Formaldehyde gas generation system and control method thereof

Abstract

The invention relates to a formaldehyde gas generation system and a control method thereof. The formaldehyde gas generation system comprises a gas generator body, a concentration monitoring element, a flow monitoring element, a temperature and humidity monitoring element, a temperature control assembly and a control module, the gas generator body is provided with a liquid quantitative ring and a gas diffusion area, and the temperature control assembly is arranged on a communicating pipeline between the liquid quantitative ring and the gas diffusion area; the method is applied to a control module and comprises the following steps: acquiring current environment temperature and humidity data acquired by a temperature and humidity monitoring element, current carrier gas flow data acquired by a flow monitoring element, and current initial concentration data and current target concentration data acquired by a concentration monitoring element; inputting the data into a pre-configured temperature prediction model, and calculating to obtain target temperature adjustment data of the temperature control assembly; and controlling the temperature control assembly based on the target temperature adjustment data. By adopting the method, the problem of slow response of formaldehyde gas concentration control can be avoided.

Description

Technical Field

[0001] This application relates to the field of gas control technology, and in particular to a formaldehyde gas generating system and its control method. Background Art

[0002] Formaldehyde gas generators, as key equipment in environmental testing and industrial catalysis, typically generate formaldehyde gas by vaporizing a 37%–40% formaldehyde solution. This gas is then transported to a gas diffusion zone where it is diluted with background gas to the target concentration. The formaldehyde gas concentration control process is generally achieved through a traditional closed-loop feedback mechanism. This involves deploying a concentration sensor in the gas diffusion zone. When the actual concentration is detected to be lower than the target value, a feedback signal is sent, and the heating temperature is increased to increase vaporization; conversely, the temperature is decreased to reduce vaporization, thereby ensuring that the formaldehyde gas concentration in the diffusion zone reaches the target value.

[0003] However, this control mode suffers from lag in the coordinated control of temperature and concentration. Because there is a physical distance between the liquid vaporization zone and the gas diffusion zone, the concentration feedback signal needs to be detected, transmitted, and processed before triggering the temperature adjustment command; and the temperature adjustment itself must first affect the vaporization rate, then be transmitted to the gas diffusion zone via gas transport, and finally be detected. This series of steps creates multiple delays, resulting in a slow system response. To achieve the target concentration control accuracy, multiple adjustments are often required, thus reducing experimental or process efficiency.

[0004] Therefore, there is an urgent need to develop a formaldehyde gas generator control architecture to achieve efficient control of formaldehyde gas concentration. Summary of the Invention

[0005] The purpose of this application is to provide a formaldehyde gas generation system and its control method, aiming to solve the technical problem of slow response in formaldehyde gas concentration control in existing formaldehyde gas generation systems.

[0006] In a first aspect, this application provides a method for controlling formaldehyde gas generation. The formaldehyde gas generation system includes a gas generator body, a concentration monitoring element, a flow monitoring element, a temperature and humidity monitoring element, a temperature control component, and a control module. The gas generator body has a liquid metering loop and a gas diffusion zone. The temperature control component is located on a connecting pipe between the liquid metering loop and the gas diffusion zone. A carrier gas inlet pipe is connected to the liquid metering loop. The concentration monitoring element is located within the gas diffusion zone, the flow monitoring element is located within the carrier gas inlet pipe, and the temperature and humidity monitoring element is located outside the gas generator body. The control module communicates with the concentration monitoring element, the flow monitoring element, the temperature and humidity monitoring element, and the temperature control component. The method is applied to the control module and includes: The system acquires the current ambient temperature and humidity data collected by the temperature and humidity monitoring element, the current carrier gas flow rate data collected by the flow rate monitoring element, the current initial concentration data collected by the concentration monitoring element, and the current target concentration data. The current ambient temperature and humidity data, the current carrier gas flow rate data, the current initial concentration data, and the current target concentration data are input into a pre-configured temperature prediction model to calculate the target temperature control data of the temperature control component. The temperature control component is controlled based on the target temperature control data and the actual temperature control data of the temperature control component.

[0007] In one embodiment, the steps for constructing the temperature prediction model include: Collect historical ambient temperature and humidity data, historical carrier gas flow rate data, historical initial concentration data, historical target concentration data, and corresponding historical target temperature control data from the historical operation of the formaldehyde gas generation system to construct a dataset; Based on the dataset, a regression model is trained using the gradient boosting decision tree algorithm to obtain the temperature prediction model. The regression model takes ambient temperature, ambient humidity, initial concentration, target concentration, and carrier gas flow rate as input features and target temperature control data as output labels.

[0008] In one embodiment, the temperature prediction model satisfies the following formula: T target = T base ( Q z )+ K h × H env + K t × T env + K c ×( C target - C initial ); in, T target Characterized as target temperature control data; Q z This is represented by the current carrier gas flow rate data; T base ( Q z ) characterized as Q z The basic temperature control function for input variables; K hCharacterized as the environmental humidity compensation coefficient; H env Represented as current ambient humidity data; K t Characterized as the environmental temperature compensation coefficient; T env Represented as current ambient temperature data; K c Characterized as the concentration compensation coefficient; C target Characterized as current target concentration data; C initial This is represented by the current initial concentration data.

[0009] In one embodiment, the basic temperature control function T base ( Q z The following conditions must be met: T base ( Q z The function value of ) varies with Q z It increases and decreases monotonically; T base ( Q z The first derivative of ) dT base / dQ z It is negative, and its absolute value increases with... Q z Increases and decreases.

[0010] In one embodiment, after obtaining the current initial concentration data, the current target concentration data, and the current carrier gas flow rate data, the method further includes: The current initial concentration data and the current target concentration data are input into the pre-configured flow prediction model to calculate the target carrier gas flow rate data in the carrier gas inlet pipe. Based on the target carrier gas flow rate data and the current carrier gas flow rate data, the gas flow rate in the carrier gas inlet pipe is controlled.

[0011] In one embodiment, the flow prediction model further calculates target air flow data in the air intake pipe and target bypass flow data in the bypass intake pipe based on the input current initial concentration data and the current target concentration data; the formaldehyde gas generation system also includes a zero-stage air generator, which is connected to the carrier gas intake pipe and connected to the connecting pipe between the temperature control component and the gas diffusion zone through the air intake pipe, and connected to the gas diffusion zone through the bypass intake pipe; The method further includes: Based on the target airflow data and the target bypass airflow data, the airflow output from the zero-stage air generator to the air intake pipe and the bypass air intake pipe are controlled respectively.

[0012] In one embodiment, the traffic prediction model satisfies the following formula: Q z-target =Q vapor × (α+β × e -γ•∣ΔC∣ ) ,in Q vapor =C target × Q ref , ΔC=C target -C initial ; Q k-target =Q base × (1+K p × ΔC) ; Q p-target =max(0 , η × (-ΔC) × Q ref ) ; in, Q z-target Characterized as target carrier gas flow rate data; Q k-target Characterized as target airflow data; Q p-target Characterized as target bypass traffic data; Q vapor Characterized as the baseline vaporization flow rate; Qref Characterized as the system's reference total flow rate; α、β Characterized as the attenuation coefficient, satisfying α+β=1 ; γ Characterized as the decay rate coefficient, satisfying γ>0 ; Q base Characterized by basic airflow rate; K p Characterized as a proportionality coefficient; η Characterized as a dilution factor.

[0013] In one embodiment, the method further includes: When the formaldehyde gas generating system is detected to have completed its gas generation task, the regular cleaning mode is activated. The regular cleaning mode first flushes the liquid metering ring with high-pressure gas output from the zero-stage air generator, and then controls the zero-stage air generator and the temperature control component to purge the gas diffusion area with low-pressure gas at 50-60°C until the residual formaldehyde detection value drops below the first safety threshold. And / or, if the deviation between the current initial concentration data and the current target concentration data is detected to be greater than the second safety threshold for a preset time, a deep cleaning mode is activated; the deep cleaning mode controls the zero-level air generator and the temperature control component to flush the gas diffusion area with gas at 95-100°C, and to assist in adsorption by the adsorbent material coated on the inner wall of the pipe, until the residual formaldehyde detection value drops below the third safety threshold.

[0014] Secondly, this application also provides a formaldehyde gas generating system, including a gas generator body, a concentration monitoring element, a flow monitoring element, a temperature and humidity monitoring element, a temperature control component, and a control module. The gas generator body is provided with a liquid metering loop and a gas diffusion zone. The temperature control component is located on a connecting pipe between the liquid metering loop and the gas diffusion zone. A carrier gas inlet pipe is connected to the liquid metering loop. The concentration monitoring element is located in the gas diffusion zone, the flow monitoring element is located in the carrier gas inlet pipe, and the temperature and humidity monitoring element is located outside the gas generator body. The control module communicates with the concentration monitoring element, the flow monitoring element, the temperature and humidity monitoring element, and the temperature control component. The control module is used to acquire the current ambient temperature and humidity data collected by the temperature and humidity monitoring element, the current carrier gas flow rate data collected by the flow monitoring element, the current initial concentration data collected by the concentration monitoring element, and the current target concentration data; input the current ambient temperature and humidity data, the current carrier gas flow rate data, the current initial concentration data, and the current target concentration data into a pre-configured temperature prediction model to calculate the target temperature control data of the temperature control component; and control the temperature control component based on the target temperature control data and the actual temperature control data of the temperature control component.

[0015] In one embodiment, the formaldehyde gas generating system further includes a zero-stage air generator, which is connected to the carrier gas inlet pipe and connected to the connecting pipe between the temperature control component and the gas diffusion zone via the air inlet pipe, and connected to the gas diffusion zone via a bypass inlet pipe. The control module is further configured to input the current initial concentration data and the current target concentration data into a pre-configured flow prediction model to calculate the target carrier gas flow rate data in the carrier gas inlet pipe, the target air flow rate data in the air inlet pipe, and the target bypass flow rate data in the bypass inlet pipe; control the air flow rate in the carrier gas inlet pipe based on the target carrier gas flow rate data and the current carrier gas flow rate data; and control the air flow rate output from the zero-stage air generator to the air inlet pipe and the bypass inlet pipe based on the target air flow rate data and the target bypass flow rate data, respectively.

[0016] One of the above technical solutions has the following advantages or beneficial effects: by introducing predictive temperature control (PTC) into the entire control system, a predictive feedforward-feedback composite control mechanism is constructed, fundamentally solving the multiple delay problems of the traditional closed-loop feedback mode. Specifically, by introducing a temperature prediction model based on multi-parameter fusion, using ambient temperature and humidity, carrier gas flow rate, current concentration, and target concentration as collaborative input variables, it can actively and in real time predict the optimal vaporization temperature required for the target concentration, i.e., the target temperature control data. Before the gas concentration changes, the power and other parameters of the temperature control component are adjusted in advance, allowing for precise intervention before the gas enters the gas diffusion zone, rather than passively waiting for concentration feedback, thus avoiding the problem of slow concentration control response. Attached Figure Description

[0017] Figure 1 This is an application environment diagram of a formaldehyde gas generation control method in one embodiment; Figure 2 This is a flowchart illustrating a formaldehyde gas generation control method in one embodiment; Figure 3This is a flowchart illustrating a formaldehyde gas generation control method in another embodiment; Figure 4 This is an internal structure diagram of the control module in one embodiment. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0019] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0020] The formaldehyde gas generation control method provided in this application can be applied to, for example... Figure 1 In the application environment shown, it can be specifically applied to Figure 1 In the control module of the system shown. Figure 1A specific embodiment of a formaldehyde gas generating system is provided. The system may include a gas generator body, a concentration monitoring element 110, a flow monitoring element 108, a temperature and humidity monitoring element 109, a temperature control component 103, and a control module 106. The gas generator body is provided with a liquid metering ring 102 and a gas diffusion zone 104. The liquid metering ring 102 can be used to accurately measure a small-volume ring tube of formaldehyde solution. The gas diffusion zone 104 may be configured with a large chamber to allow formaldehyde vapor to be fully mixed with the carrier gas. The temperature control component 103 is located on the connecting pipe A between the liquid metering ring 102 and the gas diffusion zone 104. By directly deploying the temperature control component 103 on the connecting pipe A between the liquid metering ring 102 and the gas diffusion zone 104, rather than at the liquid vaporization source, this design allows temperature regulation to act on the formaldehyde vapor transmission path. When the temperature control component 103 increases the heating temperature, it can accelerate the diffusion rate of formaldehyde molecules in the pipe and shorten the time for vapor to be transferred to the diffusion zone. When the temperature control component 103 decreases the heating temperature, it can effectively suppress vapor diffusion and achieve rapid braking. A carrier gas inlet pipe B is connected to the liquid metering loop 102. The carrier gas inlet pipe B can be used to introduce carrier gas such as nitrogen or air. The concentration monitoring element 110 is located in the gas diffusion zone 104, the flow monitoring element 108 is located in the carrier gas inlet pipe B, and the temperature and humidity monitoring element 109 is located outside the gas generator body. The figure shows that it is located outside the gas diffusion zone 104, but it can also be located in other positions, as long as it can measure the ambient temperature and humidity of the gas generator body. The control module 106 communicates with the concentration monitoring element 110, the flow monitoring element 108, the temperature and humidity monitoring element 109, and the temperature control component 103.

[0021] The control method based on this formaldehyde gas generation system may include: the control module 106 acquiring in real time the current ambient temperature and humidity data collected by the temperature and humidity monitoring element 109, the current carrier gas flow rate data collected by the flow monitoring element 108, the current initial concentration data in the gas diffusion zone collected by the concentration monitoring element 110, and the current target concentration data set by the user. Subsequently, the control module 106 can input these data into a pre-configured temperature prediction model for calculation. The temperature prediction model can be an algorithm or formula stored in the memory of the control module 106. It outputs the target temperature control data of the temperature control component 103, which can be understood as the target heating temperature. Finally, the control module 106 compares the target temperature control data with the actual temperature control data fed back by the temperature control component 103, and adjusts the power output of the temperature control component 103 through a PID algorithm or other control algorithm, such as increasing the heating power, until the actual temperature reaches the target temperature. By monitoring the environment, flow rate, and concentration in real time and using a model to predict the optimal temperature, precise control of the formaldehyde gas generation process can be achieved, ensuring that the output gas concentration quickly and stably reaches the target value, reducing the impact of environmental fluctuations.

[0022] In at least one embodiment, Figure 1 The system shown may also include a zero-stage air generator 105, which is connected to a carrier gas inlet pipe B. Specifically, the carrier gas inlet pipe B may be connected between the zero-stage air generator 105 and the liquid metering ring 102 to provide dry and clean carrier gas with a flow rate range of 0.1–5 L / min. The zero-stage air generator 105 can also be connected to the connecting pipe A between the temperature control component 103 and the gas diffusion zone 104 via the air inlet pipe C, so as to mix clean air into the gas diffusion zone 104 before formaldehyde vapor enters the gas diffusion zone 104, thereby achieving primary dilution and fine-tuning of the concentration of vaporized formaldehyde gas, reducing the local concentration of formaldehyde vapor and preventing high-temperature gas from condensing in the diffusion zone; the zero-stage air generator 105 can also be connected to the gas diffusion zone 104 via the bypass inlet pipe D, so as to directly inject clean air into the downstream output end of the gas diffusion zone 104, thereby achieving rapid correction and wide-range adjustment of the final output gas concentration. If a significant reduction in concentration is required, the bypass high-pressure air can dilute it instantly, with a response speed faster than temperature control.

[0023] Specifically, the gas generator body may also include a liquid sampling pump 101 connected to the liquid metering loop 102, the inlet formed in the liquid metering loop 102 being the... Figure 1 Port 1; the volume of the liquid metering ring 102 is adjustable, with an adjustment range of 0.5–5 μL. An exhaust pipe 107 can be installed on the liquid metering ring 102, and the exhaust port formed at the liquid metering ring 102 is the [unclear - likely a port number]. Figure 1 Port 2 is located in the gas diffusion zone 104. Port 3 is formed on the liquid metering ring 102 via carrier gas inlet pipe B. Port 4 is formed on the connecting pipe A via air inlet pipe C. Port 5 is formed on the outer wall of the gas diffusion zone 104 via bypass inlet pipe D. An exhaust port is also provided on the outer wall of the gas diffusion zone 104. Figure 1 Port 6 on the road.

[0024] It should be noted that, in some embodiments, a piezoelectric ceramic micro-vibrator can be installed at the bottom of the gas diffusion zone 104. Optionally, a spring buffer pad 111 can also be installed between the outside of the gas diffusion zone 104 and the zero-level air generator 105. By installing a spring buffer pad on the base, the mixing efficiency of the entire gas diffusion zone 104 can be improved.

[0025] The connecting pipe between the liquid metering loop 102 and the gas diffusion zone 104 is preferably a graphene-coated copper pipe, which has good thermal conductivity. The concentration monitoring element 110 can be an electrochemical sensor or a photoionization detector, and its sampling frequency can be configured to 10Hz. The flow monitoring element 108 can be a mass flow meter. The temperature and humidity monitoring element 109 can be an integrated temperature and humidity sensor, or temperature and humidity can be monitored by separate sensors. The temperature control component 103 can be a heating belt wrapped around the connecting pipe A and its temperature controller. The control module 106 can be a PLC or an embedded computer for communication with all monitoring elements and actuators. The zero-stage air generator 105 can be connected to the carrier gas inlet pipe B, the air inlet pipe C (connected to the outlet of the temperature control component 103), and the bypass inlet pipe D (directly connected to the gas diffusion zone 104) via a three-way valve.

[0026] Specifically, after being precisely metered by the liquid metering loop 102, the liquid formaldehyde is pushed by the carrier gas to the temperature control component 103 for vaporization; the vaporized gas is fully mixed and diffused with the zero-level air in the gas diffusion zone 104, and the concentration data is fed back to the control module 106 in real time; the control module 106 can dynamically adjust parameters such as the temperature control temperature and the flow rate of the three gas channels to achieve closed-loop concentration control.

[0027] In one embodiment, such as Figure 2 As shown, a method for controlling formaldehyde gas generation is provided, which can be applied to... Figure 1 Taking the formaldehyde gas generation system in the example, the following steps are included: S202, acquire the current ambient temperature and humidity data collected by the temperature and humidity monitoring element, the current carrier gas flow rate data collected by the flow monitoring element, the current initial concentration data and the current target concentration data collected by the concentration monitoring element.

[0028] S204: Input the current ambient temperature and humidity data, current carrier gas flow rate data, current initial concentration data, and current target concentration data into the pre-configured temperature prediction model to calculate the target temperature control data of the temperature control component.

[0029] The temperature prediction model can be an algorithm or formula stored in the memory of the control module. That is, it can be trained by a training dataset composed of historical data, or it can be implemented by a formula model with clear physical meaning.

[0030] S206 controls the temperature control component based on the target temperature control data and the actual temperature control data of the temperature control component.

[0031] In this embodiment, the controller can perform the following judgments: if the deviation between the target temperature control data and the actual temperature control data is within a set value, the controller controls the heating temperature of the temperature control component to maintain the actual temperature control data; if the deviation between the target temperature control data and the actual temperature control data is higher than the set value, the controller controls the heating temperature of the temperature control component to rise to the target temperature control data when the target temperature control data is higher than the actual temperature control data; and if the target temperature control data is lower than the actual temperature control data, the controller controls the heating temperature of the temperature control component to decrease to the target temperature control data.

[0032] In the above embodiments of this application, the executing entity can be a control module, control element, or control platform, which can be located locally or in the cloud. Of course, the executing entity can also be selected and changed according to the actual situation.

[0033] In the formaldehyde gas generation control method described in the above embodiments, predictive temperature control (PTC) is introduced into the entire control system to construct a predictive feedforward-feedback composite control mechanism, fundamentally solving the multiple delay problems of the traditional closed-loop feedback mode. Specifically, by introducing a temperature prediction model based on multi-parameter fusion, ambient temperature and humidity, carrier gas flow rate, current concentration, and target concentration are used as collaborative input variables to directly calculate the optimal temperature setpoint, rather than passively waiting for concentration feedback. It should be explained that traditional methods must wait for the gas to be transported from the liquid vaporization zone to the gas diffusion zone and detected before temperature adjustment can be triggered, which involves physical transmission delay and sensor response delay. In contrast, this solution actively and in real-time predicts the optimal vaporization temperature required for the target concentration, i.e., the target temperature adjustment data, through the temperature prediction model. Before the concentration changes, the power and other parameters of the temperature control component are adjusted in advance, so that the gas is precisely intervened before entering the diffusion zone. For example, when a user needs to increase the current concentration data from 10ppm to the target concentration of 50ppm, the temperature prediction model can instantly calculate the heating temperature of the temperature control component to be controlled at 65°C based on ΔC=40ppm, the current flow data, and environmental parameters, and execute it immediately without waiting for the diffusion zone concentration to detect an insufficient signal.

[0034] In one or more embodiments, the steps for constructing the temperature prediction model described above include: collecting historical ambient temperature and humidity data, historical carrier gas flow rate data, historical initial concentration data, historical target concentration data, and corresponding historical target temperature control data from the historical operation of the formaldehyde gas generation system to construct a dataset; training a regression model based on the dataset using a gradient boosting decision tree algorithm to obtain the temperature prediction model; the regression model uses ambient temperature, ambient humidity, initial concentration, target concentration, and carrier gas flow rate as input features, and target temperature control data as output labels.

[0035] A further implementation method includes the following steps in constructing a temperature prediction model: First, during system debugging or historical operation, a large number of historical data samples are collected, and the historical data samples are cleaned and processed to build a training dataset.

[0036] Each sample may include: historical ambient temperature and humidity data, historical carrier gas flow rate data, historical initial concentration data, historical target concentration data, and corresponding historical target temperature control data that has been verified to achieve the target concentration. The historical ambient temperature and humidity data can be understood as the ambient temperature and humidity recorded by the temperature and humidity monitoring element for the current sample. The historical carrier gas flow rate data can be understood as the carrier gas flow rate measurement value collected by the flow monitoring element for the current sample. The historical initial concentration data can be understood as the concentration measurement value collected by the concentration monitoring element before the current sample was adjusted. The historical target concentration data can be understood as the target concentration set for the current sample. The historical target temperature control data can be understood as the optimal temperature setting value when the current sample reaches the target concentration and is in a stable state.

[0037] Secondly, a regression model can be trained on this dataset using the Gradient Boosting Decision Tree (GBDT) algorithm. This regression model uses five parameters—ambient temperature, ambient humidity, initial concentration, target concentration, and carrier gas flow rate—as input features, and the target temperature control data as the output label to be predicted. The training process learns the complex nonlinear relationship between these features and the optimal temperature setpoint by optimizing the loss function, preferably the mean squared error. The trained model is then the temperature prediction model and can be deployed into the control module.

[0038] By utilizing machine learning algorithms to automatically learn the optimal control strategy from historical data, complex nonlinear relationships can be captured, improving the accuracy and adaptability of temperature prediction models.

[0039] In one or more embodiments, the temperature prediction model described above satisfies the following formula: T target = T base ( Q z )+ K h × H env + K t × T env + K c ×( C target - C initial ); in,T target Characterized as target temperature control data; Q z This is represented by the current carrier gas flow rate data; T base ( Q z ) characterized as Q z The basic temperature control function for input variables; K h Characterized as the environmental humidity compensation coefficient; H env Represented as current ambient humidity data; K t Characterized as the environmental temperature compensation coefficient; T env Represented as current ambient temperature data; K c Characterized as the concentration compensation coefficient; C target Characterized as current target concentration data; C initial This is represented by the current initial concentration data.

[0040] It should be noted that the temperature prediction model at this time is a formulaic model, in which... T base ( Q z This can be understood as a system based on current carrier gas flow rate data. Q z The fundamental temperature control function, with the only input variable, reflects the effect of carrier gas flow rate on the vaporization temperature under standard environmental conditions. The temperature prediction model uses carrier gas flow rate as a key input; as the flow rate increases, the gas velocity increases and the transport delay shortens, but the heat gain per unit gas decreases. The model uses a function... T base ( Q z It can dynamically reduce the base temperature requirement and avoid control instability caused by sudden changes in flow rate in traditional methods.

[0041] K h , K t , K c All of these can be understood as preset coefficient constants, which can be calibrated through experiments.

[0042] This formula shows that the target temperature control data is composed of four parts: a base temperature dependent on carrier gas flow rate, an ambient humidity compensation term, an ambient temperature compensation term, and a concentration compensation term. It can compensate for ambient temperature and humidity disturbances on top of the base temperature to offset fluctuations in vaporization efficiency caused by the environment; and compensate for concentration changes (…). ΔC=C target -C initial The required heat, preventing concentration deviations from the source, for example when ΔC At its maximum, the model automatically outputs a higher temperature and injects excess steam in advance to offset transmission losses. ΔC A negative value indicates that the model can reduce the temperature, specifically as follows: Figure 3 As shown, by configuring the temperature prediction model as a formulaic model, its structure is clear, its physical meaning is explicit, it is easy to implement and debug in engineering, its calculation speed is fast, and its performance requirements for the control module are relatively low.

[0043] In other embodiments, the base temperature control function can be set as a constant. Since the boiling point of a 37% formaldehyde solution is approximately 100°C under standard atmospheric pressure, this constant can be set to 100°C. Using this constant as a benchmark value for temperature prediction provides a reference for subsequent temperature compensation calculations, simplifying the calculation process and making it suitable for scenarios with high requirements for algorithm efficiency. In this case, it can be understood that the carrier gas flow rate has no effect on the base temperature. The input to the temperature prediction model may not require the carrier gas flow rate, or the input may still include the carrier gas flow rate, but the carrier gas flow rate can appear as a compensation term for the base temperature.

[0044] In one or more embodiments, the above-described basic temperature control function T base ( Q z The following conditions must be met: T base ( Q z The function value of ) varies with Q z It increases and decreases monotonically; T base ( Q z The first derivative of ) dT base / dQ z It is negative, and its absolute value increases with... Q z Increases and decreases.

[0045] In this embodiment, the basic temperature control function T base ( Q z) Specific physical constraints must be met: First, its function value varies with the carrier gas flow rate. Q z The increase and monotonically decrease means that when the carrier gas flow rate... Q z As the temperature increases, the required baseline temperature decreases. Secondly, the first derivative... dT base / dQ z It is a negative value, and its absolute value increases with... Q z The decrease in temperature setting due to the increase in flow rate reflects a thermodynamic law: as the flow rate increases, the time the gas spends in the heating zone shortens, resulting in less heat gained per unit mass of gas. Therefore, a lower temperature setting is needed to avoid overheating. However, as the flow rate further increases, the sensitivity of temperature to flow rate (i.e., the absolute value of the first derivative) gradually decreases, and the change tends to level off. For example, T base (Q z )=A / (Q z +B)+C ,in A , B , C These can be positive coefficients obtained by fitting experimental data.

[0046] The constraints in the above embodiments can ensure T base (Q z ) It conforms to the basic physical principles of gas heat transfer and vaporization, such as the relationship between thermal saturated vapor pressure, residence time and heat transfer efficiency, thus making the prediction results of the temperature prediction model more consistent with the actual physical process and improving the reliability of the prediction.

[0047] In one or more embodiments, after obtaining the current initial concentration data, the current target concentration data, and the current carrier gas flow rate data, the formaldehyde gas generation control method further includes: inputting the current initial concentration data and the current target concentration data into a pre-configured flow prediction model to calculate the target carrier gas flow rate data in the carrier gas inlet pipe; and controlling the gas flow rate in the carrier gas inlet pipe based on the target carrier gas flow rate data and the current carrier gas flow rate data.

[0048] After acquiring the current initial concentration data, current target concentration data, and current carrier gas flow rate data, the control method also includes a flow feedforward control step, which can be further referred to. Figure 3 The control module inputs the current initial concentration data and the current target concentration data into another pre-configured flow prediction model for calculation. This flow prediction model can calculate based on the difference between the target concentration and the current concentration ( ΔC)The target carrier gas flow rate in the carrier gas inlet pipe is calculated. Then, the control module compares this target carrier gas flow rate with the current carrier gas flow rate collected by the flow monitoring element. Based on this deviation, the control module can control the actual air flow rate in the carrier gas inlet pipe by adjusting the proportional valve at the carrier gas inlet end or the carrier gas flow rate setpoint of the zero-stage air generator, so that it approaches the target carrier gas flow rate.

[0049] By adding direct feedforward control of the key input variable, carrier gas flow rate, to the temperature control, the system can respond more quickly to changes in the concentration target (especially when there are large changes), forming a synergy with the temperature control to further accelerate the process of the system reaching the target concentration and improve dynamic response performance.

[0050] In one or more embodiments, the above-described flow prediction model can calculate, based on the input current initial concentration data and current target concentration data, target airflow data in the air intake pipe and target bypass flow data in the bypass intake pipe. The formaldehyde gas generation system also includes a zero-stage air generator, which is connected to the carrier gas intake pipe and connected to the connecting pipe between the temperature control component and the gas diffusion zone via the air intake pipe, and connected to the gas diffusion zone via the bypass intake pipe. In one specific embodiment, the formaldehyde gas generation control method further includes controlling the airflow output from the zero-stage air generator to the air intake pipe and the bypass intake pipe, respectively, based on the target airflow data and the target bypass flow data.

[0051] A zero-stage air generator can produce dry, clean air free of organic matter. By introducing a zero-stage air generator and independently controllable three-way (carrier gas, air, and bypass) flow, the system's ability and range for regulating formaldehyde gas concentration are greatly enhanced. As described above, the air inlet pipe can be used for fine dilution in the low to medium concentration range, while the bypass inlet pipe enables rapid switching from high to low concentrations and stable output at extremely low concentrations. This configuration improves the system's control flexibility and applicability.

[0052] In one or more embodiments, the above traffic prediction model satisfies the following formula: Q z-target =Q vapor × (α+β × e -γ•∣ΔC∣ ) ,in Q vapor =C target × Q ref , ΔC=C target-C initial ; Q k-target =Q base × (1+K p × ΔC) ; Q p-target =max(0 , η × (-ΔC) × Q ref ) ; in, Q z-target Characterized as target carrier gas flow rate data; Q k-target Characterized as target airflow data; Q p-target Characterized as target bypass traffic data; Q vapor Characterized as the baseline vaporization flow rate, this variable represents the minimum effective carrier gas flow rate theoretically required to produce the target concentration of gas, which is obtained by multiplying the target concentration by the system reference total flow rate; Q ref Characterized as the total reference flow rate of the system, such as the optimal flow rate obtained based on the design of the gas diffusion zone; α、β Characterized as the attenuation coefficient, α、β These are pre-calibrated constants that satisfy... α+β=1 Optional, α=0.7 , β=0.3 ; γ Characterized as the decay rate coefficient, satisfying γ>0 .

[0053] It should be explained that the configuration index item e -γ•∣ΔC∣ It can make the concentration change range |ΔC| When the actual target carrier gas flow rate is large, Q z-target It will be lower than the baseline flow rate. Q vapor Because higher vaporization efficiency and transmission control precision are required when there are large concentration changes, reducing the carrier gas flow rate can simultaneously achieve the following objectives: prolonging the residence time of formaldehyde liquid in the heating zone (at the temperature control component), thereby increasing the saturated concentration of formaldehyde vapor per unit volume of carrier gas; reducing the carrier gas flow rate can also reduce the gas flow velocity, weakening the concentration diffusion loss during transmission. |ΔC| When the value is relatively small, i.e. in a fine-tuning scenario, configure the exponential term. e -γ•∣ΔC∣ This can makeQ z-target near Q vapor At this point, the system can prioritize maintaining flow stability to avoid excessive disturbance to the vaporization balance.

[0054] Q base Characterized by the base airflow, it can be understood as a preset constant; K p It is represented by a proportionality coefficient, which is a preset constant; η The dilution factor is a preset normal number, such as 0.8.

[0055] The combination of the above three sets of formulas forms a flow prediction model, providing a clear, calculable, and physically meaningful mathematical basis for three-way flow control. All constant parameters can be calibrated experimentally. The flow prediction model is easy to implement in control systems and can effectively support multi-way flow coordinated control strategies.

[0056] In one or more embodiments, the formaldehyde gas generation control method further includes: when the formaldehyde gas generation system is detected to have completed its gas generation task, activating a regular cleaning mode; the regular cleaning mode first flushes the liquid metering loop with high-pressure gas output from the zero-stage air generator, and then controls the zero-stage air generator and temperature control components to purge the gas diffusion area with low-pressure gas at 50-60°C until the residual formaldehyde detection value drops below the first safety threshold.

[0057] The standard cleaning mode can be automatically activated when the gas concentration in the gas diffusion zone reaches the target concentration and stabilizes for a specified time, or when a stop command is issued by the user. (See also...) Figure 1 The standard cleaning mode can be described as follows: First, open ports 2 and 3, and close the remaining ports. The zero-stage air generator can deliver high-pressure clean air to the liquid metering loop through the carrier air inlet pipe B to flush the liquid metering loop. The flushing time is not limited here and can be selected as 2 minutes. Then, close port 2 and open ports 4 and 6. Control the zero-stage air generator to switch to a lower pressure and control the temperature control component to heat the gas to 50-60℃. This temperature can promote the volatilization of residual formaldehyde and prevent polymer formation. This process of purging the gas diffusion area and connected pipelines continues, while the concentration monitoring element continuously monitors the residual formaldehyde concentration at the gas diffusion area outlet or the dedicated cleaning outlet. When the detected residual formaldehyde value drops below the first safety threshold, the purging can be stopped.

[0058] In one or more embodiments, the formaldehyde gas generation control method further includes: activating a deep cleaning mode when the deviation between the current initial concentration data and the current target concentration data is detected to be greater than a second safety threshold for a preset time; the deep cleaning mode controls a zero-level air generator and a temperature control component to flush the gas diffusion area with gas at 95-100°C, and to assist in adsorption by an adsorbent substance coated on the inner wall of the pipe, until the residual formaldehyde detection value drops below a third safety threshold.

[0059] Specifically, when the control module detects an anomaly in the concentration feedback control—specifically, the deviation between the current initial concentration data and the current target concentration data consistently exceeding a preset second safety threshold (e.g., 10% of the target concentration or 5 ppm absolute value) for a preset duration—where the second safety threshold can be set to 5-10% of the target concentration or a constant value, and the preset duration can be set to 5-20 minutes—this anomaly may indicate severe contamination or polymer blockage, in which case the deep cleaning mode will be automatically activated. (See also...) Figure 1 The specific steps are as follows: First, open ports 3, 4, and 6, control the zero-stage air generator to output clean air, and control the temperature control component to heat the gas to a high temperature of 95-100℃. The pressure can be higher than or equal to that of conventional cleaning. Use this high-temperature gas to flush the gas diffusion area and key pipelines. At the same time, utilize the pre-coated adsorbent materials (such as activated carbon coatings or certain polymer adsorbent materials) on the gas diffusion area and pipeline inner walls to enhance the adsorption and decomposition of stubborn residual formaldehyde or its polymers at high temperature. This process can continue until the residual formaldehyde detection value drops below the third safety threshold.

[0060] The aforementioned formaldehyde gas generation control method provides an automated, tiered cleaning solution. The regular cleaning mode quickly removes daily residues, maintaining a baseline cleanliness of the system; the deep cleaning mode addresses severe contamination or polymerization issues, restoring system performance. Combined with temperature control and formaldehyde adsorption materials, cleaning efficiency is significantly improved, maintenance needs are reduced, long-term operational stability and safety are guaranteed, and cross-contamination is avoided.

[0061] It should be understood that, for the foregoing method embodiments, although the steps in the flowcharts are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the method embodiments may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.

[0062] Based on the same inventive concept, this application also provides a formaldehyde gas generating system, including a gas generator body, a concentration monitoring element, a flow monitoring element, a temperature and humidity monitoring element, a temperature control component, and a control module. The gas generator body has a liquid metering loop and a gas diffusion zone. The temperature control component is located on the connecting pipe between the liquid metering loop and the gas diffusion zone. A carrier gas inlet pipe is connected to the liquid metering loop. The concentration monitoring element is located in the gas diffusion zone, the flow monitoring element is located in the carrier gas inlet pipe, and the temperature and humidity monitoring element is located outside the gas generator body. The control module communicates with the concentration monitoring element, the flow monitoring element, the temperature and humidity monitoring element, and the temperature control component. The control module is used to acquire the current ambient temperature and humidity data collected by the temperature and humidity monitoring element, the current carrier gas flow rate data collected by the flow monitoring element, the current initial concentration data collected by the concentration monitoring element, and the current target concentration data. The control module inputs the current ambient temperature and humidity data, the current carrier gas flow rate data, the current initial concentration data, and the current target concentration data into a pre-configured temperature prediction model to calculate the target temperature control data of the temperature control component. Based on the target temperature control data and the actual temperature control data of the temperature control component, the control module controls the temperature control component.

[0063] In one embodiment, the system further includes a zero-stage air generator connected to the carrier gas inlet pipe and connected to the connecting pipe between the temperature control component and the gas diffusion zone via an air inlet pipe, and connected to the gas diffusion zone via a bypass inlet pipe; the control module is also used to input the current initial concentration data and the current target concentration data into a pre-configured flow prediction model to calculate the target carrier gas flow rate data in the carrier gas inlet pipe, the target air flow rate data in the air inlet pipe, and the target bypass flow rate data in the bypass inlet pipe; control the air flow rate in the carrier gas inlet pipe based on the target carrier gas flow rate data and the current carrier gas flow rate data; and control the air flow rate output by the zero-stage air generator to the air inlet pipe and the bypass inlet pipe based on the target air flow rate data and the target bypass flow rate data, respectively.

[0064] For specific limitations on formaldehyde gas generation systems, please refer to the limitations on formaldehyde gas generation control methods mentioned above, which will not be repeated here.

[0065] In one embodiment, a control module is provided, the internal structure diagram of which can be as follows: Figure 4 As shown, the control module includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a formaldehyde gas generation control method. The display unit of the control module is used to form a visually visible image and can be a display screen, projection device, or virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the control module can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the housing of the control module, or external keyboards, touchpads, or mice, etc.

[0066] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the control module applied thereto. The specific control module may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0067] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0068] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification. In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0069] The terms “comprising” and “having”, and any variations thereof, in the embodiments herein are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or (module) units is not limited to the steps or units listed, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus.

[0070] In this article, "multiple" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0071] The terms "first" and "second" used herein are merely to distinguish similar objects and do not represent a specific ordering of objects. It is understood that "first" and "second" can be interchanged in a specific order or sequence where permissible. It should be understood that the objects distinguished by "first" and "second" can be interchanged where appropriate so that the embodiments described herein can be implemented in an order other than those illustrated or described herein.

[0072] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A control method for a formaldehyde gas generating system, characterized in that, The formaldehyde gas generating system includes a gas generator body, a concentration monitoring element, a flow monitoring element, a temperature and humidity monitoring element, a temperature control component, and a control module. The gas generator body has a liquid metering loop and a gas diffusion zone. The temperature control component is located on the connecting pipe between the liquid metering loop and the gas diffusion zone. A carrier gas inlet pipe is connected to the liquid metering loop. The concentration monitoring element is located in the gas diffusion zone, the flow monitoring element is located in the carrier gas inlet pipe, and the temperature and humidity monitoring element is located outside the gas generator body. The control module communicates with the concentration monitoring element, the flow monitoring element, the temperature and humidity monitoring element, and the temperature control component. The method is applied to the control module and includes: The system acquires the current ambient temperature and humidity data collected by the temperature and humidity monitoring element, the current carrier gas flow rate data collected by the flow rate monitoring element, the current initial concentration data collected by the concentration monitoring element, and the current target concentration data. The current ambient temperature and humidity data, the current carrier gas flow rate data, the current initial concentration data, and the current target concentration data are input into a pre-configured temperature prediction model to calculate the target temperature control data of the temperature control component. The temperature control component is controlled based on the target temperature control data and the actual temperature control data of the temperature control component.

2. The method according to claim 1, characterized in that, The steps for constructing the temperature prediction model include: Collect historical ambient temperature and humidity data, historical carrier gas flow rate data, historical initial concentration data, historical target concentration data, and corresponding historical target temperature control data from the historical operation of the formaldehyde gas generation system to construct a dataset; Based on the dataset, a regression model is trained using the gradient boosting decision tree algorithm to obtain the temperature prediction model. The regression model takes ambient temperature, ambient humidity, initial concentration, target concentration, and carrier gas flow rate as input features and target temperature control data as output labels.

3. The method according to claim 1, characterized in that, The temperature prediction model satisfies the following formula: T target = T base ( Q z )+ K h × H env + K t × T env + K c ×( C target - C initial )； in, T target Characterized as target temperature control data; Q z This is represented by the current carrier gas flow rate data; T base ( Q z ) characterized as Q z The basic temperature control function for input variables; K h Characterized as the environmental humidity compensation coefficient; H env Represented as current ambient humidity data; K t Characterized as the environmental temperature compensation coefficient; T env Represented as current ambient temperature data; K c Characterized as a concentration compensation coefficient; C target Characterized as current target concentration data; C initial This is represented by the current initial concentration data.

4. The method according to claim 3, characterized in that, The basic temperature control function T base ( Q z The following conditions must be met: T base ( Q z The function value of ) varies with Q z It increases and then monotonically decreases. T base ( Q z The first derivative of ) dT base / dQ z It is negative, and its absolute value increases with... Q z Increases and decreases.

5. The method according to claim 3 or 4, characterized in that, After obtaining the current initial concentration data, the current target concentration data, and the current carrier gas flow rate data, the method further includes: The current initial concentration data and the current target concentration data are input into the pre-configured flow prediction model to calculate the target carrier gas flow rate data in the carrier gas inlet pipe. Based on the target carrier gas flow rate data and the current carrier gas flow rate data, the gas flow rate in the carrier gas inlet pipe is controlled.

6. The method according to claim 5, characterized in that, The flow prediction model also calculates the target air flow rate in the air intake pipe and the target bypass flow rate in the bypass intake pipe based on the input current initial concentration data and the current target concentration data; the formaldehyde gas generation system also includes a zero-stage air generator, which is connected to the carrier gas intake pipe and connected to the connecting pipe between the temperature control component and the gas diffusion zone through the air intake pipe, and connected to the gas diffusion zone through the bypass intake pipe; The method further includes: Based on the target airflow data and the target bypass airflow data, the airflow output from the zero-stage air generator to the air intake pipe and the bypass air intake pipe are controlled respectively.

7. The method according to claim 6, characterized in that, The flow prediction model satisfies the following formula: Q z-target =Q vapor × (α+β × e -γ•∣ΔC∣ ) ,in Q vapor =C target × Q ref , ΔC=C target -C initial ; Q k-target =Q base × (1+K p × ΔC) ； Q p-target =max(0 ， η × (-ΔC) × Q ref ) ； in, Q z-target Characterized as target carrier gas flow rate data; Q k-target Characterized as target airflow data; Q p-target Characterized as target bypass traffic data; Q vapor Characterized as the baseline vaporization flow rate; Q ref Characterized as the system's reference total flow rate; α、β Characterized as the attenuation coefficient, satisfying α+β=1 ; γ Characterized as the decay rate coefficient, satisfying γ>0 ; Q base Characterized by basic airflow rate; K p Characterized as a proportionality coefficient; η Characterized as a dilution factor.

8. The method according to claim 6 or 7, characterized in that, The method further includes: When the formaldehyde gas generating system is detected to have completed its gas generation task, the regular cleaning mode is activated. The regular cleaning mode first flushes the liquid metering ring with high-pressure gas output from the zero-stage air generator, and then controls the zero-stage air generator and the temperature control component to purge the gas diffusion area with low-pressure gas at 50-60°C until the residual formaldehyde detection value drops below the first safety threshold. And / or, if the deviation between the current initial concentration data and the current target concentration data is detected to be greater than the second safety threshold for a preset time, a deep cleaning mode is activated; the deep cleaning mode controls the zero-level air generator and the temperature control component to flush the gas diffusion area with gas at 95-100°C, and to assist in adsorption by the adsorbent material coated on the inner wall of the pipe, until the residual formaldehyde detection value drops below the third safety threshold.

9. A formaldehyde gas generating system, characterized in that, The device includes a gas generator body, a concentration monitoring element, a flow monitoring element, a temperature and humidity monitoring element, a temperature control component, and a control module. The gas generator body has a liquid metering loop and a gas diffusion zone. The temperature control component is located on the connecting pipe between the liquid metering loop and the gas diffusion zone. A carrier gas inlet pipe is connected to the liquid metering loop. The concentration monitoring element is located in the gas diffusion zone, the flow monitoring element is located in the carrier gas inlet pipe, and the temperature and humidity monitoring element is located outside the gas generator body. The control module communicates with the concentration monitoring element, the flow monitoring element, the temperature and humidity monitoring element, and the temperature control component. The control module is used to acquire the current ambient temperature and humidity data collected by the temperature and humidity monitoring element, the current carrier gas flow rate data collected by the flow monitoring element, the current initial concentration data collected by the concentration monitoring element, and the current target concentration data; and input the current ambient temperature and humidity data, the current carrier gas flow rate data, the current initial concentration data, and the current target concentration data into a pre-configured temperature prediction model to calculate the target temperature adjustment data of the temperature control component. The temperature control component is controlled based on the target temperature control data and the actual temperature control data of the temperature control component.

10. The formaldehyde gas generating system according to claim 9, characterized in that, It also includes a zero-stage air generator, which is connected to the carrier gas inlet pipe and connected to the connecting pipe between the temperature control component and the gas diffusion zone through the air inlet pipe, and connected to the gas diffusion zone through the bypass air inlet pipe; The control module is also used to input the current initial concentration data and the current target concentration data into a pre-configured flow prediction model to calculate the target carrier gas flow rate data in the carrier gas inlet pipe, the target air flow rate data in the air inlet pipe, and the target bypass flow rate data in the bypass inlet pipe. Based on the target carrier gas flow rate data and the current carrier gas flow rate data, the gas flow rate in the carrier gas inlet pipe is controlled; Based on the target airflow data and the target bypass airflow data, the airflow output from the zero-stage air generator to the air intake pipe and the bypass air intake pipe are controlled respectively.

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