Multi-layer continuous medium and low temperature drying method, system and device

Abstract

The invention relates to the technical field of material drying, in particular to a multi-layer continuous medium and low temperature drying method, system and device, which comprises the following steps: regulating and controlling the wavelength of a material to be dried, then placing the material on multiple layers of parallel heating plates which are spaced up and down, and forming a gradient temperature zone by the multiple layers of heating plates for adapting to a material drying curve; an IGBT power module based on a PLC fuzzy control algorithm optimizes infrared wavelength and power distribution; heat energy discharged from dried materials is recycled through a double-channel air supply and exhaust structure, and the problems that existing drying equipment is insufficient in temperature and humidity control precision, wavelength and thermal field distribution cannot be dynamically adjusted, and drying is uneven are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of material drying, and in particular to a multi-layer continuous medium- and low-temperature drying method, system and device. Background Art

[0002] Traditional hot air dryers (100-200°C) have high energy consumption (typically >30kW) and low thermal efficiency, and high temperatures can easily damage food's nutritional value and flavor. Air-source heat pump dryers offer lower energy consumption, but they are expensive, poorly adaptable to low-temperature environments, and difficult to achieve continuous production. While freeze-drying technology can preserve quality, it consumes extremely high energy (>200kW) and has a long processing cycle, making it suitable only for high-value-added products.

[0003] The temperature and humidity control accuracy of existing drying equipment is insufficient, and the wavelength and heat field distribution cannot be dynamically adjusted, resulting in uneven drying. Summary of the Invention

[0004] The purpose of the present invention is to provide a multi-layer continuous medium and low temperature drying method, system and device to solve the problem that the temperature and humidity control accuracy of existing drying equipment is insufficient, the wavelength and heat field distribution cannot be dynamically adjusted, and the drying process is uneven.

[0005] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0006] A multi-layer continuous medium-low temperature drying method comprises the following steps:

[0007] S1. The wavelength of the material to be dried is adjusted, and then the material is placed on multiple parallel heating plates spaced above and below. The multiple heating plates form a gradient temperature zone to adapt to the material drying curve;

[0008] S2, IGBT power module based on PLC fuzzy control algorithm to optimize infrared wavelength and power distribution;

[0009] S3. Recover the heat energy emitted from the drying materials through the dual-channel air supply and exhaust structure.

[0010] A further technical solution is that, in step S2, it also includes determining the optimal wavelength combination, that is, by analyzing the matching relationship between the material properties and the infrared radiation wavelength, specifically including the following steps:

[0011] S21. Analyze the spectral characteristics of the material, specifically by measuring the absorptivity, reflectivity, and transmittance of the material at different wavelengths using a near-infrared spectrometer, and establish a material spectral characteristics database;

[0012] S22. Based on the material spectral characteristic data, a model of the material's response to infrared radiation of different wavelengths is constructed:

[0013] E(λ)=α(λ)×P(λ), where E(λ) represents the effective energy absorbed by the material, α(λ) represents the absorption coefficient of the material at wavelength λ, and P(λ) represents the radiation power at wavelength λ;

[0014] S23. Optimize the wavelength combination by using a genetic algorithm or a particle swarm optimization algorithm to find the best combination among short-wave (0.76-2μm), medium-wave (2-4μm), and long-wave (4-1000μm) infrared radiation to maximize energy utilization efficiency:

[0015] maxη=∫E(λ)dλ / ∫P(λ)dλ, where η represents the energy utilization efficiency, the numerator is the total energy absorbed by the material, and the denominator is the total energy output by the heating system;

[0016] S24. Dynamic adjustment of wavelength: According to the real-time changes of material moisture content and thickness parameters, the system can dynamically adjust the wavelength combination to adapt to different working conditions.

[0017] A further technical solution is to also include an optimization algorithm for power distribution, which is intended to ensure uniform temperature distribution within the heating area and includes the following steps:

[0018] Step 1: Model the temperature field. Specifically, based on the finite element analysis method, a temperature field model of the heating area is established to predict the temperature distribution under different power allocation schemes. The formula is expressed as:

[0019] Where T represents temperature, t represents time, α represents thermal diffusion coefficient, q(x,y,z) represents the power density of the heat source at the spatial point (x,y,z), ρ represents density, and c represents specific heat capacity;

[0020] Step 2: uniformity evaluation index, specifically defining the temperature distribution uniformity index, which is reflected as the temperature standard deviation or maximum temperature difference: U = 1-(Tmax-Tmin) / Tavg, where U represents the uniformity index, Tmax, Tmin, and Tavg represent the maximum temperature, minimum temperature, and average temperature in the area, respectively;

[0021] Step 3: Multi-objective optimization solution: energy efficiency and temperature uniformity are used as optimization objectives, and a multi-objective optimization algorithm is used to solve the optimal power allocation solution;

[0022] minf(P)=w1(1-η)+w2(1-U), where f(P) is the comprehensive optimization objective function, P is the power allocation vector, and w1 and w2 are weight coefficients;

[0023] Step 4: Boundary constraint processing, considering the physical limitations and safety boundaries of the IGBT power module to ensure that the optimization results are within the practical feasible range:

[0024] Pmin≤P≤Pmax|dP / dt|≤ΔPmax, where Pmin and Pmax represent the lower and upper power limits, respectively, and ΔPmax represents the maximum allowable power change rate.

[0025] A multi-layer continuous medium and low temperature drying system comprises a signal input layer, a signal control layer, a signal execution layer and a monitoring layer.

[0026] A further technical solution is that the signal input layer includes a material moisture content sensor, a temperature sensor and a pressure sensor for detecting material drying.

[0027] A further technical solution is that the signal control layer includes a PLC fuzzy control algorithm module for receiving information from a material moisture content sensor, a temperature sensor and a pressure sensor, and a dynamic adjustment decision engine connected to the PLC fuzzy control algorithm module signal.

[0028] A further technical solution is that the signal execution layer includes an IGBT power module, heater control and motor speed regulation, all of which are connected to the dynamic adjustment decision engine signal.

[0029] A further technical solution is that the monitoring layer includes a real-time moisture content monitoring system and an alarm and safety protection module, wherein the PLC fuzzy control algorithm module, IGBT power module, motor speed regulation, and safety protection module are all electrically connected to the real-time moisture content monitoring system, and the IGBT power module, heater control, and motor speed regulation are all electrically connected to the safety protection module.

[0030] A multi-layer continuous medium- and low-temperature drying device includes a cabinet, a heating cavity is provided within the cabinet, and a plurality of glass-ceramic-based heating plates are arranged in an upper and lower interval within the heating cavity. The cabinet has a built-in PLC fuzzy control algorithm module for controlling the heating temperature of the glass-ceramic-based heating plates. A heat recovery system is provided on the top of the cabinet.

[0031] The heat energy recovery system includes: two support frames arranged on the top of the cabinet, the support frames are provided with a horizontally arranged cylindrical tube body, the tube body is provided with a plurality of heat exchange tubes distributed in a ring array, the tube body is provided with a fixing plate for fixing the plurality of heat exchange tubes, the fixing plate is fixedly connected to the inner wall of the tube body, the fixing plate is provided with a plurality of through holes for the heat exchange tubes to pass through, the left top of the tube body is provided with an exhaust gas outlet, the right lower end of the tube body is provided with an exhaust gas inlet, sealing covers are provided on both sides of the tube body, and chambers connected to the tube body are provided in the two sealing covers, both ends of the heat exchange tube are connected to the two chambers, and the two sealing covers arranged on the left and right are respectively provided with a water inlet pipe and a drain pipe.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] 1. Provide a medium and low temperature continuous drying equipment to reduce the risk of thermal damage through precise wavelength control.

[0034] 2. Integrate PLC fuzzy control algorithm and IGBT power module to dynamically match temperature, humidity and material properties to improve energy efficiency.

[0035] 3. Recover 50% of exhaust heat energy through the heat recovery system, reducing energy consumption to 1 / 3-1 / 20 of traditional equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 The figure is a schematic flow chart of a multi-layer continuous medium-low temperature drying method of the present invention.

[0037] Figure 2 This is a schematic flow chart of a multi-layer continuous medium and low temperature drying system of the present invention.

[0038] Figure 3 It is a structural schematic diagram of a multi-layer continuous medium and low temperature drying device in the present invention.

[0039] Figure 4 It is a structural schematic diagram of the heat energy recovery system in the present invention. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0041] Example:

[0042] refer to Figures 1 to 4 As shown, a multi-layer continuous medium and low temperature drying method is disclosed, comprising the following steps:

[0043] S1. The wavelength of the material to be dried is adjusted, and then the material is placed on multiple parallel heating plates spaced above and below. The multiple heating plates form a gradient temperature zone to adapt to the material drying curve;

[0044] S2, IGBT power module based on PLC fuzzy control algorithm to optimize infrared wavelength and power distribution;

[0045] S3. Recover the heat energy emitted from the drying materials through the dual-channel air supply and exhaust structure.

[0046] In step S2, the optimal wavelength combination is determined by analyzing the matching relationship between the material properties and the infrared radiation wavelength, which specifically includes the following steps:

[0047] S21. Analyze the spectral characteristics of the material, specifically by measuring the absorptivity, reflectivity, and transmittance of the material at different wavelengths using a near-infrared spectrometer, and establish a material spectral characteristics database;

[0048] S22. Based on the material spectral characteristic data, a model of the material's response to infrared radiation of different wavelengths is constructed:

[0049] E(λ)=α(λ)×P(λ), where E(λ) represents the effective energy absorbed by the material, α(λ) represents the absorption coefficient of the material at wavelength λ, and P(λ) represents the radiation power at wavelength λ;

[0050] S23. Optimize the wavelength combination by using a genetic algorithm or a particle swarm optimization algorithm to find the best combination among short-wave (0.76-2μm), medium-wave (2-4μm), and long-wave (4-1000μm) infrared radiation to maximize energy utilization efficiency:

[0051] maxη=∫E(λ)dλ / ∫P(λ)dλ, where η represents the energy utilization efficiency, the numerator is the total energy absorbed by the material, and the denominator is the total energy output by the heating system;

[0052] S24. Dynamic adjustment of wavelength: According to the real-time changes of material moisture content and thickness parameters, the system can dynamically adjust the wavelength combination to adapt to different working conditions.

[0053] It also includes an optimization algorithm for power distribution, which aims to ensure uniform temperature distribution within the heating area, including the following steps:

[0054] Step 1: Model the temperature field. Specifically, based on the finite element analysis method, a temperature field model of the heating area is established to predict the temperature distribution under different power allocation schemes. The formula is expressed as:

[0055] Where T represents temperature, t represents time, α represents thermal diffusion coefficient, q(x,y,z) represents the power density of the heat source at the spatial point (x,y,z), ρ represents density, and c represents specific heat capacity;

[0056] Step 2: uniformity evaluation index, specifically defining the temperature distribution uniformity index, which is reflected as the temperature standard deviation or maximum temperature difference: U = 1-(Tmax-Tmin) / Tavg, where U represents the uniformity index, Tmax, Tmin, and Tavg represent the maximum temperature, minimum temperature, and average temperature in the area, respectively;

[0057] Step 3: Multi-objective optimization solution: energy efficiency and temperature uniformity are used as optimization objectives, and a multi-objective optimization algorithm is used to solve the optimal power allocation solution;

[0058] minf(P)=w1(1-η)+w2(1-U), where f(P) is the comprehensive optimization objective function, P is the power allocation vector, and w1 and w2 are weight coefficients;

[0059] Step 4: Boundary constraint processing, considering the physical limitations and safety boundaries of the IGBT power module to ensure that the optimization results are within the practical feasible range:

[0060] Pmin≤P≤Pmax|dP / dt|≤ΔPmax, where Pmin and Pmax represent the lower and upper power limits, respectively, and ΔPmax represents the maximum allowable power change rate.

[0061] Example 2:

[0062] A multi-layer continuous medium and low temperature drying system is provided, comprising a signal input layer, a signal control layer, a signal execution layer and a monitoring layer.

[0063] Specifically, the signal input layer includes a material moisture content sensor, a temperature sensor, and a pressure sensor for detecting material drying.

[0064] The temperature sensor is a PT100 platinum resistance temperature sensor with a measurement range of -50°C to 800°C and an accuracy of ±0.5°C. Redundancy is used in key areas to ensure measurement reliability.

[0065] The material moisture content sensor uses a near-infrared reflective sensor to calculate the material moisture content by measuring the reflectivity of light of different wavelengths. The measurement range is 0 to 100% and the accuracy is ±1%.

[0066] At the same time, data integration and preprocessing also occur during the data collection process, including:

[0067] Time synchronization: All sensor data collection uses a unified time tag to ensure the temporal consistency of the data and facilitate subsequent correlation analysis.

[0068] Data preprocessing: The raw data undergoes preprocessing steps such as outlier detection, missing value processing, and noise filtering to improve data quality.

[0069] Feature extraction: The system automatically extracts key features from multi-source data, such as temperature uniformity index and humidity change trend, to provide high-level semantic information for fuzzy control.

[0070] Data caching mechanism: A double buffer design is used to ensure that data processing will not cause collection interruption or loss under high-speed data flow.

[0071] The signal control layer includes a PLC fuzzy control algorithm module for receiving information from a material moisture content sensor, a temperature sensor, and a pressure sensor, and a dynamic adjustment decision engine connected to the PLC fuzzy control algorithm module signal.

[0072] The signal execution layer includes an IGBT power module, heater control and motor speed regulation, all of which are connected to the dynamic adjustment decision engine signal. The motor here is an exhaust fan arranged in the cabinet.

[0073] The monitoring layer includes a real-time moisture content monitoring system and an alarm and safety protection module, wherein the PLC fuzzy control algorithm module, IGBT power module, motor speed regulation, and safety protection module are all electrically connected to the real-time moisture content monitoring system, and the IGBT power module, heater control, and motor speed regulation are all electrically connected to the safety protection module.

[0074] An intelligent control system that combines fuzzy control algorithms with a programmable logic controller (PLC) and implements dynamic power regulation using insulated-gate bipolar transistor (IGBT) power modules demonstrates significant application potential. By collecting key parameters such as temperature and humidity, belt speed, and material moisture content in real time and incorporating fuzzy logic control decisions, the system achieves precise control and optimization of the heating process.

[0075] Example 3:

[0076] A multi-layer continuous medium and low temperature drying device is provided, comprising a cabinet 1, wherein a heating cavity 2 is provided in the cabinet 1, wherein a plurality of microcrystalline glass-based heating plates 3 are provided in the heating cavity 2 and are arranged in an upper and lower interval, wherein the cabinet 1 has a built-in PLC fuzzy control algorithm module for controlling the heating temperature of the microcrystalline glass-based heating plates 3, wherein a heat recovery system is provided on the top of the cabinet 1: wherein the heat recovery system comprises: two support frames 4 provided on the top of the cabinet 1, wherein a horizontally arranged cylindrical tube body 5 is provided on the support frame 4, wherein a plurality of heat exchange tubes 6 distributed in an annular array are provided in the tube body 5, wherein a plurality of heat exchange tubes 6 ... A fixing plate 7 of the heat exchange tube 6 is fixedly connected to the inner wall of the tube body 5. The fixing plate 7 is provided with a plurality of through holes for the heat exchange tube 6 to pass through. The left top of the tube body 5 is provided with an exhaust gas outlet 8, and the right lower end of the tube body 5 is provided with an exhaust gas inlet 9. Both sides of the tube body 5 are provided with sealing covers 10, which are used to seal both sides of the tube body 5. The two sealing covers 10 are provided with a chamber connected to the tube body 5. Both ends of the heat exchange tube 6 are connected to the two chambers. The two sealing covers 10 arranged on the left and right are respectively provided with a water inlet pipe 11 and a drain pipe 12.

[0077] The material placed on the upper end of the microcrystalline glass-based heating plate 3 is heated, the temperature of different microcrystalline glass-based heating plates 3 is controlled by the PLC fuzzy control algorithm module, and the heat energy is recovered and utilized by the heat recovery system arranged at the top, thereby reducing the energy consumption of the device.

[0078] Specifically, high-temperature air is discharged into the pipe body 5 through the exhaust gas inlet 9, and comes into contact with the heat exchange tube 6 in the pipe body 5. The heat exchange tube 6 absorbs the heat energy of the exhaust gas. Liquid is provided in the heat exchange tube 6 to facilitate the absorption of heat from the heat exchange tube 6, and the hot water is discharged through the drain pipe 12, thereby realizing the recovery and utilization of heat energy.

[0079] Specifically, the exhaust gas inlet 9 is communicated with the heating cavity 2 .

[0080] Although the present invention has been described herein with reference to a number of illustrative embodiments thereof, it will be understood that numerous other modifications and implementations may be devised by those skilled in the art that fall within the scope and spirit of the principles disclosed herein. More specifically, within the scope of the present disclosure, the drawings, and the claims, numerous variations and modifications may be made to the components and / or layout of the subject combination arrangement. In addition to variations and modifications to the components and / or layout, other uses will also be apparent to those skilled in the art.

Claims

1. A multi-layer continuous medium and low temperature drying method, characterized in that: The following steps are involved: S1. The wavelength of the material to be dried is adjusted, and then the material is placed on multiple parallel heating plates spaced above and below. The multiple heating plates form a gradient temperature zone to adapt to the material drying curve; S2, IGBT power module based on PLC fuzzy control algorithm to optimize infrared wavelength and power distribution; S3. Recover the heat energy emitted from the drying materials through the dual-channel air supply and exhaust structure.

2. In step S2, the optimal wavelength combination is determined by analyzing the matching relationship between the material properties and the infrared radiation wavelength, which specifically includes the following steps: S21. Analyze the spectral characteristics of the material, specifically by measuring the absorptivity, reflectivity, and transmittance of the material at different wavelengths using a near-infrared spectrometer, and establish a material spectral characteristics database; S22. Based on the material spectral characteristic data, construct a model for the material's response to infrared radiation of different wavelengths: E(λ) = α(λ) × P(λ), where E(λ) represents the effective energy absorbed by the material, α(λ) represents the absorption coefficient of the material at wavelength λ, and P(λ) represents the radiation power at wavelength λ; S23. Optimize the wavelength combination, specifically by using a genetic algorithm or a particle swarm optimization algorithm to find the best combination among short-wave (0.76-2 μm), medium-wave (2-4 μm), and long-wave (4-1000 μm) infrared radiation to maximize energy utilization efficiency: maxη=∫E(λ)dλ / ∫P(λ)dλ, where η represents energy utilization efficiency, the numerator is the total energy absorbed by the material, and the denominator is the total energy output by the heating system; S24. Dynamic adjustment of wavelength: According to the real-time changes of material moisture content and thickness parameters, the system can dynamically adjust the wavelength combination to adapt to different working conditions.

3. The multi-layer continuous medium and low temperature drying method according to claim 2, characterized in that: It also includes an optimization algorithm for power distribution, which aims to ensure uniform temperature distribution within the heating area, including the following steps: Step 1: Model the temperature field. Specifically, based on the finite element analysis method, a temperature field model of the heating area is established to predict the temperature distribution under different power allocation schemes. The formula is expressed as: Where T represents temperature, t represents time, α represents thermal diffusion coefficient, q(x,y,z) represents the power density of the heat source at the spatial point (x,y,z), ρ represents density, and c represents specific heat capacity; Step 2: uniformity evaluation index, specifically defining the temperature distribution uniformity index, which is reflected as the temperature standard deviation or maximum temperature difference: U = 1-(Tmax-Tmin) / Tavg, where U represents the uniformity index, Tmax, Tmin, and Tavg represent the maximum temperature, minimum temperature, and average temperature in the area, respectively; Step 3: Multi-objective optimization solution: energy efficiency and temperature uniformity are used as optimization objectives, and a multi-objective optimization algorithm is used to solve the optimal power allocation solution; minf(P)=w1(1-η)+w2(1-U), where f(P) is the comprehensive optimization objective function, P is the power allocation vector, and w1 and w2 are weight coefficients; Step 4: Boundary constraint processing, considering the physical limitations and safety boundaries of the IGBT power module to ensure that the optimization results are within the practical feasible range: Pmin≤P≤Pmax|dP / dt|≤ΔPmax, where Pmin and Pmax represent the lower and upper power limits, respectively, and ΔPmax represents the maximum allowable power change rate.

4. A multi-layer continuous medium and low temperature drying system, characterized by: It includes signal input layer, signal control layer, signal execution layer and monitoring layer.

5. The multi-layer continuous medium and low temperature drying system according to claim 4, characterized in that: The signal input layer includes a material moisture content sensor, a temperature sensor and a pressure sensor for detecting material drying.

6. The multi-layer continuous medium and low temperature drying system according to claim 5, characterized in that: The signal control layer includes a PLC fuzzy control algorithm module for receiving information from a material moisture content sensor, a temperature sensor, and a pressure sensor, and a dynamic adjustment decision engine connected to the PLC fuzzy control algorithm module signal.

7. The multi-layer continuous medium and low temperature drying system according to claim 6, characterized in that: The signal execution layer includes an IGBT power module, heater control and motor speed regulation, all of which are connected to the dynamic adjustment decision engine signal.

8. The multi-layer continuous medium and low temperature drying system according to claim 7, characterized in that: The monitoring layer includes a real-time moisture content monitoring system and an alarm and safety protection module, wherein the PLC fuzzy control algorithm module, IGBT power module, motor speed regulation, and safety protection module are all electrically connected to the real-time moisture content monitoring system, and the IGBT power module, heater control, and motor speed regulation are all electrically connected to the safety protection module.

9. A multi-layer continuous medium and low temperature drying device, characterized by: The device is used to implement the steps of a multi-layer continuous medium-low temperature drying method according to any one of claims 1 to 3, comprising a cabinet, a heating cavity provided in the cabinet, a plurality of glass-ceramic-based heating plates spaced apart from each other in an upper and lower direction, a PLC fuzzy control algorithm module built into the cabinet for controlling the heating temperature of the glass-ceramic-based heating plates, and a heat recovery system provided on the top of the cabinet: The heat energy recovery system includes: two support frames arranged on the top of the cabinet, the support frames are provided with a horizontally arranged cylindrical tube body, the tube body is provided with a plurality of heat exchange tubes distributed in a ring array, the tube body is provided with a fixing plate for fixing the plurality of heat exchange tubes, the fixing plate is fixedly connected to the inner wall of the tube body, the fixing plate is provided with a plurality of through holes for the heat exchange tubes to pass through, the left top of the tube body is provided with an exhaust gas outlet, the right lower end of the tube body is provided with an exhaust gas inlet, sealing covers are provided on both sides of the tube body, and chambers connected to the tube body are provided in the two sealing covers, both ends of the heat exchange tube are connected to the two chambers, and the two sealing covers arranged on the left and right are respectively provided with a water inlet pipe and a drain pipe.

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