Methanol-to-hydrogen purification device with pipeline cleaning structure

Abstract

The invention provides a methanol-to-hydrogen purification device with a pipeline cleaning structure. The methanol-to-hydrogen purification device comprises a PSA device, a desorption / regeneration system, an exhaust system, a product hydrogen buffer tank, a hydrogen compressor, a hydrogen conveying pipeline and an integrated pipeline cleaning module. And the pipeline cleaning module realizes automatic cleaning of the inner wall of the pipeline by utilizing a high-pressure water jet technology and abrasive flushing and combining with the acoustic emission detection module. The acoustic emission detection module evaluates the cleaning effect by capturing acoustic emission signals in the cleaning process and conducting intelligent analysis through a deep learning model. When the detected signal reaches the preset threshold value and is stable, it is indicated that cleaning is completed. According to the method, the cleaning efficiency can be improved, the maintenance cost is reduced, and the system downtime is shortened, so that the performance and reliability of the methanol-to-hydrogen purification device are improved.

Description

Technical Field

[0001] The invention relates to the field of methanol hydrogen production, and in particular to a methanol hydrogen production purification device with a pipeline cleaning structure. Background Art

[0002] With the development of renewable energy and clean energy technologies, methanol-to-hydrogen has attracted widespread attention as an efficient and clean method for producing hydrogen. However, the use of adsorbents in the methanol-to-hydrogen purification process can lead to the accumulation of impurities, affecting the purification efficiency and product quality. Traditional pipeline cleaning methods often rely on manual operations or simple mechanical cleaning, which are not only inefficient, but also difficult to completely remove deposits in the pipeline, which may lead to increased equipment maintenance costs and extended system downtime. Therefore, the development of an automated and efficient pipeline cleaning technology is crucial to improving the overall performance and reliability of methanol-to-hydrogen purification equipment.

[0003] CN216988997U provides a pipeline cleaning device for purification of methanol hydrogen production, comprising: a lifting trolley, a driving part arranged on the lifting trolley, a shot blasting cylinder arranged on the driving part, and a plurality of shot blasting beads arranged in the shot blasting cylinder; the shot blasting cylinder can be arranged outside the hydrogen pipeline, wherein; the driving part is driven, the shot blasting cylinder can rotate, so that the shot blasting cylinder drives a plurality of the shot blasting beads to knock and clean the hydrogen pipeline, and the detachable shot blasting cylinder is moved to the outer wall of the hydrogen pipeline at different heights and positions by the lifting trolley, and the driving part works to drive the shot blasting cylinder to rotate, so that the shot blasting cylinder drives a plurality of shot blasting beads to perform comprehensive rotary shot blasting cleaning treatment on the outer wall of the hydrogen pipeline. This scheme also requires manual cleaning, does not realize automatic control, and the cleaning progress cannot be known during cleaning. Summary of the invention

[0004] In order to solve the above problems, the present invention provides a methanol hydrogen purification device with a pipeline cleaning structure, including a PSA device, a desorption / regeneration system, exhaust, a product hydrogen buffer tank, a hydrogen compressor, a hydrogen delivery pipeline and a pipeline cleaning module;

[0005] The PSA device is connected to the desorption / regeneration system and the product hydrogen buffer tank, the desorption / regeneration system is connected to the exhaust, the product hydrogen buffer tank is connected to the hydrogen compressor, and the hydrogen compressor is connected to the hydrogen delivery pipeline;

[0006] The PSA unit is used to purify hydrogen through adsorption and desorption processes. It is equipped with activated carbon or PSA-specific adsorbents and adopts a double-tower or four-tower configuration;

[0007] The desorption / regeneration system is used to desorb impurities on the adsorbent by introducing desorption gas, and the desorbed gas is discharged through the exhaust gas;

[0008] The product hydrogen buffer tank is used to store purified hydrogen and stabilize pressure fluctuations, and then output the hydrogen through the hydrogen compressor and hydrogen transmission pipeline;

[0009] The pipeline cleaning module is arranged on the pipelines connecting the PSA device to the desorption / regeneration system and the desorption / regeneration system to the exhaust gas, and is used to clean the desorption pipeline from the PSA device to the exhaust gas.

[0010] The pipeline cleaning module includes a main controller, an acoustic emission detection module and a cleaning module; the cleaning module includes a high-pressure water module and a drying module; the high-pressure water module includes an abrasive flushing module and a pure water flushing module;

[0011] The acoustic emission detection module is used to detect the acoustic emission signal emitted from the pipeline during the cleaning process, and determine whether the pipeline is cleaned according to the acoustic emission signal;

[0012] The high-pressure water module is used to generate high-pressure water to clean the desorption pipeline;

[0013] The main controller is connected to the acoustic emission detection module and the cleaning module, and is used for controlling the cleaning process of the cleaning module according to the data sent by the acoustic emission detection module.

[0014] The abrasive washing module includes an abrasive mixing chamber and a pulse controller, wherein the abrasive mixing chamber is used to mix and stir water and abrasive, and the pulse controller controls the injection pressure and injection frequency of the mixed liquid pulse injection;

[0015] The pure water flushing module includes a water storage tank and a pressure controller, and the pressure controller controls the flushing pressure during pure water flushing.

[0016] The pulse controller of the abrasive washing module includes a pressure regulating valve, a frequency regulator and a control logic unit; the pressure regulating valve is used to adjust the pressure of the abrasive mixed liquid to control the injection pressure; the frequency regulator is used to adjust the frequency of the pulse injection; the control logic unit is used to coordinate the work of the pressure regulating valve and the frequency regulator according to the preset cleaning program and the feedback signal of the pipeline to achieve accurate control of the injection pressure and injection frequency of the abrasive mixed liquid;

[0017] The pressure regulating valve adjusts the pressure of the abrasive mixed liquid according to the instructions of the control logic unit, thereby controlling the size of the injection pressure;

[0018] The frequency regulator is an electronic or mechanical device that controls the pulse jet frequency. According to the setting of the control logic unit, the frequency of the jet is changed to adapt to different cleaning requirements.

[0019] The pure water flushing module also includes a filtering system; the pure water flushing module is used to flush the pipeline after the abrasive flushing module to remove the residual abrasive and impurities in the pipeline;

[0020] The filtration system is used to filter the pure water in the water tank to ensure that the ejected water is pure and free of impurities;

[0021] The water tank is used to store pure water for flushing, and its capacity is determined according to the length of the pipeline and cleaning requirements.

[0022] The acoustic emission detection module includes a plurality of acoustic emission sensors, a signal conditioning unit, a data acquisition unit and an analysis and processing module; the acoustic emission detection module is used to detect and analyze the acoustic emission signal emitted by the inner wall of the pipeline during the pipeline cleaning process, analyze the cleaning effect and determine whether the cleaning process is completed;

[0023] Acoustic emission sensors are distributed at different locations on the outer wall of the pipeline to capture the acoustic emission signals generated by the inner wall of the pipeline during the cleaning process;

[0024] The signal conditioning unit is connected to the acoustic emission sensor and is used to amplify, filter and condition the acoustic emission signal so as to facilitate collection by the data acquisition unit;

[0025] A data acquisition unit, used for receiving the conditioned signal from the signal conditioning unit, and performing digital processing and storage;

[0026] The analysis and processing module receives the digital signal from the data acquisition unit and performs signal processing and analysis.

[0027] The analysis and processing module receives the digital signal from the data acquisition unit and performs signal processing and analysis as follows:

[0028] Preprocess the collected acoustic emission signals, including denoising, signal enhancement and trend removal, to improve signal quality;

[0029] Extract characteristic parameters from the preprocessed acoustic emission signal, the characteristic parameters including signal amplitude, energy, frequency component, signal duration, rise time and count rate;

[0030] The deep learning model is used to classify the acoustic emission signals, distinguishing between signals caused by the shedding of deposits during the cleaning process, pipeline vibration signals, and signals caused by environmental noise;

[0031] When the signal caused by the shedding of deposits in the acoustic emission signal reaches or is lower than the preset threshold and remains stable for a period of time, it indicates that the deposits on the inner wall of the pipeline have basically fallen off and the cleaning process is completed.

[0032] Data preprocessing:

[0033] Use wavelet transform or Fourier transform to remove noise from the signal, improve the signal-to-noise ratio by amplifying the useful components of the signal, and use Gaussian smoothing or other methods to remove linear or nonlinear trends in the signal;

[0034] The following features are extracted during feature extraction:

[0035] Signal amplitude: calculate the maximum and minimum values ​​of the signal;

[0036] Energy: Calculates the total energy of the signal, specifically the integral of the square of the signal;

[0037] Frequency component: Use Fourier transform to extract the spectrum of the signal and analyze the main frequency components;

[0038] Signal duration: measures the duration of a signal;

[0039] Rise time: The time interval from the start of a signal to the time it reaches its maximum value;

[0040] Count rate: the number of events in a signal during the detection period;

[0041] The deep learning model structure is as follows:

[0042] Input layer: accepts data after preprocessing and feature extraction, determines the number of neurons in the input layer according to the characteristic dimension of the acoustic emission signal, and each feature requires one or more neurons; uses the normalization method Z-score normalization for normalization;

[0043] Hidden layer: multiple hidden layers, using activation function ReLU or sigmoid for nonlinear transformation;

[0044] The number of neurons in each layer is determined by the dimension of the data, and the number of neurons in the hidden layer is more than that in the input layer;

[0045] First hidden layer: 256 neurons, ReLU activation function; second hidden layer: 128 neurons, ReLU activation function, dropout layer: dropout is applied after each hidden layer with a dropout rate of 0.5 to reduce overfitting;

[0046] Classification layer: Output layer, using softmax or other activation functions for classification, maps the output of the last hidden layer to the number of categories C, applies the softmax activation function, and converts the output into a probability distribution;

[0047] Output layer:

[0048] The final classification results are output, with one neuron for each category corresponding to a type of acoustic emission signal.

[0049] The parameters of the deep learning model training process are as follows:

[0050] Optimization algorithm: Use the Adam optimizer to adaptively adjust the learning rate to handle problems of different sizes;

[0051] Learning rate: The initial learning rate is set to 0.001 and adjusted according to the performance of the validation set;

[0052] Batch processing: Mini-batch gradient descent is used for training, and the batch size is set to 32 or 64;

[0053] Iteration number: Determined based on the performance on the validation set, ranging from 100 to 5000 iterations.

[0054] A methanol hydrogen purification method, using the methanol hydrogen purification device with a pipeline cleaning structure, specifically comprises the following steps:

[0055] a. Preparation:

[0056] Check all components of the methanol-to-hydrogen purification unit, including the PSA unit, desorption / regeneration system, exhaust system, product hydrogen buffer tank, hydrogen compressor and hydrogen delivery pipeline to ensure they are in good working condition;

[0057] Start the acoustic emission detection module of the pipeline cleaning module and perform initialization settings, including installation and calibration of the acoustic emission sensor;

[0058] b.PSA purification process:

[0059] The raw hydrogen is introduced into the PSA unit and the hydrogen is purified through adsorption and desorption processes;

[0060] The activated carbon or special adsorbent inside the PSA unit begins to adsorb impurities in the raw hydrogen;

[0061] Achieve continuous adsorption and desorption cycles through a dual-tower or quad-tower PSA unit;

[0062] c. Desorption / regeneration process:

[0063] The desorption / regeneration system introduces desorption gas to desorb impurities on the adsorbent;

[0064] The desorbed gas is discharged through the exhaust system, and the components in the exhaust are monitored to ensure that impurities are effectively removed;

[0065] d. Hydrogen buffering and compression:

[0066] The purified hydrogen is stored in the product hydrogen buffer tank to stabilize pressure fluctuations;

[0067] The hydrogen compressor compresses the hydrogen in the buffer tank to the required pressure;

[0068] The compressed hydrogen is output through the hydrogen transmission pipeline, ready for further use or storage;

[0069] e. Start pipeline cleaning:

[0070] The pipeline cleaning module starts working, firstly by abrasive flushing, using a pulse controller to adjust the jet pressure and frequency to remove the deposits in the pipeline;

[0071] f. Acoustic emission detection and analysis:

[0072] During the cleaning process, the acoustic emission detection module captures the acoustic emission signals emitted by the inner wall of the pipeline in real time. The data acquisition unit transmits the conditioned signals to the analysis and processing module, which pre-processes and extracts features from the signals, and then uses a deep learning model to classify the signals.

[0073] g. Cleaning effect evaluation:

[0074] The analysis and processing module evaluates the cleaning effect according to the characteristic parameters of the acoustic emission signal. When the signal caused by the fall of sediment in the acoustic emission signal reaches or falls below the preset threshold and remains stable for a period of time, the analysis and processing module determines that the cleaning process is completed;

[0075] h. Cleaning completion and subsequent processing:

[0076] After the main controller receives the signal that the cleaning is completed, it stops the cleaning module and starts the pure water flushing module for the final flushing. After the cleaning is completed, the pipeline is dried to remove residual moisture. After the drying is completed, the methanol hydrogen purification device is restarted to continue the hydrogen purification process.

[0077] The beneficial effects of the present invention are:

[0078] By using high-pressure water modules and abrasive flushing modules, strong mechanical impact can be generated to effectively remove stubborn deposits on the inner wall of the pipeline, greatly improving the cleaning efficiency compared to traditional chemical cleaning or manual cleaning methods. The integrated acoustic emission detection module can monitor the cleaning process in the pipeline in real time and provide accurate cleaning feedback. The main controller intelligently adjusts the cleaning parameters based on these feedback signals to ensure that the cleaning process is both efficient and energy-saving. Regular and efficient pipeline cleaning can reduce the risk of pipeline blockage and corrosion, thereby extending the service life of the PSA unit, desorption / regeneration system and other key components.

[0079] This solution integrates advanced acoustic emission detection technology and intelligent control algorithms to achieve automatic cleaning of the pipeline of the methanol hydrogen purification device. The use of high-pressure water jet and abrasive flushing technology, combined with precise pulse control, can effectively remove sediments in the pipeline. In addition, through real-time monitoring of acoustic emission signals and intelligent analysis of deep learning models, this solution can accurately evaluate the cleaning effect and ensure thorough cleaning of the inner wall of the pipeline. This automated cleaning method not only improves cleaning efficiency and reduces labor costs, but also reduces system maintenance time and downtime risks, thereby improving the overall operating efficiency and economy of the methanol hydrogen purification device. BRIEF DESCRIPTION OF THE DRAWINGS

[0080] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0081] Attached Figure 1 This is a schematic diagram of the overall structure of the hydrogen production device of the present invention;

[0082] Attached Figure 2 This is a schematic diagram of the overall structure of the purification device of the present invention;

[0083] Attached Figure 3 This is a schematic diagram of the overall architecture of the pipeline cleaning module of the present invention;

[0084] Attached Figure 4 It is a schematic diagram of the overall structure of the high-pressure water module of the present invention. DETAILED DESCRIPTION

[0085] Embodiment 1:

[0086] See also Figures 1 to 4 , the present invention provides a methanol hydrogen production purification device with a pipeline cleaning structure, including a PSA device, a desorption / regeneration system, an exhaust, a product hydrogen buffer tank, a hydrogen compressor, a hydrogen delivery pipeline and a pipeline cleaning module;

[0087] The PSA device is connected to the desorption / regeneration system and the product hydrogen buffer tank, the desorption / regeneration system is connected to the exhaust, the product hydrogen buffer tank is connected to the hydrogen compressor, and the hydrogen compressor is connected to the hydrogen delivery pipeline;

[0088] The PSA unit is used to purify hydrogen through adsorption and desorption processes. It is equipped with activated carbon or PSA-specific adsorbents and adopts a double-tower or four-tower configuration;

[0089] The desorption / regeneration system is used to desorb impurities on the adsorbent by introducing desorption gas, and the desorbed gas is discharged through the exhaust gas;

[0090] The product hydrogen buffer tank is used to store purified hydrogen and stabilize pressure fluctuations, and then output the hydrogen through the hydrogen compressor and hydrogen transmission pipeline;

[0091] The pipeline cleaning module is arranged on the pipelines connecting the PSA device to the desorption / regeneration system and the desorption / regeneration system to the exhaust gas, and is used to clean the desorption pipeline from the PSA device to the exhaust gas.

[0092] The pipeline cleaning module includes a main controller, an acoustic emission detection module and a cleaning module; the cleaning module includes a high-pressure water module and a drying module; the high-pressure water module includes an abrasive flushing module and a pure water flushing module;

[0093] The acoustic emission detection module is used to detect the acoustic emission signal emitted from the pipeline during the cleaning process, and determine whether the pipeline is cleaned according to the acoustic emission signal;

[0094] The high-pressure water module is used to generate high-pressure water to clean the desorption pipeline;

[0095] The main controller is connected to the acoustic emission detection module and the cleaning module, and is used for controlling the cleaning process of the cleaning module according to the data sent by the acoustic emission detection module.

[0096] The abrasive washing module includes an abrasive mixing chamber and a pulse controller, wherein the abrasive mixing chamber is used to mix and stir water and abrasive, and the pulse controller controls the injection pressure and injection frequency of the mixed liquid pulse injection;

[0097] The pure water flushing module includes a water storage tank and a pressure controller, and the pressure controller controls the flushing pressure during pure water flushing.

[0098] The pulse controller of the abrasive washing module includes a pressure regulating valve, a frequency regulator and a control logic unit; the pressure regulating valve is used to adjust the pressure of the abrasive mixed liquid to control the injection pressure; the frequency regulator is used to adjust the frequency of the pulse injection; the control logic unit is used to coordinate the work of the pressure regulating valve and the frequency regulator according to the preset cleaning program and the feedback signal of the pipeline to achieve accurate control of the injection pressure and injection frequency of the abrasive mixed liquid;

[0099] The pressure regulating valve adjusts the pressure of the abrasive mixed liquid according to the instructions of the control logic unit, thereby controlling the size of the injection pressure;

[0100] The frequency regulator is an electronic or mechanical device that controls the pulse jet frequency. According to the setting of the control logic unit, the frequency of the jet is changed to adapt to different cleaning requirements.

[0101] The pure water flushing module also includes a filtering system; the pure water flushing module is used to flush the pipeline after the abrasive flushing module to remove the residual abrasive and impurities in the pipeline;

[0102] The filtration system is used to filter the pure water in the water tank to ensure that the ejected water is pure and free of impurities;

[0103] The water tank is used to store pure water for flushing, and its capacity is determined according to the length of the pipeline and cleaning requirements.

[0104] The acoustic emission detection module includes a plurality of acoustic emission sensors, a signal conditioning unit, a data acquisition unit and an analysis and processing module; the acoustic emission detection module is used to detect and analyze the acoustic emission signal emitted by the inner wall of the pipeline during the pipeline cleaning process, analyze the cleaning effect and determine whether the cleaning process is completed;

[0105] Acoustic emission sensors are distributed at different locations on the outer wall of the pipeline to capture the acoustic emission signals generated by the inner wall of the pipeline during the cleaning process;

[0106] The signal conditioning unit is connected to the acoustic emission sensor and is used to amplify, filter and condition the acoustic emission signal so as to facilitate collection by the data acquisition unit;

[0107] A data acquisition unit, used for receiving the conditioned signal from the signal conditioning unit, and performing digital processing and storage;

[0108] The analysis and processing module receives the digital signal from the data acquisition unit and performs signal processing and analysis.

[0109] The analysis and processing module receives the digital signal from the data acquisition unit and performs signal processing and analysis as follows:

[0110] Preprocess the collected acoustic emission signals, including denoising, signal enhancement and trend removal, to improve signal quality;

[0111] Extract characteristic parameters from the preprocessed acoustic emission signal, the characteristic parameters including signal amplitude, energy, frequency component, signal duration, rise time and count rate;

[0112] The deep learning model is used to classify the acoustic emission signals, distinguishing between signals caused by the shedding of deposits during the cleaning process, pipeline vibration signals, and signals caused by environmental noise;

[0113] When the signal caused by the shedding of deposits in the acoustic emission signal reaches or is lower than the preset threshold and remains stable for a period of time, it indicates that the deposits on the inner wall of the pipeline have basically fallen off and the cleaning process is completed.

[0114] Data preprocessing:

[0115] Use wavelet transform or Fourier transform to remove noise from the signal, improve the signal-to-noise ratio by amplifying the useful components of the signal, and use Gaussian smoothing or other methods to remove linear or nonlinear trends in the signal;

[0116] The following features are extracted during feature extraction:

[0117] Signal amplitude: calculate the maximum and minimum values ​​of the signal;

[0118] Energy: Calculates the total energy of the signal, specifically the integral of the square of the signal;

[0119] Frequency component: Use Fourier transform to extract the spectrum of the signal and analyze the main frequency components;

[0120] Signal duration: measures the duration of a signal;

[0121] Rise time: The time interval from the start of a signal to the time it reaches its maximum value;

[0122] Count rate: the number of events in a signal during the detection period;

[0123] The deep learning model structure is as follows:

[0124] Input layer: accepts data after preprocessing and feature extraction, determines the number of neurons in the input layer according to the characteristic dimension of the acoustic emission signal, and each feature requires one or more neurons; uses the normalization method Z-score normalization for normalization;

[0125] Hidden layer: multiple hidden layers, using activation function ReLU or sigmoid for nonlinear transformation;

[0126] The number of neurons in each layer is determined by the dimension of the data, and the number of neurons in the hidden layer is more than that in the input layer;

[0127] First hidden layer: 256 neurons, ReLU activation function; second hidden layer: 128 neurons, ReLU activation function, dropout layer: dropout is applied after each hidden layer with a dropout rate of 0.5 to reduce overfitting;

[0128] Classification layer: Output layer, using softmax or other activation functions for classification, maps the output of the last hidden layer to the number of categories C, applies the softmax activation function, and converts the output into a probability distribution;

[0129] Output layer:

[0130] The final classification results are output, with one neuron for each category corresponding to a type of acoustic emission signal.

[0131] The parameters of the deep learning model training process are as follows:

[0132] Optimization algorithm: Use the Adam optimizer to adaptively adjust the learning rate to handle problems of different sizes;

[0133] Learning rate: The initial learning rate is set to 0.001 and adjusted according to the performance of the validation set;

[0134] Batch processing: Mini-batch gradient descent is used for training, and the batch size is set to 32 or 64;

[0135] Iteration number: Determined based on the performance on the validation set, ranging from 100 to 5000 iterations.

[0136] Embodiment 2:

[0137] A methanol hydrogen purification method, using the methanol hydrogen purification device with a pipeline cleaning structure, specifically comprises the following steps:

[0138] a. Preparation:

[0139] Check all components of the methanol-to-hydrogen purification unit, including the PSA unit, desorption / regeneration system, exhaust system, product hydrogen buffer tank, hydrogen compressor and hydrogen delivery pipeline to ensure they are in good working condition;

[0140] Start the acoustic emission detection module of the pipeline cleaning module and perform initialization settings, including installation and calibration of the acoustic emission sensor;

[0141] b.PSA purification process:

[0142] The raw hydrogen is introduced into the PSA unit and the hydrogen is purified through adsorption and desorption processes;

[0143] The activated carbon or special adsorbent inside the PSA unit begins to adsorb impurities in the raw hydrogen;

[0144] Achieve continuous adsorption and desorption cycles through a dual-tower or quad-tower PSA unit;

[0145] c. Desorption / regeneration process:

[0146] The desorption / regeneration system introduces desorption gas to desorb impurities on the adsorbent;

[0147] The desorbed gas is discharged through the exhaust system, and the components in the exhaust are monitored to ensure that impurities are effectively removed;

[0148] d. Hydrogen buffering and compression:

[0149] The purified hydrogen is stored in the product hydrogen buffer tank to stabilize pressure fluctuations;

[0150] The hydrogen compressor compresses the hydrogen in the buffer tank to the required pressure;

[0151] The compressed hydrogen is output through the hydrogen transmission pipeline, ready for further use or storage;

[0152] e. Start pipeline cleaning:

[0153] The pipeline cleaning module starts working, firstly by abrasive flushing, using a pulse controller to adjust the jet pressure and frequency to remove the deposits in the pipeline;

[0154] f. Acoustic emission detection and analysis:

[0155] During the cleaning process, the acoustic emission detection module captures the acoustic emission signals emitted by the inner wall of the pipeline in real time. The data acquisition unit transmits the conditioned signals to the analysis and processing module, which pre-processes and extracts features from the signals, and then uses a deep learning model to classify the signals.

[0156] g. Cleaning effect evaluation:

[0157] The analysis and processing module evaluates the cleaning effect according to the characteristic parameters of the acoustic emission signal. When the signal caused by the fall of sediment in the acoustic emission signal reaches or falls below the preset threshold and remains stable for a period of time, the analysis and processing module determines that the cleaning process is completed;

[0158] h. Cleaning completion and subsequent processing:

[0159] After the main controller receives the signal that the cleaning is completed, it stops the cleaning module and starts the pure water flushing module for the final flushing. After the cleaning is completed, the pipeline is dried to remove residual moisture. After the drying is completed, the methanol hydrogen purification device is restarted to continue the hydrogen purification process.

[0160] Embodiment 3:

[0161] Raw material adding device and other auxiliary systems:

[0162] Methanol storage tank

[0163] Function: Storage of methanol raw materials. Performance parameters: Capacity 1000 liters, working pressure 0.5MPa.

[0164] Size: 1.5m in diameter, 2.5m in height. Connection: Connected to the methanol delivery pump via a pipeline.

[0165] Methanol delivery pump

[0166] Function: To transport methanol from the storage tank to the mixer. Performance parameters: Flow rate 5 liters / minute, head 30 meters. Size: Diameter 0.3 meters, length 1.0 meters. Connection: Connected to the mixer through a pipeline.

[0167] Water storage tank

[0168] Function: Store deionized water. Performance parameters: Capacity 2000 liters, working pressure 0.5MPa.

[0169] Size: 1.5m in diameter, 2.5m in height. Connection: Connected to water delivery pump via pipe.

[0170] Water transfer pump

[0171] Function: To transport water from the storage tank to the mixer. Performance parameters: Flow rate 10 l / min, head 30 m. Size: Diameter 0.3 m, length 1.0 m. Connection: Connected to the mixer through a pipe.

[0172] mixer

[0173] Function: Mix methanol and water in a certain proportion. Performance parameters: Mixing ratio 1:1.5 (methanol: water), operating pressure 0.3MPa. Size: diameter 0.3m, length 1.0m. Connection: Connected to the preheating heat exchanger through a pipeline.

[0174] Preheating heat exchanger

[0175] Function: Preheating the mixed flow. Performance parameters: Heat exchange area 10 square meters, operating temperature 150℃.

[0176] Size: 0.5m in diameter, 2.0m in length. Connection: Connected to the vaporizer via a pipe.

[0177] Vaporization tower

[0178] Function: vaporize liquid mixture into steam. Performance parameters: operating pressure 1.0MPa, operating temperature 200℃. Dimensions: diameter 0.6m, height 3.0m. Connection: connected to superheater through pipeline.

[0179] Superheater

[0180] Function: Further heat the steam. Performance parameters: Operating temperature 250℃. Dimensions: 0.5m diameter, 1.5m length. Connection: Connected to the reactor through a pipeline.

[0181] Reforming Reactor

[0182] Function: Methanol steam reforming reaction. Performance parameters: Operating temperature 250℃, pressure 2.0MPa. Size: Diameter 0.8m, length 4.0m. Connection: Connected to the cooler through a pipeline.

[0183] Cooler

[0184] Function: Cooling the gas mixture at the reactor outlet. Performance parameters: Operating temperature 100℃.

[0185] Size: 0.5m diameter, 2.0m length. Connection: Connected to the separator via pipe.

[0186] Separator

[0187] Function: Separation of gas and unreacted methanol / water. Performance parameters: Operating pressure 0.5MPa. Dimensions: Diameter 0.6m, height 2.0m. Connection: Connected to PSA unit through pipeline.

[0188] Pressure Swing Adsorption (PSA) Unit

[0189] Function: Purify hydrogen. Performance parameters: Hydrogen purity 99.9%, recovery rate 85%. Size: Diameter 0.8m, height 3.0m. Connection: Connected to hydrogen buffer tank through pipeline.

[0190] Hydrogen buffer tank

[0191] Function: To store purified hydrogen. Performance parameters: Capacity 500 liters, working pressure 3.0 MPa.

[0192] Dimensions: 0.8m diameter, 1.5m height. Connection: Connected to the hydrogen compressor via pipeline.

[0193] Hydrogen compressor

[0194] Function: compress hydrogen. Performance parameters: pressure ratio 1.5, motor power 30kW. Size: diameter 0.6m, length 1.2m. Connection: connected to the hydrogen delivery pipeline through a pipeline.

[0195] Control System

[0196] Function: monitor and control the temperature, pressure, flow and other key parameters of the whole system. Performance parameters: including PLC controller, sensor, actuator, etc. Size: determined according to actual needs.

[0197] Safety devices

[0198] Function: Ensure the safe operation of the system. Performance parameters: including pressure relief valve, emergency stop button, flame detector, etc. Size: Determined according to actual needs.

[0199] Thus far, the description of the above-described embodiments is provided for the purpose of illustration and description. It is not intended to be exhaustive or to limit the present disclosure. The individual elements or features of a specific embodiment are generally not subject to the limitations of the specific embodiment, but when applicable, they can be interchanged and used for selected embodiments even if not specifically shown or described. In many respects, the same element or feature also can be changed. This variation is not considered to be a departure from the present disclosure, and all such modifications are intended to be included in the scope of the present disclosure.

[0200] Example embodiments are provided so that the present disclosure will be thorough and the scope will be fully conveyed to those skilled in the art. In order to thoroughly understand the embodiments of the present disclosure, numerous details are set forth, such as examples of specific parts, devices, and methods. Obviously, for those skilled in the art, it is not necessary to use specific details, the example embodiments can be implemented in many different forms, and neither should be construed as limiting the scope of the present disclosure. In certain example embodiments, well-known processes, well-known device structures, and well-known technologies are not described in detail.

[0201] Here, specialized vocabulary is used only for the purpose of describing specific example embodiments, and is not intended to be limiting. Unless the context clearly indicates otherwise, the singular forms "a" and "the" used herein may be intended to include plural forms as well. The terms "including" and "having" are inclusive, and therefore specify the presence of the claimed features, wholes, steps, operations, elements and / or components, but do not exclude the presence or additional presence of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof. Unless the order of execution is clearly indicated, the method steps, processing and operations described herein are not interpreted as necessarily needing to be performed in the specific order discussed and shown. It should also be understood that additional or optional steps may be adopted.

Claims

1. A methanol hydrogen production purification device with a pipeline cleaning structure, comprising a PSA device, a desorption / regeneration system, an exhaust, a product hydrogen buffer tank, a hydrogen compressor, a hydrogen delivery pipeline and a pipeline cleaning module; characterized in that: The PSA device is connected to the desorption / regeneration system and the product hydrogen buffer tank, the desorption / regeneration system is connected to the exhaust, the product hydrogen buffer tank is connected to the hydrogen compressor, and the hydrogen compressor is connected to the hydrogen delivery pipeline; The PSA unit is used to purify hydrogen through adsorption and desorption processes. It is equipped with activated carbon or PSA-specific adsorbents and adopts a double-tower or four-tower configuration; The desorption / regeneration system is used to desorb impurities on the adsorbent by introducing desorption gas, and the desorbed gas is discharged through the exhaust gas; The product hydrogen buffer tank is used to store purified hydrogen and stabilize pressure fluctuations, and then output the hydrogen through the hydrogen compressor and hydrogen transmission pipeline; The pipeline cleaning module is arranged on the pipelines connecting the PSA device to the desorption / regeneration system and the desorption / regeneration system to the exhaust gas, and is used to clean the desorption pipeline from the PSA device to the exhaust gas.

2. The methanol-to-hydrogen purification device with a pipeline cleaning structure according to claim 1, characterized in that: The pipeline cleaning module includes a main controller, an acoustic emission detection module and a cleaning module; the cleaning module includes a high-pressure water module and a drying module; the high-pressure water module includes an abrasive flushing module and a pure water flushing module; The acoustic emission detection module is used to detect the acoustic emission signal emitted from the pipeline during the cleaning process, and determine whether the pipeline is cleaned according to the acoustic emission signal; The high-pressure water module is used to generate high-pressure water to clean the desorption pipeline; The main controller is connected to the acoustic emission detection module and the cleaning module, and is used for controlling the cleaning process of the cleaning module according to the data sent by the acoustic emission detection module.

3. The methanol-to-hydrogen purification device with a pipeline cleaning structure according to claim 2, characterized in that: The abrasive washing module includes an abrasive mixing chamber and a pulse controller, wherein the abrasive mixing chamber is used to mix and stir water and abrasive, and the pulse controller controls the injection pressure and injection frequency of the mixed liquid pulse injection; The pure water flushing module includes a water storage tank and a pressure controller, and the pressure controller controls the flushing pressure during pure water flushing.

4. The methanol-to-hydrogen purification device with a pipeline cleaning structure according to claim 3 is characterized in that: The pulse controller of the abrasive washing module includes a pressure regulating valve, a frequency regulator and a control logic unit; the pressure regulating valve is used to adjust the pressure of the abrasive mixed liquid to control the injection pressure; the frequency regulator is used to adjust the frequency of the pulse injection; the control logic unit is used to coordinate the work of the pressure regulating valve and the frequency regulator according to the preset cleaning program and the feedback signal of the pipeline to achieve accurate control of the injection pressure and injection frequency of the abrasive mixed liquid; The pressure regulating valve adjusts the pressure of the abrasive mixed liquid according to the instructions of the control logic unit, thereby controlling the size of the injection pressure; The frequency regulator is an electronic or mechanical device that controls the pulse jet frequency. According to the setting of the control logic unit, the frequency of the jet is changed to adapt to different cleaning requirements.

5. The methanol-to-hydrogen purification device with a pipeline cleaning structure according to claim 3 is characterized in that: The pure water flushing module also includes a filtering system; the pure water flushing module is used to flush the pipeline after the abrasive flushing module to remove the residual abrasive and impurities in the pipeline; The filtration system is used to filter the pure water in the water tank to ensure that the ejected water is pure and free of impurities; The water tank is used to store pure water for flushing, and its capacity is determined according to the length of the pipeline and cleaning requirements.

6. The methanol-to-hydrogen purification device with a pipeline cleaning structure according to claim 3, characterized in that: The acoustic emission detection module includes a plurality of acoustic emission sensors, a signal conditioning unit, a data acquisition unit and an analysis and processing module; the acoustic emission detection module is used to detect and analyze the acoustic emission signal emitted by the inner wall of the pipeline during the pipeline cleaning process, analyze the cleaning effect and determine whether the cleaning process is completed; Acoustic emission sensors are distributed at different locations on the outer wall of the pipeline to capture the acoustic emission signals generated by the inner wall of the pipeline during the cleaning process; The signal conditioning unit is connected to the acoustic emission sensor and is used to amplify, filter and condition the acoustic emission signal so as to facilitate collection by the data acquisition unit; A data acquisition unit, used for receiving the conditioned signal from the signal conditioning unit, and performing digital processing and storage; The analysis and processing module receives the digital signal from the data acquisition unit and performs signal processing and analysis.

7. The methanol-to-hydrogen purification device with a pipeline cleaning structure according to claim 6, characterized in that: The analysis and processing module receives the digital signal from the data acquisition unit and performs signal processing and analysis as follows: Preprocess the collected acoustic emission signals, including denoising, signal enhancement and trend removal, to improve signal quality; Extract characteristic parameters from the preprocessed acoustic emission signal, the characteristic parameters including signal amplitude, energy, frequency component, signal duration, rise time and count rate; The deep learning model is used to classify the acoustic emission signals, distinguishing between signals caused by the shedding of deposits during the cleaning process, pipeline vibration signals, and signals caused by environmental noise; When the signal caused by the shedding of deposits in the acoustic emission signal reaches or is lower than the preset threshold and remains stable for a period of time, it indicates that the deposits on the inner wall of the pipeline have basically fallen off and the cleaning process is completed.

8. The methanol-to-hydrogen purification device with a pipeline cleaning structure according to claim 7, characterized in that: The data preprocessing process is: Use wavelet transform or Fourier transform to remove noise from the signal, improve the signal-to-noise ratio by amplifying the useful components of the signal, and use Gaussian smoothing or other methods to remove linear or nonlinear trends in the signal; The following features are extracted during feature extraction: Signal amplitude: calculate the maximum and minimum values ​​of the signal; Energy: Calculates the total energy of the signal, specifically the integral of the square of the signal; Frequency component: Use Fourier transform to extract the spectrum of the signal and analyze the main frequency components; Signal duration: measures the duration of a signal; Rise time: The time interval from the start of a signal to the time it reaches its maximum value; Count rate: the number of events in a signal during the detection period; The deep learning model structure is as follows: Input layer: accepts data after preprocessing and feature extraction, determines the number of neurons in the input layer according to the characteristic dimension of the acoustic emission signal, and each feature requires one or more neurons; uses the normalization method Z-score normalization for normalization; Hidden layer: multiple hidden layers, using activation function ReLU or sigmoid for nonlinear transformation; The number of neurons in each layer is determined by the dimension of the data, and the number of neurons in the hidden layer is more than that in the input layer; First hidden layer: 256 neurons, ReLU activation function; second hidden layer: 128 neurons, ReLU activation function, dropout layer: dropout is applied after each hidden layer with a dropout rate of 0.5 to reduce overfitting; Classification layer: Output layer, using softmax or other activation functions for classification, maps the output of the last hidden layer to the number of categories C, applies the softmax activation function, and converts the output into a probability distribution; Output layer: The final classification results are output, with one neuron for each category corresponding to a type of acoustic emission signal.

9. The methanol-to-hydrogen purification device with a pipeline cleaning structure according to claim 8, characterized in that: The parameters of the deep learning model training process are as follows: Optimization algorithm: Use the Adam optimizer to adaptively adjust the learning rate to handle problems of different sizes; Learning rate: The initial learning rate is set to 0.001 and adjusted according to the performance of the validation set; Batch processing: Mini-batch gradient descent is used for training, and the batch size is set to 32 or 64; Iteration number: Determined based on the performance on the validation set, ranging from 100 to 5000 iterations.

10. A methanol hydrogen purification method, using the methanol hydrogen purification device with a pipeline cleaning structure according to any one of claims 1 to 9, characterized in that The specific steps include: a. Preparation: Check all components of the methanol-to-hydrogen purification unit, including the PSA unit, desorption / regeneration system, exhaust system, product hydrogen buffer tank, hydrogen compressor and hydrogen delivery pipeline to ensure they are in good working condition; Start the acoustic emission detection module of the pipeline cleaning module and perform initialization settings, including installation and calibration of the acoustic emission sensor; b.PSA purification process: The raw hydrogen is introduced into the PSA unit and the hydrogen is purified through adsorption and desorption processes; The activated carbon or special adsorbent inside the PSA unit begins to adsorb impurities in the raw hydrogen; Achieve continuous adsorption and desorption cycles through a dual-tower or quad-tower PSA unit; c. Desorption / regeneration process: The desorption / regeneration system introduces desorption gas to desorb impurities on the adsorbent; The desorbed gas is discharged through the exhaust system, and the components in the exhaust are monitored to ensure that impurities are effectively removed; d. Hydrogen buffering and compression: The purified hydrogen is stored in the product hydrogen buffer tank to stabilize pressure fluctuations; The hydrogen compressor compresses the hydrogen in the buffer tank to the required pressure; The compressed hydrogen is output through the hydrogen transmission pipeline, ready for further use or storage; e. Start pipeline cleaning: The pipeline cleaning module starts working, firstly by abrasive flushing, using a pulse controller to adjust the jet pressure and frequency to remove the deposits in the pipeline; f. Acoustic emission detection and analysis: During the cleaning process, the acoustic emission detection module captures the acoustic emission signals emitted by the inner wall of the pipeline in real time. The data acquisition unit transmits the conditioned signals to the analysis and processing module, which pre-processes and extracts features from the signals, and then uses a deep learning model to classify the signals. g. Cleaning effect evaluation: The analysis and processing module evaluates the cleaning effect according to the characteristic parameters of the acoustic emission signal. When the signal caused by the fall of sediment in the acoustic emission signal reaches or falls below the preset threshold and remains stable for a period of time, the analysis and processing module determines that the cleaning process is completed; h. Cleaning completion and subsequent processing: After the main controller receives the signal that the cleaning is completed, it stops the cleaning module and starts the pure water flushing module for the final flushing. After the cleaning is completed, the pipeline is dried to remove residual moisture. After the drying is completed, the methanol hydrogen purification device is restarted to continue the hydrogen purification process.

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