Layered fabric heating core, heating core manufacturing equipment and control system thereof

Abstract

The present invention relates to the technical field of heaters, and in particular to a layered fabric heating core, a heating core manufacturing device and a control system thereof, comprising warp yarns and weft yarns composed of conductive composite fibers, the warp yarns and weft yarns being woven into a layered fabric heating core by a loom, the conductive composite fibers being prepared by laminating conductive materials and fiber matrix materials; the layered fabric heating core provided by the present invention, through the uniform weaving of flexible conductive composite fibers, makes heat evenly distributed in the fabric, thereby avoiding the problem of local overheating or overcooling, and because the conductive composite fibers have low electrical resistance, the power consumption required for heating is reduced.

Description

Technical Field

[0001] The invention relates to the technical field of heaters, in particular to a layered fabric heating core, heating core manufacturing equipment and a control system thereof. Background Art

[0002] Layered fabric heating technology is widely used in modern life. Traditional heating methods mainly rely on conductive materials such as metal wire or carbon fiber, which need to be evenly distributed in the fabric to ensure uniform heat transfer.

[0003] The patent application with publication number CN101437332A discloses an electric blanket. The invention provides an electric blanket with adjustable temperature and electromagnetic shielding device, including blanket cloth, electric heating wire and temperature controller, wherein the blanket cloth is three layers, wherein the four sides of the two outer layers are connected to form a bag body, one side of which has an opening, and the opening has a sealing device that can be opened and closed, and a third layer of blanket cloth is attached to one side of the bag body, and the two are connected together along parallel alternating straight lines, and a channel is formed between the two layers of blanket cloth between every two adjacent straight lines, and the electric heating wire passes through each channel in turn, and is connected to the temperature control device and the power cord in turn, and the temperature can be adjusted at will.

[0004] As in the above application, the existing electric blanket metal wire or carbon fiber is used as the heating element in the form of a hose line, and the heating method is linear when the power is turned on. Therefore, there is a phenomenon that the temperature of the wire tube area is high and the temperature of other areas is low. The linear heating method requires a higher temperature to be transmitted to the entire surface, which increases energy consumption, and the higher temperature will affect the user experience. The heating soft wire material mainly relies on the external plastic tube for insulation. After long-term high-temperature use, the plastic is prone to aging and cracking, causing a safety hazard of leakage. At the same time, in order to achieve the insulation effect, the wall thickness of the plastic tube needs to meet certain requirements, which makes the area with the soft wire tube feel, affecting the flexibility and comfort of the fabric. Summary of the invention

[0005] In order to solve the above problems, the present invention provides a layered fabric heating core, a heating core manufacturing device and a control system thereof.

[0006] The present invention adopts the following technical scheme, a heating core manufacturing device, which is used to manufacture a heating core in which warp yarns and weft yarns composed of conductive composite fibers are woven into a layered fabric by a loom, comprising:

[0007] A laminated tank, which is composed of a tank body and an upper cover;

[0008] A fiber line arrangement component, which is arranged on the upper cover and is used to arrange the conductive composite fibers to ensure that the conductive composite fibers are in a stable position;

[0009] A boosting assembly, the boosting assembly comprises a boosting pump and an air duct, one end of the air duct is conductively connected to the air outlet of the boosting pump, and the other end of the air duct is conductively connected to the tank body.

[0010] As a further description of the above technical solution: the fiber line arrangement assembly includes an arrangement base, the arrangement base is a spindle-shaped structure, and a plurality of winding mechanisms are staggered and arranged at equal intervals from bottom to top on the outer wall of the arrangement base along its circumference;

[0011] The winding mechanism includes a strip seat, one end of which is inserted into a limiting groove provided in the arrangement base, a limiting block is welded to one end of the strip seat located in the limiting groove, a spring is arranged between the limiting block and the inner wall of the limiting groove, and the other end of the strip seat is rotatably connected to a winding roller.

[0012] As a further description of the above technical solution: a pressure sensor is arranged on the upper cover, an electric heating plate is installed in the arrangement base, and supporting legs are installed on the outer wall of the lamination tank.

[0013] As a further description of the above technical solution: a base is installed on the upper part of the outer wall of the laminated tank, an L-shaped frame is rotatably connected to the base, an electric telescopic rod is installed on the upper surface of the horizontal end of the L-shaped frame, the bottom end of the electric telescopic rod is welded and fixed to the upper cover, and a driving mechanism is provided on the base, which is used to drive the L-shaped frame to rotate axially along its vertical end;

[0014] The driving mechanism comprises a linkage gear fixed to the vertical end of the L-shaped frame and a driving motor embedded in the base. The output shaft of the driving motor is fixedly connected with a driving gear, and the driving gear is meshed with the linkage gear.

[0015] The layered fabric heating core is prepared using the heating core manufacturing equipment. The layered fabric heating core includes warp yarns and weft yarns composed of conductive composite fibers. The warp yarns and weft yarns are woven into a layered fabric heating core by a loom. The conductive composite fibers are prepared by laminating conductive materials and fiber matrix materials.

[0016] As a further description of the above technical solution: the conductive material is one of carbon nanotubes, graphene, and conductive polymers;

[0017] The fiber matrix material is one of polypropylene, polyacrylonitrile, PET and polyethylene terephthalate.

[0018] A control system for a heating cell manufacturing device comprises: the above-mentioned heating cell manufacturing device and a control unit, wherein the control unit comprises:

[0019] A data collection module collects historical lamination training data of the conductive composite fiber, the historical lamination training data is collected when the conductive composite fiber lamination processing meets the standards, and the historical lamination training data includes first historical training data and second historical training data;

[0020] The first historical training data includes the material composition of the conductive composite fiber, the heating coefficient of the conductive composite fiber and the heating temperature;

[0021] The second historical training data includes the material composition of the conductive composite fiber, the diameter and heating temperature of the conductive composite fiber and the lamination control parameters;

[0022] A temperature prediction module, which trains a machine learning model for predicting the heating temperature based on the first historical training data, collects the material composition of the conductive composite fiber to be laminated and the heating coefficient of the conductive composite fiber, and predicts the heating temperature based on the trained machine learning model;

[0023] The parameter prediction module trains the lamination control parameter recommendation model based on the second historical training data, collects the material composition of the conductive composite fiber to be processed, the diameter of the conductive composite fiber and the heating temperature, and inputs them into the trained lamination control parameter recommendation model to obtain the lamination control parameter recommendation set label, and then obtains the lamination control parameter recommendation set corresponding to the lamination control parameter recommendation set label, and controls the operation of the lamination tank based on the lamination control parameters in the lamination control parameter recommendation set.

[0024] As a further description of the above technical solution: the parameters affecting the heating coefficient of the conductive composite fiber include the melting point of the conductive material, the thermal expansion coefficient of the fiber matrix material and the diameter of the conductive composite fiber;

[0025] The expression of the heating coefficient of the conductive composite fiber is:

[0026] ;

[0027] In the formula, is the heating coefficient of the conductive composite fiber, is the melting point of the conductive material, is the thermal expansion coefficient of the fiber matrix material, is the diameter of the conductive composite fiber, , and is the weight factor, , and Both are greater than zero.

[0028] As a further description of the above technical solution: the method for training a machine learning model for predicting heating temperature based on the first historical training data includes:

[0029] Converting the collected first historical training data into a corresponding set of feature vectors;

[0030] Each group of feature vectors is used as the input of the machine learning model. The machine learning model takes the material composition of each group of collected conductive composite fibers and the heating temperature corresponding to the heating coefficient of the conductive composite fibers as outputs, and takes the material composition of each group of collected conductive composite fibers and the heating temperature actually corresponding to the heating coefficient of the conductive composite fibers as prediction targets, and takes minimizing the loss function value of the machine learning model as the training target; training stops when the loss function value of the machine learning model is less than or equal to the preset first target loss value.

[0031] As a further description of the above technical solution: the recommended set of lamination control parameters is , The collection label is The corresponding pressure is The pressurization time corresponding to the set label is;

[0032] The method for training a lamination control parameter recommendation model based on the second historical training data includes:

[0033] Pre-set the recommended set of lamination control parameters with corresponding numbers;

[0034] The second historical training data is converted into a corresponding set of second eigenvectors, and each set of second eigenvectors is used as the input of the lamination control parameter recommendation model. The lamination control parameter recommendation model uses a set of lamination control parameter recommendation set labels corresponding to the material composition of the conductive composite fibers, the diameter of the conductive composite fibers, and the heating temperature as output, and a set of lamination control parameter recommendation set labels actually corresponding to the material composition of each group of conductive composite fibers, the diameter of the conductive composite fibers, and the heating temperature as prediction targets, and minimizing the loss function value of the lamination control parameter recommendation model as a training target; the training is stopped when the loss function value of the lamination control parameter recommendation model is less than or equal to the preset second target loss value.

[0035] Beneficial effects:

[0036] The layered fabric heating core provided by the present invention is prepared by laminating a conductive material and a fiber matrix material to form a conductive composite fiber, and then the conductive composite fiber is used to form a heating core woven from warp yarns and weft yarns to form a layered fabric. The heat is evenly distributed in the fabric through the uniform weaving of the flexible conductive composite fiber, thereby avoiding the problem of local overheating or overcooling. Since the conductive composite fiber has a low resistance, the power consumption required for heating is reduced, the energy utilization efficiency is improved, and the problem in the prior art that the power-on heating method is linear heating, so the temperature of the wire tube area is high and the temperature of other areas is low.

[0037] Furthermore, by setting up a fiber line arrangement component, the conductive composite fibers to be laminated can be evenly staggered and arranged on the outside of the arrangement matrix, and the arrangement matrix is ​​a spindle-shaped structure, so that the conductive composite fibers arranged on the winding mechanism outside the arrangement matrix are staggered with each other, ensuring that the conductive composite fibers remain evenly distributed during the lamination process, and when the conductive composite fibers are arranged by the winding mechanism, the strip seat is inserted into the limit groove opened in the arrangement matrix, and cooperates with the setting of the spring. When in use, the tension of the conductive composite fibers wound on the winding mechanism can be adaptively adjusted according to the elastic force contraction of the spring to keep the tension and position stability of the conductive composite fibers. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The present invention will be further explained below in conjunction with the accompanying drawings and embodiments:

[0039] Figure 1 A schematic diagram of the structure of a layered fabric heating core provided in Example 1 of the present invention;

[0040] Figure 2 A schematic diagram of the structure of the conductive composite fiber provided in Example 1 of the present invention;

[0041] Figure 3 A schematic diagram of the structure of a heating cell manufacturing device provided in Example 2 of the present invention;

[0042] Figure 4 Provided for Example 2 of the present invention Figure 3 A magnified view of area A in;

[0043] Figure 5 A schematic diagram of the structure of a laminated tank provided in Example 2 of the present invention;

[0044] Figure 6 A schematic structural diagram of a fiber line arrangement assembly provided in Example 2 of the present invention;

[0045] Figure 7 Provided for Example 2 of the present invention Figure 6 A magnified view of area B in FIG.

[0046] Figure 8 This is a module connection diagram of the control unit provided in Example 3 of the present invention.

[0047] Attached figures: 101, heating cell; 102, weft yarn; 103, warp yarn; 104, conductive composite fiber; 105, fiber matrix material; 106, conductive material; 1, laminated tank; 11, pressure sensor; 2, tank body; 3, upper cover; 31, arrangement base; 32, winding mechanism; 33, strip seat; 34, winding roller; 35, limit groove; 36, spring; 37, limit block; 38, electric heating plate; 41, linkage gear; 42, drive motor; 43, drive gear; 5, support leg; 6, base; 7, L-shaped frame; 8, electric telescopic rod; 9, air duct; 10, booster pump. DETAILED DESCRIPTION

[0048] In order to make the technical means, creative features, objectives and effects of the present invention easy to understand, the present invention is further described below with reference to specific diagrams. It should be noted that the embodiments and features in the embodiments of the present application can be combined with each other without conflict.

[0049] Example 1

[0050] See also Figure 1-Figure 2 The embodiment of the present invention provides a technical solution: a layered fabric heating core, comprising a warp yarn 103 and a weft yarn 102 composed of a conductive composite fiber 104, the warp yarn 103 and the weft yarn 102 are woven into a layered fabric heating core 101 by a loom;

[0051] The conductive composite fiber 104 is prepared by laminating a conductive material 106 and a fiber matrix material 105 .

[0052] The conductive material 106 is one of carbon nanotubes, graphene, and conductive polymer;

[0053] The fiber matrix material 105 is one of polypropylene, polyacrylonitrile, PET and polyethylene terephthalate.

[0054] In this embodiment, a conductive composite fiber 104 is prepared by laminating a conductive material 106 and a fiber matrix material 105, and then the conductive composite fiber 104 is used to form a heating core 101 which is woven into a layered fabric by warp yarns 103 and weft yarns 102. The heat is evenly distributed in the fabric through the uniform weaving of the flexible conductive composite fiber 104, thereby avoiding the problem of local overheating or overcooling. Since the conductive composite fiber 104 has a low resistance, the power consumption required for heating is reduced, and the energy utilization efficiency is improved. The problem in the prior art that the heating method is linear heating, so there is a phenomenon that the temperature of the wire tube area is high and the temperature of other areas is low, and the heating soft wire material mainly relies on the external plastic tube for insulation. After long-term high-temperature use, the plastic is prone to aging and cracking, causing a safety hazard of leakage. At the same time, in order to achieve the insulation effect, the wall thickness of the plastic tube needs to meet certain requirements, which makes the area with the soft wire tube feel, affecting the flexibility and comfort of the fabric.

[0055] Example 2

[0056] See also Figure 3-Figure 7 The embodiment of the present invention provides a technical solution: a heating core manufacturing device for manufacturing a layered fabric heating core, comprising:

[0057] A laminated tank 1, which is composed of a tank body 2 and an upper cover 3;

[0058] A fiber line arrangement component is disposed on the upper cover 3 and is used for arranging the conductive composite fibers 104 to ensure that the conductive composite fibers 104 are in a stable position;

[0059] The boosting assembly includes a boosting pump 10 and an air duct 9 , one end of the air duct 9 is conductively connected to the air outlet of the boosting pump 10 , and the other end of the air duct 9 is conductively connected to the tank body 2 .

[0060] The fiber line arrangement assembly includes an arrangement base 31, which is a spindle-shaped structure, and a plurality of winding mechanisms 32 are staggered and arranged at equal intervals from bottom to top on the outer wall of the arrangement base 31 along its circumference;

[0061] The winding mechanism 32 includes a strip seat 33, one end of the strip seat 33 is inserted into a limiting groove 35 opened in the arrangement base 31, and a limiting block 37 is welded to one end of the strip seat 33 located in the limiting groove 35, a spring 36 is arranged between the limiting block 37 and the inner wall of the limiting groove 35, and the other end of the strip seat 33 is rotatably connected to the winding roller 34.

[0062] Specifically, when the conductive composite fibers 104 are arranged by the winding mechanism 32, the winding roller 34 is firstly rotated and connected to the strip seat 33, and the strip seat 33 is inserted into the limiting groove 35 provided in the arrangement base 31, and cooperates with the setting of the spring 36. When in use, the tension of the conductive composite fibers 104 wound on the winding mechanism 32 can be adaptively adjusted according to the elastic force contraction of the spring 36, so as to keep the tension and position stability of the conductive composite fibers 104.

[0063] A pressure sensor 11 is disposed on the upper cover 3 , an electric heating plate 38 is installed in the arrangement base 31 , and legs 5 are installed on the outer wall of the lamination tank 1 .

[0064] A base 6 is installed on the upper part of the outer wall of the laminating tank 1, and an L-shaped frame 7 is rotatably connected to the base 6. An electric telescopic rod 8 is installed on the upper surface of the horizontal end of the L-shaped frame 7. The bottom end of the electric telescopic rod 8 is welded and fixed to the upper cover 3. A driving mechanism is provided on the base 6, which is used to drive the L-shaped frame 7 to rotate axially along its vertical end;

[0065] The driving mechanism includes a linkage gear 41 fixed to the vertical end of the L-shaped frame 7 and a driving motor 42 embedded in the base 6 . A driving gear 43 is fixed to the output shaft of the driving motor 42 , and the driving gear 43 is meshed with the linkage gear 41 .

[0066] Specifically, the position of the winding mechanism 32 is adjusted by setting the base 6 and the L-shaped frame 7. When in use, the electric telescopic rod 8 is first controlled to retract to drive the upper cover 3 to move upward, so that the fiber line arrangement assembly arranged under the upper cover 3 is moved out of the tank body 2, and then the driving mechanism is controlled to drive the L-shaped frame 7 to rotate, so as to drive the fiber line arrangement assembly and the tank body 2 to be misaligned with each other, and then the electric telescopic rod 8 is controlled to extend again to drive the fiber line arrangement assembly to move downward, and the height of the fiber line arrangement assembly is adjusted, and then the conductive composite fiber 104 is wound around it. On the winding mechanism 32, the conductive composite fibers 104 are evenly arranged on the outside of the arrangement matrix 31, and the fiber line arrangement assembly is moved down into the tank body 2 by controlling the extension and retraction of the electric telescopic rod 8 and the rotation of the L-shaped frame 7, and the tank body 2 is sealed with the upper cover 3, and then the electric heating plate 38 is controlled to work to heat the conductive composite fibers 104, and then the booster pump 10 is controlled to work, and the internal pressure of the laminating tank 1 is adjusted to laminate the conductive composite fibers 104, so that the conductive material 106 and the fiber matrix material 105 are tightly combined.

[0067] In this embodiment, by setting up a fiber line arrangement component, the conductive composite fibers 104 to be laminated can be evenly staggered and arranged on the outside of the arrangement matrix 31, and the arrangement matrix 31 is a spindle-shaped structure, so that the conductive composite fibers 104 arranged on the winding mechanism 32 outside the arrangement matrix 31 are staggered with each other, and the adjacent conductive composite fibers 104 wound on the arrangement matrix 31 will not be on the same horizontal plane, ensuring that the conductive composite fibers 104 remain evenly distributed during the lamination process.

[0068] Example 3

[0069] See also Figure 3-Figure 8 The embodiment of the present invention provides a technical solution: a control system for heating cell manufacturing equipment, comprising: the heating cell manufacturing equipment and a control unit in embodiment 2, the control unit comprising:

[0070] A data collection module collects historical lamination training data of the conductive composite fiber 104, wherein the historical lamination training data is collected when the lamination processing of the conductive composite fiber 104 meets the standards, and the historical lamination training data includes first historical training data and second historical training data;

[0071] The first historical training data includes the material composition of the conductive composite fiber 104, the heating coefficient of the conductive composite fiber 104, and the heating temperature;

[0072] The second historical training data includes the material composition of the conductive composite fiber 104, the diameter and heating temperature of the conductive composite fiber 104, and the lamination control parameters;

[0073] A temperature prediction module, which trains a machine learning model for predicting the heating temperature based on the first historical training data, collects the material composition of the conductive composite fiber 104 to be laminated and the heating coefficient of the conductive composite fiber 104, and predicts the heating temperature based on the trained machine learning model;

[0074] The parameter prediction module trains the lamination control parameter recommendation model based on the second historical training data, collects the material composition of the conductive composite fiber 104 to be processed, the diameter of the conductive composite fiber 104 and the heating temperature, and inputs them into the trained lamination control parameter recommendation model to obtain the lamination control parameter recommendation set label, and then obtains the lamination control parameter recommendation set corresponding to the lamination control parameter recommendation set label, and controls the operation of the lamination tank 1 based on the lamination control parameters in the lamination control parameter recommendation set.

[0075] The parameters that affect the heating coefficient of the conductive composite fiber 104 include the melting point of the conductive material 106 and the thermal expansion coefficient of the fiber matrix material 105 and the diameter of the conductive composite fiber 104;

[0076] The expression of the heating coefficient of the conductive composite fiber 104 is:

[0077] ;

[0078] In the formula, is the heating coefficient of the conductive composite fiber 104, is the melting point of the conductive material 106, is the thermal expansion coefficient of the fiber matrix material 105, is the diameter of the conductive composite fiber 104, , and is the weight factor, , and Both are greater than zero.

[0079] Specifically, the thermal expansion coefficient of the fiber matrix material 105 will also affect the selection of the heating temperature, and it is necessary to avoid fiber expansion or warping due to excessively high temperature. That is, the greater the thermal expansion coefficient of the fiber matrix material 105, the lower the heating temperature, and vice versa. The higher the melting point of the conductive material 106, the higher the heating temperature, and vice versa. The larger the diameter of the conductive composite fiber 104, the higher the heating temperature, and vice versa. In summary, the greater the heating coefficient of the conductive composite fiber 104, the higher the heating temperature, and vice versa.

[0080] It should be noted that the size of the weight factor is a specific value obtained by quantifying each data to facilitate subsequent comparison. The size of the weight factor depends on the number of comprehensive parameters and the preliminary setting of the corresponding weight factor for each set of comprehensive parameters by technical personnel in this field.

[0081] The method of training a machine learning model for predicting a heating temperature based on first historical training data includes:

[0082] Converting the collected first historical training data into a corresponding set of feature vectors;

[0083] Each group of feature vectors is used as the input of the machine learning model. The machine learning model takes the material composition of each group of conductive composite fibers 104 collected and the heating temperature corresponding to the heating coefficient of the conductive composite fibers 104 as output, and takes the material composition of each group of conductive composite fibers 104 collected and the heating temperature actually corresponding to the heating coefficient of the conductive composite fibers 104 as prediction targets. Minimizing the loss function value of the machine learning model is used as the training target. Training stops when the loss function value of the machine learning model is less than or equal to the preset first target loss value.

[0084] Specifically, the machine learning model is a deep belief network model. It should be noted that in the machine learning model, the calculation formula of the loss function is: ,in, is the feature vector number, is the prediction error, For the The predicted state value corresponding to the group feature vector is the heating temperature. For the The actual state value corresponding to the group feature vector.

[0085] The recommended set of lamination control parameters is: , The collection label is The corresponding pressure is The collection label is The corresponding pressurization time;

[0086] The method for training a lamination control parameter recommendation model based on the second historical training data includes:

[0087] Pre-set the recommended set of lamination control parameters with corresponding numbers;

[0088] The second historical training data is converted into a corresponding set of second eigenvectors, and each set of second eigenvectors is used as the input of the lamination control parameter recommendation model. The lamination control parameter recommendation model uses a set of lamination control parameter recommendation set labels corresponding to the material composition of the conductive composite fiber 104, the diameter of the conductive composite fiber 104, and the heating temperature as output, and a set of lamination control parameter recommendation set labels actually corresponding to the material composition of each group of conductive composite fibers 104, the diameter of the conductive composite fiber 104, and the heating temperature as prediction targets, and minimizing the loss function value of the lamination control parameter recommendation model as the training target; the training is stopped when the loss function value of the lamination control parameter recommendation model is less than or equal to the preset second target loss value.

[0089] Specifically, the lamination control parameter recommendation model is a deep neural network model.

[0090] It should be noted that in the recommended model for lamination control parameters, the calculation formula for prediction error is:

[0091] ,in, is the number of the second eigenvector, is the prediction error, For the The predicted state value corresponding to the second eigenvector of the group is the recommended set label of the control parameter. For the The actual state value corresponding to the second eigenvector of the group.

[0092] In this embodiment, a control unit is added to collect historical lamination training data of the conductive composite fiber 104, the historical lamination training data includes first historical training data and second historical training data, a machine learning model for predicting the heating temperature is trained based on the first historical training data, and then the material composition of the conductive composite fiber 104 to be laminated and the heating coefficient of the conductive composite fiber 104 are collected, and the heating temperature is predicted based on the trained machine learning model, and then the conductive composite fiber 104 is heated at the predicted heating temperature, that is, the machine learning model is trained by comprehensively collecting parameters affecting the heating temperature, and then the heating temperature is predicted based on the trained machine learning model, and then the electric heating plate 38 is controlled to work according to the predicted heating temperature, thereby ensuring the softening effect of the conductive material 106 and the fiber matrix material 105, and ensuring the tight combination of the conductive material 106 and the fiber matrix material 105 after lamination;

[0093] Furthermore, on the basis of predicting the heating temperature based on the trained machine learning model, the lamination control parameter recommendation model is trained through the second historical training data, that is, the parameters affecting the lamination control parameters and the predicted heating temperature are comprehensively collected to train the lamination control parameter recommendation model, and then the lamination control parameter recommendation set label is obtained based on the trained lamination control parameter recommendation model, and then the lamination control parameter recommendation set corresponding to the lamination control parameter recommendation set label is obtained, and the lamination tank 1 is controlled to work based on the lamination control parameters in the lamination control parameter recommendation set, so as to ensure the close combination of the conductive material 106 and the fiber matrix material 105 after lamination, and secondly, the automatic generation of control parameters is realized, and the pressurization pressure and pressurization time are automatically controlled based on the control parameters, without the need for manpower to rely on experience to adjust the pressurization level and pressurization time, thereby further ensuring the lamination effect of the conductive composite fiber 104.

[0094] The basic principles, main features and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and the description in the specification are only to illustrate the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A heating core manufacturing device, used for manufacturing a heating core (101) in which warp yarns (103) and weft yarns (102) composed of conductive composite fibers (104), the warp yarns (103) and weft yarns (102) being woven into a layered fabric by a loom, characterized in that: include: A laminated tank (1), wherein the laminated tank (1) is composed of a tank body (2) and an upper cover (3); A fiber line arrangement component, the fiber line arrangement component being arranged on the upper cover (3), and the fiber line arrangement component being used for arranging the conductive composite fibers (104) to ensure that the conductive composite fibers (104) are positioned stably; A boosting assembly, the boosting assembly comprising a boosting pump (10) and an air guide pipe (9), one end of the air guide pipe (9) being conductively connected to an air outlet of the boosting pump (10), and the other end of the air guide pipe (9) being conductively connected to a tank body (2); The fiber line arrangement assembly comprises an arrangement base (31), the arrangement base (31) being a spindle-shaped structure, and winding mechanisms (32) are arranged on the outer wall of the arrangement base (31) at equal intervals and staggered from bottom to top along the circumference thereof; The winding mechanism (32) comprises a strip seat (33), one end of the strip seat (33) being inserted into a limiting groove (35) provided in the arrangement base (31), a limiting block (37) being welded to one end of the strip seat (33) located in the limiting groove (35), a spring (36) being provided between the limiting block (37) and the inner wall of the limiting groove (35), and the other end of the strip seat (33) being rotatably connected to a winding roller (34).

2. The heating core manufacturing equipment according to claim 1, characterized in that: A pressure sensor (11) is provided on the upper cover (3), an electric heating plate (38) is installed in the arrangement base (31), and supporting legs (5) are installed on the outer wall of the lamination tank (1).

3. The heating core manufacturing equipment according to claim 1, characterized in that: A base (6) is installed on the upper part of the outer wall of the laminating tank (1), an L-shaped frame (7) is rotatably connected to the base (6), an electric telescopic rod (8) is installed on the upper surface of the horizontal end of the L-shaped frame (7), the bottom end of the electric telescopic rod (8) is welded and fixed to the upper cover (3), and a driving mechanism is provided on the base (6) for driving the L-shaped frame (7) to rotate axially along its vertical end; The driving mechanism comprises a linkage gear (41) fixed to the vertical end of the L-shaped frame (7) and a driving motor (42) embedded in the base (6); a driving gear (43) is fixedly connected to the output shaft of the driving motor (42); and the driving gear (43) is meshingly connected to the linkage gear (41).

4. A layered fabric heating core, prepared using the heating core manufacturing equipment as described in any one of claims 1 to 3, characterized in that: The layered fabric heating core comprises warp yarns (103) and weft yarns (102) composed of conductive composite fibers (104); the warp yarns (103) and weft yarns (102) are woven by a loom into a layered fabric heating core (101); the conductive composite fibers (104) are prepared by laminating conductive materials (106) and fiber matrix materials (105).

5. The layered fabric heating core according to claim 4, characterized in that: The conductive material (106) is one of carbon nanotubes, graphene, and conductive polymers; The fiber matrix material (105) is one of polypropylene, polyacrylonitrile, PET and polyethylene terephthalate.

6. A control system for heating cell manufacturing equipment, characterized in that: include: The heating cell manufacturing device and control unit according to any one of claims 1 to 3, wherein the control unit comprises: A data collection module for collecting historical lamination training data of the conductive composite fiber (104), the historical lamination training data being collected when the lamination processing of the conductive composite fiber (104) meets the standards, the historical lamination training data comprising first historical training data and second historical training data; The first historical training data includes the material composition of the conductive composite fiber (104), the heating coefficient of the conductive composite fiber (104), and the heating temperature; The second historical training data includes the material composition of the conductive composite fiber (104), the diameter and heating temperature of the conductive composite fiber (104), and lamination control parameters; A temperature prediction module, which trains a machine learning model for predicting heating temperature based on the first historical training data, collects the material composition of the conductive composite fibers (104) to be laminated and the heating coefficient of the conductive composite fibers (104), and predicts the heating temperature based on the trained machine learning model; The parameter prediction module trains a lamination control parameter recommendation model based on the second historical training data, collects the material composition of the conductive composite fiber (104) to be processed, the diameter of the conductive composite fiber (104) and the heating temperature, and inputs them into the trained lamination control parameter recommendation model to obtain a lamination control parameter recommendation set label, and then obtains a lamination control parameter recommendation set corresponding to the lamination control parameter recommendation set label, and controls the lamination tank (1) to work based on the lamination control parameters in the lamination control parameter recommendation set.

7. The control system of the heating core manufacturing equipment according to claim 6, characterized in that: The parameters affecting the heating coefficient of the conductive composite fiber (104) include the melting point of the conductive material (106), the thermal expansion coefficient of the fiber matrix material (105), and the diameter of the conductive composite fiber (104); The heating coefficient of the conductive composite fiber (104) is expressed as: ； In the formula, is the heating coefficient of the conductive composite fiber (104), is the melting point of the conductive material (106), is the thermal expansion coefficient of the fiber matrix material (105), is the diameter of the conductive composite fiber (104), , and is the weight factor, , and Both are greater than zero.

8. The control system of the heating core manufacturing equipment according to claim 6, characterized in that: The method for training a machine learning model for predicting heating temperature based on first historical training data includes: Converting the collected first historical training data into a corresponding set of feature vectors; Each group of feature vectors is used as the input of the machine learning model. The machine learning model uses the material composition of each group of collected conductive composite fibers (104) and the heating temperature corresponding to the heating coefficient of the conductive composite fibers (104) as outputs, and uses the material composition of each group of collected conductive composite fibers (104) and the heating temperature actually corresponding to the heating coefficient of the conductive composite fibers (104) as prediction targets, and uses minimizing the loss function value of the machine learning model as a training target; and stops training when the loss function value of the machine learning model is less than or equal to a preset first target loss value.

9. The control system of the heating core manufacturing equipment according to claim 6, characterized in that: The recommended set of lamination control parameters is: , The collection label is The corresponding pressure is The collection label is The corresponding pressurization time; The method for training a lamination control parameter recommendation model based on the second historical training data includes: Pre-set the recommended set of lamination control parameters with corresponding numbers; The second historical training data is converted into a corresponding set of second feature vectors, and each set of second feature vectors is used as the input of the lamination control parameter recommendation model. The lamination control parameter recommendation model uses a set of lamination control parameter recommendation set labels corresponding to the material composition of the conductive composite fiber (104), the diameter of the conductive composite fiber (104), and the heating temperature as output, and uses a set of lamination control parameter recommendation set labels actually corresponding to the material composition of each set of conductive composite fibers (104), the diameter of the conductive composite fibers (104), and the heating temperature as a prediction target, and uses minimizing the lamination control parameter recommendation model loss function value as a training target; when the lamination control parameter recommendation model loss function value is less than or equal to a preset second target loss value, the training is stopped.

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