Evaporation equipment supervision system and method based on data analysis

Abstract

The invention discloses an evaporation equipment supervision system and method based on data analysis, and relates to the technical field of winding evaporation equipment. The system comprises a thermal radiation data acquisition module, a process parameter acquisition module, a data processing and analysis module, a monitoring result output module, a multi-parameter correlation regulation and control module and a model optimization module. According to the system, all the modules work cooperatively, the heat radiation data acquisition module acquires heat radiation data of an aluminum sputtering area, and the process parameter acquisition module collects process parameters of evaporation equipment; the data processing and analyzing module integrates and processes the data to obtain aluminum splashing data, and the monitoring result output module displays and transmits the data in real time for closed-loop control; and the multi-parameter association regulation and control module constructs a coupling model to realize self-adaptive regulation and control, and the model optimization module updates an optimization model according to new data, so that effective supervision on the aluminum sputtering process of the evaporation equipment is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of winding evaporation coating equipment, and specifically to an evaporation coating equipment supervision system and method based on data analysis. Background Art

[0002] In winding evaporation coating equipment, accurate monitoring of the aluminum sputtering height is crucial for ensuring the coating quality. Currently, the detection method of the aluminum sputtering height is to manually pass through a slit, cut a specific 200-mm wide strip, and the error of manual operation detection is relatively large. For example, the angle of the slit placement, the flatness of the receiving material, and the deviation during the manual pulling of the aluminum film may all affect the measurement results. Moreover, this method belongs to off-line detection and cannot monitor the aluminum sputtering height in real time, and cannot adjust the evaporation coating process in a timely manner. In addition, the uniform distribution of aluminum sputtering may not conform to the actual situation, resulting in a certain deviation in the measurement results. The present invention aims to provide a more reliable and accurate thermal radiation monitoring method, specifically an evaporation coating equipment supervision system and method based on data analysis. Summary of the Invention

[0003] The purpose of the present invention is to provide an evaporation coating equipment supervision system and method based on data analysis to solve the problems raised in the prior art.

[0004] To achieve the above purpose, the present invention provides the following technical solutions:

[0005] An evaporation coating equipment supervision system based on data analysis includes a thermal radiation data acquisition module, a process parameter acquisition module, a data processing and analysis module, a monitoring result output module, a multi-parameter correlation regulation module, and a model optimization module; the thermal radiation data acquisition module is used to acquire thermal radiation data of the aluminum sputtering area; the process parameter acquisition module is used to acquire process parameter data of the evaporation coating equipment; the data processing and analysis module receives the data transmitted by the thermal radiation data acquisition module and the process parameter acquisition module, uses a data processing system to organize the data, constructs a complete data set, and performs analysis and processing on the data set to obtain aluminum sputtering data; the monitoring result output module is used to display the aluminum sputtering data calculated by the data processing and analysis module on the monitoring interface in real time and transmit it to the equipment control system; the multi-parameter correlation regulation module is used to establish a multi-parameter coupling model between the thermal radiation monitoring data and the process parameters of the evaporation coating equipment, and perform adaptive regulation on the evaporation coating process; the model optimization module is used to update and optimize the data processing model and the multi-parameter coupling model, and continuously supervise the aluminum sputtering process of the evaporation coating equipment.

[0006] The thermal radiation data acquisition module includes an aluminum sputtering height measurement unit, a hot spot temperature measurement unit, and a radiation intensity distribution measurement unit;

[0007] The aluminum sputtering height measurement unit sets height points according to the set measurement range, conducts multiple repeated tests at each height point, and obtains the average value of the data obtained at each height point as the accurate data;

[0008] The hot spot temperature measurement unit is responsible for using an infrared thermal imager to monitor the temperature distribution in the aluminum sputtering area in real time during each aluminum sputtering process, recording the highest temperature point, which is the hot spot temperature; meanwhile, when the equipment is running, the infrared thermal imager continuously acquires the thermal image data of the aluminum sputtering area at a pre-set frame rate, and these image data contain the thermal distribution information of aluminum sputtering at different moments;

[0009] The radiation intensity distribution measurement unit first uses a spectral radiometer to measure the radiation intensity of aluminum sputtering at different wavelengths to obtain the distribution data of the radiation intensity with respect to the wavelength; then uses a spectral analyzer to collect the spectral data of the thermal radiation of aluminum sputtering to obtain the radiation intensity information of the thermal radiation wavelengths within a preset wavelength range.

[0010] The process parameter acquisition module includes a temperature acquisition unit, a speed acquisition unit, a pressure acquisition unit, and an angle acquisition unit;

[0011] The temperature acquisition unit uses a temperature sensor to monitor the temperature of the evaporation source of the evaporation equipment in real time and transmits the temperature data to the system in real time. The system can clarify the temperature fluctuation situation through data feedback;

[0012] The speed acquisition unit uses a photoelectric sensor to measure the wire feeding speed and a rotary encoder to monitor the winding speed; among them, the photoelectric sensor calculates the wire feeding speed by detecting the changes in light shielding and light transmission during the wire feeding process, and the rotary encoder is connected to the winding shaft to convert the rotation angle of the shaft into an electrical signal to measure the winding speed; meanwhile, the system will monitor these two speeds in real time;

[0013] The pressure acquisition unit uses a pressure sensor to monitor the pressure in the evaporation chamber of the evaporation equipment in real time, and the pressure sensor will transmit the pressure data to the system in real time for monitoring the evaporation environment;

[0014] The angle acquisition unit uses an inclination sensor and a rotation angle sensor to measure the wire feeding pitch angle parameter and transmits the angle data to the system, and the system will monitor the wire feeding pitch angle in real time;

[0015] The data processing and analysis module includes a data sorting unit, a radiation intensity parameter extraction unit, an infrared thermal image preprocessing unit, and a spectral data analysis unit;

[0016] The data sorting unit is used to sort out the aluminum splash height, hot spot temperature and radiation intensity distribution data collected in each experiment to establish a data set; and mark and process abnormal data that exceeds the set threshold range, and eliminate abnormal values ​​that deviate from other data points;

[0017] The radiation intensity parameter extraction unit first uses a spectrum analyzer to collect radiation intensity values ​​at different wavelengths, and then calculates the total radiation intensity and the radiation intensity of a specific band; the radiation intensity data can be represented by a continuous function I(λ). For the total radiation intensity I total , use the integral formula to calculate, the formula is as follows:

[0018]

[0019] where λ max and λ min Respectively represent the maximum and minimum wavelengths of radiation intensity measurement;

[0020] For a specific band, the radiation intensity I band Calculated by the following integral formula:

[0021]

[0022] where [λ start ,λ end ] represents the wavelength range of a specific band;

[0023] After obtaining the data of total radiation intensity and radiation intensity in a specific band, these parameters together with the hot spot temperature are used as thermal radiation characteristic parameters to establish a relationship with the aluminum splash height in the future;

[0024] The infrared thermal imaging preprocessing unit is used to preprocess the infrared thermal imaging to improve the image quality, and then use the image recognition algorithm to identify the aluminum splashing area and extract the characteristic parameters of the aluminum splashing area, including the average temperature and the position of the highest temperature point. These characteristic parameters are part of the thermal radiation characteristic parameters;

[0025] The spectral data analysis unit determines the peak wavelength and radiation intensity distribution of the thermal radiation; according to Wien's displacement law, the peak wavelength is inversely proportional to the temperature of the object, and the temperature state of the splashed aluminum is further determined; then all the extracted thermal radiation characteristic parameters are compared with a pre-established database; the database stores the thermal radiation characteristic parameters corresponding to different splashed aluminum heights, and combines the collected process parameter data, and calculates through a similarity matching algorithm to obtain the current splashed aluminum height.

[0026] The monitoring result output module includes a display unit and a data transmission unit;

[0027] The display unit is used to display the sputtering aluminum height value in real time, highlight the abnormal sputtering aluminum height through a preset threshold, and present the change of the sputtering aluminum height over time in the form of a trend chart to help the staff analyze the change trend of the sputtering aluminum height;

[0028] The data transmission unit is used to transmit the sputtering aluminum height data to the system, and the system will automatically adjust the evaporation source power, wire feeding speed, wire feeding angle and evaporation chamber pressure according to the transmitted data to achieve adaptive control of the evaporation coating process.

[0029] The multi-parameter correlation regulation module includes a model construction unit and a parameter regulation unit; the model construction unit is responsible for establishing a multi-parameter coupling model between the thermal radiation monitoring data and the evaporation coating equipment process parameters; the thermal radiation monitoring data and the evaporation coating equipment process parameters are respectively the data collected by the thermal radiation data acquisition module and the process parameter acquisition module, and are processed and integrated by the data processing and analysis module and then transmitted to the coupling model as a training set, and then using data analysis algorithms to analyze the mutual influence relationship between the parameters and construct a multi-parameter coupling model that can reflect the mathematical relationship between the parameters;

[0030] The parameter regulation unit is responsible for monitoring the sputtering aluminum height data in real time; the parameter regulation unit receives the sputtering aluminum height data transmitted by the data transmission unit, and when it monitors that the sputtering aluminum height data exceeds the preset normal range, it starts the regulation program to adjust the parameters; the parameter adjustment is based on the multi-parameter coupling model provided by the model construction unit, uses the method of multiple regression analysis to analyze the influence of multiple related processes on the sputtering aluminum parameters, and uses the multi-parameter coupling model for prediction, gives the target value of the sputtering aluminum height, and inversely deduces the parameter value x that needs to be adjusted through the model i , the formula is as follows:

[0031] y = β0 + β1x1 + β2x2 +... + β n x n

[0032] Among them, y represents the predicted value of the sputtering aluminum height, β0 is the constant term, which is a fixed parameter in the model; β1, β2,..., β n are the regression coefficients corresponding to the process parameters x1, x2,..., x n in the model, which reflects the influence degree and direction of the relevant process parameters on the sputtering aluminum height y, and x1, x2,..., x n represent the process parameters of the evaporation coating equipment, including but not limited to the evaporation source power, wire feeding speed, evaporation chamber pressure and wire feeding angle;

[0033] Through the known parameter values and the predicted value of the sputtering aluminum height, inversely deduce the parameter value x that needs to be adjusted i , x iRepresent the process parameters of the evaporation equipment, which are x1, x2,,, x n in a general representation form, where i is an index with a value range of 1 - n; then calculate the process parameter adjustment amount Δx i according to the formula as follows:

[0034] Δx i = x i，new - x i，current

[0035] where x i,new is the new value of the process parameter obtained by back - calculating through the multi - parameter coupling model to make the aluminum sputtering height reach the target value, and x i is the actual value of the current process parameter x i,current ; i

[0036] According to the calculated adjustment amount of the process parameter, send a control instruction to the control system of the evaporation equipment to automatically adjust the process parameter to be adjusted, and realize the adaptive regulation of the evaporation process.

[0037] The model optimization module includes an optimization data acquisition unit and a model feedback optimization unit;

[0038] The optimization data acquisition unit is responsible for collecting new thermal radiation data, aluminum sputtering height data, and key process parameter data during the operation of the evaporation equipment to provide basic data for model optimization; the data it collects is fed back to the model construction unit of the multi - parameter correlation regulation module, enabling the model construction unit to continuously improve the multi - parameter coupling model based on the new data;

[0039] The model feedback optimization unit uses the newly collected data to evaluate the multi - parameter coupling model in the multi - parameter correlation regulation module. When the deviation between the model prediction result and the actual data exceeds the set threshold range, adjust and optimize the model; at the same time, feedback the optimized model to the parameter regulation unit of the multi - parameter correlation regulation module, so that after the parameter regulation unit detects that the aluminum sputtering height exceeds the set threshold range, calculate the adjustment amount based on the model and continuously adjust the process parameters of the evaporation equipment.

[0040] A supervision method for an evaporation equipment based on data analysis includes the following steps:

[0041] S1. The thermal radiation data acquisition module acquires thermal radiation data from three aspects: aluminum sputtering height, hot spot temperature, and radiation intensity distribution, and each unit collaborates to obtain information; the process parameter acquisition module collects process parameter data through temperature, speed, pressure, and angle acquisition units;

[0042] ​S2. Receive the data transmitted by the thermal radiation acquisition module and the process parameter acquisition module, organize the data, construct a complete data set, mark and process abnormal data; then calculate the total radiation intensity and the radiation intensity of a specific band of the radiation intensity distribution data;

[0043] S3. Preprocess the infrared thermal image, and use the image recognition algorithm to extract the thermal characteristic parameters of the sputtered aluminum area; analyze the spectral data to determine the peak wavelength and radiation intensity distribution of the thermal radiation; finally, compare the extracted thermal characteristic parameters with the pre-established database, and combine the process parameter data to obtain the current sputtered aluminum height through the data processing model;

[0044] S4. The monitoring result output module displays the sputtered aluminum height in real time, and presents normal and abnormal data and change trends in different ways; then use the data transmission unit to transmit the sputtered aluminum height data to the system to provide data support for the closed-loop control of the evaporation process;

[0045] S5. The multi-parameter correlation regulation module uses the collected and processed data to construct a multi-parameter coupling model through the data analysis algorithm to analyze the parameter relationship; after the model is constructed, the parameter regulation unit monitors the sputtered aluminum height, and when the data is abnormal, it analyzes the influence according to the model, calculates the parameter adjustment amount and sends an instruction to achieve adaptive regulation;

[0046] S6. During the actual operation of the evaporation equipment, the model optimization module continuously collects new thermal radiation data, sputtered aluminum height data and key process parameter data, and provides them to the model construction unit of the multi-parameter correlation regulation module to improve the model, and updates and optimizes the data processing model and the multi-parameter coupling model.

[0047] Compared with the prior art, the beneficial effects of the present invention are:

[0048] 1. Strong high-temperature adaptability: In the high-temperature environment of the winding evaporation equipment, traditional detection methods may cause the performance of the equipment to decline and the detection accuracy to decrease due to high temperature. The thermal radiation detection method is based on the thermal radiation characteristics of the object itself and is not directly affected by the high-temperature environment, and can stably and accurately monitor the sputtered aluminum height at high temperature.

[0049] 2. Non-contact detection: Using thermal radiation detection, there is no need to directly contact the sputtered aluminum, which avoids interference with the sputtered aluminum process and reduces the risk of damage to the detection equipment due to contact with high-temperature sputtered aluminum, improving the reliability and service life of the detection system.

[0050] 3. Real-time and accuracy: It can collect and process thermal radiation data in real time and quickly obtain the sputtered aluminum height information. Through high-precision detection devices and advanced data processing algorithms, the accuracy of the detection results is guaranteed, providing a reliable basis for timely adjustment of the evaporation process. Description of the Drawings

[0051] Figure 1 It is the organizational structure diagram of a supervision system for evaporation coating equipment based on data analysis according to the present invention;

[0052] Figure 2 It is the method flowchart of a method for supervising evaporation coating equipment based on data analysis according to the present invention. Specific embodiments

[0053] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0054] Embodiment: As Figure 1 - Figure 2 shown, the present invention provides a technical solution,

[0055] A supervision system for evaporation coating equipment based on data analysis includes a thermal radiation data acquisition module, a process parameter acquisition module, a data processing and analysis module, a monitoring result output module, a multi-parameter correlation regulation module, and a model optimization module; the thermal radiation data acquisition module is used to acquire the thermal radiation data of the aluminum sputtering area; the process parameter acquisition module is used to acquire the process parameter data of the evaporation coating equipment; the data processing and analysis module receives the data transmitted by the thermal radiation data acquisition module and the process parameter acquisition module, uses the data processing system to organize the data, constructs a complete data set, and analyzes and processes the data set to obtain aluminum sputtering data; the monitoring result output module is used to display the aluminum sputtering data calculated by the data processing and analysis module on the monitoring interface in real time and transmit it to the equipment control system; the multi-parameter correlation regulation module is used to establish a multi-parameter coupling model between the thermal radiation monitoring data and the process parameters of the evaporation coating equipment, and perform adaptive regulation on the evaporation process; the model optimization module is used to update and optimize the data processing model and the multi-parameter coupling model, and continuously supervise the aluminum sputtering process of the evaporation coating equipment.

[0056] The thermal radiation data acquisition module includes an aluminum sputtering height measurement unit, a hot spot temperature measurement unit, and a radiation intensity distribution measurement unit;

[0057] The aluminum sputtering height measurement unit sets height points according to the set measurement range, conducts multiple repeated tests at each height point, and takes the average value of the data obtained at each height point as the accurate data;

[0058] The hot spot temperature measurement unit is responsible for monitoring the temperature distribution of the aluminum splashing area in real time using an infrared thermal imager during each aluminum splashing process, and recording the highest temperature point, which is the hot spot temperature; at the same time, when the equipment is running, the infrared thermal imager continuously collects thermal image data of the aluminum splashing area at a preset frame rate, and these image data contain the thermal distribution information of the aluminum splashing at different times;

[0059] The radiation intensity distribution measurement unit first uses a spectroradiometer to measure the radiation intensity of the sputtered aluminum at different wavelengths to obtain the distribution data of the radiation intensity with wavelength; then uses a spectrometer to collect the spectral data of the thermal radiation of the sputtered aluminum to obtain the radiation intensity information of the thermal radiation wavelength within a preset wavelength range.

[0060] The process parameter acquisition module includes a temperature acquisition unit, a speed acquisition unit, a pressure acquisition unit and an angle acquisition unit;

[0061] The temperature acquisition unit uses a temperature sensor to monitor the evaporation source temperature of the evaporation equipment in real time, and transmits the temperature data to the system in real time. The system can clearly understand the temperature fluctuation through data feedback;

[0062] The speed acquisition unit uses a photoelectric sensor to measure the wire feeding speed and a rotary encoder to monitor the winding speed; the photoelectric sensor calculates the wire feeding speed by detecting the changes in light shielding and light transmittance during the wire feeding process, and the rotary encoder is connected to the winding shaft to convert the rotation angle of the shaft into an electrical signal to measure the winding speed; at the same time, the system monitors these two speeds in real time;

[0063] The pressure acquisition unit uses a pressure sensor to monitor the pressure of the evaporation chamber in the evaporation equipment in real time, and the pressure sensor transmits the pressure data to the system in real time for monitoring the evaporation environment;

[0064] The angle acquisition unit uses an inclination sensor and a rotation angle sensor to measure the wire feeding pitch angle parameters, and transmits the angle data to the system, which monitors the wire feeding pitch angle in real time;

[0065] The data processing and analysis module includes a data sorting unit, a radiation intensity parameter extraction unit, an infrared thermal image preprocessing unit and a spectrum data analysis unit;

[0066] The data sorting unit is used to sort out the aluminum splash height, hot spot temperature and radiation intensity distribution data collected in each experiment to establish a data set; and mark and process abnormal data that exceeds the set threshold range, and eliminate abnormal values ​​that deviate from other data points;

[0067] The radiation intensity parameter extraction unit first uses a spectral analyzer to collect the radiation intensity values at different wavelengths, and then calculates the total radiation intensity and the radiation intensity in a specific band; the radiation intensity data can be represented by a continuous function I(λ). For the total radiation intensity I total , it is calculated using the integral formula as follows:

[0068]

[0069] where λ max and λ min represent the maximum and minimum wavelengths for measuring the radiation intensity respectively;

[0070] For the radiation intensity I band in a specific band, it is calculated through the following integral formula:

[0071]

[0072] where [λ start , λ end represents the wavelength range of the specific band;

[0073] After obtaining the data of the total radiation intensity and the radiation intensity in a specific band, these parameters, together with the hot spot temperature, are used as thermal radiation characteristic parameters for subsequent establishment of a relationship with the aluminum splashing height;

[0074] The infrared thermal imaging preprocessing unit is used to preprocess the infrared thermal imaging to improve the image quality, and then uses an image recognition algorithm to identify the aluminum splashing area and extract the characteristic parameters of the aluminum splashing area, including the average temperature and the position of the highest temperature point. These characteristic parameters are part of the thermal radiation characteristic parameters;

[0075] The spectral data analysis unit determines the peak wavelength and the radiation intensity distribution of the thermal radiation; according to Wien's displacement law, the peak wavelength is inversely proportional to the object temperature, and further determines the temperature state of the aluminum splashing; then compares all the extracted thermal radiation characteristic parameters with a pre-established database; the database stores the thermal radiation characteristic parameters corresponding to different aluminum splashing heights. Combining with the collected process parameter data, through similarity matching algorithm calculation, the height of the current aluminum splashing is obtained.

[0076] The monitoring result output module includes a display unit and a data transmission unit;

[0077] The display unit is used to display the aluminum splashing height value in real time, highlight the abnormal aluminum splashing height through a pre-set threshold, and present the change of the aluminum splashing height over time in the form of a trend chart to help the staff analyze the change trend of the aluminum splashing height;

[0078] The data transmission unit is used to transmit the sputtering aluminum height data to the system, and the system will automatically adjust the evaporation source power, wire feeding speed, wire feeding angle, and evaporation chamber pressure according to the transmitted data to achieve adaptive control of the evaporation coating process.

[0079] The multi-parameter correlation control module includes a model construction unit and a parameter control unit; the model construction unit is responsible for establishing a multi-parameter coupling model between the thermal radiation monitoring data and the evaporation coating equipment process parameters; the thermal radiation monitoring data and the evaporation coating equipment process parameters are respectively the data collected by the thermal radiation data acquisition module and the process parameter acquisition module, and after being processed and integrated by the data processing and analysis module, they are transmitted to the coupling model as a training set. Then, using data analysis algorithms, the mutual influence relationship between the parameters is analyzed, and a multi-parameter coupling model that can reflect the mathematical relationship between the parameters is constructed;

[0080] The parameter control unit is responsible for real-time monitoring of the sputtering aluminum height data; the parameter control unit receives the sputtering aluminum height data transmitted by the data transmission unit. When it monitors that the sputtering aluminum height data exceeds the preset normal range, it starts the control program to adjust the parameters; the parameter adjustment is based on the multi-parameter coupling model provided by the model construction unit, and uses the method of multiple regression analysis to analyze the influence of multiple related processes on the sputtering aluminum parameters, and uses the multi-parameter coupling model for prediction. Given the target value of the sputtering aluminum height, the parameter value x that needs to be adjusted is deduced through the model i , the formula is as follows:

[0081] y = β0 + β1x1 + β2x2 +... + β n x n

[0082] Among them, y represents the predicted value of the sputtering aluminum height, β0 is the constant term, which is a fixed parameter in the model; β1, β2,..., β n are the regression coefficients corresponding to the process parameters x1, x2,..., x n in the model, which reflects the influence degree and direction of the relevant process parameters on the sputtering aluminum height y, and x1, x2,..., x n represent the process parameters of the evaporation coating equipment, including but not limited to the evaporation source power, wire feeding speed, evaporation chamber pressure, and wire feeding angle;

[0083] Through the known parameter values and the predicted value of the sputtering aluminum height, the parameter value x that needs to be adjusted is deduced i , x i represents the process parameter of the evaporation coating equipment, which is the general representation form of x1, x2,..., x n , where i is an index, and the value range is 1 - n; then the process parameter adjustment amount Δx is calculated according to the formula i , the formula is as follows:

[0084] Δx i = x i，new - x i，current

[0085] where x i,new is the new value of the process parameter obtained by back-calculating through the multi-parameter coupling model when the aluminum sputtering height reaches the target value, and x i is the actual value of the current process parameter x i,current ; i According to the calculated adjustment amount of the process parameter, a control instruction is sent to the control system of the evaporation equipment to automatically adjust the process parameter to be adjusted, so as to realize the adaptive control of the evaporation process.

[0086] The model optimization module includes an optimization data acquisition unit and a model feedback optimization unit;

[0087] The optimization data acquisition unit is responsible for collecting new thermal radiation data, aluminum sputtering height data, and key process parameter data during the operation of the evaporation equipment, providing basic data for model optimization; the collected data is fed back to the model construction unit of the multi-parameter correlation control module, enabling the model construction unit to continuously improve the multi-parameter coupling model based on the new data;

[0088] The model feedback optimization unit uses the newly collected data to evaluate the multi-parameter coupling model in the multi-parameter correlation control module. When the deviation between the model prediction result and the actual data exceeds the set threshold range, the model is adjusted and optimized; at the same time, the optimized model is fed back to the parameter control unit of the multi-parameter correlation control module, so that after the parameter control unit detects that the aluminum sputtering height exceeds the set threshold range, it calculates the adjustment amount according to the model and continuously adjusts the process parameters of the evaporation equipment.

[0089] A method for supervising an evaporation equipment based on data analysis includes the following steps:

[0090] S1. The thermal radiation data acquisition module acquires thermal radiation data from three aspects: aluminum sputtering height, hot spot temperature, and radiation intensity distribution, and each unit collaborates to obtain information; the process parameter acquisition module collects process parameter data through temperature, speed, pressure, and angle acquisition units;

[0091] S2. Receive the data transmitted by the thermal radiation acquisition module and the process parameter acquisition module, organize the data, construct a complete data set, mark and process abnormal data; then calculate the total radiation intensity and the radiation intensity of a specific band of the radiation intensity distribution data;

[0092]

[0093] ​S3. Preprocess the infrared thermal image, and use an image recognition algorithm to extract the thermal characteristic parameters of the sputtered aluminum area; analyze the spectral data to determine the peak wavelength and radiation intensity distribution of the thermal radiation; finally, compare the extracted thermal characteristic parameters with the pre-established database, and combine with the process parameter data to obtain the current sputtered aluminum height through a data processing model.

[0094] S4. In the monitoring result output module, the sputtered aluminum height is displayed in real time, and normal and abnormal data and change trends are presented in different ways; then, use the data transmission unit to transmit the sputtered aluminum height data to the system to provide data support for the closed-loop control of the evaporation process.

[0095] S5. The multi-parameter correlation regulation module uses the collected and processed data to construct a multi-parameter coupling model through a data analysis algorithm to analyze the parameter relationship; after the model is constructed, the parameter regulation unit monitors the sputtered aluminum height, and when the data is abnormal, it analyzes the influence according to the model, calculates the parameter adjustment amount and sends an instruction to achieve adaptive regulation.

[0096] S6. During the actual operation of the evaporation equipment, the model optimization module continuously collects new thermal radiation data, sputtered aluminum height data, and key process parameter data, and provides them to the model construction unit of the multi-parameter correlation regulation module to improve the model, and updates and optimizes the data processing model and the multi-parameter coupling model.

[0097] Embodiment

[0098] For the evaporation equipment used for producing electronic component coatings, set the relevant parameters for thermal radiation data acquisition. Determine the sputtered aluminum height measurement range to be 10 - 100 μm, set a measurement point every 10 μm, and perform 5 repeated measurements at each point.

[0099] Select an infrared thermal imager with a frame rate of 30 frames per second for hot spot temperature measurement and thermal image acquisition.

[0100] Adopt a high-precision spectral radiometer and spectral analyzer that can collect radiation intensity information in the wavelength range of 3 μm - 5 μm.

[0101] Set the relevant parameters for process parameter acquisition. Use a K-type thermocouple temperature sensor with an accuracy of ±1°C to monitor the evaporation source temperature.

[0102] Use a photoelectric sensor with an accuracy of up to ±0.1 m / min to measure the wire feeding speed, and a rotary encoder with an accuracy of ±0.5 revolutions per minute to monitor the winding speed.

[0103] Install a pressure sensor with an accuracy of ±0.1 kPa to monitor the evaporation chamber pressure.

[0104] Equip an inclination sensor and a rotation angle sensor with an accuracy of ±0.1° to measure the wire feeding pitch angle.

[0105] Organize the collected data on the height of sputtered aluminum, the temperature of the hot spot, and the distribution of radiation intensity to establish a data set. If a radiation intensity data is found to be abnormally high, after checking and confirmation that it is a measurement error, it is excluded.

[0106] Assume that the radiation intensity data can be expressed by the function

[0107] I(λ) = 2λ

[0108] (in μm, with the unit of W / (m 2 ·sr)), the minimum wavelength λ of the radiation intensity measurement min = 1 μm, and the maximum wavelength λ max = 10 μm.

[0109] Calculate the total radiation intensity I according to the formula total = 99 W / (m 2 ·sr)

[0110] Assume that the specific wavelength band is 4 μm - 6 μm, and calculate the radiation intensity I of the specific wavelength band according to the formula band = 20 W / (m 2 ·sr)

[0111] Perform preprocessing operations such as noise reduction and enhancement on the infrared thermal image, and then use the image recognition algorithm to identify the sputtered aluminum area. Extract its average temperature as 450 °C, and the position of the highest temperature point is 10 pixels to the left of the center of the image.

[0112] According to Wien's displacement law (assuming the temperature of sputtered aluminum is 1000 K), calculate the peak wavelength λ of the thermal radiation max = 2.898 μm. Compare the extracted thermal characteristic parameters with the pre-established database, and combine the collected process parameter data to obtain the height of the current sputtered aluminum as 30 μm through the data processing model.

[0113] Use the thermal radiation monitoring data and the process parameter collection data. After preprocessing and integration in the early stage, use them as the training set, and adopt the multiple linear regression algorithm to construct a multi-parameter coupling model. After training, the model is as follows:

[0114] y = 10 + 0.5x1 + 0.3x2 - 0.2x3 + 0.1x4

[0115] Where y is the predicted value of the sputtered aluminum height, x1 is the evaporation source temperature, x2 is the wire feeding speed, x3 is the pressure in the evaporation chamber, and x4 is the wire feeding pitch angle.

[0116] Real-time monitor the sputtered aluminum height data. Assume that the current sputtered aluminum height is 38 μm, which exceeds the normal range; given the target sputtered aluminum height of 30 μm, invert the parameter values that need to be adjusted through the model.

[0117] Assume that currently x1 = 800 °C, x2 = 5 m / min, x3 = 100 Pa, x4 = 5°. Through calculation, it is necessary to reduce the evaporation source temperature and wire feeding speed, and appropriately adjust the evaporation chamber pressure and wire feeding pitch angle. Calculate the adjustment amount of process parameters. Assume that the evaporation source temperature needs to be reduced to 780 °C, that is, the adjustment amount is -20 °C. Send a control command to the control system of the evaporation coating equipment according to the calculation result to automatically adjust the process parameters.

[0118] During the operation of the evaporation coating equipment, continuously collect new thermal radiation data, sputtered aluminum height data, and key process parameter data every 10 minutes, and use these data for model optimization.

[0119] Evaluate the multi-parameter coupling model using the newly collected data. If it is found that the deviation between the model prediction result and the actual data exceeds the set threshold range (such as ±5 μm), adjust and optimize the model, such as retraining the model or adjusting the model parameters; when an abnormal sputtered aluminum height is detected subsequently, calculate the adjustment amount based on the optimized model and continuously adjust the process parameters of the evaporation coating equipment.

[0120] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and can be implemented in other specific forms without departing from the spirit or basic characteristics of the present invention. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be included in the present invention. Any reference signs in the claims should not be regarded as limiting the claims involved.

Claims

1. A vapor deposition equipment supervision system based on data analysis, characterized in that: It includes a thermal radiation data acquisition module, a process parameter acquisition module, a data processing and analysis module, a monitoring result output module, a multi-parameter correlation regulation module, and a model optimization module; the thermal radiation data acquisition module is used to acquire the thermal radiation data of the aluminum sputtering area; the process parameter acquisition module is used to acquire the process parameter data of the evaporation equipment; the data processing and analysis module receives the data transmitted by the thermal radiation data acquisition module and the process parameter acquisition module, uses the data processing system to organize the data, constructs a complete data set, and analyzes and processes the data set to obtain aluminum sputtering data; the monitoring result output module is used to display the aluminum sputtering data calculated by the data processing and analysis module on the monitoring interface in real time and transmit it to the equipment control system; the multi-parameter correlation regulation module is used to establish a multi-parameter coupling model between the thermal radiation monitoring data and the process parameters of the evaporation equipment, and perform adaptive regulation on the evaporation process; the model optimization module is used to update and optimize the data processing model and the multi-parameter coupling model, and continuously monitor the aluminum sputtering process of the evaporation equipment.

2. The vapor deposition equipment supervision system based on data analysis according to claim 1, wherein: The thermal radiation data acquisition module includes an aluminum sputtering height measurement unit, a hot spot temperature measurement unit, and a radiation intensity distribution measurement unit; The aluminum sputtering height measurement unit sets height points according to the set measurement range, conducts multiple repeated tests at each height point, and takes the average value of the data obtained at each height point as the accurate data; The hot spot temperature measurement unit is responsible for using an infrared thermal imager to monitor the temperature distribution of the aluminum sputtering area in real time during each aluminum sputtering process, and recording the highest temperature point, which is the hot spot temperature; at the same time, when the equipment is running, the infrared thermal imager continuously acquires the thermal image data of the aluminum sputtering area at a pre-set frame rate, and these image data contain the thermal distribution information of the aluminum sputtering at different moments; The radiation intensity distribution measurement unit first uses a spectral radiometer to measure the radiation intensity of the aluminum sputtering at different wavelengths to obtain the distribution data of the radiation intensity with respect to the wavelength; Then it uses a spectral analyzer to collect the spectral data of the thermal radiation of the aluminum sputtering to obtain the radiation intensity information of the thermal radiation wavelength within the preset wavelength range.

3. The vapor deposition equipment supervision system based on data analysis according to claim 1, characterized in that: The process parameter acquisition module includes a temperature acquisition unit, a speed acquisition unit, a pressure acquisition unit, and an angle acquisition unit; The temperature acquisition unit uses a temperature sensor to monitor the temperature of the evaporation source of the evaporation equipment in real time and transmits the temperature data to the system in real time, and the system can clarify the temperature fluctuation situation through data feedback; The speed acquisition unit uses a photoelectric sensor to measure the wire feeding speed and a rotary encoder to monitor the winding speed; Among them, the photoelectric sensor calculates the wire feeding speed by detecting the changes in light shielding and light transmission during the wire feeding process, and the rotary encoder is connected to the winding shaft to convert the rotation angle of the shaft into an electrical signal to measure the winding speed; at the same time, the system will monitor these two speeds in real time; The pressure acquisition unit uses a pressure sensor to monitor the pressure in the evaporation chamber of the evaporation equipment in real time, and the pressure sensor will transmit the pressure data to the system in real time for monitoring the evaporation environment; The angle acquisition unit uses an inclination sensor and a rotation angle sensor to measure the wire feeding pitch angle parameter and transmits the angle data to the system, which will monitor the wire feeding pitch angle in real time.

4. The vapor deposition equipment supervision system based on data analysis according to claim 1, characterized in that: The data processing and analysis module includes a data sorting unit, a radiation intensity parameter extraction unit, an infrared thermal image preprocessing unit, and a spectral data analysis unit; The data sorting unit is used to sort the splashing aluminum height, hot spot temperature, and radiation intensity distribution data collected in each experiment, establish a data set; and mark and process the abnormal data outside the set threshold range, and eliminate the outliers deviating from other data points; The radiation intensity parameter extraction unit first uses a spectrometer to collect the radiation intensity values at different wavelengths, and then calculates the total radiation intensity and the radiation intensity in a specific band; the radiation intensity data can be represented by a continuous function I(λ). For the total radiation intensity I total , the integral formula is used for calculation, and the formula is as follows: where λ max and λ min represent the maximum and minimum wavelengths for the measurement of radiation intensity, respectively; For the radiation intensity I in a specific wavelength band band It is calculated by the following integral formula: where [λ start , λ end represents the wavelength range of a specific band; After obtaining the data of the total radiation intensity and the radiation intensity in a specific band, these parameters, together with the hot spot temperature, are used as thermal radiation characteristic parameters for subsequent establishment of a relationship with the splashing aluminum height; The infrared thermal imaging preprocessing unit is used to preprocess the infrared thermal imaging to improve the image quality, and then use an image recognition algorithm to identify the splashing aluminum area and extract the characteristic parameters of the splashing aluminum area, including the average temperature and the position of the highest temperature point. These characteristic parameters are part of the thermal radiation characteristic parameters; The spectral data analysis unit determines the peak wavelength and radiation intensity distribution of the thermal radiation; according to Wien's displacement law, the peak wavelength is inversely proportional to the object temperature, and further determines the temperature state of the splashing aluminum; then compares all the extracted thermal radiation characteristic parameters with the pre-established database; the database stores the thermal radiation characteristic parameters corresponding to different splashing aluminum heights, and combines the collected process parameter data. Through the similarity matching algorithm calculation, the height of the current splashing aluminum is obtained.

5. The vapor deposition equipment supervision system based on data analysis according to claim 1, characterized in that: The monitoring result output module includes a display unit and a data transmission unit; The display unit is used to display the splashing aluminum height value in real time, highlight the abnormal splashing aluminum height through a pre-set threshold, and present the change of the splashing aluminum height over time in the form of a trend chart to help the staff analyze the change trend of the splashing aluminum height; The data transmission unit is used to transmit the splashing aluminum height data to the system, and the system will automatically adjust the evaporation source power, wire feeding speed, wire feeding angle, and evaporation chamber pressure according to the transmitted data to achieve adaptive control of the evaporation process.

6. The vapor deposition equipment supervision system based on data analysis according to claim 5, characterized in that: The multi-parameter correlation control module includes a model construction unit and a parameter control unit; the model construction unit is responsible for establishing a multi-parameter coupling model between the thermal radiation monitoring data and the evaporation equipment process parameters; the thermal radiation monitoring data and the evaporation equipment process parameters are the data collected by the thermal radiation data collection module and the process parameter collection module respectively, and are processed and integrated by the data processing and analysis module and then transmitted to the coupling model as a training set. Then, using the data analysis algorithm, analyze the mutual influence relationship between the parameters and construct a multi-parameter coupling model that can reflect the mathematical relationship between the parameters; The parameter control unit is responsible for real-time monitoring of the aluminum sputtering height data; the parameter control unit receives the aluminum sputtering height data transmitted by the data transmission unit, and when it monitors that the aluminum sputtering height data exceeds the preset normal range, it starts a control program to adjust the parameters; the parameter adjustment is based on the multi-parameter coupling model provided by the model construction unit, uses the method of multiple regression analysis to analyze the influence of multiple related processes on the aluminum sputtering parameters, and uses the multi-parameter coupling model for prediction. Given the target value of the aluminum sputtering height, the parameter value x that needs to be adjusted is deduced by the model i , and the formula is as follows: y = β0 + β1x1 + β2x2 + … + β n x n Among them, y represents the predicted value of the aluminum sputtering height, β0 is the constant term, which is a fixed parameter in the model; β1, β2,..., β n are the regression coefficients corresponding to the process parameters x1, x2,..., x n in the model, reflecting the influence degree and direction of the relevant process parameters on the aluminum sputtering height y, and x1, x2,..., x n represent the process parameters of the evaporation equipment, including but not limited to the evaporation source power, wire feeding speed, evaporation chamber pressure, and wire feeding angle; Based on the known parameter values and the predicted sputtering aluminum height, the parameter value x that needs to be adjusted is deduced inversely. i , x i represents the process parameters of the evaporation equipment and is the general representation form of x1, x2,,, x n , where i is an index with a value range of 1 - n; then the process parameter adjustment amount Δx is calculated according to the formula i , and the formula is as follows: Δx i = x i，new - x i，current where x i,new is the new value of the process parameter x obtained by back - calculating through the multi - parameter coupling model when the aluminum splashing height reaches the target value, i and x i,current is the actual value of the current process parameter x i ; According to the calculated adjustment amount of the process parameters, then send a control command to the control system of the evaporation equipment to automatically adjust the process parameters to be adjusted to achieve adaptive control of the evaporation process.

7. A supervision system for evaporation equipment based on data analysis according to claim 1, characterized in that: The model optimization module includes an optimized data collection unit and a model feedback optimization unit; The optimized data acquisition unit is responsible for collecting new thermal radiation data, sputtering aluminum height data, and key process parameter data during the operation of the evaporation equipment, providing basic data for model optimization; the collected data is fed back to the model construction unit of the multi-parameter correlation regulation module, enabling the model construction unit to continuously improve the multi-parameter coupling model based on the new data; The model feedback optimization unit uses the newly collected data to evaluate the multi-parameter coupling model in the multi-parameter correlation regulation module. When the deviation between the model prediction result and the actual data exceeds the set threshold range, the model is adjusted and optimized; at the same time, the optimized model is fed back to the parameter regulation unit of the multi-parameter correlation regulation module, enabling the parameter regulation unit to calculate the adjustment amount based on the model after detecting that the sputtering aluminum height exceeds the set threshold range, and continuously adjust the process parameters of the evaporation equipment.

8. A supervision method for evaporation equipment based on data analysis, which is applied to a supervision system for evaporation equipment based on data analysis described in any one of claims 1-8, characterized in that: It includes the following steps: S1. The thermal radiation data acquisition module collects thermal radiation data from three aspects: sputtering aluminum height, hot spot temperature, and radiation intensity distribution, and each unit collaborates to obtain information; The process parameter acquisition module collects process parameter data through temperature, speed, pressure, and angle acquisition units; S2. Receive the data transmitted by the thermal radiation acquisition module and the process parameter acquisition module, organize the data, construct a complete data set, and mark and process abnormal data; Then calculate the total radiation intensity and the radiation intensity in a specific band of the radiation intensity distribution data; S3. Preprocess the infrared thermal image, and use the image recognition algorithm to extract the thermal characteristic parameters of the sputtering aluminum area; Analyze the spectral data to determine the peak wavelength and radiation intensity distribution of the thermal radiation; finally, compare the extracted thermal characteristic parameters with the pre-established database, and combine the process parameter data to obtain the current sputtering aluminum height through the data processing model; S4. The monitoring result output module displays the sputtering aluminum height in real time, presenting normal and abnormal data and their change trends in different ways; then use the data transmission unit to transmit the sputtering aluminum height data to the system, providing data support for the closed-loop control of the evaporation process; S5. The multi-parameter correlation regulation module uses the collected and processed data to construct a multi-parameter coupling model through data analysis algorithms and analyze the parameter relationships; after the model construction is completed, the parameter regulation unit monitors the sputtering aluminum height, analyzes the influence based on the model when the data is abnormal, calculates the parameter adjustment amount, and sends instructions to achieve adaptive regulation; S6. During the actual operation of the evaporation equipment, the model optimization module continuously collects new thermal radiation data, sputtering aluminum height data, and key process parameter data, and provides them to the model construction unit of the multi-parameter correlation regulation module to improve the model, and updates and optimizes the data processing model and the multi-parameter coupling model.

Images