Method and device for dynamically detecting moisture content of fluidized bed air inlet
By simultaneously acquiring relative humidity, temperature, and total pressure of humid air in the fluidized bed inlet duct, and performing hysteresis compensation and total pressure correction, the problems of hysteresis and accuracy in inlet air humidity detection are solved, enabling timely and accurate adjustment of fluidized bed inlet air humidity and ensuring stable operation of the fluidized bed.
Patent Information
- Application Number
- CN202611126208.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-07-28
- Publication Date
- 2026-08-25
AI Technical Summary
Existing methods for detecting the moisture content of incoming air are lagging and lack accuracy when operating conditions change rapidly, resulting in inaccurate humidity regulation of fluidized bed incoming air and difficulty in maintaining it within a suitable humidity window.
Relative humidity, temperature, and total pressure of humid air are acquired simultaneously at the same sampling time. The moisture content of the incoming air is dynamically detected through lag time constant compensation and total pressure enhancement correction. Lag compensation and early warning are performed using first-order prediction-correction recursion and state observer to ensure the timeliness and accuracy of detection.
Under conditions of rapid changes in operating conditions and pressure fluctuations, timely and accurate detection of the moisture content of the incoming air was achieved, improving the dynamic response speed and steady-state accuracy, and ensuring the stable operation of the fluidized bed.
Smart Images
Figure CN122631841A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of humidity detection, and in particular to a method and apparatus for dynamic detection of humidity content in fluidized bed inlet air. Background Technology
[0002] Fluidized beds are widely used in processes such as drying, granulation, and coating. The moisture content of the inlet air, acting as the carrier for fluidization and heat and mass transfer, directly affects the fluidization state, product quality, and operating energy consumption. Excessively humid inlet air weakens drying capacity, causes material agglomeration, and may even lead to bed collapse, while excessively dry inlet air may result in over-drying and static electricity accumulation. Therefore, during fluidized bed operation, it is necessary to monitor the moisture content of the inlet air in real time and adjust dehumidification, humidification, and airflow accordingly in a closed-loop manner to maintain the fluidization process within a suitable humidity window.
[0003] The humidity of the incoming air fluctuates rapidly with changes in ambient weather, dehumidification equipment operation, and filter resistance, while the temperature and pressure conditions of the fluidized bed air inlet duct vary considerably. This requires the detection system to not only keep pace with the actual humidity when operating conditions change rapidly, but also to maintain the accuracy of moisture content conversion at different altitudes and pressures, placing high demands on the dynamic detection of the incoming air moisture content.
[0004] Existing methods for detecting the moisture content of incoming air either directly collect relative humidity, temperature, and a fixed atmospheric pressure and calculate the moisture content based on the partial pressure relationship, or assume relative humidity to be saturated in situations such as steam without actually measuring the relative humidity. Because relative humidity sensors generally have inherent response lag, their readings lag behind the actual humidity when the incoming air humidity changes rapidly. At the same time, the total pressure of the humid air fluctuates with altitude and filter resistance, but is still calculated using a fixed atmospheric pressure instead of the saturated water vapor pressure. This results in the detected moisture content being both lagging behind the actual value and having the total pressure deviation superimposed. Consequently, dehumidification, humidification, and closed-loop airflow regulation based on this moisture content exhibit slow response and insufficient accuracy, making it difficult to stably maintain the fluidized bed incoming air within a suitable humidity window. Summary of the Invention
[0005] In order to detect the moisture content of the incoming air in a timely and accurate manner when the air intake conditions change rapidly, and to avoid inaccurate detection values and slow closed-loop regulation caused by the lag of the relative humidity sensor and fluctuations in total pressure, this application provides a method and device for dynamic detection of moisture content in fluidized bed incoming air.
[0006] Firstly, this application provides a method for dynamically detecting the moisture content of fluidized bed inlet air, which adopts the following technical solution: A method for dynamically detecting the moisture content of inlet air in a fluidized bed includes the following steps: S1. Using a relative humidity sensor, a temperature sensor, and an absolute pressure sensor installed in the air inlet duct, the relative humidity, temperature, and total pressure of the humid air inlet are simultaneously acquired at the same sampling time; the hysteresis time constant of the relative humidity sensor is determined based on the temperature, and the compensated relative humidity is reconstructed based on the relative humidity and the rate of change of relative humidity; S2. Determine the saturated water vapor pressure based on the relationship between temperature and saturated water vapor pressure, and apply a total pressure enhancement correction to the saturated water vapor pressure based on the total pressure of moist air to obtain the corrected saturated water vapor pressure; S3. Determine the actual water vapor partial pressure of the intake air based on the compensated relative humidity and the corrected saturated water vapor pressure; S4. Determine the moisture content of the intake air based on the actual water vapor partial pressure and the difference between the total pressure of humid air and the actual water vapor partial pressure; S5. Output the humidity level to the controller to adjust the dehumidification, humidification, or airflow of the incoming air.
[0007] By adopting the above technical solution, relative humidity, temperature, and total pressure of humid air are acquired synchronously at the same sampling time, so that the three correspond to the same air intake state, avoiding phase errors introduced by asynchronous sampling. Before determining the moisture content, the hysteresis time constant of the relative humidity sensor is determined based on the temperature, and the compensated relative humidity is reconstructed from the readings and their rate of change, so that the relative humidity under rapidly changing operating conditions no longer lags behind the true value. At the same time, a total pressure enhancement correction is applied to the saturated water vapor pressure according to the total pressure of humid air, so that the total pressure deviation caused by changes in altitude and filter resistance is included in the partial pressure conversion. Thus, the moisture content of the intake air can still be obtained in a timely and accurate manner under conditions of rapid changes in operating conditions and pressure fluctuations, providing a reliable basis for closed-loop regulation of dehumidification, humidification, and air volume.
[0008] Optionally, the compensated relative humidity is obtained through a first-order prediction-correction recursion. The first-order prediction-correction recursion makes an advance prediction of the relative humidity based on the lag time constant, and corrects the advance prediction with the measured value of the relative humidity, in order to replace the direct differentiation of the rate of change of the relative humidity.
[0009] By adopting the above technical solution, the direct differentiation of the reading is replaced by prediction-correction recursion, which suppresses the amplification of sampling noise by direct differentiation and keeps the hysteresis compensation stable under noisy readings.
[0010] Optionally, under the condition that the relative humidity of the incoming air is in a steady state, the estimated lag time constant of the relative humidity sensor is obtained by back-calculating the prediction residual between the measured value of the relative humidity and the advanced prediction in the first-order prediction-correction recursion. When the deviation between the estimated lag time constant and the lag time constant exceeds the preset deviation threshold, an aging warning for the relative humidity sensor is output.
[0011] By adopting the above technical solution, the actual hysteresis time constant of the sensor can be identified online using the predictive residual under steady state, so that the hysteresis change caused by sensor aging can be detected and warned in a timely manner.
[0012] Optionally, when the deviation does not exceed the preset deviation threshold, the estimated lag time constant is used to progressively correct the lag time constant as the lag time constant used in the subsequent first-order prediction-correction recursion; when the deviation exceeds the preset deviation threshold, progressive correction is stopped and an aging warning is output.
[0013] By adopting the above technical solution, normal drift and aging are distinguished by a two-level threshold. Within the normal range, the compensation parameters are gradually corrected with the estimated value to maintain the compensation accuracy. When the limit is exceeded, the correction is stopped and an early warning is issued to avoid mistaking aging for normal drift and continuing to correct it.
[0014] Optionally, the lag time constant and the predictor gain used in the first-order predictor-corrector recursion are scheduled online based on the rate of change of temperature and relative humidity.
[0015] By adopting the above technical solution, the compensation parameters can be adjusted online according to the rate of change of temperature and humidity, so that the hysteresis compensation can match the actual response characteristics of the sensor in a wide temperature range and at different rates of change.
[0016] Optionally, when the reading of the absolute pressure sensor exceeds the preset range or a sudden change occurs, the backup estimated value of the total humid air pressure is used to replace the reading of the absolute pressure sensor to participate in the determination of the corrected saturated water vapor pressure, and a fault alarm of the absolute pressure sensor is output.
[0017] By adopting the above technical solution, when the barometer reading is abnormal, the total pressure enhancement correction is maintained by the backup estimated value, so that the moisture content detection will not be interrupted or inaccurate during barometer failure, and a fault alarm will be given simultaneously.
[0018] Optionally, during periods when the absolute pressure sensor reading is normal, the slow drift trend of the total pressure of humid air is identified, and when the absolute pressure sensor reading exceeds the preset range or a sudden change occurs, a backup estimate is obtained by extrapolation based on the slow drift trend.
[0019] By adopting the above technical solution, the total pressure slow drift trend identified during the healthy period is used to extrapolate the backup estimate, so that the total pressure estimate during the fault period conforms to the gradual change law of altitude and filter resistance, thereby improving the reliability of the backup estimate.
[0020] Optionally, during the period when the backup estimate is used, the extrapolation uncertainty of the backup estimate accumulated over the duration can be assessed, and the intake air volume can be limited when the extrapolation uncertainty exceeds a preset limit.
[0021] By adopting the above technical solution, the extrapolation uncertainty is cumulatively assessed as the backup estimate continues for a long period of time, and the air volume is tightened when the uncertainty is too large, so as to avoid making large adjustments based on the moisture content that may be deviated when the total pressure estimate is inaccurate for a long period of time.
[0022] Optionally, the rate of change is determined based on the difference between temperature and total humid air pressure between adjacent sampling periods, and the sampling period obtained synchronously is dynamically adjusted between the upper and lower limits of the preset period according to the rate of change. When the temperature and total humid air pressure change rapidly, a shorter period is taken, and when they are stable, a longer period is taken.
[0023] By adopting the above technical solution, the sampling period can be made adaptive to the rate of change of operating conditions. When the conditions change rapidly, the sampling frequency is increased to follow the humidity changes, and when the conditions are stable, the sampling frequency is reduced to reduce power consumption.
[0024] Optionally, the disturbance of the total pressure of moist air is divided into fast-changing components and slow-changing components according to the time scale. The slow-changing components are corrected by long-period baseline estimation, and the fast-changing components are directly tracked by synchronous acquisition, so that the slow-changing baseline drift caused by altitude or filter resistance is not filtered out as noise.
[0025] By adopting the above technical solution, the slow-changing baseline of total pressure is separated from the fast-changing disturbance, so that the slow drift caused by altitude and filter resistance is retained rather than filtered out, thus improving the accuracy of total pressure estimation.
[0026] Optionally, the window length for applying the moving average filter to the moisture content can be dynamically adjusted based on the variation of moisture content over the most recent sampling periods, increasing the window when the moisture content is stable and decreasing the window when the moisture content changes rapidly.
[0027] By adopting the above technical solution, the filter window adapts to the change in moisture content, enhancing smoothness when the output is stable and shortening lag when the output changes rapidly, thus balancing output stability and responsiveness.
[0028] Optionally, in response to the moisture content falling within a preset accuracy band centered on the target moisture content, the current dehumidification, humidification, or airflow setting is maintained, and adjustments are made only when the moisture content exceeds the preset accuracy band.
[0029] By adopting the above technical solution, the frequent adjustments caused by small fluctuations are suppressed with precision bands, thereby reducing the ineffective movements and reciprocating switching of the actuator.
[0030] Optionally, during the period when the standby total pressure estimate is used, the preset accuracy band is gradually tightened according to the duration of its duration or the cumulative extrapolation uncertainty, and the air volume is forcibly limited when the cumulative extrapolation uncertainty exceeds the preset limit.
[0031] By adopting the above technical solution, the accuracy band is gradually tightened during the total pressure-dependent backup estimation period, and the air volume is limited when necessary, so that the adjustment strategy tends to be conservative as the reliability of the total pressure decreases.
[0032] Optionally, under near-saturation conditions where the actual water vapor partial pressure is close to the corrected saturated water vapor pressure, a lower limit clamp is set for the difference between the total pressure of moist air and the actual water vapor partial pressure, and the output update step size of the moisture content is reduced.
[0033] By adopting the above technical solution, the differential pressure is clamped and the update step size is reduced under near-saturation conditions, thus avoiding drastic changes in the moisture content value caused by the denominator approaching zero.
[0034] Optionally, temperature cross-sensitivity compensation can be performed on relative humidity using the synchronously acquired temperature to remove the temperature drift component in the relative humidity sensor readings.
[0035] By adopting the above technical solution, the temperature cross-drift in the relative humidity readings is compensated by synchronously acquired temperature data, thereby improving the measurement accuracy of relative humidity over a wide temperature range.
[0036] Optionally, the exponential operation term in the relationship between saturated water vapor pressure and temperature can be pre-made into a piecewise lookup table and combined with linear interpolation to obtain the value in real time, so as to reduce the real-time calculation load of the controller.
[0037] By adopting the above technical solution, segmented table lookup combined with interpolation is used to replace real-time exponential calculation, reducing the computational burden on the controller and facilitating real-time implementation on a low-cost embedded platform.
[0038] Optionally, the same sampling time timestamp can be added to the synchronously acquired relative humidity, temperature and total humid air pressure to verify the consistency of the three timestamps, and the corresponding value of the previous valid sampling period can be extrapolated to replace the timestamps that deviate.
[0039] By adopting the above technical solution, the time consistency of the three readings is ensured by timestamp verification, and historical values are extrapolated to replace the timestamp of a certain channel when it deviates, thus preventing asynchronous data from entering the moisture content conversion.
[0040] Optionally, the first-order prediction-correction recursion is implemented in the form of a state observer, which makes a state prediction of relative humidity and corrects it with the measured value.
[0041] By adopting the above technical solution, prediction-correction recursion is realized in the form of a state observer, which makes it easier to incorporate the hysteresis dynamics of relative humidity into a unified state estimation framework for compensation.
[0042] Optionally, the relationship between the lag time constant and temperature can be implemented by looking up a table.
[0043] By adopting the above technical solution, the lag time constant corresponding to the temperature can be obtained by looking up a table, avoiding online solution of parameter relationships and further reducing the real-time computation load of the controller.
[0044] Secondly, the fluidized bed inlet air moisture content dynamic detection device provided in this application adopts the following technical solution: A dynamic detection device for the moisture content of fluidized bed inlet air includes: A relative humidity sensor, a temperature sensor, and an absolute pressure sensor are installed in the air inlet duct to simultaneously acquire the relative humidity, temperature, and total pressure of the incoming air at the same sampling time. The controller is configured to: determine the hysteresis time constant of the relative humidity sensor based on temperature, and reconstruct the compensated relative humidity based on the relative humidity and the rate of change of relative humidity; determine the saturated water vapor pressure based on the relationship between the saturated water vapor pressure and temperature, and apply a total pressure enhancement correction to the saturated water vapor pressure based on the total pressure of humid air to obtain the corrected saturated water vapor pressure; determine the actual water vapor partial pressure of the intake air based on the compensated relative humidity and the corrected saturated water vapor pressure; determine the moisture content of the intake air based on the actual water vapor partial pressure and the difference between the total pressure of humid air and the actual water vapor partial pressure; and output the moisture content to adjust the dehumidification, humidification, or airflow of the intake air.
[0045] By adopting the above technical solution, three sensors installed in the air inlet duct synchronously collect relative humidity, temperature and total pressure of humid air at the same sampling time. The controller performs hysteresis compensation and total pressure enhancement correction to calculate the moisture content. This allows the device to output the moisture content of the inlet air in a timely and accurate manner when the air inlet conditions change rapidly and the pressure fluctuates, providing an execution basis for the closed-loop regulation of dehumidification, humidification and air volume.
[0046] Optionally, the controller is also configured to perform the dynamic detection method for the moisture content of the fluidized bed inlet air in the first aspect.
[0047] By adopting the above technical solutions, the device is equipped with noise resistance capability for hysteresis compensation, online identification and graded early warning capability for sensor hysteresis, and adaptive capability for compensation parameters.
[0048] Optionally, the controller is also configured to: replace the reading of the absolute pressure sensor with a backup estimate of the total humid air pressure and output a fault alarm when the reading exceeds the preset range or a sudden change occurs; identify the slow drift trend of the total humid air pressure during normal readings for extrapolation to obtain a backup estimate during fault periods; and limit the intake air volume when the cumulative extrapolation uncertainty of the backup estimate exceeds a preset limit.
[0049] By adopting the above technical solution, the device can maintain total pressure enhancement correction during barometer failure and gradually tighten the regulation of air volume as the reliability of total pressure estimation decreases.
[0050] Optionally, a data acquisition module may also be included, which is located between the relative humidity sensor, temperature sensor, absolute pressure sensor and controller. The data acquisition module collects the readings from the three sensors and sends them to the controller.
[0051] By adopting the above technical solution, the data acquisition module collects the readings from the three sensors and sends them to the controller, which simplifies the interface between the controller and the sensors and facilitates synchronous sampling.
[0052] Optionally, the relative humidity sensor, temperature sensor, and absolute pressure sensor are located on the same cross section of the air inlet duct and are adjacent to each other.
[0053] By adopting the above technical solution, the three sensors are arranged on the same cross section of the air inlet duct and are close to each other, so that the relative humidity, temperature and total pressure collected by them correspond to the same spatial position of the air inlet, reducing the error introduced by spatial inconsistency.
[0054] In summary, this application includes at least one of the following beneficial technical effects: 1. By synchronously collecting relative humidity, temperature and total pressure of humid air, and performing dynamic compensation based on the lag time constant for relative humidity and total pressure enhancement correction for saturated water vapor pressure before converting moisture content, the moisture content of the incoming air can still be detected in a timely and accurate manner when the operating conditions change rapidly and the pressure fluctuates, thus improving both dynamic response speed and steady-state accuracy.
[0055] 2. By suppressing differential noise through prediction-correction recursion, identifying sensor hysteresis online and performing graded correction and early warning through steady-state prediction residuals, and maintaining total pressure correction by extrapolating the total pressure slow drift trend when the barometer is abnormal, the detection remains reliable even under non-ideal conditions such as sensor aging and barometer failure.
[0056] 3. By adapting the sampling period and filtering window to the operating conditions, clamping the differential pressure under near-saturation conditions, and simplifying operations such as exponential term lookup and parameter lookup, this method reduces the computational burden while ensuring both tracking performance and stability, making it easy to implement in real time on a low-cost embedded platform. Attached Figure Description
[0057] Figure 1 This is a flowchart illustrating the dynamic detection method for the moisture content of fluidized bed inlet air provided in an embodiment of this application.
[0058] Figure 2 This is a block diagram of the intake air moisture content detection device provided in the embodiments of this application. Detailed Implementation
[0059] The present application will be further described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely illustrative of the application and are not intended to limit the scope of the application.
[0060] This application discloses a method for dynamically detecting the moisture content of fluidized bed inlet air. The method simultaneously measures the relative humidity, temperature, and total pressure of the inlet air at the same sampling time. It calculates the saturated water vapor pressure using the Buck formula with total pressure enhancement correction, then converts it to the moisture content based on Dalton's law of partial pressures, and dynamically compensates for the response lag of the relative humidity sensor. First, relative humidity, temperature, and total pressure of the saturated air are simultaneously acquired at the same sampling time, and lag compensation is applied to the relative humidity. Then, the saturated water vapor pressure is calculated from the temperature using the Buck formula, with total pressure enhancement correction applied. Next, the actual water vapor partial pressure is obtained based on the compensated relative humidity and the corrected saturated water vapor pressure. Finally, the moisture content is calculated based on Dalton's law of partial pressures and output to the controller to adjust the inlet air. This improves the calculation accuracy of saturated water vapor pressure and moisture content over a wide temperature and pressure range and shortens the dynamic response time of humidity detection. The following provides a detailed description of the relevant terminology, the overall flow of the detection method, the specific implementation of each step, and several optional implementation methods.
[0061] The following section will first explain some of the technical terms involved in the embodiments of this application.
[0062] Moisture content refers to the ratio of the mass of water vapor in moist air to the mass of dry air. It is used to characterize the actual moisture-carrying level of incoming air and is usually measured in kilograms per kilogram or grams per kilogram. Moisture content differs from relative humidity. Relative humidity only reflects the ratio of water vapor pressure to saturated water vapor pressure, while moisture content directly reflects the mass of water vapor carried per unit mass of dry air. Therefore, it is more suitable as a controlled variable for fluidized bed inlet air regulation.
[0063] Relative humidity is the ratio of the actual partial pressure of water vapor in moist air to the saturated water vapor pressure at the same temperature. It is usually expressed as a percentage and is directly measured by a relative humidity sensor.
[0064] The total pressure of humid air refers to the sum of the partial pressure of dry air and the partial pressure of water vapor in the intake air, that is, the absolute pressure of the intake air, which is measured by an absolute pressure sensor. The total pressure of humid air in the intake air will change with altitude and filter resistance.
[0065] Saturated water vapor pressure refers to the water vapor pressure when water vapor and liquid water reach phase equilibrium at a given temperature. It changes only with temperature and is a key intermediate quantity in the process of converting temperature into moisture content.
[0066] The hysteresis time constant is a parameter used to characterize the degree of hysteresis in the response of a relative humidity sensor. The larger the value, the slower the sensor follows changes in relative humidity, and it usually varies with temperature.
[0067] For ease of understanding, the following example scenario is taken as the air inlet condition of a fluidized bed granulation process, in which the air inlet temperature is about 60℃, the total pressure of the humid air is about 1013hPa, and the relative humidity of the air inlet is about 30%. The numerical examples in the subsequent steps are based on this condition.
[0068] The following section provides a detailed description of each step in conjunction with the overall workflow of this detection method. (Refer to...) Figure 1 The method includes steps S1 to S5.
[0069] In S1, a relative humidity sensor, a temperature sensor, and an absolute pressure sensor located in the air inlet duct are used to simultaneously acquire the relative humidity, temperature, and total humid air pressure of the incoming air at the same sampling time. The hysteresis time constant of the relative humidity sensor is determined based on the temperature, and the compensated relative humidity is reconstructed based on the relative humidity and its rate of change. In specific implementation, the relative humidity sensor is located on a straight section of the air inlet duct to measure the relative humidity φ, the temperature sensor is located adjacent to the relative humidity sensor to measure the incoming air temperature Tc (in °C), and the absolute pressure sensor is located at the same cross-section to measure the total humid air pressure Pt (in hPa). The subsequent formula calculations and moisture content output are executed by a programmable logic controller located in the electrical control cabinet. (Refer to...) Figure 2 The three sensors read synchronously at the same sampling time, for example, by acquiring the above three quantities synchronously with a sampling period of 0.5 seconds to 2 seconds, which can eliminate the phase error introduced by asynchronous sampling under conditions of rapid temperature or total pressure change.
[0070] Because the humidity-sensitive element of a relative humidity sensor exhibits response hysteresis, the measured relative humidity lags behind the true relative humidity of the incoming air, which is particularly noticeable during rapid changes in temperature or humidity. Therefore, the hysteresis time constant τ of the relative humidity sensor is determined based on the incoming air temperature, and the compensated relative humidity is reconstructed using the measured relative humidity value and its rate of change over time. In specific implementation, the compensated relative humidity can be obtained through a first-order hysteresis inverse model, reconstructed according to the following relationship: ; in, The relative humidity after compensation. The measured relative humidity is from the relative humidity sensor. The time lag constant is This refers to the rate of change of the measured relative humidity over time. For example, when the relative humidity of the incoming air is in a dynamically changing condition, if the measured relative humidity... 30%, lag time constant Given an 8-second interval and a measured relative humidity change rate of 0.5% per second, the compensated relative humidity... The result is 30% + 8 × 0.5% = 34%, thus compensating for the low reading caused by sensor hysteresis. The baseline operating condition mentioned throughout the text is the steady-state operating point where the rate of change of relative humidity is approximately zero. At this point, the compensated relative humidity is equal to the measured relative humidity, which is 30%. The numerical examples in the following steps are all based on this steady-state operating point.
[0071] As an alternative to relative humidity hysteresis compensation, the reconstructed relative humidity is not limited to the direct differentiation of the rate of change mentioned above. It can also be achieved through first-order prediction-correction recursion or state observers, so as to complete advance compensation while suppressing measurement noise. The specific implementation methods will be illustrated in the following examples.
[0072] To compensate for lag while suppressing measurement noise amplified by direct differentiation of the rate of change, in some embodiments, the compensated relative humidity is obtained through a first-order prediction-correction recursion. This first-order prediction-correction recursion makes a leading prediction of relative humidity based on the lag time constant, and corrects the leading prediction with the measured value of relative humidity, replacing the direct differentiation of the rate of change of relative humidity. In specific implementations, this recursion consists of two steps: prediction and correction. The prediction step extrapolates the leading prediction value of the current period using the compensation value of the previous period and the lag time constant. The correction step corrects the predicted value based on the deviation between the current measured relative humidity and the leading prediction value, obtaining the compensated relative humidity of the current period. For example, it can be recursively deduced according to the following relationship: ; ; in, For the first The forward forecast value for each cycle, This is the relative humidity after compensation from the previous cycle. and These are the measured relative humidity values for the current cycle and the previous cycle, respectively. The sampling period is To correct the gain, This is the lag time constant. For example, take the correction gain. With a value of 0.6, it can suppress abrupt jumps in measurement noise within a single cycle while following changes in actual relative humidity. This first-order prediction-correction recursion can also be equivalently implemented in the form of a state observer, as detailed below.
[0073] In other embodiments, when the relative humidity of the incoming air is in a steady state, the estimated hysteresis time constant of the relative humidity sensor is derived by back-calculating the prediction residual between the measured value of the relative humidity and the advance prediction in the first-order prediction-correction recursion. When the deviation between the estimated hysteresis time constant and the actual hysteresis time constant exceeds a preset deviation threshold, an aging warning for the relative humidity sensor is output. In specific implementations, a steady state of relative humidity means that its rate of change is below a set small threshold for a certain period of time. At this time, the advance prediction is mainly determined by the hysteresis time constant, so the prediction residual can reflect the mismatch between the current actual hysteresis and the used hysteresis time constant, and the estimated hysteresis time constant is derived accordingly. When the deviation of the estimated hysteresis time constant from the currently used value continuously exceeds the preset deviation threshold, it indicates that the sensor's response characteristics have drifted or aged, thus an aging warning is output.
[0074] In some implementations, a two-stage threshold processing is applied to the lag time constant based on the aforementioned deviation: when the deviation does not exceed a preset deviation threshold, the estimated lag time constant is used to progressively correct the lag time constant, which is then used as the lag time constant for subsequent first-order prediction-correction recursion; when the deviation exceeds the preset deviation threshold, progressive correction is stopped and an aging warning is output. In a specific implementation, progressive correction can be performed according to the following relationship: ; in, This is the corrected lag time constant. The current lag time constant is used. To estimate the lag time constant, This is the correction step size coefficient, with a value between 0 and 1. Therefore, within the normal drift range, the hysteresis characteristics of the continuously tracking sensor are progressively corrected. When the deviation is too large, it is judged as an anomaly, and the correction stops, instead issuing an output warning, thus preventing the abnormal estimated values from contaminating the compensation parameters.
[0075] Considering the wide temperature range covered by the intake air conditions (e.g., -40°C to 50°C), fixed compensation parameters are difficult to maintain optimal performance across all operating conditions. Optionally, the lag time constant and the predictor gain used in the first-order prediction-correction recursion are scheduled online based on the rate of change of temperature and relative humidity. In specific implementations, a correspondence between the lag time constant and the predictor gain relative to the rate of change of temperature and relative humidity is established in advance, and values are obtained during runtime based on the current rate of change of temperature and relative humidity through table lookup or interpolation. A larger lag time constant and a smaller predictor gain are used to suppress noise under low temperature and slowly changing relative humidity conditions, while a smaller lag time constant and a larger predictor gain are used to accelerate tracking under high temperature and rapidly changing relative humidity conditions. For example, a lag time constant of 12 seconds and a predictor gain of 0.4 are used under conditions of intake air temperature of -20°C and slowly changing relative humidity, while a lag time constant of 5 seconds and a predictor gain of 0.7 are used under conditions of intake air temperature of 50°C and rapidly changing relative humidity. In addition to table lookup or interpolation, the relationship between the lag time constant and the predictor gain as a function of temperature and rate of change can also be fitted as a continuous function and calculated online to reduce storage overhead.
[0076] As an optional implementation, the first-order prediction-correction recursion is implemented in the form of a state observer. The state observer makes a state prediction of the relative humidity and corrects it with the measured value. In the specific implementation, the actual relative humidity of the incoming air is used as the state variable. A state prediction model is constructed using the lag time constant. The state estimate is corrected by the observer gain feedback using the deviation between the measured relative humidity and the predicted output, thus obtaining the compensated relative humidity in a manner equivalent to the first-order prediction-correction recursion.
[0077] The relationship between the hysteresis time constant and temperature can also be achieved by looking up a table. In some embodiments, the hysteresis time constant of the relative humidity sensor is pre-calibrated according to different temperatures and stored as table entries. During runtime, the table is looked up based on the current temperature, and values are obtained by linear interpolation between adjacent entries to reduce the amount of real-time calculation.
[0078] To ensure temporal consistency in synchronous sampling, in some embodiments, the relative humidity, temperature, and total humid air pressure acquired synchronously are appended with the same sampling time timestamp. The consistency of these three timestamps is verified, and any timestamps that deviate are extrapolated from the corresponding values of the previous valid sampling period. In specific implementations, each of the three readings is stamped with a sampling time timestamp during acquisition. If the timestamp of one reading deviates from the other two by more than the allowable range, it is determined that the reading for that reading is not strictly synchronized with the other two in this period. Instead, the corresponding value of that reading from the previous valid sampling period is extrapolated to replace it, preventing asynchronous readings from being included in subsequent humidity content calculations.
[0079] In some implementations, the rate of change is determined based on the difference between temperature and total humid air pressure between adjacent sampling periods. The synchronously acquired sampling period is then dynamically adjusted between a preset upper and lower limit based on this rate of change. A shorter period is used when temperature and total humid air pressure change rapidly, and a longer period is used when they are stable. In specific implementations, the synchronously acquired sampling period is adjusted between a preset lower and upper limit. For example, the lower and upper limits can be set to 0.5 seconds and 2 seconds, respectively. When the rate of change of temperature and total pressure is large between adjacent periods, a shorter period closer to the lower limit is used to improve real-time tracking; when temperature and total pressure are stable, a longer period closer to the upper limit is used to reduce the burden of data acquisition and computation.
[0080] By utilizing the synchronously acquired temperature, temperature cross-sensitivity compensation can also be performed on the relative humidity readings to remove the temperature drift component from the relative humidity sensor readings. Optionally, based on the temperature drift characteristics of the relative humidity sensor at different temperatures, the relative humidity readings can be corrected using the synchronously measured temperature, thereby improving the accuracy of relative humidity measurements over a wide temperature range.
[0081] In S2, the saturated water vapor pressure is determined based on the relationship between temperature and saturated water vapor pressure. A total pressure enhancement correction is then applied to the saturated water vapor pressure based on the total pressure of the moist air to obtain the corrected saturated water vapor pressure. In the specific implementation, the relationship between saturated water vapor pressure and temperature is characterized using the Buck formula, and a total pressure enhancement coefficient is applied to correct it. The corrected saturated water vapor pressure is then calculated using the following formula. : ; in, This is the corrected saturated water vapor pressure, in hPa. This refers to the intake air temperature, expressed in °C. The total pressure of moist air is expressed in hPa; the exponential term characterizes the nonlinear change of saturated water vapor pressure with temperature, and the coefficient is... This is the total pressure enhancement factor, used to compensate for the effects of non-ideal gas behavior and total pressure variations caused by altitude, filter resistance, etc., on the saturated water vapor pressure. This formula originates from Buck's saturated water vapor pressure formula proposed in 1981 and has been optimized with coefficients, achieving high calculation accuracy over a wide temperature range. For example, under the above-mentioned baseline conditions, the inlet air temperature... 60℃, total pressure of humid air The value is 1013 hPa. Substituting this into the above formula, the exponential term is approximately... The total pressure enhancement coefficient is approximately The corrected saturated water vapor pressure hPa, of which the total pressure enhancement correction contributes approximately 0.8 hPa. Furthermore, the exponential operation terms in the saturated water vapor pressure calculation can be pre-prepared as lookup tables to reduce the real-time computational load on the controller, as detailed below.
[0082] In some embodiments, when the reading of the absolute pressure bar sensor exceeds a preset range or undergoes a sudden change, a backup estimate of the total humid air pressure is used to replace the absolute pressure bar sensor reading in determining the corrected saturated water vapor pressure, and a fault alarm for the absolute pressure bar sensor is output. In a specific implementation, the preset range can be set according to the air intake conditions; for example, this range can be 80 kPa to 120 kPa. When the reading of the absolute pressure bar sensor exceeds this range, or when a sudden change exceeding a set amplitude occurs between adjacent sampling periods, the absolute pressure bar sensor is determined to be faulty. The backup estimate of the total humid air pressure is then used to correct the saturated water vapor pressure, and a fault alarm is output simultaneously. The backup estimate can be obtained based on the nominal altitude of the installation location and the current temperature, according to the relationship between atmospheric pressure and altitude.
[0083] To ensure that the backup estimate reflects the total pressure variation pattern prior to the fault, the slow drift trend of the humid air total pressure is identified during periods when the absolute pressure bar sensor readings are normal. When the absolute pressure bar sensor readings exceed the preset range or experience a sudden change, the backup estimate is extrapolated based on this slow drift trend. In practice, the humid air total pressure typically exhibits a slow drift with changes in altitude and filter resistance. During periods of normal readings, the measured humid air total pressure sequence within a time window is fitted using a low-order trend model, such as fitting its linear trend over time using least squares, to obtain the slow drift trend. When the absolute pressure bar sensor fails, the total pressure at the time of the fault is used as a benchmark, and the backup estimate for the current period is extrapolated based on the identified slow drift trend. This ensures that the backup estimate reflects the total pressure variation pattern prior to the fault, making it closer to the actual total pressure than directly using a fixed nominal total pressure.
[0084] In some implementations, during the period when the backup estimate is used, the accumulated extrapolation uncertainty of the backup estimate over the duration is assessed, and the airflow is limited when the extrapolation uncertainty exceeds a preset limit. In a specific implementation, the backup estimate is obtained by extrapolation based on a slow drift trend, and its uncertainty deviating from the true total pressure accumulates and increases with the duration of the extrapolation. Based on this, the extrapolation uncertainty of the current backup estimate is estimated according to the duration. When the extrapolation uncertainty exceeds a preset limit, it indicates that the reliability of continuing to rely on the backup estimate for moisture content calculation has decreased, thereby limiting the airflow to make the fluidized bed operation more conservative and avoid improper airflow control due to moisture content calculation deviations when the total pressure information is unreliable.
[0085] Optionally, the disturbance of the total pressure of moist air is divided into fast-changing and slow-changing components according to the time scale. The slow-changing component is corrected using a long-period baseline estimate, while the fast-changing component is directly tracked by synchronous acquisition. This ensures that the slow-changing baseline drift caused by altitude or filter resistance is not filtered out as noise. In specific implementation, the change in total pressure caused by changes in altitude or filter resistance manifests as a slow baseline drift, while instantaneous disturbances manifest as a fast-changing component. The total pressure of moist air is separated according to the time scale, and its slow-changing component is tracked and corrected using a long-period baseline estimate, while the fast-changing component is directly tracked by synchronously acquired real-time readings. Thus, the slow-changing baseline drift is included as an effective change in total pressure in the correction of saturated water vapor pressure, and is not filtered out as noise during the denoising process.
[0086] The exponential term in the relationship between saturated water vapor pressure and temperature can be pre-configured as a segmented lookup table to reduce the real-time computational load on the controller. In some embodiments, this exponential term... By pre-classifying the calculation of saturated water vapor pressure into a lookup table based on temperature segments and combining it with real-time linear interpolation, the calculation of saturated water vapor pressure becomes simple and easy to run in real time on a microcontroller or programmable logic controller without the need for a high-performance computing platform.
[0087] In S3, the actual water vapor partial pressure of the intake air is determined based on the compensated relative humidity and the corrected saturated water vapor pressure. In practical implementation, the actual water vapor partial pressure... From the compensated relative humidity With the corrected saturated water vapor pressure Multiplying them together gives: ; in, This represents the actual partial pressure of water vapor. The compensated relative humidity (expressed as a decimal, or divided by 100 if expressed as a percentage). This is the corrected saturated water vapor pressure. For example, under the above baseline conditions, the compensated relative humidity... 30%, corrected saturated water vapor pressure The actual water vapor partial pressure is 201.1 hPa. hPa.
[0088] In S4, the moisture content of the intake air is determined based on the actual water vapor partial pressure and the difference between the total pressure of the moist air and the actual water vapor partial pressure. In practice, the moisture content is determined based on Dalton's law of partial pressures and the definition of moisture content, calculated using the following formula: ; in, Moisture content, expressed in kg / kg; This represents the actual partial pressure of water vapor; The total pressure of the moist air; The partial pressure of dry air is given; the coefficient 0.622 represents the ratio of the molar mass of water vapor to that of dry air, derived from the definition of moisture content. ,in , These are the masses of water vapor and dry air, respectively. , These are the gas constants for dry air and water vapor, respectively. This refers to the partial pressure of dry air. In engineering applications, the moisture content can be multiplied by 1000 to convert from kg / kg to g / kg. For example, under the above baseline conditions, the actual water vapor partial pressure is... The total pressure of moist air is 60.3 hPa. If the Pa is 1013 hPa, then the moisture content is... kg / kg, which is approximately 39.4 g / kg.
[0089] In some embodiments, under near-saturation conditions where the actual water vapor partial pressure is close to the corrected saturated water vapor pressure, a lower limit clamp is set on the difference between the total humid air pressure and the actual water vapor partial pressure, and the output update step size for moisture content is reduced. In a specific implementation, when the actual water vapor partial pressure... Approximately the corrected saturated water vapor pressure At that time, the partial pressure of dry air As the value of moisture content approaches a smaller value, the denominator in the moisture content calculation formula also approaches zero, making the moisture content highly sensitive to small changes in partial pressure; therefore, the denominator... Set a lower limit clamp to ensure that the output moisture content is not lower than the set lower limit value, and at the same time reduce the output update step size of moisture content, thereby suppressing the jump of moisture content output under near-saturation conditions and improving numerical stability.
[0090] In S5, the moisture content is output to the controller to adjust the dehumidification, humidification, or airflow of the incoming air. In a specific implementation, the moisture content can be output after being filtered by a moving average. As an example, the window of the moving average filter can be set to 3 to 5 times. The filtered moisture content is output to the fluidized bed PID controller, which adjusts the operation of the dehumidification and humidification valves or the variable frequency fan of the incoming air accordingly.
[0091] To balance the smoothness of filtering with the speed of response, in some embodiments, the window length for the moving average filtering of moisture content is dynamically adjusted based on the variation amplitude of moisture content over the most recent sampling periods. The window is increased when the moisture content is stable and decreased when it changes rapidly. In specific implementations, the variation amplitude of moisture content over the most recent sampling periods is statistically analyzed. When the variation amplitude is small (i.e., the moisture content is stable), the window length of the moving average filtering is increased to enhance smoothness and suppress noise. When the variation amplitude is large (i.e., the moisture content changes rapidly), the window length is decreased to speed up the response. The window length can be dynamically adjusted from the aforementioned 3 to 5 times to a larger or smaller range.
[0092] In some implementations, in response to the moisture content falling within a preset accuracy band centered on the target moisture content, the current dehumidification, humidification, or airflow setting is maintained, and adjustments are made only when the moisture content exceeds the preset accuracy band. In practice, if the instantaneous value of the moisture content is tracked and adjusted point by point, the dehumidification or humidification valves or variable frequency fans are prone to frequent fine-tuning, resulting in oscillations. Therefore, a preset accuracy band is set centered on the target moisture content. When the moisture content falls within this accuracy band, the current setting remains unchanged, and adjustments are made only when the moisture content exceeds this accuracy band, thereby reducing the frequent operation of the actuator.
[0093] To make regulation more robust when the reliability of total pressure information decreases, during the period when the backup total pressure estimate is used, the preset accuracy band is gradually tightened according to its duration or the accumulated extrapolation uncertainty, and the air volume is forcibly limited when the accumulated extrapolation uncertainty exceeds a preset limit. In specific implementation, during the period when the backup total pressure estimate is used, the preset accuracy band centered on the target moisture content is gradually tightened as the duration of the backup estimate increases or the accumulated extrapolation uncertainty increases, making the regulation threshold more stringent; when the accumulated extrapolation uncertainty exceeds the preset limit, the intake air volume is forcibly limited. Thus, when the reliability of the total pressure estimate decreases, the moisture content regulation becomes more conservative, which is consistent with the aforementioned air volume limitation treatment during the period when the backup estimate is used.
[0094] See Figure 2 As shown, this application also provides a dynamic detection device for the moisture content of fluidized bed inlet air, which adopts the following technical solution: A dynamic detection device for the moisture content of fluidized bed inlet air includes: A relative humidity sensor, a temperature sensor, and an absolute pressure sensor are installed in the air inlet duct to simultaneously acquire the relative humidity, temperature, and total pressure of the incoming air at the same sampling time. The controller is configured to: determine the hysteresis time constant of the relative humidity sensor based on temperature, and reconstruct the compensated relative humidity based on the relative humidity and the rate of change of relative humidity; determine the saturated water vapor pressure based on the relationship between the saturated water vapor pressure and temperature, and apply a total pressure enhancement correction to the saturated water vapor pressure based on the total pressure of humid air to obtain the corrected saturated water vapor pressure; determine the actual water vapor partial pressure of the intake air based on the compensated relative humidity and the corrected saturated water vapor pressure; determine the moisture content of the intake air based on the actual water vapor partial pressure and the difference between the total pressure of humid air and the actual water vapor partial pressure; and output the moisture content to adjust the dehumidification, humidification, or airflow of the intake air.
[0095] By adopting the above technical solution, three sensors installed in the air inlet duct synchronously collect relative humidity, temperature and total pressure of humid air at the same sampling time. The controller performs hysteresis compensation and total pressure enhancement correction to calculate the moisture content. This allows the device to output the moisture content of the inlet air in a timely and accurate manner when the air inlet conditions change rapidly and the pressure fluctuates, providing an execution basis for the closed-loop regulation of dehumidification, humidification and air volume.
[0096] The controller is also configured to: reconstruct the compensated relative humidity using a first-order prediction-correction recursion; estimate the lag time constant based on the prediction residual when the relative humidity is in a steady state and output an aging warning when the deviation exceeds a preset deviation threshold; gradually correct the lag time constant used for compensation using the estimated lag time constant when the deviation does not exceed the preset deviation threshold; and schedule the lag time constant used for compensation and the predictor gain online according to the rate of change of temperature and relative humidity.
[0097] By adopting the above technical solutions, the device is equipped with noise resistance capability for hysteresis compensation, online identification and graded early warning capability for sensor hysteresis, and adaptive capability for compensation parameters.
[0098] Optionally, the controller is also configured to: replace the reading of the absolute pressure sensor with a backup estimate of the total humid air pressure and output a fault alarm when the reading exceeds the preset range or a sudden change occurs; identify the slow drift trend of the total humid air pressure during normal readings for extrapolation to obtain a backup estimate during fault periods; and limit the intake air volume when the cumulative extrapolation uncertainty of the backup estimate exceeds a preset limit.
[0099] By adopting the above technical solution, the device can maintain total pressure enhancement correction during barometer failure and gradually tighten the regulation of air volume as the reliability of total pressure estimation decreases.
[0100] A dynamic detection device for the moisture content of fluidized bed inlet air further includes a data acquisition module that connects a relative humidity sensor, a temperature sensor, an absolute pressure sensor, and a controller. The data acquisition module collects the readings from the three sensors and sends them to the controller. By adopting the above technical solution, the data acquisition module collects the readings from the three sensors and sends them to the controller, simplifying the interface between the controller and the sensors and facilitating synchronous sampling.
[0101] The relative humidity sensor, temperature sensor, and absolute pressure sensor are located on the same cross-section of the air intake duct and are adjacent to each other. The arrangement of the three sensors on the same cross-section of the air intake duct and their proximity to each other ensures that the relative humidity, temperature, and total pressure they collect correspond to the same spatial location of the air intake, reducing errors introduced by spatial inconsistencies.
[0102] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.
[0103] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.
Claims
1. A method for dynamically detecting the moisture content of inlet air in a fluidized bed, characterized in that, The steps are as follows: S1. Using a relative humidity sensor, a temperature sensor, and an absolute pressure sensor installed in the air inlet duct, the relative humidity, temperature, and total pressure of the incoming air are simultaneously acquired at the same sampling time; the hysteresis time constant of the relative humidity sensor is determined based on the temperature, and the compensated relative humidity is reconstructed based on the relative humidity and the rate of change of the relative humidity; S2. Determine the saturated water vapor pressure based on the relationship between the saturated water vapor pressure and temperature according to the temperature, and apply a total pressure enhancement correction to the saturated water vapor pressure based on the total pressure of the moist air to obtain the corrected saturated water vapor pressure; S3. Determine the actual water vapor partial pressure of the incoming air based on the compensated relative humidity and the corrected saturated water vapor pressure; S4. Determine the moisture content of the incoming air based on the actual water vapor partial pressure and the difference between the total pressure of the humid air and the actual water vapor partial pressure; S5. Output the moisture content to the controller to adjust the dehumidification, humidification or airflow of the incoming air.
2. The method for dynamic detection of moisture content in fluidized bed inlet air according to claim 1, characterized in that, The compensated relative humidity described in S1 is obtained through a first-order prediction-correction recursion. The first-order prediction-correction recursion makes an advance prediction of the relative humidity according to the lag time constant, and corrects the advance prediction with the measured value of the relative humidity, in order to replace the direct differentiation of the rate of change of the relative humidity.
3. The method for dynamic detection of moisture content in fluidized bed inlet air according to claim 2, characterized in that, When the relative humidity of the incoming air is in a steady state, the estimated lag time constant of the relative humidity sensor is obtained by back-calculating the prediction residual between the measured value of the relative humidity and the advanced prediction in the first-order prediction-correction recursion. When the deviation between the estimated lag time constant and the lag time constant exceeds a preset deviation threshold, an aging warning for the relative humidity sensor is output.
4. The method for dynamic detection of moisture content in fluidized bed inlet air according to claim 3, characterized in that, When the deviation does not exceed the preset deviation threshold, the estimated lag time constant is used to progressively correct the lag time constant, which is then used as the lag time constant for the subsequent first-order prediction-correction recursion. When the deviation exceeds the preset deviation threshold, the gradual correction is stopped and the aging warning is output.
5. The method for dynamic detection of moisture content in fluidized bed inlet air according to claim 2, characterized in that, The lag time constant and the predictor gain used in the first-order prediction-correction recursion are scheduled online according to the rate of change of the temperature and the relative humidity.
6. The method for dynamic detection of moisture content in fluidized bed inlet air according to claim 1, characterized in that, When the reading of the absolute pressure type barometer exceeds the preset range or a sudden change occurs, the backup estimated value of the total humid air pressure is used to replace the reading of the absolute pressure type barometer to participate in the determination of the corrected saturated water vapor pressure, and a fault alarm of the absolute pressure type barometer is output.
7. The method for dynamic detection of moisture content in fluidized bed inlet air according to claim 6, characterized in that, During the period when the absolute pressure sensor reading is normal, the slow drift trend of the total pressure of the humid air is identified, and when the reading of the absolute pressure sensor exceeds the preset range or a sudden change occurs, the backup estimate is extrapolated according to the slow drift trend.
8. The method for dynamic detection of moisture content in fluidized bed inlet air according to claim 7, characterized in that, During the period when the backup estimate is used, the extrapolation uncertainty of the backup estimate accumulated over the duration is assessed, and when the extrapolation uncertainty exceeds a preset limit, the intake air volume is limited.
9. A dynamic detection device for the moisture content of fluidized bed inlet air, characterized in that, include: A relative humidity sensor, a temperature sensor, and an absolute pressure sensor are installed in the air inlet duct to simultaneously acquire the relative humidity, temperature, and total pressure of the incoming air at the same sampling time. The controller is configured to: determine the hysteresis time constant of the relative humidity sensor based on the temperature, and reconstruct the compensated relative humidity based on the relative humidity and the rate of change of the relative humidity; determine the saturated water vapor pressure based on the relationship between the saturated water vapor pressure and the temperature based on the temperature, and apply a total pressure enhancement correction to the saturated water vapor pressure based on the total pressure of the humid air to obtain the corrected saturated water vapor pressure; The actual water vapor partial pressure of the intake air is determined based on the compensated relative humidity and the corrected saturated water vapor pressure; the moisture content of the intake air is determined based on the actual water vapor partial pressure and the difference between the total humid air pressure and the actual water vapor partial pressure; and the moisture content is output to adjust the dehumidification, humidification, or airflow of the intake air.
10. The fluidized bed inlet air moisture content dynamic detection device according to claim 9, characterized in that, The controller is also configured to perform the dynamic detection method for the moisture content of fluidized bed inlet air as described in any one of claims 1 to 8.