Titanium alloy processing heat and mass transfer health state online identification and closed loop control method thereof

Abstract

The application discloses an online identification and closed-loop control method for a heat and mass transfer health state of titanium alloy machining, and the method comprises the following steps: obtaining mist droplets for lubrication and cooling of titanium alloy machining through a gas-liquid two-phase spraying control system; changing the heat and mass transfer state in the titanium alloy machining process by regulating and controlling the characteristics of the lubrication and cooling mist droplets; collecting and denoising multiple heat and mass transfer state data by using a data acquisition system, calculating a correlation dimension value, establishing a multi-parameter and multi-target database of the heat and mass transfer state data through a deep learning algorithm, comparing the correlation dimension value calculated from the collected data with a correlation dimension prediction value in the database, evaluating the health state of the heat and mass transfer of the titanium alloy machining, and feeding back the real-time result to the gas-liquid two-phase spraying control system, so as to realize the online identification and closed-loop control of the heat and mass transfer health state of the titanium alloy machining, and provide strong theoretical guidance and scientific basis for energy saving, emission reduction and intelligent control of the titanium alloy machining process.

Description

Technical Field

[0001] This invention relates to the field of heat and mass transfer health status monitoring and control in machining, and particularly to an online identification and closed-loop control method for the heat and mass transfer health status of titanium alloy machining. Background Technology

[0002] In the actual machining of titanium alloys, rapid tool wear and unstable workpiece surface quality are key technical challenges restricting high-speed and high-efficiency machining. How to efficiently control the contact state between the tool and workpiece surface, significantly reduce the temperature in the contact area and the cutting force between the tool and workpiece, significantly slow down tool wear, and improve workpiece surface quality are urgent problems to be solved. Real-time monitoring and automatic control of the heat and mass transfer state during titanium alloy machining is beneficial for predicting machining failure trends in advance, reducing tool and machining equipment wear, reducing downtime and maintenance frequency and time, achieving significant energy savings and improving productivity and economic benefits. Therefore, monitoring, understanding, and controlling the heat and mass transfer state is crucial for titanium alloy machining.

[0003] Currently, the heat and mass transfer status of titanium alloy machining relies primarily on the long-term experience of operators. Health status is assessed by observing tool condition, titanium alloy surface quality, and lubricant characteristics. This not only requires shutting down the machining equipment for inspection, increasing workload and reducing processing efficiency, but also demands a high level of professional competence from operators, and the judgment and decision-making lack objectivity. Furthermore, health status detection is somewhat delayed, leading to reduced product quality and performance, as well as wasted equipment energy and materials.

[0004] Currently, there is limited research both domestically and internationally on the online identification and closed-loop control of the heat and mass transfer health status during titanium alloy processing. Achieving online identification and closed-loop control of the heat and mass transfer health status during titanium alloy processing is urgently needed and crucial. Summary of the Invention

[0005] The technical problem to be solved by this invention is to overcome the shortcomings of existing methods and propose a method and apparatus for online identification and closed-loop control of the heat and mass transfer health status of titanium alloy processing. By establishing a multi-parameter, multi-objective database of heat and mass transfer status data, the correlation dimension value calculated from the collected data is compared with the predicted correlation dimension value in the database to evaluate the health status of heat and mass transfer in titanium alloy processing. The real-time results are then fed back to the gas-liquid two-phase spray control system, thereby realizing online identification and closed-loop control of the heat and mass transfer health status of titanium alloy processing. This provides strong theoretical guidance and scientific basis for energy conservation, emission reduction, and intelligent control in titanium alloy processing.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0007] This invention provides an online identification and closed-loop control method for the heat and mass transfer health status of titanium alloy processing. The online identification and closed-loop control method includes the following steps:

[0008] (1) Compressed gas and lubricating fluid are introduced into the gas-liquid two-phase spray control system and atomized by the gas-liquid two-phase atomizing nozzle to obtain droplets for lubrication and cooling of titanium alloy processing.

[0009] (2) By adjusting the matching relationship between the working parameters of the gas-liquid two-phase spray control system, the characteristics of the lubricating and cooling droplets are controlled, thereby changing the heat and mass transfer state during the titanium alloy processing.

[0010] (3) Measure the temperature of the processing area, the thickness of the lubricating fluid film and the concentration of lubricating fluid droplets in the processing of titanium alloy to obtain comprehensive data on heat and mass transfer status;

[0011] (4) The collected heat and mass transfer state data are denoised using signal denoising methods, and the correlation dimension of the heat and mass transfer state data is calculated based on chaos theory.

[0012] (5) Establish a multi-parameter, multi-objective database through deep learning algorithms, extract the predicted value of the correlation dimension under the working parameters of the corresponding spray control system, and compare it with the correlation dimension value calculated from the real-time collected data.

[0013] (6) Based on the comparison results, determine whether the heat and mass transfer of the titanium alloy processing is in a healthy state. If it is not in a healthy state, repeat steps (2) to (5) to perform real-time dynamic closed-loop control on the heat and mass transfer state and regulate the heat and mass transfer in the processing process to be in a healthy state.

[0014] Preferably, the operating parameters of the gas-liquid two-phase spray control system in step (2) include gas pressure, lubricating fluid pressure, gas flow rate, lubricating fluid flow rate, gas temperature, and lubricating fluid temperature; the characteristics of the lubricating cooling droplets include droplet size, droplet spraying speed, and spray coverage; and the heat and mass transfer states include the temperature of the titanium alloy workpiece processing area, the thickness of the lubricating oil film on the surface of the titanium alloy workpiece, and the concentration of lubricating fluid spray droplets.

[0015] Preferably, the temperature in step (3) is measured by a temperature sensor installed in the processing area of ​​the titanium alloy workpiece, the liquid film thickness is measured by a liquid film measuring device, and the droplet concentration is measured by a three-dimensional particle dynamic analyzer.

[0016] Preferably, the signal denoising method in step (4) includes hierarchical adaptive wavelet threshold denoising, sparse decomposition denoising, principal component analysis and Wiener filtering-based denoising, quantum Gaussian mixture model denoising, and empirical mode decomposition low-pass filtering denoising.

[0017] Preferably, the deep learning algorithm in step (5) learns and trains on six spray control system operating parameters and three types of lubrication and cooling state data to establish a nonlinear mapping relationship between multiple parameters and multiple objectives; the multi-parameter multi-objective database predicts the target value of lubrication and cooling state and the value of the associated dimension under different spray control system operating parameter matching through the nonlinear mapping relationship.

[0018] Preferably, the unhealthy state described in step (6) mainly includes over-lubricated cooling state or under-lubricated cooling state.

[0019] This invention also provides an online identification and closed-loop control device for the heat and mass transfer health status of titanium alloy processing, including a lubricant spraying device, a heat and mass transfer status data acquisition system, and a data processing system. The lubricant spraying device includes a gas-liquid two-phase spray control system, a gas-liquid two-phase atomizing nozzle, and a lubricant purification device. The inlet of the gas-liquid two-phase spray control system is connected to the lubricant and compressed gas pipelines, respectively. The heat and mass transfer status data acquisition system includes a temperature sensor for measuring temperature characteristics, a three-dimensional particle dynamic analyzer for measuring droplet characteristics, and a liquid film measuring device for measuring lubricant film thickness.

[0020] Preferably, the gas-liquid two-phase spray control system includes a pressure solenoid valve for gas and liquid pressure control, a flow solenoid valve for gas and liquid flow control, a digital pressure gauge for gas and liquid detection, and a digital flow meter for gas and liquid detection.

[0021] Preferably, the lubricant spraying device includes N gas-liquid two-phase atomizing nozzles.

[0022] Lubricating fluid and compressed gas are atomized through a gas-liquid two-phase nozzle to obtain lubricating and cooling droplets for titanium alloy processing. The characteristics of these droplets are controlled by a gas-liquid two-phase spray control system to alter the heat and mass transfer state. A massive amount of heat and mass transfer state data is acquired through a data acquisition system, and a multi-parameter, multi-objective database is established using deep learning algorithms. Real-time acquired data is compared with data in the database, and the online identification results are fed back to the gas-liquid two-phase spray control system. This enables online identification and closed-loop control of the heat and mass transfer health status during titanium alloy processing. The beneficial effects of this testing method are:

[0023] First, the characteristics of lubricating and cooling droplets can be controlled through a gas-liquid two-phase spray control system, thereby changing the heat and mass transfer state in real time.

[0024] Second, a nonlinear mapping relationship between multiple parameters and multiple objectives can be established through deep learning algorithms, enabling accurate prediction of lubrication and cooling states under different operating parameter matching conditions.

[0025] Third, a massive number of samples of the heat and mass transfer health status of titanium alloy processing can be obtained through a heat and mass transfer state data processing system combined with deep learning algorithms, enabling online identification and closed-loop control under big data.

[0026] Fourth, a heat transfer and mass transfer health big data platform and Internet of Things can be built through 5G wireless communication technology to realize data interaction between the data processing system, the health status big data platform and mobile terminals, and complete real-time dynamic monitoring and closed-loop control of the titanium alloy processing process.

[0027] Fifth, a lubricant purification device can be used to recover, purify, and recycle the lubricant used in titanium alloy processing, which is energy-saving and environmentally friendly. Attached Figure Description

[0028] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0029] Figure 1 This is a flowchart of the online identification and closed-loop control of the heat and mass transfer health status of the present invention.

[0030] Figure 2 This is a flowchart illustrating the establishment of a multi-parameter, multi-objective database for heat and mass transfer health status according to the present invention.

[0031] Figure 3 This is a diagram of the online identification and closed-loop control system for heat and mass transfer health status of the present invention. Detailed Implementation

[0032] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0033] Figure 1 The flowchart of the online identification and closed-loop control of the present invention is as follows: Figure 1 As shown, the testing and control device of the present invention includes a lubricating fluid spraying device 13, a heat and mass transfer state data acquisition system 14, and a data processing system 15. The lubricating fluid spraying device 13 mainly includes a gas-liquid two-phase spray control system 9, a gas-liquid two-phase atomizing nozzle 1, and a lubricating fluid purification device 2. The inlet of the gas-liquid two-phase spray control system 9 is connected to the pipelines of compressed gas 10 and lubricating fluid 11, respectively, to provide the raw materials required for atomization to the gas-liquid two-phase spray control system 9. The gas pipeline and lubricating fluid pipeline of the gas-liquid two-phase atomizing nozzle 1 are independently controlled by the gas-liquid two-phase spray control system 9 to achieve the pressure P of the compressed air. g Traffic Q g and the pressure P of the lubricating fluid l Traffic Ql Individually adjustable, enhancing the parameter adjustment capability of the control system. The pressure (P) of the gas and liquid is controlled via a pressure solenoid valve. g and P l Real-time closed-loop feedback control is performed, and the gas and liquid flow rates (Q) are controlled via flow solenoid valves. g and Q l Real-time closed-loop feedback control is implemented, using digital pressure gauges to monitor the pressure (P) of the gas and liquid. g and P l Real-time monitoring is performed using a digital flow meter to measure the pressure (Q) of the gas and liquid. g and Q l Real-time monitoring is performed. Among them, P g =0-1MPa, Q g =0-50m 3 / h、P l =0-4MPa, Q l =0-0.5m 3 / h. The gas-liquid two-phase atomizing nozzle 1, under different parameter adjustment and control, produces extremely small lubricating liquid droplets, which can improve the lubrication and cooling effect of the titanium alloy machining table 7 during operation.

[0034] The heat and mass transfer state data acquisition system 14 mainly includes a three-dimensional particle dynamic analyzer 6 for measuring droplet characteristics, a temperature sensor 8 for measuring temperature characteristics, and a liquid film measuring device 12 for measuring lubricating oil film thickness. The liquid film measuring device 12 includes an ultrasonic transducer 3, a pulse receiver 4, and a digital oscilloscope 5. Based on the ultrasonic measurement principle using an equivalent spring model, the liquid film thickness signal is converted and extracted to obtain real-time oil film lubrication information during the titanium alloy processing. The three-dimensional particle dynamic analyzer 6 collects information such as lubricating oil droplet concentration, droplet size, droplet spray velocity, and spray coverage in the spray field space of N gas-liquid two-phase atomizing nozzles 1, obtaining real-time dynamic droplet characteristics of the lubricating oil. The temperature sensor 8 is installed on the side wall of the titanium alloy sample, 2-6 mm away from the processed surface, to obtain the real-time dynamic temperature change curve of the titanium alloy sample surface.

[0035] like Figure 1 As shown, an online identification method for the heat and mass transfer health status of titanium alloy processing is described. This method uses a three-dimensional particle dynamic analyzer 6, a temperature sensor 8, and a liquid film measurement device 12 to collect data on the characteristics of lubrication and cooling droplets and the heat and mass transfer status. Specifically, it includes the following steps:

[0036] (1) Adjust the working parameters of the gas-liquid two-phase spray control system (including gas pressure, lubricating fluid pressure, gas flow rate, lubricating fluid flow rate, gas temperature and lubricating fluid temperature, etc.) and collect the heat and mass transfer status (including droplet size, droplet spray speed, spray coverage, processing area temperature, lubricating oil film thickness and droplet concentration) signals in real time.

[0037] (2) 5000 data points were continuously collected as stage data values. The collected heat and mass transfer state data were denoised using signal denoising methods. The optimal embedding dimension k and time delay t were obtained through an embedded program, and the phase space of the collected signal was reconstructed. The calculation formula is as follows:

[0038]

[0039] N=n-(k-1)t (2)

[0040] (3) The correlation dimension of the reconstructed heat and mass transfer state signal is calculated using the following formula:

[0041]

[0042]

[0043] (4) The correlation dimension D of heat and mass transfer state data based on chaos theory i Calculations are performed. A multi-parameter, multi-objective database is established using deep learning algorithms, and the predicted correlation dimension D under the corresponding operating parameters of the spray control system is extracted. pi And the correlation dimension value D calculated with the real-time collected data. i Compare;

[0044] (5) Based on the comparison results, determine whether the current heat and mass transfer in titanium alloy processing is in a healthy state. If it is in an unhealthy state, i.e., D i -D pi If ≠0, then repeat steps (2) to (5) to perform real-time dynamic closed-loop control of the heat and mass transfer state and regulate the heat and mass transfer in the processing process to be in a healthy state.

[0045] The method for establishing a multi-parameter, multi-objective database using deep learning algorithms in step 4 is as follows: Figure 2 As shown, the specific process is as follows:

[0046] (1) Establish a multi-factor, multi-level orthogonal experimental scheme and carry out experiments. Adjust the working parameters of the gas-liquid two-phase spray control system, including gas pressure, lubricating fluid pressure, gas flow rate, lubricating fluid flow rate, gas temperature and lubricating fluid temperature. Each experiment is carried out 3 times to ensure the stability of the experimental data. A large amount of heat transfer and mass transfer state signal data is obtained through a large number of experiments.

[0047] (2) Use signal denoising methods, such as hierarchical adaptive wavelet threshold denoising, sparse decomposition denoising, principal component analysis and Wiener filtering denoising, quantum Gaussian mixture model denoising, and empirical mode decomposition low-pass filtering denoising, to denoise the collected heat transfer and mass transfer state data.

[0048] (3) Calculate the correlation dimension of heat transfer and mass transfer state data based on chaos theory;

[0049] (4) Establish a deep learning model for the heat and mass transfer state of titanium alloy processing. Gas pressure, lubricant pressure, gas flow rate, lubricant flow rate, gas temperature and lubricant temperature are used as input variables of the deep learning model. Droplet size, droplet spray speed, spray coverage, processing area temperature, lubricant film thickness and lubricant spray droplet concentration are used as output variables. Establish a nonlinear mapping relationship between multiple parameters and multiple objectives to obtain a deep learning prediction model for the heat and mass transfer state.

[0050] (5) The deep learning prediction model of heat and mass transfer state is embedded into the data processing system 15. The target value of lubrication and cooling state and the value of related dimensions under different spray control system working parameters are predicted by nonlinear mapping relationship, so as to obtain a multi-parameter multi-objective database of heat and mass transfer state.

[0051] The online identification and closed-loop control system for heat and mass transfer health status consists of, as follows: Figure 3 As shown, the matching relationship between working parameters is adjusted through the gas-liquid two-phase spray control system in the lubricant spray device 13, and comprehensive data of heat and mass transfer status are acquired in real time using the temperature sensor 8, three-dimensional particle dynamic analyzer 6 and liquid film measuring device 12 in the heat and mass transfer state data acquisition system.

[0052] A heat and mass transfer health big data platform based on 5G wireless communication technology has been established to obtain a high-bandwidth, low-latency, and high-efficiency IoT for monitoring the heat and mass transfer health status of titanium alloy processing. A 5G wireless communication module is used to transmit heat and mass transfer health status data wirelessly in real time, improving data response speed and long-distance transmission accuracy.

[0053] Through data interaction between the data processing system and the health status big data platform, the heat and mass transfer status during the titanium alloy processing is monitored in real time, and it is used to diagnose whether the processing is under-lubricated or under-lubricated, so as to accurately assess the health status of heat and mass transfer.

[0054] The data processing system transmits data in real time to the on-site monitoring display screen and mobile client APP through the constructed Internet of Things. Workers, engineers, managers and others can use the monitoring display screen and mobile client APP to realize online and offline assessment of the heat and mass transfer health status of titanium alloy processing, ensuring that the heat and mass transfer process of titanium alloy processing is in a healthy state from multiple dimensions.

[0055] This invention utilizes deep learning algorithms to identify the heat and mass transfer health status of titanium alloy processing online. It acquires signals in real time through a heat and mass transfer status data acquisition system and calculates characteristic parameter values ​​based on chaos theory. Simultaneously, it integrates 5G wireless communication technology to build a heat and mass transfer health big data platform and a monitoring IoT. Through data interaction between the data processing system and the health status big data platform, it adjusts the matching relationship of the gas-liquid two-phase spray control parameters in the lubricant spraying device 13, achieving real-time dynamic monitoring and closed-loop control of the titanium alloy processing process. In summary, this invention has the following advantages: First, the characteristics of lubricating and cooling droplets can be controlled by a gas-liquid two-phase spray control system, thereby changing the heat and mass transfer state in real time. Second, a nonlinear mapping relationship between multiple parameters and multiple objectives can be established through deep learning algorithms, enabling accurate prediction of the lubrication and cooling state under different operating parameter matching conditions. Third, a massive amount of heat and mass transfer health status samples of titanium alloy processing can be obtained through a heat and mass transfer status data acquisition system combined with deep learning algorithms, achieving big data analytics. Fourth, a heat and mass transfer health big data platform and Internet of Things can be built using 5G wireless communication technology, enabling data interaction between the data processing system, the health status big data platform, and mobile terminals, completing real-time dynamic monitoring and closed-loop control of the titanium alloy processing process. Fifth, the lubricating fluid purification device 2 can be used to recover, purify, and recycle the lubricating fluid used in titanium alloy processing, saving energy and protecting the environment.

[0056] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An online identification and closed-loop control method for the heat and mass transfer health status of titanium alloy processing, characterized in that: The online identification and closed-loop control method includes the following steps: (1) Compressed gas and lubricating fluid are introduced into the gas-liquid two-phase spray control system and atomized by the gas-liquid two-phase atomizing nozzle to obtain droplets for lubrication and cooling of titanium alloy processing. (2) By adjusting the matching relationship between the working parameters of the gas-liquid two-phase spray control system, the characteristics of the lubricating and cooling droplets are controlled, thereby changing the heat and mass transfer state during the titanium alloy processing. (3) Measure the temperature of the processing area, the thickness of the lubricating fluid film and the concentration of lubricating fluid droplets in the processing area during the titanium alloy processing to obtain comprehensive data on the heat and mass transfer status; (4) The collected heat and mass transfer state data are denoised using signal denoising methods, and the correlation dimension of the heat and mass transfer state data is calculated based on chaos theory. (5) Establish a multi-parameter, multi-objective database through deep learning algorithms, extract the predicted value of the correlation dimension under the working parameters of the corresponding spray control system, and compare it with the correlation dimension value calculated from the real-time collected data. (6) Based on the comparison results, determine whether the heat and mass transfer of the titanium alloy processing is in a healthy state. If it is not in a healthy state, repeat steps (2) to (5) to perform real-time dynamic closed-loop control on the heat and mass transfer state and regulate the heat and mass transfer in the processing process to be in a healthy state.

2. The method for online identification and closed-loop control of the heat and mass transfer health status of titanium alloy processing according to claim 1, characterized in that: The operating parameters of the gas-liquid two-phase spray control system in step (2) include gas pressure, lubricating fluid pressure, gas flow rate, lubricating fluid flow rate, gas temperature, and lubricating fluid temperature; the characteristics of the lubricating cooling droplets include droplet size, droplet spray speed, and spray coverage; the heat and mass transfer states include the temperature of the titanium alloy workpiece processing area, the thickness of the lubricating oil film on the surface of the titanium alloy workpiece, and the concentration of lubricating fluid spray droplets.

3. The method for online identification and closed-loop control of the heat and mass transfer health status of titanium alloy processing according to claim 1, characterized in that: The temperature mentioned in step (3) is measured by a temperature sensor installed in the processing area of ​​the titanium alloy workpiece, the liquid film thickness is measured by a liquid film measuring device, and the droplet concentration is measured by a three-dimensional particle dynamic analyzer.

4. The method for online identification and closed-loop control of the heat and mass transfer health status of titanium alloy processing according to claim 1, characterized in that: The signal denoising methods described in step (4) include hierarchical adaptive wavelet threshold denoising, sparse decomposition denoising, principal component analysis and Wiener filtering-based denoising, quantum Gaussian mixture model denoising, and empirical mode decomposition low-pass filtering denoising.

5. The method for online identification and closed-loop control of the heat and mass transfer health status of titanium alloy processing according to claim 1, characterized in that: The deep learning algorithm described in step (5) establishes a nonlinear mapping relationship between multiple parameters and multiple objectives by learning and training on six types of spray control system operating parameters and three types of lubrication and cooling state data; the multi-parameter multi-objective database predicts the target value of lubrication and cooling state and the value of the associated dimension under different spray control system operating parameter matching through the nonlinear mapping relationship.

6. The method for online identification and closed-loop control of the heat and mass transfer health status of titanium alloy processing according to claim 1, characterized in that: The unhealthy state mentioned in step (6) includes over-lubricated cooling state or under-lubricated cooling state.

7. The method for online identification and closed-loop control of the heat and mass transfer health status of titanium alloy processing according to claim 1, characterized in that: The apparatus used in this online identification and closed-loop control method includes a lubricating fluid spraying device, a heat and mass transfer state data acquisition system, and a data processing system. The lubricating fluid spraying device includes a gas-liquid two-phase spray control system, a gas-liquid two-phase atomizing nozzle, and a lubricating fluid purification device. The inlet of the gas-liquid two-phase spray control system is connected to the lubricating fluid and compressed gas pipelines, respectively. The heat and mass transfer state data acquisition system includes a temperature sensor for measuring temperature characteristics, a three-dimensional particle dynamic analyzer for measuring droplet characteristics, and a liquid film measuring device for measuring lubricating oil film thickness.

8. The online identification and closed-loop control method according to claim 7, characterized in that: The gas-liquid two-phase spray control system used in this online identification and closed-loop control method includes a pressure solenoid valve for gas and liquid pressure control, a flow solenoid valve for gas and liquid flow control, a digital pressure gauge for gas and liquid detection, and a digital flow meter for gas and liquid detection.

9. The online identification and closed-loop control method according to claim 7, characterized in that: The lubricating fluid spraying equipment used in this online identification and closed-loop control method contains N gas-liquid two-phase atomizing nozzles.

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