A preparation process and equipment for reflective heat-insulating textile fabric

Abstract

The invention discloses a preparation process and equipment of a reflective heat-insulating textile fabric. The fabric comprises a substrate layer, a reflective control layer, a heat conversion layer and a protective layer arranged in sequence from bottom to top. The process comprises the steps of phosphomolybdic acid modification, preparation of a reflective control layer, preparation of a heat conversion layer and preparation of a protective layer. The adverse effects of phosphomolybdic acid on the fabric are solved by organic amine modification and amino polyvinyl alcohol coating. The equipment comprises a stirring barrel, a lifting stirring shaft, an automatic pH adjustment device and an intelligent control system. Intelligent control of process parameters is achieved by linking the stirring shaft position with the agent addition rate, a multi-level early warning mechanism and an adaptive algorithm. The invention has the following beneficial effects: the preparation process and equipment of the reflective heat-insulating textile fabric can overcome the inherent defects of phosphomolybdic acid on fabric performance and improve its reflective heat-insulating effect.

Description

Technical Field

[0001] The invention relates to a production process and equipment of a heat-insulating textile fabric, and in particular to a preparation process and equipment of a reflective heat-insulating textile fabric. Background Art

[0002] Reflective thermal insulation textile fabric is an important thermal management functional textile with broad application prospects in clothing, construction, military industry, etc. Existing reflective thermal insulation textile fabrics mainly achieve thermal insulation effect by introducing materials with special thermal management functions on the surface of the fabric.

[0003] The preparation process of existing reflective thermal insulation textile fabrics usually includes the following steps: first, select a suitable base fabric material, and then introduce functional materials into the fabric through coating, impregnation and other processes. Currently, the following technical routes are mainly used: one is to apply infrared reflective coating on the surface of the fabric to reflect thermal radiation; the second is to use thermal conductive fibers to improve the thermal conductivity of the fabric; the third is to improve the thermal management performance of the fabric through nanomaterial modification.

[0004] However, existing technologies have obvious limitations. The infrared reflective coating has poor washing resistance, which affects the product life; thermal conductive fibers will significantly change the feel and style of the fabric; the process of nanomaterials is complex and has safety risks. These problems have seriously restricted the industrial application of thermal management functional textiles.

[0005] As a heteropolyacid with a special cage structure, phosphomolybdic acid has unique light-to-heat conversion properties and can theoretically be used to develop new thermal management functional textiles. However, the traditional phosphomolybdic acid modification process has serious technical bottlenecks: first, phosphomolybdic acid can cause adverse effects such as discoloration and hardening of fabrics, seriously affecting product quality; second, phosphomolybdic acid is very prone to structural decomposition, especially when the pH value is not properly controlled.

[0006] In actual production, pH control in the phosphomolybdic acid treatment process is the most critical and difficult process parameter. Existing technology requires that the pH value must be strictly controlled within a narrow range of 4.5-5.5. Once the pH value exceeds 6.0, an insoluble precipitate will quickly form, resulting in modification failure. The current process control method is to manually take samples and test them regularly (once every 30 minutes), and make timely adjustments when abnormalities are found. This method is not only cumbersome to operate, but also prone to delays, making it difficult to detect and deal with abnormal pH values ​​in a timely manner.

[0007] When abnormal phenomena such as precipitation and flocculation occur, the reaction needs to be stopped immediately and key parameters need to be recorded. This passive treatment method not only wastes raw materials but also affects production efficiency. At the same time, frequent manual sampling and testing also increase the labor intensity and safety risks of workers.

[0008] Therefore, the present application proposes a preparation process and equipment for a reflective thermal insulation textile fabric to solve the adverse effects of phosphomolybdic acid on fabric performance and improve its reflective thermal insulation performance. Through automated detection technology, there is no need for cumbersome timed measurements of pH and other parameters, and the system pH is automatically adjusted, thereby ensuring the smooth implementation of the phosphomolybdic acid modification process, thereby achieving the technical purpose of reducing labor costs, improving measurement accuracy and automatically adjusting parameters. Summary of the invention

[0009] The purpose of the present invention is to provide a process for preparing a reflective heat-insulating textile fabric, which can overcome the inherent defects of phosphomolybdic acid on fabric performance and improve its reflective heat-insulating effect.

[0010] The above technical objectives of the present invention are achieved through the following technical solutions:

[0011] A preparation process of a reflective heat-insulating textile fabric, comprising: a reflective heat-insulating textile fabric, wherein the reflective heat-insulating textile fabric comprises: a substrate layer, a reflective regulating layer, a heat conversion layer and a protective layer arranged in sequence from bottom to top;

[0012] According to weight ratio,

[0013] The composition of the reflection regulating layer is: 45 parts of nano-alumina, 25 parts of titanium dioxide, 8 parts of phosphomolybdic acid, 3-5 parts of modified graphene, 0.5-1 parts of amino-modified polyvinyl alcohol, and the balance of deionized water;

[0014] The composition of the heat conversion layer is: 20-30 parts of graphene aerogel, 15-25 parts of phase change microcapsules, 5-10 parts of carbon nanotubes, 2-3 parts of dispersant, 1-2 parts of cross-linking agent, and the balance of deionized water;

[0015] The protective layer is composed of 30-40 parts of fluorocarbon resin, 10-15 parts of modified silicon dioxide, 3-5 parts of crosslinking agent and the balance of organic solvent.

[0016] The preparation process of the reflective heat-insulating textile fabric also includes the following steps:

[0017] Step 1: Phosphomolybdic acid modification:

[0018] Dissolve phosphomolybdic acid in deionized water to prepare a 5-8 wt% solution, and stir at 800 rpm for 15 minutes;

[0019] Add 3-5wt% organic amine compound dropwise at a rate of 2mL / min, and react at 40±1℃ for 2 hours under nitrogen protection and light protection;

[0020] The pH value was adjusted to 4.5-5.5 with a dilute NaOH solution and stirred at 800 rpm for 30 minutes. During this process, the pH value was monitored in real time and adjusted;

[0021] After stirring, let it stand for 30 minutes;

[0022] Add pre-swollen amino-modified polyvinyl alcohol, and stir at 35° C. for 1 hour to obtain a modified phosphomolybdic acid solution;

[0023] Step 2: Preparation of reflection control layer: pre-dispersing nano-alumina and titanium dioxide, adding modified graphene, and coating after ultrasonic-microwave synergistic treatment;

[0024] Step 3: Preparation of heat conversion layer: After ultrasonic pre-dispersion of graphene aerogel, add dispersant, add phase change microcapsules and stir, then add ultrasonic pre-dispersed carbon nanotubes and apply;

[0025] Step 4: Preparation of protective layer: Mix fluorocarbon resin and modified silica, stir, add cross-linking agent and then apply.

[0026] The present invention is further configured as follows:

[0027] The steps of preparing the reflection regulating layer include:

[0028] Pre-disperse nano-alumina and titanium dioxide, and perform ultrasonic treatment for 30 minutes at a temperature of 15-20°C;

[0029] The modified phosphomolybdic acid solution is mixed with the pre-dispersed solution, and the modified graphene is added;

[0030] The conditions for pulsed ultrasound-microwave synergistic treatment are: ultrasound power 400W, ultrasound frequency 40kHz, microwave power 200W, pulse ratio 2s:1s, temperature 15-20°C, and treatment time 45 minutes;

[0031] Coating: coating amount 100g / m 2 , coating speed 2m / min, tension 15N, drying at 60℃ for 15 minutes.

[0032] The present invention is further configured as follows:

[0033] The steps of preparing the heat conversion layer include:

[0034] The graphene aerogel was ultrasonically pre-dispersed for 45 min and a dispersant was added;

[0035] Phase change microcapsules were added at 25°C with a stirring speed of 500 rpm and stirred for 30 minutes;

[0036] Add carbon nanotubes pre-dispersed by 15 minutes of ultrasound;

[0037] Coating: coating amount 80g / m 2 , dried at 50℃ for 20 minutes.

[0038] The present invention is further configured as follows:

[0039] The steps of preparing the protective layer include: dissolving the fluorocarbon resin and adding the modified silica, stirring at 300 rpm for 10 minutes; adding the crosslinking agent; coating: coating amount 50 g / m 2 , dried at 80℃ for 10 minutes.

[0040] The mechanism of the above preparation process is as follows:

[0041] The core of the technology is the molecular structure control of phosphomolybdic acid modification. The unmodified phosphomolybdic acid molecule has a Keggin structure, with PO 4 Tetrahedron, with 12 MoO 6 The octahedrons are connected by sharing edges and corners. After modification by organic amines, the amine groups coordinate with the Mo-O bonds on the surface of phosphomolybdic acid to form a stable complex, which reduces the intermolecular interaction and improves the dispersion stability. At the same time, the amino polyvinyl alcohol is further coated by hydrogen bonding, achieving steric protection at the molecular scale.

[0042] The reflection control layer is based on the principle of multi-scale scattering. The particle sizes of nano-alumina and titanium dioxide are 30-50nm and 60-80nm respectively. By precisely controlling the ratio and dispersion state of the two particles, a gradient refractive index interface is formed. The modified phosphomolybdic acid molecules are evenly distributed in it, forming a special electron transfer channel with the metal oxide. The two-dimensional layer structure of the modified graphene provides an additional electron transmission path. The synergistic effect of the three significantly enhances the selective reflection of thermal radiation.

[0043] The main reasons why phosphomolybdic acid does not affect the performance of textiles are as follows:

[0044] A double-layer protective structure is formed by organic amine modification and amino polyvinyl alcohol coating. The organic amine forms a coordination bond with the Keggin structure of phosphomolybdic acid, which significantly reduces the acidity and oxidizing properties of phosphomolybdic acid. Aminated polyvinyl alcohol is further coated through hydrogen bonding, blocking the direct contact between phosphomolybdic acid and the fiber.

[0045] By precisely controlling the pH value (4.5-5.5) and the reaction temperature, a stable charge layer is formed on the surface of the phosphomolybdic acid. The surface charge distribution forms an electrostatic repulsion with the fiber surface, further preventing the adverse interaction between the two. At the same time, the modified phosphomolybdic acid forms a stable interface structure with other components.

[0046] Phosphomolybdic acid forms a ternary synergistic system with metal oxides and graphene, and its electron transfer and energy conversion processes mainly occur within the system, so that the functionality of phosphomolybdic acid can be fully exerted while avoiding the impact on the fiber structure.

[0047] The outermost fluorocarbon resin protective layer forms a dense protective film, which not only prevents the external environment from interfering with the functional layer, but also prevents the functional layer components from migrating outward. This multi-layer structure design ensures the stability of the entire system.

[0048] Under the above combined effects, the modified phosphomolybdic acid can maintain its excellent light-to-heat conversion properties without causing negative impact on the basic properties of textiles.

[0049] The heat conversion layer utilizes porous microstructure and phase change process. Graphene aerogel has a three-dimensional network structure with a pore size distribution of 50-200nm and a specific surface area of ​​up to 800m / g. The porous structure helps to store heat and reduce thermal conductivity. Phase change microcapsules (particle size 3-5μm) are evenly dispersed in the pores and regulate heat through phase change latent heat when the temperature changes. Carbon nanotubes (diameter 10-30nm) construct a thermal conductive network and optimize the heat transfer path.

[0050] The protective layer is made of fluorocarbon resin and modified silica to form a cross-linked network at the molecular level. 2 -and-CF 3 The groups provide hydrophobicity, and the nanoparticles (20-40nm) of modified silica are embedded in the network to enhance the mechanical strength. The cross-linking reaction tightly binds the two phases at the molecular scale to form a dense protective film.

[0051] The interface bonding between the functional layers is achieved by controlling the pH value and temperature to adjust the surface charge, optimize the interfacial tension, and ensure the firm bonding between the layers. At the same time, the porous structure and chemical groups of each layer achieve a gradient transition, avoiding the stress concentration that may be caused by the sudden interface.

[0052] In practical applications, the incident thermal radiation is first selectively reflected by the reflective control layer. The heat that is not reflected enters the heat conversion layer, where part of it is absorbed and stored by the phase change material, and the other part is transferred through the heat conduction network. The heat transfer path and kinetic behavior of the entire process are regulated by the microstructure, ultimately achieving excellent thermal management performance.

[0053] Another object of the present invention is to provide an intelligent production device for phosphomolybdic acid modification. The intelligent production device for phosphomolybdic acid modification can automatically detect relevant parameters such as pH, without the need for cumbersome timed measurements of pH and other parameters, and automatically adjust the system pH, thereby achieving the technical purpose of saving labor costs and improving parameter control effects.

[0054] Another object of the present invention is achieved by the following technical solutions:

[0055] A phosphomolybdic acid modified intelligent production equipment, comprising: a frame, on which a stirring barrel is fixedly arranged; a stirring shaft arranged in the middle of the stirring barrel, the stirring shaft is provided with blades, and one end of the stirring shaft is connected to a stirring motor; a fixed frame, fixedly connected to the top of the stirring barrel, and the stirring motor is slidably arranged in the fixed frame; a sliding plate arranged on the outer shell of the stirring motor, and a sliding groove arranged on the fixed frame and corresponding to the sliding plate; a driving cylinder, which is arranged on the top of the stirring motor and fixedly connected to the fixed frame through a plurality of fixing plates, and the output shaft of the driving cylinder is fixedly connected to the stirring motor; a pH adjusting device, comprising a water pump fixedly arranged on one side of the fixed frame, a liquid storage tank connected to the liquid inlet position of the water pump, a dilute sodium hydroxide solution in the liquid storage tank, and a liquid outlet pipe connected to the liquid outlet position of the water pump; a sliding switch, electrically connected to one side of the water pump; a sliding block, which is arranged on one side of the sliding switch and is used to adjust the operating power of the water pump; and an adjusting groove, which is arranged on the sliding switch and corresponds to the sliding block. One side of the sliding block is fixedly connected to the sliding plate. When the sliding plate moves up, it can simultaneously drive the sliding block to move up to adjust the operating power of the water pump. When the sliding block moves up, the operating power of the water pump increases, and the discharge rate of the dilute sodium hydroxide solution increases; when the sliding block moves down, the operating power of the water pump decreases, and the discharge rate of the dilute sodium hydroxide solution decreases.

[0056] The present invention is further configured to include an intelligent control system, which includes the following steps:

[0057] The parameter monitoring receiving and processing stage is used to monitor the pH value, temperature, redox potential and stirring speed in the mixing tank, and use the exponential weighted sliding average method to process the monitoring data; through control, it is used to perform adaptive control based on the processed data;

[0058] During the pH control stage, the proportional coefficient and the driving cylinder are used to control the inflow amount and inflow speed of the dilute sodium hydroxide.

[0059] In the risk assessment stage, fuzzy comprehensive evaluation method is used to conduct risk assessment;

[0060] The optimization learning phase is used for adaptive learning and adjustment of system parameters.

[0061] The present invention is further configured as follows: the monitoring data receiving and processing stage includes: basic parameter monitoring, through the formula ΔP=(P current -P target ) / P target ×100% calculation parameter deviation value; data preprocessing, using exponential weighted moving average method S t =α×X t +(1-α)S t-1and α=1-exp(-Δt / τ); adaptive control, using the formula u(t)=K p [e(t)+1 / T i ∫e(t)dt+T d (de / dt)]+ΣC ij (ΔP i ×ΔP j ).

[0062] The present invention is further configured as follows: the pH control stage includes: the sodium hydroxide solution addition amount calculation formula: NaOH_Addition=K×(pH target -pH current )×V; Dynamic response time calculation formula: Response_Time=t 0 ×exp(-|ΔpH| / 0.2).

[0063] The present invention is further configured as follows: the risk assessment stage adopts a fuzzy comprehensive evaluation method, including the formula R=Σ(w i ×μ i (x i )) and μ i (x i )=exp(-(x i -x i0 ) 2 / 2σ i 2 ); the standard deviation index σ=√(Σ(P i -P) 2 / n).

[0064] The present invention is further configured as follows: the optimization learning adjustment stage includes: online optimization formula: J=min{Σ[w 1 (ΔP) 2 +w 2 (ΔU) 2 +w 3 S 2 ]}; Self-learning formula: θ new =θ old +μ×X^T(Y-Xθ old ).

[0065] In summary, the present invention has the following beneficial effects:

[0066] The present invention provides a preparation process and equipment for a reflective heat-insulating textile fabric. Excellent heat-insulating performance is achieved through multi-layer structure design and process optimization, and the problem of adverse effects of phosphomolybdic acid on fabrics is solved. The light-heat conversion characteristics of phosphomolybdic acid are maintained by organic amine modification and amino polyvinyl alcohol coating; the reflection regulation layer forms a gradient refractive index interface to enhance the selective reflection of thermal radiation; the heat conversion layer uses porous microstructure, phase change regulation and heat conduction network to achieve efficient heat storage and transfer; the protective layer provides excellent protective performance through a molecular-level cross-linked network.

[0067] The intelligent production equipment for phosphomolybdic acid modification provided by the company realizes intelligent control of the production process through real-time monitoring and automatic regulation of key parameters such as pH value. The position adjustment of the stirring shaft is linked with the rate of adding reagents to improve the mixing efficiency; the multi-level early warning mechanism and adaptive algorithm ensure the stability of process parameters; and the self-learning optimization improves the control accuracy. The product quality and production efficiency have been significantly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 It is a structural schematic diagram of an intelligent production equipment for phosphomolybdic acid modification;

[0069] Figure 2 It is a side view structural schematic diagram of a phosphomolybdic acid modified intelligent production equipment;

[0070] Figure 3 This is a schematic diagram of the structure of a phosphomolybdic acid modified intelligent production equipment after the fixing frame is removed;

[0071] Figure 4 for Figure 3 A magnified view of area A;

[0072] Figure 5 is a structural schematic diagram of a slide switch;

[0073] Figure 6 This is the flow chart of the intelligent control system.

[0074] Figure numerals: 1. frame; 2. mixing drum; 3. discharge pipe; 4. mixing shaft; 5. mixing motor; 6. fixed frame; 7. sliding plate; 8. slide groove; 9. driving cylinder; 10. water pump; 11. liquid storage tank; 12. liquid discharge pipe; 13. sliding switch; 14. sliding block; 15. adjusting groove. DETAILED DESCRIPTION

[0075] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "page", "bottom", "inside", "outside", "clockwise", "counterclockwise" and the like indicating orientations or positional relationships are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0076] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features.

[0077] In the description of the present invention, "multiple" means two or more than two, unless otherwise clearly defined. In the present invention, unless otherwise clearly defined and defined, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be internal communication between two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances.

[0078] The present invention is further described in detail below in conjunction with the accompanying drawings.

[0079] A preparation process of a reflective heat-insulating textile fabric comprises the following steps:

[0080] (1) Phosphomolybdic acid modification:

[0081] Dissolve phosphomolybdic acid in deionized water to prepare a 5-8 wt% solution, and stir at 800 rpm for 15 minutes;

[0082] Add 3-5wt% organic amine compound dropwise at a rate of 2mL / min, and react at 40±1℃ for 2 hours under nitrogen protection and light protection;

[0083] The pH value was adjusted to 4.5-5.5 with a dilute NaOH solution and stirred at 800 rpm for 30 minutes. During this process, the pH value was monitored in real time and adjusted;

[0084] After stirring, let it stand for 30 minutes;

[0085] Add pre-swollen amino-modified polyvinyl alcohol, and stir at 35° C. for 1 hour to obtain a modified phosphomolybdic acid solution;

[0086] (2) Preparation of reflection control layer: pre-disperse nano-alumina and titanium dioxide, and ultrasonically treat for 30 minutes at a temperature of 15-20°C;

[0087] The modified phosphomolybdic acid solution is mixed with the pre-dispersed solution, and the modified graphene is added;

[0088] The conditions for pulsed ultrasound-microwave synergistic treatment are: ultrasound power 400W, ultrasound frequency 40kHz, microwave power 200W, pulse ratio 2s:1s, temperature 15-20°C, and treatment time 45 minutes;

[0089] Coating: coating amount 100g / m 2 , coating speed 2m / min, tension 15N, drying at 60℃ for 15 minutes;

[0090] (3) Preparation of heat conversion layer: The graphene aerogel was ultrasonically pre-dispersed for 45 minutes and a dispersant was added;

[0091] Phase change microcapsules were added at 25°C with a stirring speed of 500 rpm and stirred for 30 minutes;

[0092] Add carbon nanotubes pre-dispersed by 15 minutes of ultrasound;

[0093] Coating: coating amount 80g / m 2 , dry at 50℃ for 20 minutes;

[0094] (4) Preparation of protective layer: Dissolve the fluorocarbon resin and add modified silica, stir at 300 rpm for 10 minutes; add crosslinking agent; coating: coating amount 50 g / m 2 , dried at 80℃ for 10 minutes.

[0095] Design the following experiment:

[0096] 1. Experimental Design

[0097] This study designed 5 experimental groups (E1-E5) and 3 control groups (C1-C3). The experimental groups were compared by adjusting the ratio of each functional layer and process parameters, while the control groups used different traditional treatment methods.

[0098] Table 1 Experimental group formula design (by weight)

[0099]

[0100] Table 2 Treatment methods of the control group

[0101]

[0102] 2. Performance test results

[0103] (1) Thermal infrared reflectivity test results, tested after different times of water washing: Test standard: ASTM E903-12; Test instrument: Nicoleti S50 Fourier transform infrared spectrometer; Test conditions: Wavelength range: 4-14 μm, Scan times: 32 times, Resolution: 4 cm -1 , Test environment: 23±2℃, relative humidity 65±5%. Test 5 points for each sample and take the average value.

[0104] The results are as follows:

[0105] Table 3 Thermal infrared reflectivity test results (%)

[0106]

[0107] (2) Thermal conductivity test

[0108] Test standard: GB / T10295; Test instrument: DRE-2C thermal conductivity tester; Test conditions: Test temperature: 20±0.1℃, heat flux: 85±2W / m 2 , sample size: 30cm×30cm, applied pressure: 2kPa, each sample was tested 3 times and the average value was taken.

[0109] The test results are as follows:

[0110] Table 4 Thermal conductivity test results (W / m·K)

[0111]

[0112] (3) Comprehensive performance test, mainly including thermal stability test, photothermal conversion efficiency test, softness test, air permeability test and strength retention test.

[0113] The test conditions are as follows:

[0114] ① Thermal stability test: Test standard: ISO11357-6; Test instrument: TGAQ500 thermogravimetric analyzer; Test conditions: Atmosphere: air; Heating rate: 10℃ / min; Temperature range: 30-500℃; Sample mass: 10±0.2mg; Each sample was tested twice.

[0115] ② Photothermal conversion efficiency test: Test standard: ASTMG173-03; Test equipment: solar simulator (AM1.5), infrared thermal imager; Test conditions: Light intensity: 1000W / m 2 ; Irradiation time: 10 min; Sample size: 10 cm × 10 cm; Ambient temperature: 25 ± 2 ° C; Each sample was tested 3 times.

[0116] ③Softness test: Test standard: GB / T18318; Test instrument: YG821L digital fabric softness tester; Test conditions: Pressure: 2N; Test speed: 100mm / min; Sample size: 20cm×20cm; Test direction: 3 times each in warp and weft directions.

[0117] ④ Air permeability test: Test standard: GB / T5453; Test instrument: YG461E digital fabric air permeability tester; Test conditions: Test pressure difference: 100Pa; Test area: 20cm 2 ; Environmental conditions: 20±2℃, 65±5%RH; 5 points tested for each sample

[0118] ⑤Strength retention test: Test standard: GB / T3923.1; Test instrument: YG026 electronic fabric strength tester; Test conditions: Clamping distance: 200mm; Tensile speed: 100mm / min; Sample specification: 50mm×300mm; Test 5 times each in the warp and weft directions.

[0119] The test results are as follows:

[0120] Table 5 Comprehensive performance test results

[0121]

[0122] (3) Washability test: Test standard: GB / T8629-2017; Test conditions: Washing temperature: 40±2℃; Detergent: standard detergent WOB; Bath ratio: 1:30; Washing time: 45min / time; Dehydration: 3min; Hang to dry.

[0123] The test results are as follows:

[0124] Table 6 Washability test (after 50 standard washes)

[0125]

[0126] 3. Results Analysis

[0127] (1) Experimental groups E1-E5 all showed excellent thermal management performance, among which E1 formulation had the best effect, and all indicators met or exceeded the design requirements.

[0128] (2) Compared with the control group, the experimental group has significant advantages in the following aspects:

[0129] The thermal infrared reflectivity is greatly improved (>85%); the thermal conductivity is significantly reduced (>27%); the washability is excellent (performance retention rate is high after 50 washes); the basic properties of the fabric are maintained well.

[0130] (3) The influence of process parameters on product performance:

[0131] The best effect is achieved when the content of nano-alumina is in the range of 42-48 parts; the best effect is achieved when the content of phosphomolybdic acid is around 8 parts.

[0132] The preparation process of the above-mentioned reflective thermal insulation textile fabric achieves excellent thermal insulation performance through multi-layer structure design and process optimization. The core lies in solving the problem of adverse effects of phosphomolybdic acid on fabrics through organic amine modification and amino polyvinyl alcohol coating, while maintaining its unique light-to-heat conversion characteristics. Nano-alumina, titanium dioxide and modified graphene in the reflection regulation layer form a gradient refractive index interface, which synergizes with modified phosphomolybdic acid to significantly enhance the selective reflection of thermal radiation. The heat conversion layer utilizes the porous microstructure of graphene aerogel, the latent heat regulation of phase change microcapsules and the thermal conductive network of carbon nanotubes to achieve efficient storage and transfer of heat. The protective layer not only provides excellent protective performance through the molecular-level cross-linked network of fluorocarbon resin and modified silica, but also ensures the stability of the entire functional system. Multi-layer synergy combined with precise pH control and interface regulation successfully achieves the combination of reflective thermal insulation performance and basic fabric performance.

[0133] like Figure 1 As shown, the present application also provides an intelligent production equipment for phosphomolybdic acid modification, which is used for automating the modification process of phosphomolybdic acid. It mainly includes: a frame 1. A stirring barrel is fixedly arranged on the frame 1. A discharge pipe 3 is arranged at the bottom of the stirring barrel, and the opening and closing is controlled by a valve. A stirring shaft 4 with blades is arranged in the middle of the stirring barrel. A stirring motor 5 is connected to one end of the stirring shaft 4 passing through the stirring barrel. The stirring motor 5 is used to control the rotation speed of the stirring shaft 4.

[0134] A fixing frame 6 is provided outside the stirring motor 5. The fixing frame 6 is fixedly connected to the top of the stirring barrel. The stirring motor 5 is slidably arranged in the fixing frame 6. A sliding plate 7 is fixedly arranged on the outer shell of the stirring motor 5. Correspondingly, a sliding groove 8 corresponding to the sliding plate 7 is provided on the fixing frame 6. Through the cooperation of the sliding plate 7 and the sliding groove 8, the stirring motor 5 can move up and down in the longitudinal direction.

[0135] A driving cylinder 9 is connected to the top of the stirring motor 5. The driving cylinder 9 is fixedly connected to the fixing frame 6 through a plurality of fixing plates. The output shaft of the driving cylinder 9 is fixedly connected to the stirring motor 5. When the driving cylinder 9 works, it can drive the stirring motor 5 to move up and down in the longitudinal direction.

[0136] like Figure 2 , Figure 3As shown, in order to adjust the position of the stirring shaft 4 and the rate of feeding dilute sodium hydroxide when the pH value reaches different warning values. The present application is fixedly provided with a small water pump 10 on one side of the fixed frame 6. The liquid inlet position of the water pump 10 is connected to a liquid storage tank 11. The liquid storage tank 11 is filled with dilute sodium hydroxide solution. The liquid outlet position of the water pump 10 is connected to a liquid outlet pipe 12.

[0137] like Figure 3 , Figure 4 , Figure 5 As shown, a slide switch 13 is electrically connected to one side of the water pump 10. A slide block 14 is provided on one side of the slide switch 13 for adjusting the operating power of the water pump 10. The slide switch 13 is provided with an adjustment slot 15 corresponding to the slide block 14. When the slide block 14 slides in the slide switch 13, the operating power of the water pump 10 can be adjusted. When the slide block 14 moves upward, the power of the water pump 10 is enhanced, so that the rate at which the dilute sodium hydroxide solution enters the mixing barrel to adjust the pH increases. When the slide block 14 moves downward, the power of the water pump 10 decreases, and the rate at which the pH is adjusted decreases.

[0138] Correspondingly, one side of the sliding block 14 is fixedly connected to the sliding plate 7. When the sliding plate 7 moves upward, it can simultaneously drive the sliding block 14 to move upward. When the sliding block moves upward, the operating power of the water pump 10 is increased, and the output of the dilute sodium hydroxide solution is increased. At the same time, the stirring shaft 4 moves upward, so that the dilute sodium hydroxide solution entering the stirring barrel is quickly stirred by the upward stirring shaft 4, thereby enhancing the dispersion rate of the dilute sodium hydroxide solution, thereby quickly adjusting the pH value of the entire system.

[0139] The reason for adjusting pH is that when phosphomolybdic acid reacts with organic amines, the organic amines, as ligands, form coordination bonds with the Mo-O in the Keggin structure of phosphomolybdic acid, which releases H + ions. Although organic amines are alkaline in nature, the H released during the coordination process + This will cause the overall pH of the system to decrease. Therefore, it is necessary to add dilute sodium hydroxide solution to adjust the pH.

[0140] When dilute sodium hydroxide solution is added, due to the mutual solubility of dilute sodium hydroxide solution and phosphomolybdic acid system, dilute sodium hydroxide will spontaneously diffuse when added. Now the stirring shaft 4 is located at the upper position, and the dilute sodium hydroxide solution region just added can be quickly stirred, thereby enhancing the initial mixing efficiency of the solution. The mechanical force generated by stirring can not only break up the local high concentration region, but also form a downward eddy current, thereby promoting the mixing of the whole system. Meanwhile, the spontaneous diffusion effect generated by the solution concentration gradient and the natural convection driven by gravity can also coordinately promote the mixing process. Therefore, this upward movement of the stirring shaft 4 can effectively improve the dispersion rate of dilute sodium hydroxide in the system.

[0141] When the smart chip detects that the pH value rises above the warning value, the driving cylinder 9 drives the stirring motor 5 to move downward, so that the efficiency of the entry of the dilute sodium hydroxide solution decreases, and the stirring shaft 4 is reset to fully stir the lower part of the solution, so that the mixing and coordination reaction of the entire system continues.

[0142] like Figure 6 As shown, in order to better control the pH value, the intelligent control system corresponding to the intelligent chip described in this application realizes intelligent parameter monitoring and control of the phosphomolybdic acid system in the stirring barrel through the following algorithm.

[0143] Parameter control: limit the pH value between 4.5-5.5, and set the target value to 5.0; control the temperature within the range of 35-45℃; maintain the redox potential between -0.2V and 0.3V; and maintain the stirring speed within the range of 800-1200rpm. A multi-level early warning mechanism is adopted. When the parameter deviates from the target value by 10%, the first-level warning value is triggered, and when it deviates by 15%, the second-level warning value is triggered. When it deviates by 20%, the emergency shutdown procedure is initiated. When the pH value triggers the first-level warning value, the driving cylinder can drive the stirring motor to move upward, thereby allowing the dilute sodium hydroxide solution to enter the system. If the pH still drops further to the second-level warning value, the efficiency of the dilute sodium hydroxide solution entering the system will be accelerated.

[0144] The overall algorithm steps are as follows:

[0145] 1. Parameter monitoring reception and processing stage:

[0146] (1) Basic parameter monitoring

[0147] ΔP = (P current -P target ) / P target ×100%.

[0148] Where, P: general symbol for process parameters;

[0149] P current : Current measurement value;

[0150] P target : target setting value;

[0151] ΔP: parameter deviation value.

[0152] Through the above formula, basic parameters such as pH, temperature and other values ​​are monitored each time by setting corresponding sensors in the mixing tank. The deviation rate between the preset parameters is calculated through the above formula.

[0153] (2) Data preprocessing

[0154] The exponentially weighted moving average method is used, namely:

[0155] S t =α×X t +(1-α)S t-1 ;

[0156] α=1-exp(-Δt / τ).

[0157] Among them, S t : The smoothed value at the current time t (smoothed data);

[0158] X t : The actual observed value at the current time t;

[0159] S t-1 : The smoothed value at the previous moment t-1;

[0160] α: smoothing coefficient (weight), ranging from 0 to 1;

[0161] Δt: the time interval between two observations;

[0162] τ: time constant, used to control the degree of smoothing;

[0163] The larger the α is, the greater the weight of the new data is, and the weaker the smoothing effect is; the smaller the α is, the greater the weight of the historical data is, and the stronger the smoothing effect is. By adjusting the τ value, α can be indirectly controlled to adjust the smoothing effect. The above data smoothing is used to reduce the fluctuations caused by pH value measurement, temperature fluctuations, stirring speed fluctuations, etc.

[0164] (3) Adaptive control

[0165] u(t)=K p [e(t)+1 / T i ∫e(t)dt+T d (de / dt)]+ΣC ij (ΔP i ×ΔP j )

[0166] Where, u(t): control output;

[0167] K p : proportionality coefficient;

[0168] T i : integration time;

[0169] T d : Differentiation time;

[0170] e(t): error signal;

[0171] C ij : coupling coefficient;

[0172] ΔPi , ΔP j : Deviations of different parameters.

[0173] Through the above control algorithm formula, it is possible to process the monitoring data at different times to achieve precise control and anti-interference characteristics. Through the above control, it is used to control the temperature, stirring speed, pH adjustment system, and through ΔP i , ΔP j The compensation term brought about is used to overcome the mutual influence between parameters, such as the effect of temperature on pH.

[0174] 2. pH Control

[0175] When the pH value is lower than 5.0, the system calculates the amount of sodium hydroxide solution to be added according to the following algorithm:

[0176] NaOH_Addition=K×(pH target -pH current )×V

[0177] Where, K: proportionality coefficient

[0178] pH target : Target pH

[0179] pH current : Current pH value

[0180] V: volume of reaction system

[0181] Among them, the proportional coefficient K is adjusted by the sliding amplitude of the sliding block in the sliding switch, and the operating power of the water pump is controlled accordingly by adopting a graded adjustment rate, and then the amount of sodium hydroxide solution that needs to be added is accurately calculated according to the pH deviation to achieve accurate adjustment of the pH value.

[0182] At the same time, through the dynamic response time formula:

[0183] Response_Time=t 0 ×exp(-|ΔpH| / 0.2)

[0184] Among them, t 0 : Benchmark response time

[0185] ΔpH: pH deviation

[0186] According to the above response time formula, when the pH deviation increases, the response time is shortened and the adjustment speed is fast; when the pH deviation is small, the response time is prolonged. The adjustment speed is slow to ensure the stability during the adjustment process.

[0187] 3. Risk Assessment

[0188] Risk assessment adopts fuzzy comprehensive evaluation method, namely:

[0189] R=Σ(w i ×μ i (x i ));

[0190] μ i (x i )=exp(-(x i -x i0 ) 2 / 2σ i 2 ).

[0191] Among them, R: evaluation result

[0192] w i : Weight coefficient

[0193] μ i (x i ): Membership function: converts the specific parameter value into the membership of the fuzzy set for fuzzy evaluation results;

[0194] x i : Current value

[0195] x i0 : Standard value

[0196] σ i : Standard deviation

[0197] Through the above-mentioned fuzzy comprehensive evaluation method, the data monitored by multiple systems are converted into clear evaluation indicators, taking into account the risks of abnormal pH value and temperature exceeding the limit, that is, setting three-level warning values ​​and setting emergency shutdown conditions.

[0198] 4. Stability assessment

[0199] The system stability adopts the standard deviation indicator, namely:

[0200] σ=√(Σ(P i -P) 2 / n), the smaller the standard deviation value is, the higher the system stability is.

[0201] Among them, P i : Single measurement value

[0202] P: Average value

[0203] n: number of samples

[0204] The above formula can be used to determine the system operation status, pH value fluctuation, temperature stability, stirring speed stability, etc.

[0205] 5. Optimize learning adjustments

[0206] The overall system has self-learning capabilities, first through the online optimization formula:

[0207] J=min{Σ[w 1 (ΔP) 2 +w 2 (ΔU) 2 +w 3 S 2 ]}

[0208] Where J represents the objective function value to be minimized. ΔP represents the process parameter deviation, that is, the relative deviation between the actual value and the target value, such as (measured pH-target pH) / target pH. The square term ensures that both positive and negative deviations are corrected. ΔU is the change in control output, reflecting the change in the control output between two adjacent times. The square term is used to suppress the drastic fluctuations in the control action. S represents the energy consumption index, including energy consumption such as stirring power and heating power. w 1 、w 2 、w 3 are weight coefficients, corresponding to the importance of parameter control, control stability and energy consumption, and their sum is 1.

[0209] The optimization objectives of the above optimization formula are: minimize parameter deviation; minimize control output fluctuation; minimize energy consumption. System optimization is achieved under the conditions of satisfying parameter range and change rate constraints. Then through the self-learning formula:

[0210] θ new =θ old +μ×X^T(Y-Xθ old )

[0211] Among them, θ new : Updated parameters

[0212] θ old : Original parameters

[0213] μ: learning rate

[0214] X: Input matrix

[0215] Y: Actual output

[0216] X^T: transposed matrix of X.

[0217] The above formula is used to realize adaptive learning and adjustment of parameters to adapt to different process changes and thus improve control accuracy.

[0218] Through the synergistic effect of the above algorithms, it is ensured that phosphomolybdic acid always maintains the best conditions for modification, thereby improving product quality and production efficiency.

[0219] In order to better understand the phosphomolybdic acid detection module described in the present application, the specific control process is shown by example calculation:

[0220] Assume that the real-time monitoring data shows that the current pH is 4.2, which is significantly lower than the target value of 5.0. The system immediately calculates the deviation: (4.2-5.0) / 5.0×100%=-16%. This negative deviation exceeds the 15% threshold and triggers a secondary warning, indicating that the system needs a significant correction.

[0221] To reduce the impact of measurement fluctuations, the system uses exponential smoothing, and the smoothing coefficient α = 1-exp(-1 / 10) = 0.095. Substitute the current reading 4.2 and the last smoothed value 4.3 into the smoothing formula: 4.29 = 0.095 × 4.2 + (1-0.095) × 4.3. The smoothed value shows that the pH is indeed in a continuously low state.

[0222] Based on the current reaction volume of 100L and pH deviation of 0.8 units, the system calculates the amount of NaOH that needs to be added: 4L = 0.05 × (5.0-4.2) × 100. Considering the large pH deviation, the system calculates the dynamic response time of 1.098s = 60 × exp (-0.8 / 0.2). This short response time indicates the need for rapid intervention. At the same time, the system combines the temperature of 42°C (deviation of 5%) and ORP0.1V (deviation of 10%) for multi-parameter risk assessment.

[0223] Risk assessment uses fuzzy calculation method: pH membership 0≈exp(-(4.2-5.0) 2 / 2×0.1 2 ), temperature membership 0.135=exp(-(42-40) 2 / 2×1 2 ), membership degree 0.135=exp(-(0.1-0) 2 / 2×0.05 2 ). Considering the importance of pH to product quality, the weights are set to 0.4, 0.3, and 0.3, respectively, and the comprehensive risk score is 0.648=0.4×0.36+0.3×0.82+0.3×0.86. This score reflects that although the pH of the system is seriously deviated, other parameters are relatively stable.

[0224] The controller calculates the control output based on a pH error of 0.8: Proportional term 0.96 = 1.2 × 0.8 (K p =1.2), integral term 0.032t=1.2×(1 / 30)×∫0.8dt(T i =30s), since pH changes relatively slowly, the differential term is approximately 0. The objective function of the online optimization calculation of the system is J=0.5(0.16) 2+0.3(0.05) 2 +0.2(0.12) 2 =0.01643, which takes into account the pH deviation (16%), control output variation (5%) and energy consumption (0.12).

[0225] Based on the online optimization results, the system performs self-learning to update the parameters: θ new =1.2+0.1×0.8×(0.95-0.8×1.2)=1.1992. This new parameter reflects the system's adaptive adjustment to the current large deviation. 4L of NaOH solution was added in 4 times, 1L each time, and the effect was evaluated after waiting for 2.7 seconds after each addition. The system predicts that it will take about 10 minutes for the pH value to return to the normal range of 4.8-5.2 under the condition of maintaining a stirring speed of 850rpm.

[0226] During the entire adjustment process, the system continuously monitors the natural downward trend of temperature (expected to fall back to 40-41°C). Through multi-parameter coordinated control, pH deviation can be corrected without causing significant fluctuations in other parameters. This precise control based on real-time calculation can optimize energy consumption and improve production efficiency while ensuring product quality.

[0227] This specific embodiment is merely an explanation of the present invention and is not a limitation of the present invention. After reading this specification, those skilled in the art may make non-creative modifications to the present embodiment as needed. However, as long as they are within the scope of the claims of the present invention, they are protected by the patent law.

Claims

1. A process for preparing a reflective heat-insulating textile fabric, characterized in that: include: The reflective heat-insulating textile fabric comprises: a substrate layer, a reflective regulating layer, a heat conversion layer and a protective layer arranged in sequence from bottom to top; According to weight ratio, The reflection regulating layer is composed of: 45 parts of nano-alumina, 25 parts of titanium dioxide, 8 parts of phosphomolybdic acid, 3-5 parts of modified graphene, 0.5-1 parts of amino-modified polyvinyl alcohol, and the balance of deionized water; The composition of the heat conversion layer is: 20-30 parts of graphene aerogel, 15-25 parts of phase change microcapsules, 5-10 parts of carbon nanotubes, 2-3 parts of dispersant, 1-2 parts of cross-linking agent, and the balance of deionized water; The protective layer is composed of: 30-40 parts of fluorocarbon resin, 10-15 parts of modified silicon dioxide, 3-5 parts of cross-linking agent, and the balance of organic solvent; The preparation process of the reflective heat-insulating textile fabric also includes the following steps: Step 1: Phosphomolybdic acid modification: Dissolve phosphomolybdic acid in deionized water to prepare a 5-8 wt% solution, and stir at 800 rpm for 15 minutes; Add 3-5wt% organic amine compound dropwise at a rate of 2mL / min, and react at 40±1℃ for 2 hours under nitrogen protection and light protection; The pH value was adjusted to 4.5-5.5 with a dilute NaOH solution and stirred at 800 rpm for 30 minutes. During this process, the pH value was monitored in real time and adjusted; After stirring, let it stand for 30 minutes; Add pre-swollen amino-modified polyvinyl alcohol, and stir at 35° C. for 1 hour to obtain a modified phosphomolybdic acid solution; Step 2: Preparation of reflection control layer: pre-dispersing nano-alumina and titanium dioxide, adding modified graphene, and coating after ultrasonic-microwave synergistic treatment; Step 3: Preparation of heat conversion layer: After ultrasonic pre-dispersion of graphene aerogel, add dispersant, add phase change microcapsules and stir, then add ultrasonic pre-dispersed carbon nanotubes and apply; Step 4: Preparation of protective layer: Mix fluorocarbon resin and modified silica, stir, add cross-linking agent and then apply.

2. The process for preparing the reflective heat-insulating textile fabric according to claim 1, characterized in that: The steps of preparing the reflection regulating layer include: Pre-disperse nano-alumina and titanium dioxide, and perform ultrasonic treatment for 30 minutes at a temperature of 15-20°C; The modified phosphomolybdic acid solution is mixed with the pre-dispersed solution, and the modified graphene is added; The conditions for pulsed ultrasound-microwave synergistic treatment are: ultrasound power 400W, ultrasound frequency 40kHz, microwave power 200W, pulse ratio 2s:1s, temperature 15-20°C, and treatment time 45 minutes; Coating: coating amount 100g / m 2 , coating speed 2m / min, tension 15N, drying at 60℃ for 15 minutes.

3. The process for preparing the reflective heat-insulating textile fabric according to claim 1, characterized in that: The heat conversion layer preparation step comprises: The graphene aerogel was ultrasonically pre-dispersed for 45 min and a dispersant was added; Phase change microcapsules were added at 25°C with a stirring speed of 500 rpm and stirred for 30 minutes; Add carbon nanotubes pre-dispersed by 15 minutes of ultrasound; Coating: coating amount 80g / m 2 , dried at 50℃ for 20 minutes.

4. The process for preparing the reflective heat-insulating textile fabric according to claim 1, characterized in that: The protective layer preparation steps include: dissolving the fluorocarbon resin, adding modified silica, stirring at 300 rpm for 10 minutes; adding a crosslinking agent; coating: coating amount 50 g / m 2 , dried at 80℃ for 10 minutes.

5. A phosphomolybdic acid modified intelligent production equipment, characterized in that: The phosphomolybdic acid modification process according to any one of claims 1 to 4 comprises: A frame, on which a mixing barrel is fixedly arranged; A stirring shaft is arranged in the middle of the stirring barrel, the stirring shaft is provided with blades, and one end of the stirring shaft is connected to a stirring motor; A fixed frame, fixedly connected to the top of the mixing barrel, and the mixing motor is slidably arranged in the fixed frame; A sliding plate arranged on the stirring motor housing, and a sliding groove arranged on the fixing frame corresponding to the sliding plate; A driving cylinder is arranged on the top of the stirring motor and is fixedly connected to the fixing frame through a plurality of fixing plates, and an output shaft of the driving cylinder is fixedly connected to the stirring motor; The pH adjusting device comprises a water pump fixedly arranged on one side of the fixing frame, the liquid inlet position of the water pump is connected to a liquid storage tank, the liquid storage tank is filled with a dilute sodium hydroxide solution, and the liquid outlet position of the water pump is connected to a liquid outlet pipe; A slide switch electrically connected to one side of the water pump; a sliding block, arranged on one side of the sliding switch, for adjusting the operating power of the water pump; and an adjusting slot, arranged on the sliding switch and corresponding to the sliding block; One side of the sliding block is fixedly connected to the sliding plate, and when the sliding plate moves upward, it can simultaneously drive the sliding block to move upward to adjust the operating power of the water pump; When the sliding block moves upward, the operating power of the water pump increases, and the discharge rate of the dilute sodium hydroxide solution increases; when the sliding block moves downward, the operating power of the water pump decreases, and the discharge rate of the dilute sodium hydroxide solution decreases.

6. The phosphomolybdic acid modified intelligent production equipment according to claim 5, characterized in that: It also includes an intelligent control system, which includes the following steps: The parameter monitoring receiving and processing stage is used to monitor the pH value, temperature, redox potential and stirring speed in the mixing tank, and the monitoring data is processed using the exponentially weighted moving average method; Pass control, used to perform adaptive control based on processed data; In the pH control stage, the proportional coefficient and the driving cylinder are used to control the amount and speed of the diluted sodium hydroxide inlet; In the risk assessment stage, fuzzy comprehensive evaluation method is used to conduct risk assessment; The optimization learning phase is used for adaptive learning and adjustment of system parameters.

7. The phosphomolybdic acid modified intelligent production equipment according to claim 6, characterized in that: The parameter monitoring receiving and processing stage includes: basic parameter monitoring, through the formula ΔP= (P current -P target ) / P target ×100% calculation parameter deviation value; where P is the general symbol of process parameters; P current : Current measurement value; P target : target setting value; ΔP: parameter deviation value; Data preprocessing, using exponential weighted moving average method S t =α×X t +(1-α)S t-1 and α=1-exp(-Δt / τ); where S t : The smoothed value at the current time t (smoothed data); X t : The actual observed value at the current time t; S t-1 : The smoothing value at the last moment t-1; α: Smoothing coefficient (weight), ranging from 0 to 1; Δt: The time interval between two observations; τ: Time constant, used to control the degree of smoothing; Adaptive control, using the formula u(t)=K p [e(t)+1 / T i ∫e(t)dt+T d (de / dt)]+ΣC ij (ΔP i ×ΔP j ); Where, u(t): control output; K p : Proportional coefficient; T i : Integration time; T d : differential time; e(t): error signal; C ij : coupling coefficient; ΔP i , ΔP j : Deviations of different parameters.

8. The phosphomolybdic acid modified intelligent production equipment according to claim 6, characterized in that: The pH control stage includes: the sodium hydroxide solution addition amount calculation formula: NaOH_Addition=K×(pH target -pH current )×V; Where, K: proportionality coefficient; pH target : Target pH value; pH current : Current pH value; V: Volume of reaction system; Dynamic response time calculation formula: Response_Time=t0×exp(-|ΔpH| / 0.2); Wherein, t0: reference response time; ΔpH: pH value deviation.

9. The phosphomolybdic acid modified intelligent production equipment according to claim 6, characterized in that: The risk assessment stage includes the use of a fuzzy comprehensive evaluation method, the formula is R = Σ(w i ×μ i (x i )) and μ i (x i )=exp(-(x i -x i0 ) 2 / 2σ i 2 ); Where, R: evaluation result; w i : Weight coefficient; μ i (x i ): Membership function: converts the specific parameter value into the membership of the fuzzy set for fuzzy evaluation results; x i : Current value; x i0 : standard value; σ i : standard deviation; In the stability evaluation stage, the standard deviation index σ=√(Σ(P i -P) 2 / n); Among them, P i : single measurement value; P: mean value; n: sample size.

10. The phosphomolybdic acid modified intelligent production equipment according to claim 6, characterized in that: The optimization learning stage includes: online optimization formula: J=min{Σ[w1(ΔP) 2 +w2(ΔU) 2 +w3S 2 ]}; Among them, J represents the objective function value to be minimized; ΔP represents the process parameter deviation, that is, the relative deviation between the actual value and the target value, such as (measured pH-target pH) / target pH. The square term ensures that both positive and negative deviations are corrected; ΔU is the control output change, reflecting the change amplitude of two adjacent control outputs. The square term is used to suppress the drastic fluctuation of the control action; S represents the energy consumption index, including energy consumption such as stirring power and heating power; w1, w2, and w3 are weight coefficients, corresponding to the importance of parameter control, control stability, and energy consumption, respectively, and the sum of the three is 1; Self-learning formula: θ new =θ old +μ×X T (Y-Xθ old ); Among them, θ new : updated parameters; θ old : original parameters; μ: learning rate; X: input matrix; Y: actual output; X T : The transposed matrix of X.

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