Equipment intelligent interaction system and method based on artificial intelligence

Abstract

The invention discloses an equipment intelligent interaction system and method based on artificial intelligence, and relates to the technical field of equipment intelligent interaction, and the system comprises a processing analysis module, a hot pressing analysis module, a pressure transmission module, an intelligent interaction module and a temperature control module. The processing analysis module is used for analyzing the type of the to-be-processed material in real time; the hot-pressing analysis module is used for analyzing the target heating temperature and heating time of the heating system; and the pressure transmission module is used for analyzing a pressure application value of the hydraulic system. According to the method, the real-time adhesion coefficient and the compaction degree of the to-be-processed materials are predicted through the obtained real-time images, intelligent regulation and control of all the systems are achieved based on the prediction result, it can be guaranteed that adhesives in the to-be-processed materials can be completely activated in the regulation and control process, it can also be guaranteed that the to-be-processed materials can be tightly adhered, and the quality of the to-be-processed materials is improved. And the intelligent interaction effect among the systems of the laminating machine is improved.

Description

Technical Field

[0001] The present invention relates to the field of device intelligent interaction technology, and in particular to an artificial intelligence-based device intelligent interaction system and method. Background Art

[0002] A laminator is a mechanical device that presses multiple layers of materials together. The basic working principle is to make multiple layers of materials adhere to each other under high temperature and high pressure.

[0003] However, when the laminator is subjecting multi-layer materials to high-temperature and high-pressure treatment, it is unable to precisely control the heating temperature and heating time of the heating system in the laminator, as well as the pressure value applied by the hydraulic system in the laminator, resulting in bubbles in the multi-layer materials under high-temperature treatment or the inability to fully activate the adhesive in the materials, and the inability of the multi-layer materials to adhere tightly to each other, reducing the effectiveness of the laminator. Summary of the invention

[0004] The purpose of the present invention is to provide an artificial intelligence-based device intelligent interaction system and method to solve the problems raised in the prior art.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: an intelligent interactive system for equipment based on artificial intelligence, the system comprising: a processing analysis module, a heat pressure analysis module, a pressure transmission module, an intelligent interactive module and a temperature control module;

[0006] The processing analysis module, the hot pressing module, the pressure transmission module and the temperature control module communicate with each other respectively with the intelligent interaction module;

[0007] The processing analysis module extracts characteristic images from the real-time images collected by the image acquisition device located in the automatic feeding area, compares each extracted characteristic image with the image corresponding to each type of processing material stored in the image library, calculates the similarity between the characteristic image to be compared and the stored image by using the average hash algorithm, analyzes the type of the material to be processed in real time based on the calculation result, and transmits the first analysis result to the intelligent interaction module;

[0008] The hot pressure analysis module analyzes the target heating temperature and heating time of the heating system according to the first analysis result transmitted by the intelligent interaction module and the processing requirements of the material to be processed, and transmits the second analysis result to the intelligent interaction module;

[0009] The pressure transmission module analyzes the pressure applied value of the hydraulic system according to the first analysis result transmitted by the intelligent interaction module and the processing requirements of the material to be processed, and transmits the third analysis result to the intelligent interaction module. The pressure transmission module regulates the pressure applied value of the hydraulic system and the working time of the hydraulic system in real time according to the regulation content of the third analysis result transmitted by the intelligent interaction module and the regulation content of the second analysis result;

[0010] The intelligent interaction module uses the real-time images collected by the image acquisition devices located in the hot pressing zone and the hydraulic zone to predict the real-time adhesion coefficient and the real-time compaction degree of the material to be processed, and based on the prediction results, determines the control content of the second analysis result and the control content of the third analysis result, and transmits the control content of the second analysis result to the temperature control module, and transmits the control content of the third analysis result and the control content of the second analysis result to the pressure transmission module;

[0011] The temperature control module regulates the target heating temperature of the heating system according to the regulation content of the second analysis result transmitted by the intelligent interaction module.

[0012] Furthermore, the specific method for the processing analysis module to analyze the type of the material to be processed in real time is:

[0013] Ⅰ. If the similarity between the feature image a and the stored image b is greater than the set threshold, the type of processing material corresponding to the stored image b is determined, and the materials to be processed contain the determined type of processing material;

[0014] If the similarity between the feature image a and the stored image b is less than or equal to the set threshold, then the material to be processed does not contain the processing material of the determined type determined by the stored image b;

[0015] Ⅱ. Calculate the similarity between each extracted feature image and each stored image, and feed the calculation result back to operation Ⅰ. According to the execution result of operation Ⅰ, determine the type of processing material existing in the processing material.

[0016] Further, the thermal pressure analysis module includes a heating temperature analysis unit and a heating time analysis unit;

[0017] The heating temperature analysis unit determines the initial heating temperature of the heating system according to the first analysis result transmitted by the intelligent interaction module. The initial heating temperature of the heating system = the maximum melting temperature of the adhesive in each type of processing material in the processing material. Combined with the thermal stability coefficient and thermal expansion coefficient of the processing material at each heating temperature, the heating feasibility coefficient of the processing material at each heating temperature is predicted. Combined with the processing thickness of the processing material, the target heating temperature of the heating system is analyzed, and the target heating temperature in the second analysis result is transmitted to the intelligent interaction module.

[0018] The heating time analysis unit obtains the preheating time t1 of the hot press plate, and calculates the thermal conductivity of the material to be processed according to [thermal conductivity of the material to be processed*area of ​​the upper surface of the material to be processed*(target heating temperature-average temperature of the material to be processed before heating treatment)] / processing thickness of the material to be processed. According to the heating time Y=t1+(target heating temperature / thermal conductivity of the material to be processed), the heating time of the heating system at the target heating temperature is calculated, and the heating time in the second analysis result is transmitted to the intelligent interaction module, t1=the time taken for the hot press plate to be heated to the target heating temperature.

[0019] Furthermore, the specific method for the heating temperature analysis unit to analyze the target heating temperature of the heating system is:

[0020] according to Calculate the heating feasibility coefficient of the heating system at temperature T+k*T1 and calculate maxU k The corresponding k value is determined, and the determined k value is recorded as y, y represents a positive integer, and max represents the maximum value symbol;

[0021] The processing thickness d and thermal conductivity f of the material to be processed are obtained. If (T+y*T1)*f>T, the temperature T+y*T1 is put into the set M, and the minimum temperature value stored in the set M is used as the target heating temperature of the heating system. If (T+y*T1)*f≤T, the temperature T is used as the target heating temperature of the heating system.

[0022] Among them, i = 1, 2, ..., m, represents the number corresponding to each type of processing material in the material to be processed, m represents the total number of processing material types in the material to be processed, T represents the initial heating temperature of the heating system, β and γ represent the proportional coefficient and β + γ = 1, k = 1, 2, ..., represents the number corresponding to each temperature increase time point, T1 represents the temperature increase value, It represents the thermal stability coefficient of the i-th material to be processed at the temperature T+k*T1, It represents the thermal expansion coefficient of the i-th material to be processed at the temperature T+k*T1.

[0023] Further, the pressure transmission module includes a pressure analysis unit and a control unit;

[0024] The pressure analysis unit obtains a training data set according to the first analysis result transmitted by the intelligent interaction module to search for a relationship model between the pressure applied by the hydraulic system and the deformation amount generated by the material to be processed, where the training data = [pressure applied by the hydraulic system, deformation amount generated by the material to be processed under the pressure applied by the hydraulic system], and the absolute value of the difference between the target processing thickness value of the material to be processed and the processing thickness value of the material to be processed is input into the relationship model to be searched, and the pressure application value Q of the hydraulic system is obtained. At time Y, the pressure applied by the hydraulic system to the material to be processed is Q, and the third analysis result is transmitted to the intelligent interaction module;

[0025] The control unit receives the control content of the third analysis result and the control content of the second analysis result transmitted by the intelligent interaction module, and controls the pressure application value and working time of the hydraulic system in real time according to the received information.

[0026] Furthermore, the intelligent interaction module includes an adhesion coefficient prediction unit, a compaction degree prediction unit, and an intelligent interaction unit;

[0027] The bonding coefficient prediction unit uses the real-time image acquired by the image acquisition device located in the hot pressing zone to acquire the flow and deformation of the material to be processed in the acquired image, and predicts the bonding coefficient of the material to be processed in real time, determines the control content of the second analysis result based on the prediction result, and transmits the determination result to the intelligent interaction unit;

[0028] The compaction prediction unit acquires real-time images acquired by an image acquisition device located in the hydraulic zone, predicts the compaction of the material to be processed based on the acquired images, determines the control content of the third analysis result based on the prediction result, and transmits the determination result to the intelligent interaction unit;

[0029] The intelligent interaction unit transmits the control content of the second analysis result, the control content of the third analysis result, and the control content of the second analysis result to the temperature control module and the pressure transmission module respectively.

[0030] Furthermore, the specific method for the bonding coefficient prediction unit to predict the bonding coefficient of the material to be processed in real time is:

[0031] The image captured by the image acquisition device located in the hot pressing zone at the time p+c*s is acquired. In the acquired image, the upper surface of the material to be processed is divided into regions according to the area V, and each divided region is numbered. The numbering result is: j=1, 2, ..., n; n represents the total number of divided regions, s represents the acquisition interval time of the image acquisition device, c=1, 2, 3, ..., represents the number corresponding to each acquisition time point of the image acquisition device, and p represents the initial acquisition time of the image by the image acquisition device located in the hot pressing zone;

[0032] According to U j(p+c*s) =S j(p+c*s) / s calculates the average flow velocity of the material to be processed in the area numbered j at the time p+c*s, S j(p+c*s) It represents the area corresponding to the deformed region in the region numbered j in the image collected at time p+c*s;

[0033] according to Predict the viscosity coefficient of the material to be processed at the time p+c*s, where ρ represents the density of the material to be processed, and e=2.73;

[0034] If E p+c*s =1, the control content of the second analysis result is: at time p+c*s, the target heating temperature of the heating system is adjusted to 0. If the time p+c*s is before time Y, at time p+c*s, the hydraulic system is controlled to apply pressure to the material to be processed, and the pressure applied by the hydraulic system is Q;

[0035] If E p+c*s <1, the control content of the second analysis result is: at the moment p+c*s, there is no need to control the target heating temperature of the heating system.

[0036] Furthermore, the specific method for the compaction prediction unit to predict the compaction of the material to be processed based on the acquired image is:

[0037] The image captured by the image acquisition device located in the hydraulic system at time q is acquired, and the thickness value d of the material to be processed at time q is calculated based on the acquired image. q To obtain, according to y q =(dd q ) / (dD) predicts the compaction degree of the material to be processed at time q, where D represents the target processing thickness value of the material to be processed;

[0038] If y q =1, then the control content of the third analysis result is: at time q, adjust the pressure value Q applied by the hydraulic system to the material to be processed to 0;

[0039] If yq <1, the control content of the third analysis result is: at time q, there is no need to control the pressure applied value Q of the hydraulic system.

[0040] Furthermore, the temperature control module is a cooling system. When the regulation content of the second analysis result is: at time p+c*s, the target heating temperature of the heating system is adjusted to 0, the heating system stops working and the temperature control module starts working. When the regulation content of the second analysis result is: at time p+c*s, there is no need to regulate the target heating temperature of the heating system, the temperature control module is in a shutdown state, and the heating system continues to heat the hot pressing plate at the target heating temperature.

[0041] An artificial intelligence-based device intelligent interaction method, the method comprising:

[0042] S10: extracting feature images from the real-time image collected by the image acquisition device located in the automatic feeding area, comparing each extracted feature image with the image corresponding to each type of processing material stored in the image library, calculating the similarity between the feature image to be compared and the stored image by an average hash algorithm, and analyzing the type of the material to be processed in real time based on the calculation result;

[0043] S20: predicting the heating feasibility coefficient of the material to be processed at each heating temperature according to the thermal stability coefficient and thermal expansion coefficient of the material to be processed at each heating temperature, and analyzing the target heating temperature and heating time of the heating system in combination with the processing thickness of the material to be processed;

[0044] S30: inputting the target processing thickness of the material to be processed and the processing thickness of the material to be processed into a relationship model found through historical data, and analyzing the pressure applied value of the hydraulic system;

[0045] S40: using the real-time images collected by the image acquisition devices located in the hot pressing zone and the hydraulic zone, respectively predicting the real-time adhesion coefficient and the real-time compaction degree of the material to be processed, and based on the prediction results, respectively determining the target heating temperature control content of the heating system, and the pressure application value and working time value control content of the hydraulic system;

[0046] S50: respectively regulating the target heating temperature of the heating system, and the pressure applied value and working time of the hydraulic system.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] 1. The present invention predicts the target heating temperature of the heating system by analyzing the heating feasibility of the material to be processed at various heating temperatures, and based on the analysis results, taking into account the processing thickness and thermal conductivity of the material to be processed. The material to be processed has good thermal stability and a low thermal expansion coefficient at the target heating temperature, which is beneficial to reducing bubbles generated by the material to be processed during the heating process.

[0049] 2. The present invention predicts the real-time adhesion coefficient and compaction degree of the material to be processed by acquiring real-time images, and based on the prediction results, intelligently controls the target heating temperature of the heating system and the pressure applied value of the hydraulic system. During the control process, it can not only ensure that the adhesive in the material to be processed can be fully activated, but also ensure that the materials to be processed can be tightly adhered to each other, thereby improving the intelligent interaction effect between the various systems of the laminator.

[0050] 3. By calculating the thermal conductivity of the material to be processed, the heating time of the heating system at the target heating temperature can be predicted, ensuring that the molecules of the material to be processed can be bonded when the hydraulic system is working, avoiding the movement of the material to be processed due to the placement position when the hydraulic system is working, resulting in the material to be processed failing to meet the processing requirements, further improving the use effect of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 A schematic diagram of the working principle structure of an artificial intelligence-based device intelligent interaction system and method of the present invention;

[0052] Figure 2 The present invention is a schematic diagram of the workflow of an artificial intelligence-based device intelligent interaction system and method. DETAILED DESCRIPTION

[0053] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0054] Example: Figure 1 and Figure 2 As shown, the present invention provides a device intelligent interaction system and method technical solution based on artificial intelligence, an device intelligent interaction system based on artificial intelligence, the system includes: a processing analysis module, a heat pressure analysis module, a pressure transmission module, an intelligent interaction module and a temperature control module;

[0055] The processing analysis module, the hot pressing module, the pressure transmission module and the temperature control module communicate with each other respectively with the intelligent interaction module;

[0056] The processing analysis module extracts characteristic images from the real-time image collected by the image acquisition device located in the automatic feeding area, and compares each extracted characteristic image, which refers to a local image in the real-time image that can show the type of the material to be processed, with the images corresponding to each type of processing material stored in the image library, and calculates the similarity between the characteristic image to be compared and the stored image by an average hash algorithm. The method of calculating the image similarity between the two images by an average hash algorithm (the average hash algorithm is an algorithm for comparing image similarity, which converts the image into a grayscale image, scales the image size, calculates the average grayscale value, and compares each pixel with the average grayscale value to generate a hash value, thereby realizing rapid comparison of the image) belongs to the prior art. Based on the calculation result, the type of the material to be processed is analyzed in real time, and the first analysis result is transmitted to the intelligent interaction module. The processing material types include resin, glass fiber, carbon fiber, metal, plastic, etc. The first analysis result refers to the analyzed type of the material to be processed;

[0057] The specific method by which the processing analysis module analyzes the type of material to be processed in real time is:

[0058] Ⅰ. If the similarity between the feature image a and the stored image b is greater than the set threshold, the type of processing material corresponding to the stored image b is determined, and the materials to be processed contain the determined type of processing material;

[0059] If the similarity between the feature image a and the stored image b is less than or equal to the set threshold, then the material to be processed does not contain the processing material of the determined type determined by the stored image b;

[0060] II. Calculate the similarity between each extracted feature image and each stored image, and feed the calculation result back to operation I. According to the execution result of operation I, determine the type of processing material existing in the processing material;

[0061] The hot pressing analysis module analyzes the target heating temperature and heating time of the heating system according to the first analysis result transmitted by the intelligent interaction module and the processing requirements of the material to be processed, and transmits the second analysis result to the intelligent interaction module, where the second analysis result refers to the analyzed heating temperature and heating time of the hot pressing plate;

[0062] The thermal pressure analysis module includes a heating temperature analysis unit and a heating time analysis unit;

[0063] The heating temperature analysis unit determines the initial heating temperature of the heating system according to the first analysis result transmitted by the intelligent interaction module. The initial heating temperature of the heating system = the maximum melting temperature of the adhesive in each type of processing material in the material to be processed. Combined with the thermal stability coefficient and thermal expansion coefficient of the material to be processed at each heating temperature, the heating feasibility coefficient of the material to be processed at each heating temperature is predicted. Combined with the processing thickness of the material to be processed, the target heating temperature of the heating system is analyzed. The specific method is as follows:

[0064] according to Calculate the heating feasibility coefficient of the heating system at temperature T+k*T1 and calculate maxU k The corresponding k value is determined, and the determined k value is recorded as y, y represents a positive integer, and max represents the maximum value symbol;

[0065] The processing thickness d and thermal conductivity f of the material to be processed are obtained, d = the vertical distance value between the upper surface of the material to be processed and the upper surface of the heating plate, and the vertical distance values ​​between each position of the upper surface of the material to be processed and the upper surface of the heating plate are equal. If (T+y*T1)*f>T, the temperature T+y*T1 is put into the set M, and the minimum temperature value stored in the set M is used as the target heating temperature of the heating system. If (T+y*T1)*f≤T, the temperature T is used as the target heating temperature of the heating system. The thermal conductivity represents the heat transferred through a unit area per unit time under stable heat transfer conditions;

[0066] Among them, i = 1, 2, ..., m, represents the number corresponding to each type of processing material in the material to be processed, m represents the total number of processing material types in the material to be processed, T represents the initial heating temperature of the heating system, β and γ represent the proportional coefficient and β + γ = 1, k = 1, 2, ..., represents the number corresponding to each temperature increase time point, T1 represents the temperature increase value, It represents the thermal stability coefficient of the i-th material to be processed at the temperature T+k*T1, Deformation degree = |unit volume of the i-th processed material at temperature T+k*T1 - unit volume | / unit volume, unit volume = 1cm 3 , It represents the thermal expansion coefficient of the i-th material to be processed at the temperature T+k*T1,

[0067] and transmitting the target heating temperature in the second analysis result to the intelligent interaction module;

[0068] The heating time analysis unit obtains the preheating time t1 of the hot press plate, calculates the thermal conductivity of the material to be processed according to [thermal conductivity of the material to be processed*area of ​​the upper surface of the material to be processed*(target heating temperature-average temperature of the material to be processed before heating treatment)] / processing thickness of the material to be processed, calculates the heating time of the heating system at the target heating temperature according to the heating time Y=t1+(target heating temperature / thermal conductivity of the material to be processed), and transmits the heating time in the second analysis result to the intelligent interaction module, t1=the time taken for the hot press plate to be heated to the target heating temperature;

[0069] The pressure transmission module analyzes the pressure applied value of the hydraulic system according to the first analysis result transmitted by the intelligent interaction module and the processing requirements of the material to be processed, and transmits the third analysis result to the intelligent interaction module. The pressure transmission module regulates the pressure applied value of the hydraulic system and the working time of the hydraulic system in real time according to the regulation content of the third analysis result transmitted by the intelligent interaction module and the regulation content of the second analysis result;

[0070] The pressure transmission module includes a pressure application analysis unit and a control unit;

[0071] The pressure analysis unit obtains a training data set according to the first analysis result transmitted by the intelligent interaction module to search for a relationship model between the pressure applied by the hydraulic system and the deformation variable generated by the material to be processed, wherein the training data = [pressure applied by the hydraulic system, deformation variable generated by the material to be processed under the pressure applied by the hydraulic system], the training data is derived from historical data, the deformation variable generated by the material to be processed = thickness change of the material to be processed, the absolute value of the difference between the target processing thickness value of the material to be processed and the processing thickness value of the material to be processed is input into the relationship model to be searched, and the pressure application value Q of the hydraulic system is obtained, and pressure is applied to the material to be processed by the hydraulic system at time Y (time Y is the working time of the hydraulic system), the pressure application value of the hydraulic system is Q, and the third analysis result is transmitted to the intelligent interaction module;

[0072] The control unit receives the control content of the third analysis result and the control content of the second analysis result transmitted by the intelligent interaction module, and controls the pressure application value and working time of the hydraulic system in real time according to the received information;

[0073] The intelligent interaction module uses the real-time images collected by the image acquisition devices located in the hot pressing zone and the hydraulic zone to predict the real-time bonding coefficient and the real-time compaction degree of the material to be processed, and based on the prediction results, determines the control content of the second analysis result and the control content of the third analysis result, and transmits the control content of the second analysis result to the temperature control module, and transmits the control content of the third analysis result and the control content of the second analysis result to the pressure transmission module;

[0074] The intelligent interaction module includes an adhesion coefficient prediction unit, a compaction degree prediction unit, and an intelligent interaction unit;

[0075] The bonding coefficient prediction unit uses the real-time image acquired by the image acquisition device located in the hot pressing zone to acquire the image. The hot pressing zone refers to the area where the material to be processed is heated by the heating system. Based on the flow and deformation of the material to be processed in the acquired image, the bonding coefficient of the material to be processed is predicted in real time. Based on the prediction result, the control content of the second analysis result is determined, and the determination result is transmitted to the intelligent interaction unit;

[0076] The specific method for the bonding coefficient prediction unit to predict the bonding coefficient of the material to be processed in real time is:

[0077] The image captured by the image acquisition device located in the hot pressing zone at the time p+c*s is acquired. In the acquired image, the upper surface of the material to be processed is divided into regions according to the area V, and each divided region is numbered. The numbering result is: j=1, 2, ..., n; n represents the total number of divided regions, s represents the acquisition interval time of the image acquisition device, c=1, 2, 3, ..., represents the number corresponding to each acquisition time point of the image acquisition device, and p represents the initial acquisition time of the image by the image acquisition device located in the hot pressing zone, and the image acquisition device is a camera;

[0078] According to U j(p+c*s) =S j(p+c*s) / s calculates the average flow velocity of the material to be processed in the area numbered j at the time p+c*s, S j(p+c*s) It represents the area corresponding to the deformation region existing in the region numbered j in the image collected at the time p+c*s. The average flow velocity is used to describe the flow of the material to be processed during the heating process;

[0079] according to Predict the viscosity coefficient of the material to be processed at the time p+c*s, where ρ represents the density of the material to be processed, and e=2.73;

[0080] If E p+c*s =1, the control content of the second analysis result is: at time p+c*s, the target heating temperature of the heating system is adjusted to 0. If the time p+c*s is before time Y, then at time p+c*s, the hydraulic system is controlled to apply pressure to the material to be processed, and the pressure applied by the hydraulic system is Q. At this time, time p+c*s is the working time of the hydraulic system;

[0081] If E p+c*s<1, the control content of the second analysis result is: at the moment p+c*s, there is no need to control the target heating temperature of the heating system;

[0082] The compaction degree prediction unit acquires the real-time image acquired by the image acquisition device located in the hydraulic area, the hydraulic area refers to the area where the material to be processed is pressurized by the hydraulic system, predicts the compaction degree of the material to be processed based on the acquired image, determines the control content of the third analysis result based on the prediction result, and transmits the determination result to the intelligent interaction unit;

[0083] The specific method for the compaction degree prediction unit to predict the compaction degree of the material to be processed based on the acquired image is:

[0084] The image captured by the image acquisition device located in the hydraulic system at time q is acquired, and the thickness value d of the material to be processed at time q is calculated based on the acquired image. q To obtain, according to y q =(dd q ) / (dD) predicts the compaction degree of the material to be processed at time q, where D represents the target processing thickness value of the material to be processed;

[0085] If y q =1, then the control content of the third analysis result is: at time q, adjust the pressure value Q applied by the hydraulic system to the material to be processed to 0;

[0086] If y q <1, the control content of the third analysis result is: at time q, there is no need to control the pressure applied value Q of the hydraulic system, that is, the hydraulic system continues to act on the processing material with the pressure applied value Q;

[0087] The intelligent interaction unit transmits the control content of the second analysis result, and the control content of the third analysis result and the control content of the second analysis result to the temperature control module and the pressure transmission module respectively;

[0088] The temperature control module regulates the target heating temperature of the heating system according to the regulation content of the second analysis result transmitted by the intelligent interaction module;

[0089] The temperature control module is a cooling system. When the regulation content of the second analysis result is: at the moment p+c*s, the target heating temperature of the heating system is adjusted to 0, the heating system stops working and the temperature control module starts working. When the regulation content of the second analysis result is: at the moment p+c*s, there is no need to regulate the target heating temperature of the heating system, the temperature control module is in a shutdown state, and the heating system continues to heat the hot pressing plate at the target heating temperature.

[0090] An artificial intelligence-based device intelligent interaction method, the method comprising:

[0091] S10: extracting feature images from the real-time image collected by the image acquisition device located in the automatic feeding area, comparing each extracted feature image with the image corresponding to each type of processing material stored in the image library, calculating the similarity between the feature image to be compared and the stored image by an average hash algorithm, and analyzing the type of the material to be processed in real time based on the calculation result;

[0092] S20: predicting the heating feasibility coefficient of the material to be processed at each heating temperature according to the thermal stability coefficient and thermal expansion coefficient of the material to be processed at each heating temperature, and analyzing the target heating temperature and heating time of the heating system in combination with the processing thickness of the material to be processed;

[0093] S30: inputting the target processing thickness of the material to be processed and the processing thickness of the material to be processed into a relationship model found through historical data, and analyzing the pressure applied value of the hydraulic system;

[0094] S40: using the real-time images collected by the image acquisition devices located in the hot pressing zone and the hydraulic zone, respectively predicting the real-time adhesion coefficient and the real-time compaction degree of the material to be processed, and based on the prediction results, respectively determining the target heating temperature control content of the heating system, and the pressure application value and working time value control content of the hydraulic system;

[0095] S50: respectively regulating the target heating temperature of the heating system, and the pressure applied value and working time of the hydraulic system.

[0096] Example 1: Assume n = 4, V = 8 cm 2 , the areas corresponding to the deformed regions in the regions numbered 1, 2, 3, and 4 in the image collected at time p+2*s are: S 1(p+2*s) =4cm 2 , S 2(p+2*s) =6cm 2 , S 3(p+2*s) =0cm 2 , S 4(p+2*s) =0cm 2 , s = 4 seconds, then the average flow speeds of the materials to be processed in the areas numbered 1, 2, 3, and 4 at time p+2*s are:

[0097] U 1(p+2*s) =S 1(p+2*s) / s = 4 / 4 = 1 square centimeter / second;

[0098] U 2(p+2*s) =S 2(p+2*s) / s = 6 / 4 = 1.5 square centimeters / second;

[0099] U 3(p+2*s) =S 3(p+2*s) / s = 0 / 4 = 0 square centimeters per second;

[0100] U 3(p+2*s) =S 3(p+2*s) / s = 0 / 4 = 0 square centimeters per second;

[0101] Then the average flow speeds of the materials to be processed in the areas numbered 1, 2, 3, and 4 at the time p+2*s are 0.5 square centimeters per second, 1.5 square centimeters per second, 0 square centimeters per second, and 0 square centimeters per second respectively;

[0102] The viscosity coefficient of the material to be processed at time p+2*s is:

[0103]

[0104] Then the viscosity coefficient of the material to be processed at the time p+2*s is 0.22.

[0105] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. An artificial intelligence-based device intelligent interaction system, characterized in that: The system includes: a processing analysis module, a thermal pressure analysis module, a pressure transmission module, an intelligent interaction module and a temperature control module; The processing analysis module, the hot pressing module, the pressure transmission module and the temperature control module communicate with each other respectively with the intelligent interaction module; The processing analysis module extracts characteristic images from the real-time images collected by the image acquisition device located in the automatic feeding area, compares each extracted characteristic image with the image corresponding to each type of processing material stored in the image library, calculates the similarity between the characteristic image to be compared and the stored image by using the average hash algorithm, analyzes the type of the material to be processed in real time based on the calculation result, and transmits the first analysis result to the intelligent interaction module; The hot pressure analysis module analyzes the target heating temperature and heating time of the heating system according to the first analysis result transmitted by the intelligent interaction module and the processing requirements of the material to be processed, and transmits the second analysis result to the intelligent interaction module; The pressure transmission module analyzes the pressure applied value of the hydraulic system according to the first analysis result transmitted by the intelligent interaction module and the processing requirements of the material to be processed, and transmits the third analysis result to the intelligent interaction module. The pressure transmission module regulates the pressure applied value of the hydraulic system and the working time of the hydraulic system in real time according to the regulation content of the third analysis result transmitted by the intelligent interaction module and the regulation content of the second analysis result; The intelligent interaction module uses the real-time images collected by the image acquisition devices located in the hot pressing zone and the hydraulic zone to predict the real-time adhesion coefficient and the real-time compaction degree of the material to be processed, and based on the prediction results, determines the control content of the second analysis result and the control content of the third analysis result, and transmits the control content of the second analysis result to the temperature control module, and transmits the control content of the third analysis result and the control content of the second analysis result to the pressure transmission module; The temperature control module regulates the target heating temperature of the heating system according to the regulation content of the second analysis result transmitted by the intelligent interaction module.

2. The device intelligent interaction system based on artificial intelligence according to claim 1, characterized in that: The specific method for the processing analysis module to analyze the type of material to be processed in real time is: Ⅰ. If the similarity between the feature image a and the stored image b is greater than the set threshold, the type of processing material corresponding to the stored image b is determined, and the materials to be processed contain the determined type of processing material; If the similarity between the feature image a and the stored image b is less than or equal to the set threshold, then the material to be processed does not contain the processing material of the determined type determined by the stored image b; Ⅱ. Calculate the similarity between each extracted feature image and each stored image, and feed the calculation result back to operation Ⅰ. According to the execution result of operation Ⅰ, determine the type of processing material existing in the processing material.

3. The device intelligent interaction system based on artificial intelligence according to claim 2, characterized in that: The thermal pressure analysis module includes a heating temperature analysis unit and a heating time analysis unit; The heating temperature analysis unit determines the initial heating temperature of the heating system according to the first analysis result transmitted by the intelligent interaction module. The initial heating temperature of the heating system = the maximum melting temperature of the adhesive in each type of processing material in the processing material. Combined with the thermal stability coefficient and thermal expansion coefficient of the processing material at each heating temperature, the heating feasibility coefficient of the processing material at each heating temperature is predicted. Combined with the processing thickness of the processing material, the target heating temperature of the heating system is analyzed, and the target heating temperature in the second analysis result is transmitted to the intelligent interaction module. The heating time analysis unit obtains the preheating time t1 of the hot press plate, and calculates the thermal conductivity of the material to be processed according to [thermal conductivity of the material to be processed*area of ​​the upper surface of the material to be processed*(target heating temperature-average temperature of the material to be processed before heating treatment)] / processing thickness of the material to be processed. According to the heating time Y=t1+(target heating temperature / thermal conductivity of the material to be processed), the heating time of the heating system at the target heating temperature is calculated, and the heating time in the second analysis result is transmitted to the intelligent interaction module, t1=the time taken for the hot press plate to be heated to the target heating temperature.

4. The device intelligent interaction system based on artificial intelligence according to claim 3, characterized in that: The specific method for the heating temperature analysis unit to analyze the target heating temperature of the heating system is: according to Calculate the heating feasibility coefficient of the heating system at temperature T+k*T1 and calculate maxU k The corresponding k value is determined, and the determined k value is recorded as y, y represents a positive integer, and max represents the maximum value symbol; The processing thickness d and thermal conductivity f of the material to be processed are obtained. If (T+y*T1)*f>T, the temperature T+y*T1 is put into the set M, and the minimum temperature value stored in the set M is used as the target heating temperature of the heating system. If (T+y*T1)*f≤T, the temperature T is used as the target heating temperature of the heating system. Among them, i = 1, 2, ..., m, represents the number corresponding to each type of processing material in the material to be processed, m represents the total number of processing material types in the material to be processed, T represents the initial heating temperature of the heating system, β and γ represent the proportional coefficient and β + γ = 1, k = 1, 2, ..., represents the number corresponding to each temperature increase time point, T1 represents the temperature increase value, It represents the thermal stability coefficient of the i-th material to be processed at the temperature T+k*T1, It represents the thermal expansion coefficient of the i-th material to be processed at the temperature T+k*T1.

5. The device intelligent interaction system based on artificial intelligence according to claim 4, characterized in that: The pressure transmission module includes a pressure analysis unit and a control unit; The pressure analysis unit obtains a training data set according to the first analysis result transmitted by the intelligent interaction module to search for a relationship model between the pressure applied by the hydraulic system and the deformation amount generated by the material to be processed, where the training data = [pressure applied by the hydraulic system, deformation amount generated by the material to be processed under the pressure applied by the hydraulic system], and the absolute value of the difference between the target processing thickness value of the material to be processed and the processing thickness value of the material to be processed is input into the relationship model to be searched, and the pressure application value Q of the hydraulic system is obtained. At time Y, the pressure applied by the hydraulic system to the material to be processed is Q, and the third analysis result is transmitted to the intelligent interaction module; The control unit receives the control content of the third analysis result and the control content of the second analysis result transmitted by the intelligent interaction module, and controls the pressure application value and working time of the hydraulic system in real time according to the received information.

6. The device intelligent interaction system based on artificial intelligence according to claim 5, characterized in that: The intelligent interaction module includes an adhesion coefficient prediction unit, a compaction degree prediction unit, and an intelligent interaction unit; The bonding coefficient prediction unit uses the real-time image acquired by the image acquisition device located in the hot pressing zone to acquire the flow and deformation of the material to be processed in the acquired image, and predicts the bonding coefficient of the material to be processed in real time, determines the control content of the second analysis result based on the prediction result, and transmits the determination result to the intelligent interaction unit; The compaction prediction unit acquires real-time images acquired by an image acquisition device located in the hydraulic zone, predicts the compaction of the material to be processed based on the acquired images, determines the control content of the third analysis result based on the prediction result, and transmits the determination result to the intelligent interaction unit; The intelligent interaction unit transmits the control content of the second analysis result, the control content of the third analysis result, and the control content of the second analysis result to the temperature control module and the pressure transmission module respectively.

7. The device intelligent interaction system based on artificial intelligence according to claim 6, characterized in that: The specific method for the adhesion coefficient prediction unit to predict the adhesion coefficient of the material to be processed in real time is: The image captured by the image acquisition device located in the hot pressing zone at the time p+c*s is acquired. In the acquired image, the upper surface of the material to be processed is divided into regions according to the area V, and each divided region is numbered. The numbering result is: j=1, 2, ..., n; n represents the total number of divided regions, s represents the acquisition interval time of the image acquisition device, c=1, 2, 3, ..., represents the number corresponding to each acquisition time point of the image acquisition device, and p represents the initial acquisition time of the image by the image acquisition device located in the hot pressing zone; According to U j(p+c*s) =S j(p+c*s) / s calculates the average flow velocity of the material to be processed in the area numbered j at the time p+c*s, S j(p+c*s) It represents the area corresponding to the deformed region in the region numbered j in the image collected at time p+c*s; according to Predict the viscosity coefficient of the material to be processed at the time p+c*s, where ρ represents the density of the material to be processed, and e=2.73; If E p+c*s =1, the control content of the second analysis result is: at time p+c*s, the target heating temperature of the heating system is adjusted to 0. If the time p+c*s is before time Y, at time p+c*s, the hydraulic system is controlled to apply pressure to the material to be processed, and the pressure applied by the hydraulic system is Q; If E p+c*s <1, the control content of the second analysis result is: at the moment p+c*s, there is no need to control the target heating temperature of the heating system.

8. The device intelligent interaction system based on artificial intelligence according to claim 7, characterized in that: The specific method for the compaction prediction unit to predict the compaction of the material to be processed based on the acquired image is: The image captured by the image acquisition device located in the hydraulic system at time q is acquired, and the thickness value d of the material to be processed at time q is calculated based on the acquired image. q To obtain, according to y q =(dd q ) / (dD) predicts the compaction degree of the material to be processed at time q, where D represents the target processing thickness value of the material to be processed; If y q =1, then the control content of the third analysis result is: at time q, adjust the pressure value Q applied by the hydraulic system to the material to be processed to 0; If y q <1, the control content of the third analysis result is: at time q, there is no need to control the pressure applied value Q of the hydraulic system.

9. The device intelligent interaction system based on artificial intelligence according to claim 8, characterized in that: The temperature control module is a cooling system. When the regulation content of the second analysis result is: at time p+c*s, the target heating temperature of the heating system is adjusted to 0, the heating system stops working and the temperature control module starts working. When the regulation content of the second analysis result is: at time p+c*s, there is no need to regulate the target heating temperature of the heating system, the temperature control module is in a shutdown state, and the heating system continues to heat the hot pressing plate at the target heating temperature.

10. An artificial intelligence-based device intelligent interaction method applied to the artificial intelligence-based device intelligent interaction system according to any one of claims 1 to 9, characterized in that: The method comprises: S10: extracting feature images from the real-time image collected by the image acquisition device located in the automatic feeding area, comparing each extracted feature image with the image corresponding to each type of processing material stored in the image library, calculating the similarity between the feature image to be compared and the stored image by an average hash algorithm, and analyzing the type of the material to be processed in real time based on the calculation result; S20: predicting the heating feasibility coefficient of the material to be processed at each heating temperature according to the thermal stability coefficient and thermal expansion coefficient of the material to be processed at each heating temperature, and analyzing the target heating temperature and heating time of the heating system in combination with the processing thickness of the material to be processed; S30: inputting the target processing thickness of the material to be processed and the processing thickness of the material to be processed into a relationship model found through historical data, and analyzing the pressure applied value of the hydraulic system; S40: using the real-time images collected by the image acquisition devices located in the hot pressing zone and the hydraulic zone, respectively predicting the real-time adhesion coefficient and the real-time compaction degree of the material to be processed, and based on the prediction results, respectively determining the target heating temperature control content of the heating system, and the pressure application value and working time value control content of the hydraulic system; S50: respectively regulating the target heating temperature of the heating system, and the pressure applied value and working time of the hydraulic system.

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