-hole processing. This is crucial for real-time understanding of temperature changes and material state. The emergency stop control unit further combines the total accumulated heat Rl and the temperature change rate ΔT to calculate the perforation temperature Ckwd. By comparing this temperature with a preset safety threshold F1, the safety of the current processing state is assessed. If the perforation temperature exceeds the safety threshold F1, the system immediately executes an emergency stop strategy, stopping pulse energy input and activating the cooling system, effectively preventing the risk of material overheating and equipment damage. This module, through precise temperature monitoring and rapid emergency stop response, greatly improves the safety and reliability of the system. Compared to traditional techniques, this module achieves comprehensive monitoring and dynamic adjustment of the micro-hole processing process through refined data calculation and real-time evaluation. Traditional technologies often rely on operator experience and periodic inspections, making it difficult to achieve real-time, precise temperature control and emergency stop response. However, the preliminary emergency stop judgment module, through automated and intelligent algorithms and real-time data processing, not only improves the safety and stability of the processing, but also significantly enhances production efficiency and product quality, while reducing downtime and maintenance costs caused by equipment failures. Example 5

[0084] This embodiment is an explanation based on Embodiment 4. Please refer to it. Figure 1 Specifically: the integrated energy release analysis module includes an energy diffusion prediction unit, a thermal impact zone prediction unit, and an integrated energy release calculation unit;

[0085] The energy diffusion prediction unit is used to construct the energy diffusion prediction algorithm formula, and to combine the acquired material processing data and pulse data into the formula to calculate the energy diffusion rate Ks, analyze the heat diffusion behavior in the material, and predict the temperature change trend over time.

[0086] The heat-affected zone prediction unit constructs a heat-affected zone prediction algorithm formula, substitutes the acquired pulse data into it, calculates and obtains the heat-affected zone area Ry, determines the area of ​​the heat-affected zone, and predicts the size of the local heat-affected zone.

[0087] The energy diffusivity Ks and the heat-affected zone area Ry are calculated using the following algorithm formula;

[0088] ;

[0089] ;

[0090] In the formula, The Laplace operator represents temperature, and the spatial second derivative of temperature is denoted by . represents the time constant, and e represents the second exponential function;

[0091] D represents the perforation diameter, which is obtained through process parameter settings and actual measurement, and π represents pi.

[0092] The integrated energy release calculation unit is used to calculate the energy release control index Snkz based on the obtained energy diffusion rate Ks and heat-affected zone area Ry, and in combination with the perforation temperature Ckwd.

[0093] The energy release control index Snkz is calculated using the following algorithm formula;

[0094] ;

[0095] In the formula, Snkz(t) represents the energy release control index for the predicted time period t, and represents the energy output value of the pulse device during the time period t.

[0096] In this embodiment, the system uses an energy diffusion prediction unit to construct an energy diffusion prediction algorithm formula, combining material processing data and pulse data to calculate the energy diffusion rate Ks, accurately predicting the heat diffusion behavior in the material and the temperature change trend over time. This process helps identify potential thermal damage areas, optimize processing parameters, and ensure processing quality. The heat-affected zone prediction unit constructs a heat-affected zone prediction algorithm formula to calculate the area Ry, determining the size of the local heat-affected zone. This function is crucial for predicting and controlling the heat-affected zone, helping to reduce structural damage caused by material overheating and improve processing accuracy and product quality. The comprehensive energy release calculation unit calculates the energy release control index Snkz using the energy diffusion rate Ks, the heat-affected zone area Ry, and the perforation temperature Ckwd. This index provides the system with a comprehensive energy control reference, enabling the pulse device to adjust energy according to actual conditions and optimize energy release strategies. Compared with traditional techniques, this module achieves real-time monitoring and dynamic control of heat diffusion and the heat-affected zone through detailed data analysis and intelligent algorithms. Traditional methods often rely on experience and simple measurement methods, making it difficult to achieve accurate prediction and control of heat diffusion. The integrated energy release analysis module, through the application of big data and intelligent algorithms, achieves high-precision prediction and control of heat diffusion and heat-affected zones, effectively improving the safety and stability of the processing, reducing thermal damage, and improving product quality and processing efficiency. Example 6

[0097] This embodiment is an explanation based on Embodiment 5. Please refer to it. Figure 1 Specifically: the energy release control module performs average processing on the pulse punching frequency based on historical normal operation, sets the pulse frequency threshold F2, compares and evaluates it with the obtained energy release control index Snkz(t), and executes the energy release control strategy based on the evaluation results.

[0098] The specific assessment content is as follows:

[0099] When the energy release control index Snkz(t) > pulse frequency threshold F2, the first energy release control scheme is executed, the pulse energy E and pulse frequency f are adjusted, the heat output of the pulse device is optimized, the pulse energy E and pulse frequency f are reduced, and the heat output is reduced.

[0100] When the energy release control index Snkz(t) = pulse frequency threshold F2, there is no need to perform energy release control and the current heat output can continue to be maintained.

[0101] When the energy release control index Snkz(t) < pulse frequency threshold F2, the second energy release control scheme is executed. Compared with the first energy release control scheme, the pulse energy E and pulse frequency f are adjusted in reverse to optimize the heat output of the pulse equipment, appropriately increase the pulse energy and frequency, and improve the processing efficiency.

[0102] In this embodiment, the system uses an energy release control module to average the pulse frequencies based on historical normal operation, sets a pulse frequency threshold F2, and compares it with the energy release control index Snkz to achieve dynamic heat output regulation of the pulse equipment. When the energy release control index Snkz is higher than the pulse frequency threshold F2, the system executes a first energy release control scheme, adjusting the pulse energy E and frequency f to reduce heat output, thereby preventing material overheating and protecting the workpiece. When the energy release control index Snkz equals the pulse frequency threshold F2, the system maintains the current heat output to ensure stable processing. When the energy release control index Snkz is lower than the pulse frequency threshold F2, the system executes a second energy release control scheme, increasing the pulse energy and frequency to improve processing efficiency. This module achieves intelligent regulation of the energy output of the pulse equipment, ensuring the stability and safety of the processing process. The energy release control module achieves real-time control and optimization of the processing process by intelligently adjusting the heat output of the pulse equipment. Compared with traditional technologies, this module improves processing efficiency and product quality while ensuring processing safety and stability. By dynamically adjusting the pulse energy and frequency, the system can adapt to different processing needs, providing higher processing accuracy and efficiency, and significantly improving the overall performance and application value of pulse processing technology. Example 7

[0103] Please see Figure 1 and Figure 2 A method for controlling the emergency stop of energy release in steep pulse perforation ablation includes the following steps:

[0104] S1. First, an integrated sensor group is installed around the micro-hole machining of the engine turbine blades and on the pulse generator to collect material processing data and pulse data in real time.

[0105] S2. The collected processing data and pulse data are uploaded to the cloud platform for storage via wireless transmission, and the processing data and pulse data are preprocessed.

[0106] S3. Based on the preprocessed processing data and pulse data, construct the algorithm formula to calculate the cumulative total heat Rl and temperature change rate ΔT, and calculate the perforation temperature Ckwd in the same way. Then, set a safety threshold F1 for comparison and evaluation to determine the triggering of the emergency stop strategy.

[0107] S4. Simultaneously, based on the pre-processed processing data and pulse data, calculate the energy diffusion rate Ks and the heat-affected zone area Ry, and combine them with the perforation temperature Ckwd to calculate the energy release control index Snkz.

[0108] S5. Finally, the preset pulse frequency threshold F2 is compared and evaluated with the obtained energy release control index Snkz to analyze the pulse energy and frequency, and generate an energy release strategy.

[0109] 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. A steep-pulse perforation ablation emergency stop energy release control system, characterized in that: It includes a data acquisition module, a data processing module, a preliminary emergency stop judgment module, a comprehensive energy release analysis module, and an energy release control module; The data acquisition module is used to install an integrated sensor group around the micro-hole machining of engine turbine blades and on the pulse generator to collect material processing data and pulse data in real time. The data processing module is used to upload the collected processing data and pulse data to the cloud platform for storage via wireless transmission, and to preprocess the processing data and pulse data. The preliminary emergency stop judgment module is used to calculate the cumulative total heat Rl and temperature change rate ΔT based on the pre-processed processing data and pulse data, and to calculate the perforation temperature Ckwd in the same way. Then, it is used to compare and evaluate the preset safety threshold F1 to determine whether to trigger the emergency stop strategy. The integrated energy release analysis module is used to calculate the energy diffusion rate Ks and the heat-affected zone area Ry based on the pre-processed processing data and pulse data, and to calculate the energy release control index Snkz in combination with the perforation temperature Ckwd. The energy release control module is used to compare and evaluate the preset pulse frequency threshold F2 with the acquired energy release control index Snkz, analyze the pulse energy and frequency, and generate an energy release strategy. The integrated energy release analysis module includes an energy diffusion prediction unit, a thermally affected area prediction unit, and an integrated energy release calculation unit. The energy diffusion prediction unit is used to construct an energy diffusion prediction algorithm, and to combine the acquired material processing data and pulse data to calculate the energy diffusion rate Ks, analyze the diffusion behavior of heat in the material, and predict the temperature change trend over time. The heat-affected zone prediction unit constructs a heat-affected zone prediction algorithm, substitutes the acquired pulse data, calculates and obtains the heat-affected zone area Ry, determines the heat-affected zone area, and predicts the size of the local heat-affected zone. The integrated energy release calculation unit is used to calculate and obtain the energy release control index Snkz based on the obtained energy diffusion rate Ks and heat-affected zone area Ry, and in combination with the perforation temperature Ckwd.

2. The steep pulse perforation ablation emergency stop energy release control system according to claim 1, characterized in that: The data acquisition module includes a processing data acquisition unit and a pulse data acquisition unit; The processing data acquisition unit acquires material processing data in real time by installing a first integrated sensor group around the micro-hole machining area of ​​the engine turbine blade. The first integrated sensor group includes a thermal conductivity meter, a laser thickness gauge, a thermal diffusivity meter, a differential thermal analyzer, and a high-temperature melting point meter. The material processing data includes the material's thermal conductivity K, material thickness d, and thermal diffusivity. Heat capacity C and melting point temperature Tm; The pulse data acquisition unit is used to install a second integrated sensor group inside the pulse piercing device to collect the pulse data of the piercing pulse device in real time during the micro-hole processing of the turbine blade. The second integrated sensor group includes a pulse frequency meter and a laser energy meter, and the pulse data includes the pulse frequency f and the pulse energy E.

3. The steep pulse perforation ablation emergency stop energy release control system according to claim 2, characterized in that: The data processing module includes a data transmission unit, a cloud platform storage unit, and a data preprocessing unit; The data transmission unit converts analog signals into digital signals by installing a built-in analog-to-digital converter (ADC) in the integrated sensor. After packaging the material processing data and pulse data according to the protocol, it connects to the local gateway via the WI-FI wireless communication protocol. The local gateway then transmits the packaged material processing data and pulse data to the cloud platform in real time via the Internet. The cloud platform storage unit uses NoSQL big data technology to build a cloud platform database and stores the received material processing data and pulse data in real time. The cloud platform uses machine learning algorithms and big data analysis tools to process and analyze the real-time data, extract useful information and generate corresponding control commands. The analysis results are sent back to the local control system through the cloud platform to adjust equipment parameters and issue emergency stop commands. The data preprocessing unit is used to remove noise and interference from the material processing data and pulse data stored in the cloud platform database using Kalman digital filtering technology, then to eliminate instantaneous abnormal data points using median filtering, and finally to correct measurement errors and equipment deviations using equipment calibration data.

4. The steep pulse perforation ablation emergency stop energy release control system according to claim 3, characterized in that: The preliminary emergency stop judgment module includes a heat accumulation calculation unit, a temperature change calculation unit, and an emergency stop control unit; The heat accumulation calculation unit is used to construct a heat accumulation algorithm, and substitute the preprocessed pulse data into it to calculate and obtain the total accumulated heat Rl, and predict the heat accumulation within a unit time t. The temperature change calculation unit is used to construct a heat change algorithm, which combines the preprocessed material processing data with the accumulated total heat Rl to calculate the temperature change rate ΔT, and analyzes the thermal conduction response of the material during the micro-hole processing of engine turbine blades.

5. The steep pulse perforation ablation emergency stop energy release control system according to claim 4, characterized in that: The emergency stop control unit includes a perforation temperature calculation unit and an emergency stop evaluation unit; The perforation temperature calculation unit is used to perform dimensionless processing on the acquired cumulative total heat Rl and temperature change rate ΔT, and then combine the influence of temperature change to calculate the perforation temperature Ckwd, predicting the temperature change of engine turbine blade material caused by pulse energy input during micro-hole processing.

6. The steep pulse perforation ablation emergency stop energy release control system according to claim 5, characterized in that: The emergency stop assessment unit presets a safety threshold F1 based on material properties and process requirements, then compares and assesses it with the obtained perforation temperature Ckwd, and executes an emergency stop strategy based on the assessment results. The specific assessment plan is as follows: When the perforation temperature Ckwd(t) ≥ safety threshold F1, it indicates that the engine turbine blade material is overheating during the current micro-hole processing. At this time, an emergency stop strategy is executed. Control commands are sent to the pulse device through the cloud platform to immediately stop the pulse energy input and start the cooling system for cooling treatment. At the same time, an energy release control strategy is executed. When the perforation temperature Ckwd(t) < the safety threshold F1, it indicates that the processing parameters are safe to continue processing during the current micro-hole processing.

7. The steep pulse perforation ablation emergency stop energy release control system according to claim 6, characterized in that: The energy release control module performs average processing based on the pulse punching frequency of historical normal operation, sets a pulse frequency threshold F2, compares and evaluates it with the obtained energy release control index Snkz(t), and executes the energy release control strategy based on the evaluation result. The specific assessment content is as follows: When the energy release control index Snkz(t) > pulse frequency threshold F2, the first energy release control scheme is executed to adjust the pulse energy E and pulse frequency f and optimize the heat output of the pulse device. When the energy release control index Snkz(t) = pulse frequency threshold F2, there is no need to perform energy release control and the current heat output can continue to be maintained. When the energy release control index Snkz(t) < pulse frequency threshold F2, the second energy release control scheme is executed. Compared with the first energy release control scheme, the pulse energy E and pulse frequency f are adjusted in reverse to optimize the heat output of the pulse device.

8. A steep pulse perforation ablation emergency stop energy release control method, applied to the steep pulse perforation ablation emergency stop energy release control system according to any one of claims 1-7, characterized in that: Includes the following steps: S1. First, an integrated sensor group is installed around the micro-hole machining of the engine turbine blades and on the pulse generator to collect material processing data and pulse data in real time. S2. The collected processing data and pulse data are uploaded to the cloud platform for storage via wireless transmission, and the processing data and pulse data are preprocessed. S3. Based on the preprocessed processing data and pulse data, the algorithm is constructed to calculate the cumulative total heat Rl and the temperature change rate ΔT, and the perforation temperature Ckwd is obtained by correlation calculation. Then, the safety threshold F1 is preset for comparison and evaluation to determine the triggering of the emergency stop strategy. S4. Simultaneously, based on the pre-processed processing data and pulse data, calculate the energy diffusion rate Ks and the heat-affected zone area Ry, and combine them with the perforation temperature Ckwd to calculate the energy release control index Snkz. S5. Finally, the preset pulse frequency threshold F2 is compared and evaluated with the obtained energy release control index Snkz to analyze the pulse energy and frequency, and generate an energy release strategy.

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