A method and system for air humidification based on a food packaging printing plant

Abstract

The application provides an air humidification method and system based on a food packaging printing workshop, and relates to the technical field of industrial environment control.The system comprises a humidity sensing module, an intelligent controller, a multi-mode humidification device and a waste heat recovery system.The air humidification method based on the food packaging printing workshop comprises real-time data acquisition, humidification demand calculation and dynamic mode switching: when the humidity deviation is greater than 5% RH, the high-pressure micro-fog is started;when the humidity deviation is less than or equal to 5% RH, the ultrasonic atomization and waste heat recovery are switched;the humidification water is preheated by using the waste heat of the printing machine to reduce the energy consumption.The application realizes the dynamic regulation and control of the workshop humidity to 55±2% RH by combining the distributed humidity sensor with the intelligent fuzzy control algorithm, and the response time is only 8 seconds, which is shorter than that of the traditional system.Experimental data show that the overprint error is reduced from 0.15 mm to 0.08 mm, the ink adhesion is improved, the scrap rate is reduced from 0.7% to 0.3%, and the good product rate and the color restoration degree of the food packaging printing are significantly improved.

Description

Technical Field

[0001] This invention belongs to the field of industrial environmental control technology, and more specifically, relates to an air humidification method and system for food packaging and printing workshops. Background Technology

[0002] Air humidity control in food packaging printing workshops is a crucial step in ensuring printing quality. The core objective is to maintain a stable temperature and humidity environment to ensure that paper properties, ink drying speed, and color reproduction meet process requirements. According to the industry standard "Lithographic Printing" (GB / T17934.2-2003), the humidity in the printing workshop must be strictly controlled at 50%-60% RH and the temperature at 22±2℃. However, in actual production environments, multiple dynamic interference factors exist: the continuous release of high temperatures (120-180℃) from the printing press oven causes a sudden drop in local humidity; different printing speeds (0-150m / min) have significantly different requirements for moisture evaporation; and paper weight (80-300g / m³) varies. 2 The diversity of fiber structures further increases the difficulty of humidity control.

[0003] Traditional humidification technologies primarily rely on high-pressure micro-mist or ultrasonic atomization equipment, but these solutions have fundamental flaws. High-pressure micro-mist systems atomize water using mechanical pressure, rapidly increasing air humidity, but lack precise environmental sensing capabilities, easily leading to over-humidification or localized excessive humidity, causing problems such as paper deformation and ink adhesion. Ultrasonic atomization generates tiny droplets through high-frequency vibration, offering better humidification uniformity, but it is extremely sensitive to water quality; high calcium and magnesium ion content can easily cause scaling on the transducer surface, leading to frequent equipment malfunctions. More importantly, both systems employ open-loop control, unable to dynamically adjust based on workshop temperature and humidity, printing press operating status, and paper characteristics. Response times generally exceed 20 seconds, with humidity fluctuations reaching ±5% RH, making it difficult to meet the demands of modern high-speed, high-precision printing.

[0004] The limitations of existing technologies have led to a series of serious problems in production practice:

[0005] Unstable printing quality: Fluctuations in humidity cause changes in paper moisture content, leading to fiber expansion or contraction and resulting in registration errors. Actual test data from one company showed that the registration error under a traditional system reached as high as 0.15mm, exceeding the standard requirement (≤0.1mm) by 50%. Simultaneously, electrostatic adsorption is significant in low-humidity environments, increasing dust adhesion to the printed surface and resulting in a scrap rate as high as 0.7%.

[0006] High energy consumption and maintenance costs: Traditional systems typically operate independently without integration with the workshop waste heat recovery system. Humidification water needs to be heated from room temperature to operating temperature, resulting in persistently high energy consumption. For example, a 1000m³... 2Taking the workshop as an example, the annual electricity cost for humidification exceeds 180,000 yuan. In addition, the equipment requires frequent maintenance, with manual cleaning needed on average every two weeks to remove scale, and the cost of each maintenance exceeds 2,000 yuan.

[0007] The environmental pressure is enormous: traditional systems use tap water directly for humidification, and the minerals in the water form aerosol particles during atomization, which not only pollute the workshop air but may also migrate to the surface of food packaging, posing a food safety hazard. At the same time, unrecovered waste heat is directly emitted, exacerbating carbon emissions.

[0008] With national requirements for energy conservation and emission reduction in the printing industry (a 18% reduction in energy consumption per unit of industrial added value and a 15% reduction in water consumption), and consumers' increasing demands for the appearance and safety of food packaging, traditional humidification methods are no longer adequate to meet the needs of industrial upgrading. This invention addresses these pain points by constructing a closed-loop system of intelligent sensing, multi-mode collaboration, and waste heat recovery. This achieves humidity control accuracy of ±2%RH and reduces response time to 8 seconds. Furthermore, through RO reverse osmosis water purification technology and a waste heat recovery system, energy consumption is reduced by 35%, and the maintenance cycle is extended to 2 months. This comprehensively solves the core problems of traditional systems, such as slow response, high energy consumption, and frequent maintenance, providing an innovative solution for the green and intelligent transformation of the food packaging printing industry. Summary of the Invention

[0009] To address the aforementioned technical problems, this invention provides an air humidification method and system for food packaging printing workshops.

[0010] An air humidification system for a food packaging printing workshop includes:

[0011] Humidity sensing module: Distributed humidity sensors (accuracy ±1.5%RH), with adjacent sensor spacing ≤10 meters and distance from the printing press ≤3 meters, and data acquisition frequency ≥1 time / second;

[0012] Intelligent controller: Built-in fuzzy control algorithm, calculates humidification amount according to formula u=f(e,de / dt,v), where e is humidity deviation, de / dt is humidity change rate, v is printing speed (0-150m / min), response time ≤8 seconds;

[0013] Multi-mode humidification device: includes an ultrasonic atomization unit (particle size ≤ 5μm, humidification capacity 15kg / h·m). 2 The system includes a high-pressure micro-mist unit (particle size 10-50μm), and a mode switching mechanism is implemented when the humidity deviation is greater than 5%RH via a solenoid valve.

[0014] Waste heat recovery system: The heat pipe heat exchanger transfers the heat from the 120-180℃ printing press exhaust gas to the humidifying water, raising the water temperature to 40-50℃, with an energy saving rate of ≥35%.

[0015] Preferably, the membership function of the fuzzy control algorithm meets the GB / T10739-2002 standard, the control accuracy reaches ±2%RH, and the output parameters include the number of humidifiers turned on (n) and the operating power (P), calculated using the following formula:

[0016] Where k is a coefficient (0.8-1.2).

[0017] Preferably, the ultrasonic atomizing unit is equipped with a 1.7MHz high-frequency transducer with an automatic water level compensation accuracy of ±5mm.

[0018] Preferably, the heat pipe heat exchanger of the waste heat recovery system has a thermal conductivity ≥1000W / m·K, a heat exchange efficiency η ≥85%, and the energy saving calculation formula is: Q=Q heat ·(T ambient -T water )·η, where Q heat The waste gas heat flow rate (12000 kJ / h), T ambient =25℃, T water =40℃.

[0019] Preferred options also include:

[0020] Automatic cleaning module: pulse backflush pressure 0.6MPa, pulse width 0.1 seconds, interval 5 seconds, monthly injection of 3% citric acid solution for descaling;

[0021] Water quality monitoring module: Real-time monitoring of conductivity 50-500μS / cm, switching to RO reverse osmosis water purification (conductivity ≤10μS / cm) when the standard is exceeded.

[0022] Preferably, when linked with an air conditioning system, the fresh air volume is automatically adjusted to 500-2000 m³ / h when the humidity deviation is greater than 3% RH. 3 / h, the temperature and humidity coordinated control accuracy reaches T=22±2℃、RH=55±2%.

[0023] Another technical problem to be solved by the present invention is to provide an air humidification method based on a food packaging printing workshop, comprising:

[0024] Real-time data acquisition: Humidity (accuracy ±1.5%RH), printing speed (0-150m / min), and paper weight (80-300g / m²) are measured. 2 Sampling frequency ≥ 1 time / second;

[0025] Humidification demand calculation: The target humidification amount is generated through a fuzzy control algorithm. The input parameters include humidity deviation e, rate of change de / dt, and printing speed v.

[0026] Dynamic mode switching: High-pressure micro-mist is activated when |e|>5%RH, and ultrasonic atomization is switched when |e|≤5%RH;

[0027] Waste heat recovery: Utilizing waste heat to raise the humidification water temperature to 40-50℃, with an energy saving rate based on... calculate.

[0028] Preferably, the relationship between the output power P of the fuzzy control algorithm and the humidity deviation e satisfies:

[0029]

[0030] Where P max This represents the maximum power of the device.

[0031] Preferably, predictive maintenance is also included:

[0032] Vibration sensors (accuracy ±0.1g) monitor equipment status; the health index HI = ∑(A i / A ref ) 2 A i Let A be the vibration amplitude. ref Baseline value;

[0033] LSTM neural networks predict faults based on 24-hour historical data, providing early warnings up to 48 hours in advance with an accuracy of ≥92%.

[0034] Preferably, the humidification device has a response time of ≤8 seconds, which stabilizes the workshop humidity at 55±2%RH, reduces the overprinting error from 0.15mm to ≤0.08mm, and reduces the scrap rate from 0.7% to ≤0.3%.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] This invention combines a distributed humidity sensor (accuracy ±1.5%RH) with an intelligent fuzzy control algorithm to dynamically regulate workshop humidity to 55±2%RH with a response time of only 8 seconds, a 68% reduction compared to traditional systems. Experimental data shows that the registration error decreased from 0.15mm to 0.08mm, ink adhesion improved by 41% (reaching level 4.5 / 5), and the scrap rate decreased from 0.7% to 0.3%, significantly improving the yield and color reproduction of food packaging printing.

[0037] In this invention, the intelligent switching between ultrasonic atomization (particle size ≤ 5 μm) and high-pressure micro-mist (particle size 10-50 μm) enables a humidification efficiency of 15 kg / h·m 2 This represents a 40% improvement over a single-mode system. The system can adjust printing speed (0-150m / min) and paper weight (80-300g / m²) according to different printing speeds. 2The system automatically adjusts its strategy to quickly replenish moisture during high-speed printing (reaching the target humidity within 5 minutes) and maintain long-lasting humidification during low-speed printing (with an effect time of ≥2 hours), balancing efficiency and energy consumption.

[0038] This invention integrates a waste heat recovery system for printing presses, utilizing 120-180℃ waste gas to preheat humidified water, raising the water temperature to 40-50℃, achieving an energy saving rate of 35% and annual electricity cost savings of approximately 180,000 yuan. The automatic cleaning module (pulse backflushing + citric acid descaling) extends the pipeline maintenance cycle from 2 weeks to 2 months, reducing scale formation by 92%. The predictive maintenance system uses an LSTM neural network to provide 48-hour advance warnings of equipment failures (such as transducer scaling), reducing downtime losses by over 60%.

[0039] This invention employs RO reverse osmosis water purification (conductivity ≤10μS / cm) and ion exchange technology to ensure that the humidified water quality meets the GB5749-2022 standard and avoids scale formation. Waste heat recovery reduces carbon emissions by 30% and saves 12,000 tons of water annually (compared to traditional systems). The system is linked with air conditioning and fresh air systems, and coordinated temperature and humidity control further reduces workshop energy consumption by 15%, fully meeting the green production requirements of the food packaging industry.

[0040] In this invention, real-time monitoring of workshop humidity and equipment status is achieved through 5G communication and a cloud platform, reducing the number of maintenance personnel per workshop from 8 to 2. Fuzzy control algorithms dynamically optimize humidification strategies, reducing humidification costs to 0.12 yuan / m². 3 (40% lower than traditional systems). After large-scale deployment, the annual comprehensive income of a 1,000-square-meter workshop increases by more than 200,000 yuan, with an investment payback period of only 2.3 years. Attached Figure Description

[0041] Figure 1 This is a schematic diagram of the humidification principle of the present invention;

[0042] Figure 2 This is a schematic diagram of the system structure in this invention;

[0043] Figure 3 This is a schematic diagram of the multi-mode humidification device in this invention;

[0044] Figure 4 This is a schematic diagram illustrating the linkage between the system and the workshop air conditioning system in this invention;

[0045] Figure 5 This is a schematic diagram of the humidity sensing module in this invention;

[0046] Figure 6 This is a schematic diagram of the intelligent controller in this invention;

[0047] Figure 7 This is a complete structural diagram of the system in this invention;

[0048] Figure 8 This is a schematic diagram of the fuzzy control algorithm in this invention;

[0049] Figure 9 This is a schematic diagram of the predictive maintenance function of the system in this invention;

[0050] Figure 10 This is a schematic diagram of the humidification method in this invention. Detailed Implementation

[0051] The embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and should not be construed as limiting the scope of the invention.

[0052] Please see Figures 1-10 This invention provides an air humidification method and system for food packaging printing workshops.

[0053] I. Device Implementation Examples

[0054] Example 1: Construction of Humidity Sensing Module:

[0055] 1.1 Sensor Deployment Scheme:

[0056]

[0057] 1.2 Data Acquisition System:

[0058] Transmission protocol: Modbus RTUover RS-485, supporting multi-node networking;

[0059] Data storage: Local cache of SQLite database + cloud backup (AWSS3);

[0060] Anomaly Handling: When a single sensor fails, the system automatically switches to the average value of the three nearest sensors.

[0061] Example 2: Intelligent Controller Design:

[0062] 2.1 Hardware Configuration:

[0063]

[0064] 2.2 Software System:

[0065] Fuzzy control algorithm:

[0066] The Python code is as follows:

[0067]

[0068] Parameter adaptive: Based on paper type (80-300g / m²) 2Automatically adjust the membership function.

[0069] Example 3: Multi-mode humidification device:

[0070] 3.1 Ultrasonic atomizing unit:

[0071]

[0072] 3.2 High-pressure micro-mist unit:

[0073] Piston pump: UDOR (Italy), pressure 7MPa, flow rate 30L / h;

[0074] Nozzle: SprayingSystems 1 / 8NPT (USA), particle size 10-50μm; Pipe material: PE-RTI Type I, pressure resistant 10MPa, temperature resistant -40~70℃.

[0075] Example 4: Waste Heat Recovery System

[0076] 4.1 Heat pipe heat exchanger design:

[0077]

[0078] Example 5: Automatic Cleaning and Water Quality Assurance:

[0079] 5.1 Pulse Backflush System:

[0080] Compressed air source: 0.6MPa, pulse width 0.1 seconds, interval 5 seconds;

[0081] Cleaning frequency: Automatically runs once every 4 hours, lasting 3 minutes;

[0082] Scale removal: Inject a 3% citric acid solution and circulate for 30 minutes monthly.

[0083] 5.2 Water Treatment Module:

[0084]

[0085] II. Method Implementation Examples:

[0086] Example 6: Intelligent Humidification Control Process:

[0087] 6.1 Data Acquisition Phase:

[0088] Real-time data:

[0089] Humidity sensor: Collects data once per second, averaging over 30 seconds;

[0090] Printing press parameters: Speed ​​(0-150m / min) and oven temperature (120-180℃) are obtained via OPCUA protocol;

[0091] Paper characteristics: Input the basis weight (80-300g / m²) via barcode scanner. 2 ), moisture content (4-8%).

[0092] Data preprocessing:

[0093] Outlier detection: Removing outlier data based on the 3σ principle;

[0094] Interpolation compensation: When the sensor fails, Kriging interpolation is used to generate alternative data. 6.2 Humidification strategy generation:

[0095] Fuzzy control algorithm:

[0096] Input variables:

[0097] Humidity deviation (e = current RH - 55%);

[0098] Humidity change rate (de / dt);

[0099] Printing speed (v).

[0100] Output variables: number of humidifiers turned on (n) and operating power (P).

[0101] See mode switching logic Figure 1 .

[0102] 6.3 Waste heat recovery and utilization:

[0103] Waste heat recovery process:

[0104] The exhaust gas from the printing press is preheated and humidified by a heat pipe heat exchanger;

[0105] When the water temperature reaches 50℃, turn off the electric heating and maintain the temperature using only residual heat.

[0106] Energy saving calculation:

[0107] Energy saving = Q_heat × (T_ambient - T_water) × η.

[0108] in:

[0109] Q_heat = exhaust gas flow rate × specific heat capacity (experimental value: 12000kJ / h);

[0110] T_ambient = 25℃ (ambient temperature);

[0111] T_water = 40℃ (preheating target);

[0112] η = 0.85 (heat exchange efficiency).

[0113] Example 7: Predictive Maintenance System

[0114] 7.1 Equipment status monitoring:

[0115] Vibration monitoring:

[0116] Accelerometer: PCB356A16, frequency range 0.5-10kHz.

[0117] Health Index Calculation:

[0118] HI = Σ(A_i / A_ref)^2;

[0119] Where A_i is the amplitude of each frequency component, and A_ref is the baseline value.

[0120] Temperature monitoring:

[0121] Platinum resistance thermometer PT100, accuracy ±0.1℃;

[0122] Transducer scaling warning threshold: temperature rise rate > 2℃ / hour.

[0123] 7.2 Fault Prediction Model:

[0124] LSTM Neural Network:

[0125] Input layer: Vibration, temperature, and runtime over the past 24 hours;

[0126] Hidden layers: 2 layers, 128 neurons per layer;

[0127] Output layer: Failure probability (0-100%);

[0128] Training data: 5,000 sets of historical fault data (including transducer scaling, water pump blockage, etc.).

[0129] III. Experimental Verification

[0130] Experiment Example 1: Humidification Performance Test

[0131] 1.1 Test conditions:

[0132] Workshop area: 1000m² 2 Printing speed 100m / min, paper weight 157g / m² 2 Initial humidity: 40% RH, target humidity: 55% RH.

[0133] 1.2 Test Results:

[0134]

[0135] Conclusion: The system response speed was improved by 68%, and energy consumption was reduced by 33%.

[0136] Experiment Example 2: Improvement of Printing Quality

[0137] 2.1 Test metrics:

[0138]

[0139] 2.2 Test conditions:

[0140] Printed materials: food packaging boxes, four-color offset printing;

[0141] Ambient temperature and humidity: 22±2℃, 55±2%RH.

[0142] Conclusion: Registration error was reduced by 47%, and scrap rate decreased by 57%.

[0143] Experimental Example 3: Waste Heat Recovery Efficiency:

[0144] 3.1 Test Data:

[0145]

[0146] Conclusion: Annual electricity cost savings of approximately 180,000 yuan (based on 16 hours of operation per day). IV. Comparative Example:

[0147] Comparative Example 1: Comparison with traditional humidification systems:

[0148]

[0149] Comparative Example 2: Energy Saving Benefit Analysis:

[0150]

[0151] V. Mass Production Example:

[0152] 5.1 Parameters for large-scale deployment:

[0153]

[0154] 5.2 Implementation Results:

[0155] Investment payback period: 2.3 years (based on annual savings of 140,000 yuan);

[0156] Management efficiency: The number of maintenance personnel has been reduced from 8 to 2;

[0157] Fault Response: Automatic failover time for the system is ≤10 seconds.

[0158] Through the above embodiments and experiments, the present invention achieves breakthrough progress in the following dimensions:

[0159] Humidification efficiency: 8-second response time, humidity uniformity ±2%RH, 60% higher than traditional systems;

[0160] Printing quality: Registration error 0.08mm, scrap rate 0.3%, meeting ISO12647-2:2013 standard; Energy saving and consumption reduction: Waste heat recovery energy saving rate 35%, annual cost saving of 140,000 yuan;

[0161] Reliability: Maintenance cycle extended to 2 months, fault prediction accuracy rate 92%;

[0162] Environmentally friendly: Using RO reverse osmosis water purification reduces scale formation by 92%, meeting the GB5749-2022 drinking water standard.

[0163] This invention reshapes the technological paradigm of air humidification in printing workshops through a three-dimensional innovative architecture of "intelligent sensing, multi-mode collaboration, and waste heat recovery".

[0164] Precise dynamic control:

[0165] A distributed humidity sensor network (spacing ≤ 10 meters) combined with a fuzzy control algorithm enables precise control of workshop humidity within ±2% RH, with a response time of only 8 seconds, representing a 68% improvement over traditional systems.

[0166] The multi-mode humidification switching strategy (ultrasonic + high-pressure micro-mist) adapts to different printing conditions, achieving a humidification efficiency of 15 kg / h·m 2 This represents a 40% improvement over the single-mode approach.

[0167] Efficient use of energy and resources:

[0168] The waste heat recovery system uses waste heat from the printing press to preheat the humidifying water, achieving an energy saving rate of 35%, saving 180,000 yuan in electricity costs annually for a 1,000-square-meter workshop.

[0169] RO reverse osmosis water purification technology enables humidified water quality to meet the GB5749-2022 standard, saving 12,000 tons of water annually and reducing scale formation by 92%.

[0170] Intelligent operation and maintenance system:

[0171] The predictive maintenance system uses an LSTM neural network to provide early warnings of equipment failures up to 48 hours in advance, extending the maintenance cycle from 2 weeks to 2 months and reducing operation and maintenance costs by 75%.

[0172] The 5G+cloud management platform enables real-time monitoring of equipment status, reducing the number of maintenance personnel in a single workshop from 8 to 2, and improving management efficiency by 75%.

[0173] This invention successfully solves the industry challenge of humidity control in food packaging printing workshops through a closed-loop system of "precise perception - intelligent decision-making - efficient execution." Its technological innovation not only improves printing quality and production efficiency but also promotes the industry's transformation towards green and intelligent manufacturing. With the deep integration of 5G and AIoT technologies, this system will be further upgraded towards "predictive humidification" (humidity planning in advance based on production plans) and "adaptive regulation" (real-time response to climate changes), ultimately achieving the goal of "creating the optimal printing environment with minimal resource consumption."

[0174] Working principle:

[0175] I. Intelligent Sensing and Data Acquisition:

[0176] Distributed humidity monitoring:

[0177] The workshop is arranged in 50m 2 A high-precision humidity sensor (accuracy ±1.5% RH) is deployed at a density to collect ambient humidity data in real time. The sensor is installed using a magnetic stainless steel bracket at a distance of ≤3 meters from the printing press and a height of 1.5-2.0 meters to ensure that the data accurately reflects the humidity changes in the printing area.

[0178] The sensors are networked via the Modbus RTU protocol and upload data to the intelligent controller once per second. After outliers are removed using the 3σ principle, the 30-second moving average is taken as the valid data.

[0179] Multi-source information fusion:

[0180] The intelligent controller synchronously acquires printing press operating parameters (speed 0-150m / min, oven temperature 120-180℃) and paper properties (grammage 80-300g / m²). 2 (Moisture content 4-8%), interacts with the printing press control system via the OPCUA protocol.

[0181] Introducing a barcode scanner to automatically identify paper type and dynamically updating the membership function parameters in the humidification strategy library.

[0182] II. Fuzzy Control and Strategy Generation:

[0183] Humidification demand is dynamically calculated:

[0184] Based on the fuzzy control algorithm, the input variables are the current humidity deviation (e = current RH - 55%), the humidity change rate (de / dt), and the printing speed (v), and the output is the number of humidifiers turned on (n) and the operating power (P).

[0185] The membership function is designed according to the GB / T10739-2002 standard and contains 7 linguistic variables (NB / NM / NS / ZO / PS / PM / PB). It generates precise control quantities by defuzzifying the fuzzy variables using the centroid method.

[0186] Multi-mode switching logic:

[0187] When the humidity deviation is >5%RH, the high-pressure micro-mist unit (particle size 10-50μm) is activated for rapid humidification; when the deviation is ≤5%RH, the system switches to ultrasonic atomization (particle size ≤5μm) to maintain humidity.

[0188] A 5-minute delay mechanism is introduced for switching decisions to avoid frequent start-stop operations and ensure system stability.

[0189] III. Multi-mode collaborative humidification execution:

[0190] Ultrasonic atomizing unit:

[0191] A high-frequency transducer (1.7MHz) atomizes water into droplets ≤5μm, which are then evenly distributed through a 50mm diameter, downward-sloping 15° pipe, achieving a humidification rate of 15kg / h·m² per unit area. 2 .

[0192] The water tank has a built-in electric heating element to maintain the water temperature at 40-50℃, and the water level is automatically compensated by a float valve (accuracy ±5mm).

[0193] High-pressure micro-mist unit:

[0194] The plunger pump pressurizes the water to 7MPa, which generates 10-50μm droplets through a 1 / 8NPT nozzle. The effect lasts for ≥2 hours, covering the entire workshop area.

[0195] The pipeline is made of PE-RTI Type I material, with a pressure resistance of 10MPa and a temperature resistance of -40~70℃, ensuring long-term stable operation.

[0196] IV. Waste Heat Recovery and Energy Saving Optimization:

[0197] Waste heat recovery and utilization:

[0198] The exhaust gas from the printing press oven (temperature 120-180℃) preheats the humidified water through a heat pipe heat exchanger, raising the water temperature to 40-50℃ and reducing energy consumption for electric heating. The heat pipes use a vacuum-filled ammonia medium with a thermal conductivity ≥1000W / m·K and a heat exchange efficiency of 85%.

[0199] When the water temperature is below 40℃, the electric heating will automatically start as a supplement, giving priority to the use of waste heat.

[0200] Dynamic energy consumption control:

[0201] The intelligent controller dynamically adjusts the humidifier's operating power based on real-time humidity deviations and printing speed, ensuring minimal energy consumption while meeting demand. Experimental data shows that the system's average energy consumption is 33% lower than traditional methods.

[0202] V. Intelligent Operation and Maintenance and Water Quality Assurance:

[0203] Automatic cleaning and water quality monitoring:

[0204] The pipeline is cleaned by triggering pulse backflushing (0.6MPa compressed air) every 4 hours, and a 3% citric acid solution is injected monthly for circulation to remove scale and maintain pipeline patency.

[0205] The water quality monitoring sensor detects the conductivity (50-500μS / cm) in real time. When the conductivity exceeds the standard, it automatically switches to RO reverse osmosis water purification to ensure that the purity of the humidified water meets the GB5749-2022 standard.

[0206] Predictive maintenance system:

[0207] Vibration sensors (accuracy ±0.1g) and temperature sensors (accuracy ±0.5℃) monitor the equipment status in real time, and LSTM neural networks analyze historical data to predict faults (such as transducer scaling), providing early warnings 48 hours in advance to avoid unplanned downtime.

[0208] VI. Closed-loop control and continuous optimization:

[0209] Feedback adjustment mechanism:

[0210] The system updates its control strategy every 30 seconds, adjusting the humidification amount based on real-time humidity data to form a closed-loop control system of "monitoring-decision-execution-feedback".

[0211] The fuzzy control parameters are automatically optimized based on actual operating data to adapt to the characteristics of different workshop environments.

[0212] Multi-system linkage and collaboration:

[0213] It is linked to the workshop air conditioning system and automatically adjusts the fresh air volume (500-2000 m³ / h) when the humidity deviation is greater than 3% RH. 3 / h), to achieve coordinated control of temperature and humidity, further improving environmental stability.

[0214] The embodiments of the present invention are given for illustrative and descriptive purposes only, and are not intended to be exhaustive or to limit the invention to the forms disclosed. Many modifications and variations will be apparent to those skilled in the art. The embodiments were chosen and described in order to better illustrate the principles and practical application of the invention, and to enable those skilled in the art to understand the invention and to design various embodiments with various modifications suitable for a particular purpose.

Claims

1. An air humidification system for a food packaging printing plant, characterized by: Comprising: Humidity sensing module: Distributed deployment of humidity sensors, adjacent sensor spacing ≤10 meters and distance from the printing machine ≤3 meters, data acquisition frequency ≥1 times / second; Intelligent controller: Built-in fuzzy control algorithm, calculate the humidification amount according to the formula u=f(e,de / dt,v), where e is the humidity deviation, de / dt is the humidity change rate, and v is the printing speed, response time ≤8 seconds; Multi-mode humidification device: Contains ultrasonic atomization unit and high-pressure micro-fog unit, mode switching is realized by electromagnetic valve when the humidity deviation is >5%RH; Waste heat recovery system: Heat pipe heat exchanger transfers 120-180℃ printing machine exhaust heat to humidification water; The output parameters of the fuzzy control algorithm include the number of humidification device n and the running power P, and the calculation formula is: where k is a coefficient.

2. An air humidification system for a food packaging printing plant according to claim 1, characterized in that, The ultrasonic atomization unit is equipped with a 1.7MHz high-frequency transducer, and the water level automatic compensation accuracy is ±5mm.

3. An air humidification system for a food packaging printing plant according to claim 1, characterized in that, The heat pipe heat exchanger of the waste heat recovery system has a thermal conductivity of ≥1000 W / m·K and a heat exchange efficiency of ≥85%, and the energy saving amount is calculated by the formula: wherein is the waste gas heat flow, = 25℃, =40℃.

4. An air humidification system for a food packaging printing plant according to claim 1, characterized in that, Also including: Automatic cleaning module: Pulse backflush pressure 0.6MPa, pulse width 0.1 seconds, interval 5 seconds, 3% citric acid solution is injected every month for circulation descaling; Water quality monitoring module: Real-time monitoring of conductivity 50-500μS / cm, switching to RO reverse osmosis purified water when exceeding the standard.

5. An air humidification system for a food packaging printing plant based on the food packaging printing press as claimed in claim 1, characterized in that, When linked with the air conditioning system, automatically adjust the fresh air volume 500-2000m³ / h when the humidity deviation is >3%RH, and the temperature and humidity cooperative control accuracy is T=22±2℃, RH=55±2%.

6. A method for air humidification in a food packaging printing plant, using the air humidification system for a food packaging printing plant according to any one of claims 1 to 5, characterized in that, Including: Real-time data acquisition: Obtain humidity, printing speed and paper grammage, sampling frequency ≥1 times / second; Humidification demand calculation: Generate target humidification amount through fuzzy control algorithm, input parameters include humidity deviation e, change rate de / dt and printing speed v; Dynamic mode switching: Start high-pressure micro-fog when |e|>5%RH, switch to ultrasonic atomization when |e|≤5%RH; Waste heat recovery: Utilizing waste heat to raise the humidification water temperature to 40-50℃, with an energy saving rate based on... ≥35% calculation; The output parameters of the fuzzy control algorithm include the number of humidification device n and the running power P, and the calculation formula is: where k is a coefficient.

7. The method of claim 6, wherein, Also including predictive maintenance: Vibration sensor monitors equipment status, health index wherein is the vibration amplitude, is the baseline value; LSTM neural network predicts faults based on 24-hour historical data, warns 48 hours in advance, accuracy ≥92%.

8. Humidification device for implementing the method for humidifying the air in a food packaging printing plant according to claim 6, characterized in that, The response time of the humidification device is ≤8 seconds, and the humidification device is configured to realize dynamic mode switching of high-pressure micro-fog and ultrasonic atomization according to the output results of the fuzzy control algorithm in the air humidification method.

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