Hydrogen purification device with multi-layer filtering structure

Abstract

The utility model discloses a hydrogen purification device with a multi-layer filtering structure, and particularly relates to the field of hydrogen purification. The device comprises a dynamic fluid regulation and control system, a multi-layer filter unit, a gas-liquid separation unit, a photocatalysis auxiliary unit, a control system, a real-time monitoring system, a waste heat recovery system and a self-cleaning function module, the multi-layer filtering unit is sequentially provided with a mechanical filtering layer, an adsorption filtering layer, a chemical filtering layer and a membrane filtering layer which are used for respectively removing large-particle impurities, organic impurities, oxygen and moisture; the gas-liquid separation unit is used for removing liquid impurities through cyclone separation and condensation; the photocatalysis auxiliary unit is used for further purifying hydrogen by using a multi-wavelength LED light source and a photocatalysis material; the control system collects data through a real-time monitoring system, and realizes efficient hydrogen purification and waste heat recovery by combining a data processing module, a heat recovery efficiency calculation module, a system performance evaluation module and an optimization adjustment module; and the self-cleaning function module regularly and automatically cleans the filtering unit to prevent blockage and prolong the service life of the equipment.

Description

Technical Field

[0001] The utility model relates to the technical field of hydrogen purification, and more specifically, the utility model relates to a hydrogen purification device with a multi-layer filtration structure. Background Art

[0002] Hydrogen has a wide range of applications in the industrial and scientific research fields, such as in hydrogen fuel cells, chemical synthesis, and the electronics industry. Existing hydrogen purification technologies usually adopt methods such as physical adsorption, chemical adsorption, and membrane separation. These technologies can remove some impurities in hydrogen, but there are problems such as low efficiency, complex operation, and high maintenance costs. With the expansion of the application fields of hydrogen, the requirements for hydrogen purity and purification efficiency are getting higher and higher. Therefore, it is necessary to continuously improve the purification technology to meet the actual needs;

[0003] Existing hydrogen purification devices have significant deficiencies in efficiently removing hydrogen impurities. Specifically, these devices usually can only process a certain type of impurity singly. When facing the coexistence of multiple types of impurities, the purification effect significantly decreases, resulting in low hydrogen purity and unable to meet the application requirements of high-purity hydrogen. Summary of the Utility Model

[0004] In order to overcome the above-mentioned defects of the prior art, the embodiments of the utility model provide a hydrogen purification device with a multi-layer filtration structure. Through dynamic regulation and a multi-level filtration structure, various impurities in hydrogen can be effectively removed, and combined with an intelligent control system, efficient energy utilization and system optimization can be achieved to solve the problems raised in the above background art.

[0005] To achieve the above object, the utility model provides the following technical solutions: A hydrogen purification device with a multi-layer filtration structure, comprising:

[0006] A dynamic fluid regulation system for regulating the flow rate and pressure of hydrogen in the filtration unit;

[0007] A multi-layer filtration unit, including a mechanical filtration layer, an adsorption filtration layer, a chemical filtration layer, and a membrane filtration layer arranged in sequence;

[0008] The mechanical filtration layer, including a stainless steel filter mesh or a ceramic filter element, is used to remove large particle impurities in hydrogen;

[0009] The adsorption filtration layer, including activated carbon or carbon nanotubes, is used to adsorb organic impurities in hydrogen;

[0010] The chemical filtration layer, including a palladium catalyst and a molecular sieve, is used to remove oxygen and moisture in hydrogen;

[0011] The membrane filtration layer, including a polymer membrane or an inorganic membrane, is used for fine filtration;

[0012] The gas-liquid separation unit is arranged between the multi-layer filtration units and is used to remove liquid impurities in hydrogen;

[0013] The photocatalytic assistance unit includes a multi-wavelength LED light source and a photocatalytic material, and is used to remove impurities in hydrogen;

[0014] The control system is connected to the dynamic fluid regulation system and the multi-layer filtration unit, and is used to optimize the system operation parameters in real time. The control system includes a PLC controller, which receives the data of each sensor and controls the operation status of each unit;

[0015] The real-time monitoring system includes a temperature sensor, a pressure sensor and a gas concentration sensor, and is used to monitor various parameters in the hydrogen purification process in real time;

[0016] The waste heat recovery system includes a heat exchanger and a heat energy recovery pipeline, and is used to recover the waste heat generated during the filtration process;

[0017] The self-cleaning function module includes an ultrasonic cleaner and a backwashing system, and is used to clean the filtration unit regularly.

[0018] In a preferred embodiment, the dynamic fluid regulation system includes a micro pump, a valve and a flow sensor, and adjusts the hydrogen gas flow rate and pressure through the PLC controller to ensure the uniform distribution and optimal state of hydrogen gas between each filtration layer.

[0019] In a preferred embodiment, the gas-liquid separation unit includes a cyclone separator and a condenser, and removes liquid impurities in hydrogen through centrifugal force and condensation technology.

[0020] In a preferred embodiment, the photocatalytic assistance unit includes a multi-wavelength LED light source and a photocatalytic material, and is used to catalytically remove organic and inorganic impurities in hydrogen under light irradiation.

[0021] In a preferred embodiment, the waste heat recovery system includes a heat exchanger and a heat energy recovery pipeline, and uses the recovered waste heat to preheat the raw material hydrogen; the self-cleaning function module includes an ultrasonic cleaner and a backwashing system.

[0022] In a preferred embodiment, it includes a data acquisition module, a data preprocessing module, a heat recovery efficiency calculation module, a system performance evaluation module and an optimization adjustment module;

[0023] The data acquisition module records the temperature changes in the filtration unit and the waste heat recovery system through the temperature sensor; monitors the pressure of hydrogen gas in each unit through the pressure sensor; measures the flow rate of hydrogen gas through the flow sensor, and detects the purity and impurity content of hydrogen gas through the gas concentration sensor;

[0024] Through the data processing unit, data filtering, smoothing and synchronization are realized;

[0025] Through the heat recovery efficiency calculation module, thermal energy assessment is carried out to optimize the efficiency of waste heat recovery. By combining the heat flux density calculation method, the thermal energy recovery efficiency is dynamically evaluated;

[0026] Through the system performance evaluation module, the flow rate, pressure, temperature, and hydrogen purity are analyzed simultaneously, and the system energy efficiency is evaluated through a non - linear regression model;

[0027] Through the optimization and adjustment module, parameter optimization is carried out. Through Bayesian optimization and deep learning algorithms, the system parameters are dynamically adjusted according to real - time data and historical data.

[0028] The technical effects and advantages of the present utility model:

[0029] 1. Through a multi - layer filtration structure, including mechanical filtration, adsorption filtration, chemical filtration, and membrane filtration, large - particle impurities, organic impurities, oxygen, and moisture in hydrogen can be efficiently removed, ensuring high purity of hydrogen.

[0030] 2. By combining a dynamic fluid control system and an intelligent control system, the hydrogen flow rate and pressure can be optimized in real - time. Through real - time monitoring and data processing, the adaptive dynamic optimization of waste heat recovery and system performance is achieved, improving the system energy efficiency and extending the service life of the equipment. Brief Description of the Drawings

[0031] Figure 1 It is a structural composition diagram of the present utility model. Detailed Embodiment

[0032] Next, the technical solutions in the embodiments of the present utility model will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present utility model. Obviously, the described embodiments are only a part of the embodiments of the present utility model, rather than all of the embodiments. Based on the embodiments of the present utility model, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present utility model.

[0033] Referring to the attached Figure 1 drawings, a hydrogen purification device with a multi - layer filtration structure according to an embodiment of the present utility model includes:

[0034] A dynamic fluid control system for adjusting the flow rate and pressure of hydrogen in the filtration unit;

[0035] A multi - layer filtration unit including a mechanical filtration layer, an adsorption filtration layer, a chemical filtration layer, and a membrane filtration layer arranged in sequence;

[0036] The mechanical filtration layer includes a stainless - steel filter mesh or a ceramic filter element for removing large - particle impurities in hydrogen;

[0037] An adsorption filtration layer, including activated carbon or carbon nanotubes, is used for adsorbing organic impurities in hydrogen;

[0038] A chemical filtration layer, including palladium catalyst and molecular sieve, is used for removing oxygen and moisture in hydrogen;

[0039] A membrane filtration layer, including polymer membrane or inorganic membrane, is used for fine filtration;

[0040] A gas-liquid separation unit, arranged between the multi-layer filtration units, is used for removing liquid impurities in hydrogen;

[0041] A photocatalytic assistance unit, including multi-wavelength LED light sources and photocatalytic materials, is used for further removing impurities in hydrogen;

[0042] A control system, connected to the dynamic fluid regulation system and the multi-layer filtration unit, is used for optimizing the system operation parameters in real time. The control system includes a PLC controller, which receives the data from various sensors and controls the operation states of each unit;

[0043] A real-time monitoring system, including temperature sensors, pressure sensors and gas concentration sensors, is used for real-time monitoring of various parameters during the hydrogen purification process;

[0044] A waste heat recovery system, including a heat exchanger and heat energy recovery pipelines, is used for recovering the waste heat generated during the filtration process;

[0045] A self-cleaning function module, including an ultrasonic cleaner and a backwashing system, is used for periodically cleaning the filtration unit.

[0046] The dynamic fluid regulation system includes a micro pump, valves and flow sensors, and adjusts the hydrogen flow rate and pressure through the PLC controller to ensure uniform distribution and optimal state of hydrogen between each filtration layer. The gas-liquid separation unit includes a cyclone separator and a condenser, which remove liquid impurities in hydrogen through centrifugal force and condensation technology to improve the subsequent filtration effect. The photocatalytic assistance unit includes multi-wavelength LED light sources (ultraviolet light, visible light and infrared light) and photocatalytic materials (such as TiO2 and CdS), which are used for catalytically removing organic and inorganic impurities in hydrogen under light irradiation. The waste heat recovery system includes a heat exchanger and heat energy recovery pipelines, and uses the recovered waste heat to preheat the raw material hydrogen or other auxiliary processes; The self-cleaning function module includes an ultrasonic cleaner and a backwashing system, which automatically cleans the filtration unit regularly to prevent blockage and extend the service life of the equipment.

[0047] It also includes a data acquisition module, a data preprocessing module, a heat recovery efficiency calculation module, a system performance evaluation module and an optimization adjustment module;

[0048] The data acquisition module records the temperature changes in the filtration unit and the waste heat recovery system through temperature sensors; monitors the pressure of hydrogen in each unit through pressure sensors; measures the flow rate of hydrogen through flow sensors, and detects the purity and impurity content of hydrogen through gas concentration sensors;

[0049] Through the data processing unit, data filtering, smoothing, and synchronization are achieved to ensure the accuracy and effectiveness of the data. Specifically, the data filtering operation removes outliers and noise; the data smoothing operation smooths the data to reduce the impact of fluctuations; the data synchronization operation synchronizes the data information of different sensors to a unified time axis;

[0050] Through the heat recovery efficiency calculation module, thermal energy assessment is carried out to optimize the efficiency of waste heat recovery. Based on the data of multi-point temperature sensors and flow sensors, combined with the heat flux density calculation method, the thermal energy recovery efficiency is dynamically evaluated; the temperature and flow data of each monitoring point are collected, the heat flux density of each point is calculated, and integrated into the total heat recovery efficiency:

[0051]

[0052] where η 热回收 is the heat recovery efficiency, is the mass flow rate, c p is the specific heat capacity, ΔT i is the temperature difference at each monitoring point, is the sum of the recovered heat at all monitoring points, and the total input heat is: Q 总输入 =P 电能 +Q 环境热源 ;

[0053] Through the system performance evaluation module, multi-parameter data such as flow rate, pressure, temperature, and hydrogen purity are analyzed simultaneously, and the system energy efficiency is evaluated through a non-linear regression model; analyze multi-parameter data such as flow rate, pressure, temperature, and hydrogen purity, and evaluate the energy efficiency through a non-linear regression model:

[0054]

[0055] where η 系统 is the system energy efficiency, j,k j are the non-linear regression coefficients, Q 输入， j is the contribution of each input energy source, η 系统 is the system energy efficiency;

[0056] Among them, the hydrogen purity evaluation formula:

[0057]

[0058] Among them, C 氢气is the hydrogen concentration, C 总气体 is the total gas concentration;

[0059] Through the optimization and adjustment module, parameter optimization is carried out. Through Bayesian optimization and deep learning algorithms, the system parameters are dynamically adjusted according to real-time data and historical data;

[0060] Bayesian optimization formula:

[0061] Dynamic adjustment = argmax θ P(θ|D 实时 )

[0062] where θ is the set of optimization parameters, and P(θ|D 实时 ) is the posterior probability of the parameters based on real-time data;

[0063] Deep learning model:

[0064] System self-learning = DL model(D 历史 ,D 实时 )

[0065] The DL model is a deep learning model, D 历史 is historical data, and D 实时 is real-time data.

[0066] It should be noted that through the heat recovery efficiency calculation module for heat energy evaluation, the efficiency optimization of waste heat recovery can be achieved. This module first collects the temperature and flow data of each monitoring point through multiple temperature sensors and flow sensors, and then inputs these data into the system to calculate the heat flux density of each monitoring point. Finally, the data of all monitoring points are integrated to obtain the total heat recovery efficiency. This method of multi-point monitoring and comprehensive calculation can more accurately evaluate the heat energy utilization of each part of the system, ensure that waste heat energy is fully recovered, and thus optimize the overall energy efficiency of the system;

[0067] The system performance evaluation module realizes energy balance and system optimization through multi-parameter joint analysis. This module simultaneously analyzes multiple parameters such as flow rate, pressure, temperature, and hydrogen purity, and evaluates the overall energy efficiency of the system through a non-linear regression model. Specifically, the system collects the data of these parameters, inputs them into the regression model, analyzes the contribution of each input energy source to the system, and calculates the effective output energy of the system. In addition, through the data of the gas concentration sensor, the proportion of hydrogen in the total gas is evaluated to comprehensively understand the operating performance of the system. This comprehensive analysis method can identify possible efficiency problems in the system and provide strong data support for further optimization;

[0068] The optimization and adjustment module dynamically adjusts system parameters through real-time data and historical data to achieve the adaptive dynamic optimization of the system. This module uses the Bayesian optimization algorithm to calculate the current best system parameter settings based on real-time data and combines with a deep learning model to continuously optimize the system performance through the training of historical data. The specific operations include real-time monitoring of parameters such as the flow rate, pressure, and temperature of the system, dynamically adjusting these parameters to reach the optimal state. The Bayesian optimization algorithm determines the optimal adjustment scheme according to the changes in real-time data, while the deep learning model continuously improves the system performance through the continuous comparison and learning of historical data and real-time data. This adaptive optimization method ensures that the system always maintains the best state under different operating conditions, improving the hydrogen purity and energy efficiency;

[0069] In addition, this device achieves efficient hydrogen purification through a multi-layer filtration structure and an intelligent control system. First, hydrogen enters the dynamic fluid regulation system, which adjusts the flow rate and pressure of hydrogen in the filtration unit through a micro pump, valves, and flow sensors. Hydrogen passes through a mechanical filtration layer (removing large particle impurities), an adsorption filtration layer (adsorbing organic impurities), a chemical filtration layer (removing oxygen and moisture), and a membrane filtration layer (finely filtering trace impurities) in sequence to achieve multi-level physical and chemical purification. The gas-liquid separation unit uses a cyclone separator and a condenser to remove liquid impurities in hydrogen. The photocatalytic assistance unit further purifies hydrogen through a multi-wavelength LED light source and photocatalytic materials. The real-time monitoring system includes temperature, pressure, flow rate, and gas concentration sensors to monitor various parameters during the hydrogen purification process. The control system combines data processing, heat recovery efficiency calculation, system performance evaluation, and the optimization and adjustment module to dynamically optimize system parameters and ensure the efficient operation of the system. The waste heat recovery system recovers the waste heat generated during the filtration process through a heat exchanger and a heat energy recovery pipeline. The self-cleaning function module uses an ultrasonic cleaner and a backwashing system to regularly clean the filtration unit to prevent blockage and extend the service life of the equipment.

[0070] The above are only the preferred embodiments of the present utility model and are not intended to limit the present utility model. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present utility model shall be included within the protection scope of the present utility model.

Claims

1. A hydrogen purification device with a multi-layer filtration structure, characterized in that: include: A dynamic fluid control system for adjusting the flow rate and pressure of hydrogen in the filter unit; The multi-layer filtration unit includes a mechanical filtration layer, an adsorption filtration layer, a chemical filtration layer, and a membrane filtration layer arranged in sequence; Mechanical filter layer, including stainless steel filter or ceramic filter element, used to remove large particle impurities in hydrogen; An adsorption filter layer, including activated carbon or carbon nanotubes, is used to adsorb organic impurities in hydrogen; A chemical filtration layer, including a palladium catalyst and molecular sieves, is used to remove oxygen and water from hydrogen; Membrane filtration layer, including polymer membrane or inorganic membrane, for fine filtration; A gas-liquid separation unit is provided between the multi-layer filter units and is used to remove liquid impurities in the hydrogen; A photocatalytic auxiliary unit, including a multi-wavelength LED light source and a photocatalytic material, for removing impurities from hydrogen; A control system connected to the dynamic fluid control system and the multi-layer filtration unit for real-time optimization of system operating parameters, the control system including a PLC controller for receiving data from each sensor and controlling the operating status of each unit; Real-time monitoring system, including temperature sensor, pressure sensor and gas concentration sensor, used to monitor various parameters in the hydrogen purification process in real time; A waste heat recovery system, including a heat exchanger and a heat recovery pipeline, for recovering waste heat generated during the filtration process; Self-cleaning function module, including ultrasonic cleaner and backwash system, is used to clean the filter unit regularly.

2. The hydrogen purification device with a multi-layer filtration structure according to claim 1, characterized in that: The dynamic fluid control system includes a micro pump, a valve and a flow sensor, and the hydrogen flow rate and pressure are adjusted by a PLC controller to ensure the uniform distribution and optimal state of hydrogen between the filter layers.

3. The hydrogen purification device with a multi-layer filtration structure according to claim 2, characterized in that: The gas-liquid separation unit includes a cyclone separator and a condenser, and removes liquid impurities in hydrogen through centrifugal force and condensation technology.

4. The hydrogen purification device with a multi-layer filtration structure according to claim 3, characterized in that: The photocatalytic auxiliary unit comprises a multi-wavelength LED light source and a photocatalytic material, and is used for catalytically removing organic and inorganic impurities in hydrogen under light.

5. The hydrogen purification device with a multi-layer filtration structure according to claim 4, characterized in that: The waste heat recovery system includes a heat exchanger and a heat recovery pipeline, and the recovered waste heat is used to preheat the raw hydrogen; the self-cleaning function module includes an ultrasonic cleaner and a backwashing system.

6. The hydrogen purification device with a multi-layer filtration structure according to claim 5, characterized in that: It includes data acquisition module, data preprocessing module, heat recovery efficiency calculation module, system performance evaluation module and optimization adjustment module; The data acquisition module records the temperature changes in the filter unit and the waste heat recovery system through the temperature sensor; monitors the pressure of hydrogen in each unit through the pressure sensor; measures the flow rate of hydrogen through the flow sensor, and detects the purity and impurity content of hydrogen through the gas concentration sensor; Data filtering, smoothing and synchronization are achieved through the data processing unit; Through the heat recovery efficiency calculation module, thermal energy evaluation is carried out to optimize the efficiency of waste heat recovery. By combining the heat flux density calculation method, the heat recovery efficiency is dynamically evaluated. Through the system performance evaluation module, flow rate, pressure, temperature and hydrogen purity are analyzed simultaneously, and the system energy efficiency is evaluated through a nonlinear regression model; Parameter optimization is performed through the optimization adjustment module, and system parameters are dynamically adjusted according to real-time data and historical data through Bayesian optimization and deep learning algorithms.

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