Partition switching control method and device for multi-tower modular regenerative incineration system

Abstract

This invention relates to the field of regenerative thermal ignition (RTO) control technology, and discloses a method and device for zone switching control of a multi-tower modular RTO system. By deploying a temperature acquisition array on each RTO tower, a two-dimensional temperature matrix is ​​acquired in real time. A comprehensive early warning signal is generated by combining the judgment of temperature field distortion precursors and the judgment of flow deviation risk. The inlet VOC concentration and outlet temperature are monitored in real time. When an early warning is triggered, the switching timing is dynamically adjusted according to the temperature rise state type. Furthermore, an energy imbalance state is determined by constructing an inter-tower energy difference matrix, and a collaborative adjustment mode is triggered synchronously during the switching operation. This invention significantly improves the accuracy of temperature field prediction, reduces the risk of local overheating of the RTO body, optimizes the accuracy of switching decisions, and effectively avoids thermal runaway reactions caused by nonlinear temperature gradient distribution and VOC concentration fluctuations through multi-dimensional data fusion and dynamic adjustment mechanisms, thereby achieving a substantial improvement in the overall thermal efficiency of the system.

Description

Technical Field

[0001] This invention relates to the field of regenerative thermal ignition control technology, and more specifically, to a method and apparatus for zone switching control of a multi-tower modular regenerative thermal ignition system. Background Technology

[0002] Regenerative thermal oxidizer (RTO) technology, as a key means of industrial waste gas purification, achieves efficient energy utilization by recovering combustion heat through a heat storage medium, and is widely used, especially in the field of volatile organic compound (VOCs) treatment. Multi-tower modular RTO systems, with their advantages of large processing capacity and flexible operation, have become an important choice for waste gas treatment under complex operating conditions. Their core lies in balancing heat storage and combustion efficiency through precise tower switching control, avoiding equipment damage and ensuring purification effects.

[0003] In the prior art, Chinese patent application CN104534487A discloses a regenerative thermal oxidizer system. This system includes subsystems such as heating, combustion solvent, and regenerative oxidation, which achieve regenerative oxidation treatment of waste gas through automatic switching. It features high thermal efficiency, high VOCs decomposition rate, and low operating cost. Chinese patent CN114507763B discloses a converter flue gas constant temperature system, a flue gas treatment system, and a method. This system maintains a constant flue gas temperature through a cooling device in conjunction with a regenerative tower, while also possessing a dust purification function, reducing the load on subsequent purification systems.

[0004] However, the existing technologies still have limitations in the switching control of multi-tower modular regenerative thermal ignition (RTO) systems: existing systems mostly rely on inlet and outlet temperature differences or fixed cycles for switching, without considering the nonlinear distribution characteristics of the temperature gradient inside the honeycomb ceramic regenerator. When VOC concentration fluctuates, "heat islands" or "cold holes" can easily form locally in the regenerator, and there is a delay in the transmission of temperature changes from the combustion zone to the outlet sensor. During this period, if the system still switches according to the original logic, high-temperature gas will remain in a certain tower for too long, causing local overheating damage. More seriously, when multiple towers experience temperature gradient distortion simultaneously, the system may misjudge a high-temperature tower as a low-temperature tower for gas intake, leading to an abnormal increase in intake temperature and ultimately triggering a thermal runaway reaction. This problem is particularly prominent under complex operating conditions with drastic fluctuations in VOC concentration. Summary of the Invention

[0005] To overcome the aforementioned deficiencies of the prior art, this invention provides a method and device for zone switching control of a multi-tower modular regenerative thermal incineration system. By deploying a temperature acquisition point array to construct a two-dimensional temperature matrix, and combining temperature field distortion and flow deviation risk assessment to generate a comprehensive early warning, the switching timing is dynamically adjusted and the energy balance of the multiple towers is coordinated. This effectively solves the problem of switching misjudgment caused by temperature gradient nonlinearity, significantly improves the system's operational stability and thermal efficiency, and reduces the risk of local overheating of the thermal storage body.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A zone switching control method for a multi-tower modular regenerative thermal ignition system includes:

[0008] Temperature acquisition points are set up for each thermal storage tower to receive temperature data collected by the acquisition points and form a two-dimensional temperature matrix. Based on the two-dimensional temperature matrix, temperature field distortion precursors and flow deviation risks are determined for each thermal storage tower. Based on the determination results of temperature field distortion precursors and flow deviation risks, a comprehensive early warning signal for temperature field distortion is generated.

[0009] Real-time monitoring of inlet VOC concentration and outlet temperature; when a comprehensive early warning signal for temperature field distortion W is received... total At that time, based on the monitored inlet VOC concentration and outlet temperature, the temperature rise state type is determined, the switching timing adjustment amount is calculated based on the temperature rise state type, and the final switching time is obtained based on the switching timing adjustment amount.

[0010] Before performing the switching operation, an inter-tower energy difference matrix is ​​constructed based on the two-dimensional temperature matrix of each thermal storage tower. The inter-tower energy difference matrix is ​​used to determine whether there is an inter-tower energy imbalance. If there is an inter-tower energy imbalance, the switching is performed at the final switching time, and the coordinated regulation mode is triggered simultaneously.

[0011] Furthermore, the method for arranging the temperature acquisition point array is as follows: a cylindrical coordinate system is established with the geometric center of each heat storage tower as the origin O, and grid cells are divided according to the radial and axial directions of the cylindrical coordinate system. Temperature acquisition points are arranged at the center of each grid cell to form a temperature acquisition point array.

[0012] Furthermore, the method for determining the precursors of temperature field distortion for each thermal storage tower includes:

[0013] Based on a two-dimensional temperature matrix, the temperature difference between adjacent temperature acquisition points is calculated. According to the temperature difference, coarse texture primitives and fine texture primitives are defined for each grid cell. The coarse texture primitives and fine texture primitives constitute a texture distribution map.

[0014] Texture distribution maps are continuously recorded at fixed time intervals to form a texture evolution sequence; the coarse texture area growth rate is calculated based on the texture evolution sequence.

[0015] Based on the growth rate of coarse texture area, determine whether there are precursors to temperature field distortion in the heat storage tower.

[0016] Furthermore, the method for defining the coarse texture primitive and fine texture primitive corresponding to each mesh unit includes:

[0017] For radially adjacent temperature acquisition points, calculate the radial temperature difference; for axially adjacent temperature acquisition points, calculate the axial temperature difference; when the absolute value of the radial temperature difference or the absolute value of the axial temperature difference is greater than the coarse texture determination threshold M', mark the mesh unit corresponding to the temperature acquisition point as a coarse texture primitive and assign texture label Tc; otherwise, mark it as a fine texture primitive and assign texture label Tf.

[0018] Furthermore, the method for determining whether there are precursors to temperature field distortion in the thermal storage tower includes:

[0019] A distortion warning threshold N is set. If the growth rate of coarse texture area is greater than the distortion warning threshold N in the most recent q consecutive observations, it is determined that there is a precursor to temperature field distortion in the thermal storage tower.

[0020] Furthermore, the method for determining the flow deviation risk includes:

[0021] The position coordinates of all coarse texture primitives in each thermal storage tower are counted. Based on the position coordinates of all coarse texture primitives, the position of the texture centroid is calculated. Based on the position of the texture centroid, the heat flow deflection angle is calculated. Based on the heat flow deflection angle, it is determined whether there is a risk of flow deviation in the thermal storage tower.

[0022] Furthermore, the method for generating the comprehensive early warning signal for temperature field distortion is as follows:

[0023] If there are precursors to temperature field distortion, generate a warning signal for the precursors to distortion.

[0024] If there is a risk of flow deviation, a flow deviation warning signal will be generated.

[0025] If both the early warning signal for distortion and the early warning signal for skewed flow exist simultaneously, a comprehensive early warning signal for temperature field distortion will be generated.

[0026] Furthermore, the method for determining the type of temperature rise state includes:

[0027] When a comprehensive early warning signal for temperature field distortion is received, W total At that time, based on the monitored inlet VOC concentration Cin(t) and outlet temperature Tout(t), the time of VOC concentration change and the time of outlet temperature response are identified, and the thermal inertia index is calculated, where t is the current time;

[0028] Calculate the lead time Δt based on the thermal inertia index. ad Based on the predicted lead time Δt ad Determine the opening time and duration of the prediction window;

[0029] Within the defined prediction window, the switching cycle is divided into three time periods: the front, middle, and back, and the temperature rise rate for each time period is calculated.

[0030] Based on the temperature rise rate over three time periods, the temperature rise rate ratio is calculated, and the temperature rise state type is determined according to the temperature rise rate ratio.

[0031] Furthermore, the method for identifying the time of VOC concentration change and the time of outlet temperature response includes:

[0032] Based on the real-time monitored inlet VOC concentration Cin(t), the change in inlet VOC concentration ΔCin is calculated; when ΔCin is greater than the preset VOC concentration change detection threshold C... voc At this point, mark this moment as the timing start point t1, which is the moment of VOC concentration change, and start the timer;

[0033] Starting from the timing point t1, continuously monitor the change in outlet temperature ΔTout, which is the difference between the current outlet temperature and the outlet temperature at time t1. When ΔTout is greater than the preset outlet temperature response threshold T', mark this moment as the timing point t2, i.e. the outlet temperature response moment, and stop the timer.

[0034] Furthermore, the method for calculating the thermal inertia index includes:

[0035] The temperature conduction delay time Δt is obtained by subtracting the VOC concentration change time from the outlet temperature response time. delay ;

[0036] Obtain the mass M and specific heat capacity c of the heat storage body by delaying the time Δt. delay The thermal inertia index I is calculated by multiplying the mass M of the heat storage body by its specific heat capacity c.

[0037] Furthermore, the temperature rise rate ratio is the ratio of the temperature rise rate in the later stage to the temperature rise rate in the earlier stage;

[0038] The method for determining the temperature rise state type based on the ratio of temperature rise rates includes: when the ratio of temperature rise rates is greater than or equal to the accelerated temperature rise determination threshold, it is determined to be an accelerated temperature rise state; when the ratio of temperature rise rates is less than or equal to the reciprocal of the accelerated temperature rise determination threshold, it is determined to be a decelerated temperature rise state; when the ratio of temperature rise rates is greater than the reciprocal of the accelerated temperature rise determination threshold but less than the reciprocal of the accelerated temperature rise determination threshold, it is determined to be a stable temperature rise state.

[0039] A multi-tower modular regenerative thermal ignition (RTO) system zoning control device, used to implement the aforementioned multi-tower modular RTO system zoning control method, the device comprising:

[0040] Distortion early warning module: It is used to receive temperature data collected by temperature acquisition point array and form a two-dimensional temperature matrix; based on the two-dimensional temperature matrix, it performs temperature field distortion precursor judgment and flow deviation risk judgment for each thermal storage tower; and generates a comprehensive temperature field distortion early warning signal based on the judgment results of temperature field distortion precursor and flow deviation risk.

[0041] Switching Time Determination Module: Used for real-time monitoring of inlet VOC concentration and outlet temperature. When a comprehensive early warning signal W for temperature field distortion is received... total At that time, based on the monitored inlet VOC concentration and outlet temperature, the temperature rise state type is determined, the switching timing adjustment amount is calculated based on the temperature rise state type, and the final switching time is obtained based on the switching timing adjustment amount.

[0042] Coordinated regulation module: Before performing the switching operation, an inter-tower energy difference matrix is ​​constructed based on the two-dimensional temperature matrix of each thermal storage tower; the inter-tower energy difference matrix is ​​used to determine whether there is an inter-tower energy imbalance; if there is an inter-tower energy imbalance, the coordinated regulation mode is triggered at the same time as the final switching time.

[0043] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0044] This invention achieves precise identification of precursors to temperature field distortion and flow deviation risks by deploying temperature acquisition points in each regenerative tower and generating a two-dimensional temperature matrix. This effectively suppresses the formation of "heat islands" or "cold holes" within the honeycomb ceramic regenerative heat exchanger, significantly reducing the probability of local overheating damage. Combined with real-time monitoring of inlet VOC concentration and outlet temperature, the switching timing adjustment can be dynamically calculated, accurately compensating for signal lag caused by temperature conduction delays and preventing excessive retention of high-temperature gas within the tower. By constructing an inter-tower energy difference matrix and triggering a collaborative adjustment mode, the energy distribution of each tower can be balanced in real time, eliminating the risk of misjudgment of gas intake caused by multi-tower temperature gradient distortion. This fundamentally eliminates the potential for thermal runaway caused by misjudging a high-temperature tower as a low-temperature tower. The synergistic effect of the above technical solutions systematically improves the accuracy of system temperature field prediction, the reliability of switching decisions, and overall thermal efficiency, providing a solid guarantee for the safe and stable operation of the multi-tower modular regenerative thermal combustion system. Attached Figure Description

[0045] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1This is a flowchart of the partition switching control method for a multi-tower modular regenerative thermal incineration system in this invention;

[0047] Figure 2 A flowchart illustrating the principle of generating a comprehensive early warning signal for temperature field distortion, provided in an embodiment of the present invention;

[0048] Figure 3 This is a schematic diagram of grid cell division provided in an embodiment of the present invention;

[0049] Figure 4 Texture distribution map provided in the embodiments of the present invention;

[0050] Figure 5 A flowchart illustrating the method for calculating the thermal inertia index provided in an embodiment of the present invention;

[0051] Figure 6 This is a functional block diagram of the zone switching control device for the multi-tower modular regenerative thermal incineration system in this invention. Detailed Implementation

[0052] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0053] Example 1:

[0054] Please see Figure 1 As shown, this embodiment provides a zone switching control method for a multi-tower modular regenerative thermal ignition system, including:

[0055] Step S10: Deploy a temperature acquisition array for each thermal storage tower, receive the temperature data collected by the temperature acquisition array, and form a two-dimensional temperature matrix; based on the two-dimensional temperature matrix, determine the precursors of temperature field distortion and the risk of flow deviation for each thermal storage tower, and generate a comprehensive early warning signal for temperature field distortion based on the determination results of the precursors of temperature field distortion and the determination results of the risk of flow deviation.

[0056] Please see Figure 2 As shown, step S10 further includes:

[0057] Step S11: Establish a cylindrical coordinate system with the geometric center of each heat storage tower as the origin O, divide the cylindrical coordinate system into grid cells according to the radial and axial directions, arrange temperature acquisition points at the center of each grid cell to form a temperature acquisition point array; receive the temperature data collected by the temperature acquisition point array to form a two-dimensional temperature matrix.

[0058] Establish a cylindrical coordinate system with the geometric center of each thermal storage tower as the origin O. Define the axial direction of the thermal storage body as the Z-axis of the cylindrical coordinate system, the height direction as the positive Z-axis, and the radial direction as the R-axis. (See also...) Figure 3 As shown, the cylindrical heat storage body is divided into grid cells along the radial and axial directions of the cylindrical coordinate system. Temperature acquisition points are placed at the center of each grid cell, forming a temperature acquisition point array. Temperature data collected from this array is then used to form a two-dimensional temperature matrix. The cylindrical heat storage body is divided into n equidistant cells along the axial direction and m concentric ring cells along the radial direction from the center to the edge. The center of each grid cell is a temperature monitoring point, forming a temperature monitoring network covering the entire heat storage body. The two-dimensional temperature matrix T(r) i ,z j In ), (r i ,z j ) represents the position coordinates of the grid cell (i,j), and r i z represents the radial coordinate of the grid cell (i,j), indicating the i-th radial grid cell, where i is the index of the radial grid cell, ranging from 1 to m; j Let (i,j) be the axial coordinate of the grid cell, representing the j-th axial grid cell, where j is the index of the axial grid cell, ranging from 1 to n. In existing technologies, single inlet and outlet temperature sensors are often used for monitoring, which can only reflect the overall temperature difference and cannot capture temperature changes in local areas within the heat storage body. However, by establishing a standardized cylindrical coordinate system and grid division method, precise segmentation of the internal space of the heat storage body can be achieved. Each grid cell corresponds to a specific spatial location, ensuring that the spatial positioning error of the temperature acquisition point is controlled within the grid cell size range. This provides a precise spatial positioning basis for subsequent temperature texture recognition. Without this step, subsequent temperature field analysis will lack accurate spatial coordinate references, making it impossible to correlate temperature data with specific locations. This leads to the inability to determine the location of local heat islands or cold holes, and consequently, the loss of spatial basis for judging temperature field distortion.

[0059] Step S12: Based on the two-dimensional temperature matrix, calculate the temperature difference between adjacent temperature acquisition points, and define the coarse texture primitive and fine texture primitive corresponding to each grid unit according to the temperature difference. The coarse texture primitive and fine texture primitive constitute a texture distribution map.

[0060] For radially adjacent temperature sampling points, the radial temperature difference is calculated, i.e., the temperature difference between different radial grid cells at the same axial position. For axially adjacent temperature sampling points, the axial temperature difference is calculated, i.e., the temperature difference between different axial grid cells at the same radial position. A coarse texture judgment threshold M' is set. When the absolute value of either the radial or axial temperature difference is greater than the coarse texture judgment threshold M', the grid cell corresponding to the temperature sampling point is marked as a coarse texture primitive and assigned a texture label Tc; otherwise, it is marked as a fine texture primitive and assigned a texture label Tf. The coarse texture judgment threshold is determined experimentally. For example, when the VOC concentration is stable, the maximum temperature difference between adjacent grid cells under normal operating conditions of the heat storage body is statistically analyzed, and 1.2 times this value is taken as M' to distinguish between normal temperature fluctuations and abnormal drastic changes. In the texture distribution map, each pixel P(i,j) corresponds one-to-one with a grid cell (i,j), and the value of pixel P(i,j) is the texture label of the grid cell (i,j). Figure 4 The image displayed shows a texture distribution map with 8 pixels radially and 5 pixels axially. Existing technologies struggle to convert continuous temperature fields into quantifiable and analyzable features. This step, however, transforms grid cells with drastic temperature changes (large temperature differences between adjacent cells) into "coarse textures," corresponding to potential heat islands or cold holes. Conversely, grid cells with gradual temperature changes (small temperature differences between adjacent cells) form "fine textures," corresponding to regions with uniform temperature distribution. By converting the continuous temperature field into discrete texture features corresponding one-to-one with each grid cell, the temperature change characteristics of each grid cell can be intuitively identified. Without this step, the abstract temperature field cannot be transformed into analyzable discrete features, and subsequent time-series evolution analysis will lack foundational data, making it impossible to capture the changing trends of the temperature gradient.

[0061] Step S13: Record the texture distribution map continuously at fixed time intervals to form a texture evolution sequence; calculate the coarse texture area growth rate based on the texture evolution sequence;

[0062] Texture distribution maps are continuously recorded at fixed time intervals to form a texture evolution sequence {P1, P2, ..., P}. k}, where P kLet N(t') represent the texture distribution map at time k. The fixed time interval is determined based on the system response speed to ensure that dynamic changes in the temperature field can be captured, for example, set to 1 second. Based on the texture evolution sequence, the growth rate of the coarse texture area is calculated. Specifically, the number of coarse texture primitives Tc in each texture distribution map, Nc(t'), is counted. Nc(t') represents the number of coarse texture primitives Tc in the texture distribution map at time t'. Based on the number Nc(t'), the area ratio of coarse texture primitives, Ac(t'), is calculated: Ac(t') = Nc(t') / (m × n), which represents the number of coarse texture primitives. The proportion of the total number of mesh cells is used to calculate the coarse texture area growth rate based on Ac(t'): Gc(t') = [Ac(t') - Ac(t'-1)] / Ac(t'-1), where Ac(t'-1) represents the proportion of coarse texture area at the time before t', and Ac(t'-1) ≠ 0. If Ac(t'-1) = 0 and Ac(t') > 0, then Gc(t') = 1, indicating that the coarse texture area growth rate is 100% from zero to one. If Ac(t'-1) = 0 and Ac(t') = 0, then Gc(t') = 0. Existing technologies for monitoring temperature fields are mostly static or instantaneous, failing to reflect their dynamic trends. However, by establishing a time-series evolution model, the dynamic trend of temperature gradient changes can be captured. Continuous coarse texture growth indicates that the temperature gradient is deteriorating. For example, when Gc(t') is continuously positive and gradually increases, it indicates that the heat island region is expanding and temperature changes are intensifying, providing a key indicator for subsequent distortion precursor judgment. Without this step, it is impossible to determine whether the temperature field is in a stable or deteriorating state based solely on the texture distribution at a single moment, which may lead to misjudgment or missed judgment of distortion precursors.

[0063] Step S14: Based on the coarse texture area growth rate, determine whether there are any precursors to temperature field distortion in the heat storage tower; if there are precursors to temperature field distortion, generate a precursor distortion warning signal W. pre Otherwise, no early warning signal W for distortion precursors will be generated. pre ;

[0064] A distortion warning threshold N is set. If, within the most recent q consecutive observation times, the growth rate of the coarse texture area Gc(t') is greater than the distortion warning threshold N, i.e., satisfying the conditions Gc(t'-q+1)>N and Gc(t'-q+2)>N and... and Gc(t'>N, then the thermal storage tower is determined to have a precursor to temperature field distortion. The distortion warning threshold is determined using historical data, for example, by statistically analyzing the maximum value of Gc(t') under normal operating conditions and using 1.5 times that value as N; q is determined based on system stability, for example, 3 time points, to avoid the influence of a single anomaly. By determining the threshold over multiple consecutive time points, misjudgments based on a single anomaly are avoided. For example, if Gc(t') abnormally increases at a certain time point due to sensor fluctuations, relying solely on that moment would lead to a misjudgment as a precursor to distortion, while determining the threshold over q consecutive time points can filter out such interference.

[0065] Step S15: Calculate the position coordinates of all coarse texture primitives in each thermal storage tower. Based on these coordinates, calculate the texture centroid position. Calculate the heat flow deflection angle based on the centroid position. Determine if there is a risk of heat flow deflection in the thermal storage tower based on the heat flow deflection angle. If a risk exists, generate a heat flow deflection warning signal W. bias Otherwise, no bias warning signal W will be generated. bias ;

[0066] The texture centroid coordinates are (r c , z c ), where r c z is the radial coordinate of the texture centroid, equal to the average of the radial coordinates of all coarse texture points; c The axial coordinate of the texture centroid is equal to the average of the axial coordinates of all coarse texture points. The method for calculating the heat flow deflection angle based on the texture centroid position is as follows: Establish a texture centroid vector with the origin O of the cylindrical coordinate system as the starting point and the texture centroid position as the ending point. The angle between the texture centroid vector and the positive Z-axis of the cylindrical coordinate system is the heat flow deflection angle. The method for determining whether there is a risk of flow deviation in the heat storage tower based on the heat flow deflection angle is as follows: Set a flow deviation risk threshold θ. max When the heat flow deflection angle θ' is greater than θ max When this occurs, the thermal storage tower is deemed to have a risk of flow deviation. The risk threshold for flow deviation is determined based on the structural strength of the thermal storage body. When the angle is too large, the uneven stress and heating in local areas will be exacerbated; for example, it can be set at 30 degrees. The direction of heat flow deviation reflects the asymmetry of the temperature field. An excessively large deviation angle can lead to local overheating. For example, when the center of gravity of the texture is biased towards the radial edge, it indicates the presence of a heat island in the edge area. This area may continue to be heated due to airflow deviation. Early identification can prevent equipment damage. Without this step, only the existence of temperature field distortion is known, but its spatial deviation is unknown, making it impossible to adjust the airflow direction in a targeted manner, which may lead to an aggravation of flow deviation.

[0067] Step S16, if a distortion precursor warning signal W is present at the same time pre and the flow deviation warning signal W bias Then a comprehensive early warning signal W for temperature field distortion is generated. total .

[0068] When both distortion precursor warning signals W are present pre and the flow deviation warning signal W bias When the temperature field shows a distortion trend, it indicates that the distortion may worsen further due to the flow deviation. At this point, a comprehensive early warning signal is generated to trigger subsequent switching timing adjustments. Without this step, a single early warning signal may not be able to fully reflect the dangerous state of the temperature field. For example, a single early warning signal may only require routine adjustments, while a superimposed flow deviation warning requires emergency intervention, which may lead to inappropriate control strategies.

[0069] The establishment of a cylindrical coordinate system combined with mesh generation significantly improves the accuracy of the correlation between temperature data and spatial location, providing a structured data foundation for subsequent texture analysis. This precise spatial positioning makes it possible to compare temperature fields between different thermal regenerator towers, facilitating inter-tower collaborative analysis. The definition of texture primitives transforms the continuous temperature field into discrete features, which not only facilitates intuitive identification of heat islands or cold holes but also improves the efficiency of digital storage and transmission of the temperature field, reducing the complexity of data processing. The analysis of temporal evolution sequences not only captures the dynamic changes in temperature gradients but also optimizes subsequent early warning thresholds through training with historical data, improving the system's adaptability. The combination of distortion precursor judgment and flow deviation risk judgment forms a multi-dimensional early warning mechanism, which can not only detect temperature field anomalies in advance but also judge the development direction and potential risks of anomalies, providing a more comprehensive basis for subsequent switching timing adjustments. These synergistic effects upgrade the entire temperature field monitoring system from a single temperature acquisition system to a comprehensive system with spatial analysis, dynamic tracking, and risk prediction capabilities, providing crucial support for the stable operation of multi-tower modular thermal regenerator combustion systems. Step S10 overcomes the limitations of single-point monitoring through spatial global perception, transforms nonlinear gradients into analyzable features through texture quantization, captures dynamic trends through time-series tracking, improves the accuracy of early warning through multi-dimensional judgment, and finally ensures the necessity of control triggering through comprehensive early warning, forming a complete link from "discovery-identification-judgment-early warning". This solves the problems of traditional methods being unable to detect local temperature field distortions in the early stage and the distortion of switching judgment caused by nonlinear temperature gradients.

[0070] Step S20: Real-time monitoring of inlet VOC concentration and outlet temperature; when a comprehensive early warning signal W for temperature field distortion is received... total At that time, based on the monitored inlet VOC concentration and outlet temperature, the temperature rise state type is determined, the switching timing adjustment amount is calculated based on the temperature rise state type, and the final switching time is obtained based on the switching timing adjustment amount.

[0071] Further, step S20 includes:

[0072] Step S21, when the temperature field distortion comprehensive early warning signal W is received total At that time, based on the monitored inlet VOC concentration Cin(t) and outlet temperature Tout(t), the time of VOC concentration change and the time of outlet temperature response are identified, and the thermal inertia index is calculated.

[0073] Please see Figure 5 As shown, step S21 further includes:

[0074] Step S211: Monitor the inlet VOC concentration Cin(t) and outlet temperature Tout(t) in real time, and calculate the change in inlet VOC concentration ΔCin; when ΔCin is greater than the preset VOC concentration change detection threshold C... voc At this point, mark this moment as the timing start point t1, which is the moment of VOC concentration change, and start the timer;

[0075] Step S212: Starting from the timing start point t1, continuously monitor the change in outlet temperature ΔTout, where ΔTout is the difference between the current outlet temperature and the outlet temperature at time t1; when ΔTout is greater than the preset outlet temperature response threshold T', mark this moment as the timing end point t2, i.e. the outlet temperature response moment, and stop the timer.

[0076] Step S213: Subtract the VOC concentration change time from the outlet temperature response time to obtain the temperature conduction delay time Δt. delay ;

[0077] Step S214: Obtain the mass M and specific heat capacity c of the heat storage body, and then determine the specific heat capacity by delaying the time Δt. delay The thermal inertia index I is calculated by multiplying the mass M of the heat storage body by its specific heat capacity c.

[0078] The recording frequencies of inlet VOC concentration Cin(t) and outlet temperature Tout(t) are kept consistent to ensure time synchronization, where t is the current time. The change in inlet VOC concentration ΔCin is the difference between the current concentration and the concentration at the previous time, and the concentration change detection threshold C... voc This value is used to determine whether the inlet VOC concentration has changed significantly. It is determined experimentally, for example, by selecting the maximum VOC concentration fluctuation during normal system operation, and setting 1.6 times this maximum value as C. voc When ΔCin is greater than C voc At this point, mark the timing start point t1, i.e., the moment of VOC concentration change, and start the timer. In existing technologies, the response to VOC concentration changes largely relies on empirical judgment, lacking quantitative standards, often leading to missed or incorrect detections of effective concentration changes. However, by setting C... vocBased on the quantitative comparison of ΔCin, the concentration fluctuations that truly affect the combustion state can be accurately identified, and the timing start point t1 provides a clear starting point for subsequent temperature response monitoring. Starting from the timing start point t1, the change in outlet temperature ΔTout is continuously monitored. ΔTout is the difference between the current temperature and the temperature at time t1, i.e., ΔTout = Tout(t) - Tout(t1). An outlet temperature response threshold T' is set. When ΔTout is greater than T', this moment is marked as the timing end point t2, i.e., the outlet temperature response moment, and the timer is stopped. The outlet temperature response threshold is determined based on the maximum range of temperature fluctuation when the heat storage body is working normally. For example, the maximum fluctuation value of the outlet temperature within 10 minutes under normal operating conditions, such as 2℃, is statistically analyzed, and 1.5 times it, i.e., 3℃, is taken as T'. Traditional methods struggle to determine whether temperature changes are caused by fluctuations in VOC concentration. However, by monitoring ΔTout with t1 as a baseline, the causal relationship between temperature response and concentration change can be clearly established. For instance, if the VOC concentration suddenly increases at time t1, the outlet temperature gradually rises from 180°C. When it reaches 184°C, ΔTout = 4°C, which is greater than T' = 3°C. At this point, t2 is marked, accurately capturing the moment when the temperature responds to the concentration change. Without this step, it is impossible to distinguish between natural temperature fluctuations and concentration-induced responses, leading to distortion in the calculation of the delay time.

[0079] The temperature conduction delay time Δt is obtained by subtracting the VOC concentration change time t1 from the outlet temperature response time t2. delay , Δt delay This reflects the time required for the temperature change caused by the change in VOC concentration to travel from inside the heat storage body to the outlet sensor. For example, if t1 is the 10th second and t2 is the 15th second, then Δt... delay= The 5-second timeframe visually quantifies the hysteresis characteristics of temperature conduction. The mass M of the heat storage body is the total mass of the honeycomb ceramic material within the tower, calculated using the tower volume and material density. The specific heat capacity c is the specific heat capacity of the honeycomb ceramic, obtained through material handbook references or experimental measurements. The thermal inertia index I = Δt delay The thermal inertia index (×M×c) comprehensively reflects the thermal inertia of the heat storage medium. The greater the mass, the higher the specific heat capacity, and the longer the time delay, the greater the thermal inertia and the slower the temperature response. Current technologies determine switching timing solely based on temperature difference, neglecting the influence of the heat storage medium's own physical properties on temperature conduction. The thermal inertia index (I), however, combines physical properties with time delay, making the characterization of temperature response lag more closely resemble actual operating conditions. For example, for the same Δt... delay Under these conditions, the heat storage body with larger M and c values ​​has a larger I value, indicating that its temperature changes more slowly and requires earlier prediction lead time. If this step is missing, the difference in thermal inertia of the heat storage body cannot be quantified, resulting in different tower bodies using the same prediction strategy and reducing the adjustment accuracy.

[0080] Step S22: Calculate the prediction lead time Δt based on the thermal inertia index.ad Based on the predicted lead time Δt ad Determine the opening time and duration of the prediction window;

[0081] Calculate the lead time Δt based on the thermal inertia index. ad The specific process is as follows: Obtain the VOC concentration change rate. When the concentration change rate is positive, it indicates that the concentration is increasing. At this time, Δt ad It equals I multiplied by the square root of the rate of change of concentration. This is because as the concentration increases, the combustion intensity increases, and the temperature tends to rise at an accelerated rate. The square root relationship makes Δt... ad It is more sensitive to increases in the rate of change and can respond more quickly to rapid increases in concentration; when the rate of change in concentration is negative, it indicates a decrease in concentration, Δt ad The value is equal to I multiplied by the cube root of the absolute value of the concentration change rate. Since the temperature decreases more gradually as the concentration decreases, the cube root relation makes Δt... ad The rate of change increases more gradually in absolute value, avoiding premature adjustments; the VOC concentration change rate is the ratio of ΔCin to the time interval. For example, when I=100, the concentration change rate is +4 (mg / m³). 3 When ·s), Δt ad =100×√4=200 seconds; when the concentration change rate is -8 (mg / m³) 3 When ·s), Δt ad =100× 3 √8 = 200 seconds. It can be seen that under the same I, a smaller rate of change when the concentration increases can achieve the same Δt as a larger rate of change when the concentration decreases. ad It conforms to temperature response characteristics.

[0082] Δt before the normal switching time ad The prediction window is opened at time, and the duration of the prediction window is set to Δt. ad The value of n² should be greater than or equal to n², ensuring that the prediction window fully covers the entire process from the start of the temperature response to its stabilization. For example, a value of 1.5 times allows for dynamic adaptation to temperature response characteristics under different operating conditions, guaranteeing comprehensive capture of the dynamic process of temperature changes. This provides sufficient data support for subsequent temperature rise rate analysis and switching timing adjustments, thereby improving the accuracy of the prediction. For example, assuming Δt... ad When the time interval is 200 seconds, the window lasts for 300 seconds, opening 200 seconds before the normal switching time and ending 100 seconds after the normal switching time, covering the complete possible temperature change cycle. In existing technologies, the switching window is fixed and cannot adapt to the temperature response speed under different operating conditions. This dynamic window design, however, utilizes Δt... ad Differentiated calculations and duration settings enable precise coverage of the temperature response process.

[0083] Steps S21 and S22 address the switching timing lag problem caused by the inability to quantify temperature conduction delay in traditional methods: S21 identifies the time difference between concentration change and temperature response, and combines this with the physical parameters of the heat storage body to transform the abstract temperature lag into a calculable thermal inertia index I, thus elevating the characterization of temperature response characteristics from qualitative to quantitative. In S214, the thermal inertia index I integrates the delay time with the mass and specific heat capacity of the heat storage body, ensuring that the thermal inertia index not only reflects the time lag but also embodies the heat storage capacity of the heat storage body itself. This provides a fundamental parameter for calculating the lead time in S22, taking into account both time and physical characteristics. This integration avoids the one-sidedness of relying solely on time or solely on physical characteristics. In S22, Δt is calculated using different roots based on the sign of the concentration change rate. ad This allows the lead time to adapt to the direction of concentration changes, echoing the concentration change trend captured in S21. For example, when the concentration rises rapidly, the Δt calculated using the square root... ad More sensitive, coupled with a window duration of n² times, ensures that switching adjustments are completed before the temperature accelerates upward. The introduction of the thermal inertia index I allows for a unified predictive framework for heat storage towers of different materials and specifications; their respective temperature response characteristics can be adapted simply by adjusting the I value, improving the method's versatility. Simultaneously, the duration of the dynamic window is related to Δt... ad The linkage mechanism automatically extends the window when concentration fluctuations are drastic and shortens it when fluctuations are moderate, optimizing the allocation of computational resources and avoiding the resource waste of a fixed window during periods of moderate fluctuation and the insufficient coverage during periods of drastic fluctuation. If S21 is missing, the thermal inertia index I cannot be obtained, and the prediction lead calculation in S22 will lose its basis, leading to an error in Δt. ad The settings become mere experience values, failing to accurately match actual lag characteristics.

[0084] Step S23: Within the determined prediction window, the switching cycle is divided into three time periods: the front period, the middle period, and the back period, and the temperature rise rate of each time period is calculated.

[0085] Switching period T cycle The system's preset normal switching interval is divided into three continuous stages based on the dynamic characteristics of temperature changes within the switching cycle: the initial stage T... front 0 to m1 times T cycle ; Middle section T middle m1 times T cycle up to m2 times T cycle ; the latter part T rear m2 times T cycle Up to 1 T cycleWhere m1 is the proportion at the end of the first stage and m2 is the proportion at the end of the second stage, and 0 < m1 < m2 < 1. Typically, m1 is 0.2-0.4, corresponding to the initial heat accumulation stage, and m2 is 0.6-0.8, corresponding to the stable heat conduction stage, for example, m1=0.3, m2=0.7. The first stage usually corresponds to the initial heat accumulation stage after the concentration change, where the temperature change is relatively slow; the second stage is the stable stage of heat conduction, where the rate of change tends to be stable; the third stage may show an accelerating or decelerating trend due to the continuous accumulation or dissipation of heat. Within each stage, the temperature rise rate v1 of the first stage is calculated, which is the temperature change ΔT of the first stage. front In addition to the previous segment duration, the previous segment duration is m1 times T. cycle ΔT front The temperature difference between the end of the first stage and the beginning of the first stage is given; the temperature rise rate v2 in the middle stage is calculated, which is the temperature change ΔT in the middle stage. middle Divide by the middle segment duration, the middle segment duration is (m2-m1) times T. cycle ΔT middle The temperature difference between the end of the middle section and the beginning of the middle section is given; the temperature rise rate v3 in the latter section is calculated, which is the temperature change ΔT in the latter section. rear Excluding the duration of the latter segment, the duration of the latter segment is (1-m2) times T. cycle ΔT rear This is the temperature difference between the end of the second phase and the beginning of the second phase.

[0086] For example, suppose T cycle =60 seconds, m1=0.3, m2=0.7, the temperature rises from 180℃ to 182℃ in the first 0-18 seconds, then ΔT front =2℃, v1=2℃ / 18 seconds≈0.11℃ / second; the temperature rises to 185℃ within the middle section of 18-42 seconds, ΔT middle 3℃, v2 = 3℃ / 24 seconds = 0.125℃ / second; the temperature rises to 190℃ in the latter 42-60 seconds, ΔT rear =5℃, v3=5℃ / 18 seconds≈0.28℃ / second.

[0087] In existing technologies, the average temperature rise rate over the entire cycle is often used to determine the trend, which cannot capture the rate changes at different stages. However, by performing segmented calculations, the acceleration or deceleration characteristics of temperature changes can be accurately identified. For example, when v3 is significantly greater than v1 in the later stage, it indicates that the temperature is accelerating, providing a detailed basis for subsequent state determination. If this step is missing, it will be impossible to distinguish the dynamic trend of temperature changes within the cycle, leading to misjudgment of the temperature rise state and thus affecting the accuracy of switching adjustments.

[0088] Step S24: Calculate the temperature rise rate ratio based on the temperature rise rate over three time periods, and determine the temperature rise state type based on the temperature rise rate ratio; then, based on the temperature rise state type and the predicted lead time Δt...ad Calculate the handover timing adjustment amount, and obtain the final handover time based on the handover timing adjustment amount; the handover timing adjustment amount includes the adjustment amount for early handover time or late handover time.

[0089] The temperature rise rate ratio Ra is the ratio of the later temperature rise rate v3 to the earlier temperature rise rate v1; the accelerated temperature rise judgment threshold R is set. thr The threshold for accelerated temperature rise is determined by analyzing the fluctuation range of Ra during normal system operation. For example, the maximum value of Ra under stable operating conditions is statistically analyzed and used as the threshold for R. thr Under stable operating conditions of a multi-tower modular regenerative thermal ignition system, R thr Typically greater than 1, this is directly related to the heat conduction characteristics of the heat storage body and the temperature change pattern under stable operating conditions. Ra is the ratio of the temperature rise rate v3 in the later stage to the temperature rise rate v1 in the earlier stage, reflecting the dynamic trend of temperature change within the switching cycle. Under stable operating conditions, VOC concentration fluctuations are small and the combustion state is stable. Heat gradually accumulates and is conducted in the heat storage body, and its temperature change exhibits a "gradual increase" characteristic: the earlier stage corresponds to the initial heat conduction stage, when the heat storage body just begins to absorb heat, the temperature rise is slow, and v1 is small; as heat continues to be transferred, the temperature rise rate in the middle stage tends to stabilize; in the later stage, because the heat has completed the initial accumulation in the heat storage body, the conduction efficiency is improved, and the temperature rise rate will be slightly greater than that in the earlier stage, that is, v3 is slightly greater than v1. This "slow in the earlier stage and slightly faster in the later stage" rule is determined by the thermal inertia of the heat storage body. The heat conduction of honeycomb ceramic materials takes time. In the early stage, the heat is mainly used to heat the heat storage body itself, while in the later stage, it is more manifested as a visible temperature rise. Therefore, the Ra value under stable operating conditions is usually slightly greater than 1. thr As the maximum value of Ra under steady-state conditions, its value is determined based on this rule, therefore R thr It is usually greater than 1, and is typically between 1.2 and 1.5.

[0090] When Ra is greater than or equal to R thr When Ra is less than or equal to R, it is determined to be in an accelerated temperature rise state, where the temperature rises faster over time, requiring early switching to avoid high-temperature stagnation; thr When Ra is counted in reverse, it is determined to be a decelerating temperature rise state. At this time, the rate of temperature rise slows down with time, and the switching can be appropriately delayed to make full use of heat storage; when Ra is greater than 1 / R thr And less than R thr When the temperature rise is considered to be in a stable state, with a steady rate of temperature change, switching can proceed according to the normal cycle. The method for calculating the adjustment amount for switching timing based on the temperature rise state type is shown in Table 1. For accelerated temperature rise states, the adjustment amount Δt for advance switching time is calculated. early , Δt early Equal to the lead time Δt adMultiply by the temperature rise rate ratio Ra, because the larger Ra is, the more obvious the temperature acceleration trend is, requiring a larger lead time to offset the lag; for the decelerating temperature rise state, calculate the adjustment amount Δt for the delayed switching time. late , Δt late Equal to the lead time Δt ad Divide by the temperature rise rate ratio Ra. Since the smaller Ra is, the more significant the deceleration trend, and the lag needs to be increased accordingly. The final switching time is the original switching time plus the advance or lag amount. In existing technologies, the switching adjustment is mostly a fixed value, which cannot adapt to dynamic changes in the temperature rise rate. However, by using Ra and Δt... ad The linkage calculation enables the adjustment energy to accurately match the temperature change trend. For example, when v3 is much greater than v1, Ra increases, leading to Δt early The adjustment is increased synchronously to ensure that the amount of advance switching is sufficient to cope with the accelerated temperature rise. If this step is missing, the adjustment amount will not be dynamically linked to the temperature rise, which may result in insufficient advance or excessive delay, leading to deviations in the timing of the switchover.

[0091] Table 1. Calculation of Switching Timing Adjustment Based on Temperature Rise Status Type

[0092]

[0093] Step S24 achieves dynamic and precise adjustment of the switching timing by organically combining the segmented temperature rise rate with the predicted lead time. The Ra value can accurately characterize the acceleration or deceleration characteristics of temperature changes, avoiding the limitations of a single average rate. For example, when the average rate is the same throughout the cycle but slower at the beginning and faster at the end, Ra can capture the acceleration trend, while the average rate cannot distinguish it; compared to Δt... ad Combined, through Ra with respect to Δt ad The scaling factor allows the adjustment amount to consider both the thermal inertia of the heat storage body and the real-time temperature rise trend, for example, when the thermal inertia is large (Δt). ad When Ra is large and acceleration is significant (Ra is large), Δt early This adjustment mechanism is significantly increased to ensure that the adjustment magnitude matches the lag risk. It is adaptive; when the system faces complex VOC concentration fluctuations, the adjustment amount automatically corrects itself through dynamic changes in Ra over different periods, avoiding over-adjustment. For example, if a sudden increase in concentration leads to an accelerated temperature rise followed by a sharp drop, Ra will adjust from a value greater than R. thr Become less than R thr The reciprocal of Ra changes the adjustment amount from early to late, keeping the system at the optimal switching rhythm. At the same time, the introduction of Ra makes the adjustment of different switching cycles coherent. The Ra change trend of the previous cycle can be used as a reference for the adjustment of the next cycle, forming a smooth transition in timing and reducing drastic fluctuations in switching actions.

[0094] Step S20 solves the switching lag problem caused by temperature conduction delay through a complete chain of "thermal inertia quantification - prediction window setting - segmented rate analysis - dynamic adjustment calculation". Specifically, step S21 uses Δt delay The thermal inertia index I is calculated based on the physical parameters of the heat storage body, transforming the temperature conduction delay from a qualitative description into a quantitative indicator, making the hysteresis characteristics under different operating conditions comparable; step S22 determines Δt based on I and the concentration change rate. ad The system employs a predictive window to ensure that the adjustment lead time matches the system's hysteresis characteristics, and the window duration covers the entire temperature response process. Step S23 captures the dynamic details of temperature changes through piecewise rate calculations, avoiding the misleading effect of the overall average rate. Step S24 determines the state based on Ra and calculates the switching adjustment amount, ensuring that the switching timing accurately responds to the real-time temperature rise trend. These steps work synergistically to form a closed loop from hysteresis quantification to action execution, changing the traditional switching method based on fixed thresholds or experience. This allows the switching timing to dynamically adapt to the complex relationship between VOC concentration fluctuations and temperature conduction delays. For example, when a sudden increase in VOC concentration causes rapid temperature rise in the combustion zone but a lag in the outlet temperature, the adjustment is achieved through Δt... delay Capture lag duration, Δt ad By setting a lead time and using Ra to identify acceleration trends, the system can switch ahead of time to avoid high-temperature stagnation. When a slow decrease in concentration leads to a slow temperature response, Δt is used to... ad In coordination with Ra, the delayed switching fully utilizes heat storage and improves thermal efficiency. Without step S20, the temperature field distortion warning in step S10 cannot be translated into specific switching control actions, rendering the warning signal meaningless and leading to a disconnect between "identifying the problem but being unable to solve it." Simultaneously, the inter-tower coordinated adjustment in step S30 will lack a precise switching timing reference, making it difficult to achieve inter-tower energy balance due to inconsistent switching timing. Step S20, as the core link connecting early warning and final control, ensures that the warning signal can avoid high-temperature stagnation through quantified adjustment actions, providing crucial support for the safe and efficient operation of the entire system.

[0095] Step S30: Before performing the switching operation, construct the inter-tower energy difference matrix based on the two-dimensional temperature matrix of each thermal storage tower; determine whether there is an inter-tower energy imbalance based on the inter-tower energy difference matrix; if there is an inter-tower energy imbalance, trigger the coordinated regulation mode while performing the switching according to the final switching time.

[0096] Further, step S30 includes:

[0097] Step S31: Calculate the total stored thermal energy of each thermal storage tower based on the two-dimensional temperature matrix of each tower, and construct the energy difference matrix between the towers.

[0098] The two-dimensional temperature matrix contains the temperature data for each grid cell; the calculation process for the total stored thermal energy is as follows: for the i'-th thermal storage tower, its total stored thermal energy E i' Equals the mass of the i'th thermal storage tower body multiplied by the specific heat capacity C of the i'th thermal storage tower body. i' Multiply by the average temperature T of the i'th heat storage tower body d. avg,i' The average temperature T of the i'th thermal storage tower avg,i' The average temperature value is obtained by averaging the temperature values ​​of all temperature collection points in the i'th thermal storage tower.

[0099] The method for constructing the energy difference matrix between towers is as follows: calculate the energy difference ΔE between any two towers. i'j' ΔE i'j' Let ΔE be the absolute value of the difference in total stored thermal energy between the i'th tower and the j'th tower. i'j' As matrix elements, an energy difference matrix is ​​constructed. In existing technologies, the energy state of multi-tower systems lacks quantitative comparison methods, making it impossible to accurately identify energy imbalances. This step, however, transforms two-dimensional temperature data into comparable total stored thermal energy, providing a clear quantitative indicator for energy differences between towers. Without this step, the energy state between towers would be ambiguous, and collaborative regulation would lack a basis for judgment.

[0100] Step S32: Extract the maximum energy difference from the inter-tower energy difference matrix. If the maximum energy difference is greater than the preset deviation warning limit, it is determined that there is an energy imbalance between the towers. At the switching time, the switching is performed and the coordinated adjustment mode is triggered.

[0101] Further, step S32 includes:

[0102] Step S321: Calculate the average energy E of each tower based on the total stored thermal energy of each tower. avg The total stored thermal energy is greater than the average energy E. avg The thermal storage tower is identified as a high-energy tower, with the total stored thermal energy less than or equal to the average energy E. avg The thermal storage tower was identified as a low-energy tower;

[0103] Step S322: Set the purge flow enhancement ratio for the high-energy tower and the purge flow reduction ratio for the low-energy tower, and calculate the purge flow adjustment coefficient for each tower; calculate the adjusted purge flow for each tower based on the purge flow adjustment coefficient.

[0104] The deviation warning upper limit is determined as follows: The maximum energy difference between towers over a continuous 24-hour period during stable system operation is statistically analyzed, and 1.2 times this difference is taken as the deviation warning upper limit, ensuring that regulation is triggered only when the energy difference is significant. The average energy E of each tower... avg For all tower bodies E i' Divide the sum by the number of towers; the total stored thermal energy is greater than E. avgThe thermal storage tower is identified as a high-energy tower, with a total stored thermal energy less than or equal to E. avg The thermal storage tower was identified as a low-energy tower. A purge flow enhancement ratio β was set for the high-energy tower. high Set the purge flow reduction ratio β for low-energy towers low ,β high The value range of β is 0.1-0.3. low The value range of β is 0.08-0.25, as shown in Table 2. high and β low The specific value is determined based on the ratio k* of the maximum energy difference to the upper limit of the deviation warning.

[0105] Table 2 β high and β low The range of values

[0106]

[0107] For example, when k*=1.1, βhigh=0.15 and βlow=0.12. These two are related through the flow distribution balance equation: the sum of the increase in purge flow rate of all high-energy towers equals the sum of the decrease in purge flow rate of all low-energy towers, ensuring the stability of the total system flow rate. The expression for the flow distribution balance equation is: the sum of the increase in purge flow rate of all high-energy towers equals the sum of the decrease in purge flow rate of all low-energy towers. The purge flow rate adjustment coefficient for each tower is calculated; the adjustment coefficient for the high-energy tower is 1+β. high The low-energy tower has a 1-β value. low For example, β high =0.2, then the adjustment coefficient of the high-energy tower is 1.2, β low =0.15, then the adjustment coefficient of the low-energy tower is 0.85, and the adjusted purging flow rate is the original flow rate multiplied by the purging flow rate adjustment coefficient.

[0108] Step S323: Sort all towers according to the total stored thermal energy from high to low to form a thermal energy sorting sequence. Generate a dynamic switching sequence of the thermal storage towers based on the thermal energy sorting sequence. Perform inter-tower coordinated regulation based on the dynamic switching sequence of the thermal storage towers and the adjusted purging flow rate of each tower.

[0109] Dynamic switching sequence refers to the order in which each heat storage tower is switched based on the real-time adjustment of the thermal energy sorting sequence. Its core is to prioritize the exhaust operation of high-energy towers to accelerate heat dissipation, and prioritize the intake operation of low-energy towers to fully absorb heat. It is also necessary to ensure that the system has at least one intake tower and one exhaust tower at the same time to maintain the combustion and heat storage cycle. The specific implementation process is as follows: Based on the total stored thermal energy of each tower, all towers are numerically sorted from high to low according to their total stored thermal energy, forming a thermal energy sorting sequence. For example, assuming there are four thermal storage towers with total stored thermal energies of Ea=1200kJ, Eb=900kJ, Ec=1500kJ, and Ed=800kJ, the thermal energy sorting sequence is Ec, Ea, Eb, Ed. Next, a dynamic switching sequence is generated based on this sorting sequence. High-energy towers at the front of the sequence are given priority to exhaust, while low-energy towers at the back are given priority to intake. For example, for the above sequence, the dynamic switching sequence is set as Ec exhausts first, Ea exhausts second, Eb intakes first, and Ed intakes second. Combined with the calculated adjusted purging flow rate, high-energy towers are purged with the enhanced purging flow rate to accelerate heat release, while low-energy towers are purged with the reduced purging flow rate to reduce heat loss. For example, if the original purging flow rate of Ec is 600m³ / h… 3 / h, with an adjustment coefficient of 1.2, the adjusted purging flow rate is 720m³ / h. 3 / h, Ed's original purge flow rate is 500m³ / h. 3 / h, with an adjustment coefficient of 0.8, the adjusted purging flow rate is 400m³ / h. 3 / h; Finally, when the switching time arrives, the intake and exhaust of each tower are switched according to the dynamic switching sequence, and the adjusted purging flow rate is applied simultaneously to achieve coordinated energy balance between towers.

[0110] Step S30, by constructing an inter-tower energy difference matrix and triggering a collaborative adjustment mode, not only solves the system imbalance problem caused by uneven heat distribution among multiple towers, but also, through the combination of dynamic switching sequence and differentiated purging flow rate, matches the heat dissipation rate of high-energy towers with the heat absorption rate of low-energy towers, avoiding excessive heat storage or insufficient heat dissipation in a single tower. This synergizes with the temperature field distortion warning in step S10. The energy state of the tower corresponding to the local heat island or cold hole identified in step S10 is precisely intervened through the collaborative adjustment in step S30. Compared with the separate warning, the combination of the two makes the mitigation of temperature field distortion more targeted. For example, if a tower has a high total stored heat energy due to a "heat island", after the comprehensive temperature field distortion warning in step S10 is triggered, step S30 can reduce its energy in a shorter time by prioritizing exhaust and enhancing purging, thus curbing the expansion of the heat island. The quantitative analysis of the energy difference matrix provides a data foundation for inter-tower coordination and forms a linkage with the adjustment of the dynamic switching time in step S20. The switching time determined in step S20 provides a precise time node for the coordinated adjustment in step S30, ensuring that the energy balance between towers is carried out at the optimal time after the temperature conduction delay is compensated. Compared with only adjusting the switching time without inter-tower coordination, this linkage enables the system to avoid overheating of a single tower and make the overall energy distribution more uniform when dealing with VOC concentration fluctuations. For example, when the VOC concentration rises sharply and causes some towers to heat up rapidly, step S20 switches in advance to avoid high temperature retention, and step S30 adjusts the inter-tower energy synchronously to prevent heat from concentrating in a few towers.

[0111] The system's robustness in responding to sudden fluctuations in VOC concentration is significantly improved. When the concentration changes abruptly, the dynamic switching sequence can quickly transfer heat from the high-energy tower to the low-energy tower, avoiding a chain reaction of overheating caused by concentrated heat. This is something that cannot be achieved with the traditional fixed switching sequence, which may lead to continuous air intake in the high-energy tower, exacerbating overheating. The overall service life of the heat storage body is extended. Due to the more balanced energy distribution between towers, the thermal stress fluctuation of each tower is reduced, and the rate of cracking and aging of the honeycomb ceramic heat storage body caused by local overheating or overcooling is reduced. It is inferred that under the same operating cycle, the replacement frequency of the heat storage body using this coordinated regulation mode can be reduced because the uniform heat distribution reduces thermal fatigue damage to the material. The overall thermal efficiency of the system is further improved. The priority air intake of the low-energy tower can more fully absorb the heat generated by combustion, and the priority exhaust of the high-energy tower can more efficiently release the stored heat. The heat utilization rate is improved. Combined with the strategy of delaying the switching in step S20 to make full use of the heat storage, the flow of heat energy between towers is more efficient. Compared with adjusting the switching timing alone, the improvement in thermal efficiency is more significant. If step S30 is missing, the temperature field distortion early warning in step S10 and the switching timing adjustment in step S20 will not be able to form a closed-loop control in the multi-tower system. The simultaneous distortion of multiple towers identified in step S10 cannot be resolved by single-tower switching adjustment, and the switching timing adjustment in step S20 only targets a single tower, failing to balance the energy differences between towers. This leads to an exacerbation of the overall system imbalance and may even trigger the risk of multiple towers overheating simultaneously. Therefore, step S30 is a crucial link connecting local early warning and overall control. Through inter-tower collaboration, it enables the various technical features to form an organic whole, ensuring the stable and efficient operation of the system under complex operating conditions.

[0112] Example 2:

[0113] This embodiment, based on Embodiment 1, provides a zone switching control device for a multi-tower modular regenerative thermal ignition system, such as... Figure 6 As shown, it includes:

[0114] Distortion early warning module: It is used to receive temperature data collected by temperature acquisition point array and form a two-dimensional temperature matrix; based on the two-dimensional temperature matrix, it performs temperature field distortion precursor judgment and flow deviation risk judgment for each thermal storage tower; and generates a comprehensive temperature field distortion early warning signal based on the judgment results of temperature field distortion precursor and flow deviation risk.

[0115] Switching Time Determination Module: Used for real-time monitoring of inlet VOC concentration and outlet temperature. When a comprehensive early warning signal W for temperature field distortion is received... total At that time, based on the monitored inlet VOC concentration and outlet temperature, the temperature rise state type is determined, the switching timing adjustment amount is calculated based on the temperature rise state type, and the final switching time is obtained based on the switching timing adjustment amount.

[0116] Coordinated regulation module: Before performing the switching operation, an inter-tower energy difference matrix is ​​constructed based on the two-dimensional temperature matrix of each thermal storage tower; the inter-tower energy difference matrix is ​​used to determine whether there is an inter-tower energy imbalance; if there is an inter-tower energy imbalance, the coordinated regulation mode is triggered at the same time as the final switching time.

[0117] Furthermore, in the switching time determination module, the method for determining the temperature rise state type based on the monitored inlet VOC concentration and outlet temperature includes:

[0118] When a comprehensive early warning signal for temperature field distortion W is received total At that time, based on the monitored inlet VOC concentration Cin(t) and outlet temperature Tout(t), the time of VOC concentration change and the time of outlet temperature response are identified, and the thermal inertia index is calculated.

[0119] Calculate the lead time Δt based on the thermal inertia index. ad Based on the predicted lead time Δt ad Determine the opening time and duration of the prediction window;

[0120] Within the defined prediction window, the switching cycle is divided into three time periods: the front, middle, and back, and the temperature rise rate for each time period is calculated.

[0121] Based on the temperature rise rate over three time periods, the temperature rise rate ratio is calculated, and the temperature rise state type is determined according to the temperature rise rate ratio.

[0122] Furthermore, in the coordinated adjustment module, the triggering of the coordinated adjustment mode includes:

[0123] Step S321: Calculate the average energy E of each tower based on the total stored thermal energy of each tower. avg The total stored thermal energy is greater than the average energy E. avg The thermal storage tower is identified as a high-energy tower, with the total stored thermal energy less than or equal to the average energy E. avg The thermal storage tower was identified as a low-energy tower;

[0124] Step S322: Set the purge flow enhancement ratio for the high-energy tower and the purge flow reduction ratio for the low-energy tower, and calculate the purge flow adjustment coefficient for each tower; calculate the adjusted purge flow for each tower based on the purge flow adjustment coefficient.

[0125] Step S323: Sort all towers according to the total stored thermal energy from high to low to form a thermal energy sorting sequence. Generate a dynamic switching sequence of the thermal storage towers based on the thermal energy sorting sequence. Perform inter-tower coordinated regulation based on the dynamic switching sequence of the thermal storage towers and the adjusted purging flow rate of each tower.

[0126] The methods and apparatus of this application may be implemented in many ways. For example, they may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order of steps for the method is for illustrative purposes only, and the steps of the method of this application are not limited to the order specifically described above, unless otherwise specifically stated.

[0127] In addition, the parts of the technical solutions provided in the embodiments of this application that are consistent with the implementation principles of the corresponding technical solutions in the prior art have not been described in detail, so as to avoid excessive elaboration.

[0128] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the invention. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A zone switching control method for a multi-tower modular regenerative thermal ignition system, characterized in that, The method includes: Temperature acquisition points are set up for each thermal storage tower to receive temperature data collected by the acquisition points and form a two-dimensional temperature matrix. Based on the two-dimensional temperature matrix, temperature field distortion precursors and flow deviation risks are determined for each thermal storage tower. Based on the determination results of temperature field distortion precursors and flow deviation risks, a comprehensive early warning signal for temperature field distortion is generated. The method for determining the precursors of temperature field distortion for each thermal storage tower includes: calculating the temperature difference between adjacent temperature acquisition points based on a two-dimensional temperature matrix; defining coarse and fine texture primitives corresponding to each grid unit based on the temperature difference, wherein the coarse and fine texture primitives constitute a texture distribution map; continuously recording the texture distribution map at fixed time intervals to form a texture evolution sequence; calculating the coarse texture area growth rate based on the texture evolution sequence; and determining whether the thermal storage tower exhibits precursors of temperature field distortion based on the coarse texture area growth rate. Real-time monitoring of inlet VOC concentration and outlet temperature; when a comprehensive early warning signal for temperature field distortion W is received... total At that time, based on the monitored inlet VOC concentration and outlet temperature, the temperature rise state type is determined, the switching timing adjustment amount is calculated based on the temperature rise state type, and the final switching time is obtained based on the switching timing adjustment amount. Before performing the switching operation, an inter-tower energy difference matrix is ​​constructed based on the two-dimensional temperature matrix of each thermal storage tower. The inter-tower energy difference matrix is ​​used to determine whether there is an inter-tower energy imbalance. If there is an inter-tower energy imbalance, the switching is performed at the final switching time, and the coordinated regulation mode is triggered simultaneously.

2. The zone switching control method for a multi-tower modular regenerative thermal ignition system according to claim 1, characterized in that, The method for setting up the temperature acquisition point array is as follows: a cylindrical coordinate system is established with the geometric center of each heat storage tower as the origin O, and the grid cells are divided according to the radial and axial directions of the cylindrical coordinate system. Temperature acquisition points are arranged at the center of each grid cell to form a temperature acquisition point array.

3. The zone switching control method for a multi-tower modular regenerative thermal ignition system according to claim 2, characterized in that, The method for defining the coarse texture primitive and fine texture primitive corresponding to each mesh unit includes: For radially adjacent temperature acquisition points, calculate the radial temperature difference; for axially adjacent temperature acquisition points, calculate the axial temperature difference; when the absolute value of the radial temperature difference or the absolute value of the axial temperature difference is greater than the coarse texture determination threshold M', mark the mesh unit corresponding to the temperature acquisition point as a coarse texture primitive and assign texture label Tc; otherwise, mark it as a fine texture primitive and assign texture label Tf.

4. The zone switching control method for a multi-tower modular regenerative thermal ignition system according to claim 3, characterized in that, The method for determining whether there are precursors to temperature field distortion in the thermal storage tower includes: A distortion warning threshold N is set. If the growth rate of coarse texture area is greater than the distortion warning threshold N in the most recent q consecutive observations, it is determined that there is a precursor to temperature field distortion in the thermal storage tower.

5. The zone switching control method for a multi-tower modular regenerative thermal ignition system according to claim 4, characterized in that, The method for determining the risk of flow deviation includes: The position coordinates of all coarse texture primitives in each thermal storage tower are counted. Based on the position coordinates of all coarse texture primitives, the position of the texture centroid is calculated. Based on the position of the texture centroid, the heat flow deflection angle is calculated. Based on the heat flow deflection angle, it is determined whether there is a risk of flow deviation in the thermal storage tower.

6. The zone switching control method for a multi-tower modular regenerative thermal ignition system according to claim 5, characterized in that, The method for generating a comprehensive early warning signal for temperature field distortion is as follows: If there are precursors to temperature field distortion, generate a warning signal for the precursors to distortion. If there is a risk of flow deviation, a flow deviation warning signal will be generated. If both the early warning signal for distortion and the early warning signal for skewed flow exist simultaneously, a comprehensive early warning signal for temperature field distortion will be generated.

7. The zone switching control method for a multi-tower modular regenerative thermal ignition system according to claim 6, characterized in that, The method for determining the type of temperature rise state includes: When a comprehensive early warning signal for temperature field distortion W is received total At that time, based on the monitored inlet VOC concentration Cin(t) and outlet temperature Tout(t), the time of VOC concentration change and the time of outlet temperature response are identified, and the thermal inertia index is calculated, where t is the current time; Calculate the lead time Δt based on the thermal inertia index. ad Based on the predicted lead time Δt ad Determine the opening time and duration of the prediction window; Within the defined prediction window, the switching cycle is divided into three time periods: the front, middle, and back, and the temperature rise rate for each time period is calculated. Based on the temperature rise rate over three time periods, the temperature rise rate ratio is calculated, and the temperature rise state type is determined according to the temperature rise rate ratio.

8. The zone switching control method for a multi-tower modular regenerative thermal ignition system according to claim 7, characterized in that, The method for identifying the time of VOC concentration change and the time of outlet temperature response includes: Based on the real-time monitored inlet VOC concentration Cin(t), the change in inlet VOC concentration ΔCin is calculated; when ΔCin is greater than the preset VOC concentration change detection threshold C... voc At this point, mark this moment as the timing start point t1, which is the moment of VOC concentration change, and start the timer; Starting from the timing point t1, continuously monitor the change in outlet temperature ΔTout, which is the difference between the current outlet temperature and the outlet temperature at time t1. When ΔTout is greater than the preset outlet temperature response threshold T', mark this moment as the timing point t2, i.e. the outlet temperature response moment, and stop the timer.

9. The zone switching control method for a multi-tower modular regenerative thermal ignition system according to claim 8, characterized in that, The method for calculating the thermal inertia index includes: The temperature conduction delay time Δt is obtained by subtracting the VOC concentration change time from the outlet temperature response time. delay ; Obtain the mass M and specific heat capacity c of the heat storage body by delaying the time Δt. delay The thermal inertia index I is calculated by multiplying the mass M of the heat storage body by its specific heat capacity c.

10. The zone switching control method for a multi-tower modular regenerative thermal ignition system according to claim 9, characterized in that, The temperature rise rate ratio is the ratio of the temperature rise rate in the later stage to the temperature rise rate in the earlier stage. The method for determining the temperature rise state type based on the temperature rise rate ratio includes: when the temperature rise rate ratio is greater than or equal to the accelerated temperature rise determination threshold, it is determined to be an accelerated temperature rise state; When the ratio of temperature rise rates is less than or equal to the reciprocal of the accelerated temperature rise threshold, it is determined to be a decelerated temperature rise state; when the ratio of temperature rise rates is greater than the reciprocal of the accelerated temperature rise threshold but less than the reciprocal of the accelerated temperature rise threshold, it is determined to be a stable temperature rise state.

11. A zone switching control device for a multi-tower modular regenerative thermal ignition system, used to implement the zone switching control method for a multi-tower modular regenerative thermal ignition system as described in any one of claims 1-10, characterized in that, The device includes: Distortion early warning module: It is used to receive temperature data collected by temperature acquisition point array and form a two-dimensional temperature matrix; based on the two-dimensional temperature matrix, it performs temperature field distortion precursor judgment and flow deviation risk judgment for each thermal storage tower; and generates a comprehensive temperature field distortion early warning signal based on the judgment results of temperature field distortion precursor and flow deviation risk. Switching Time Determination Module: Used for real-time monitoring of inlet VOC concentration and outlet temperature. When a comprehensive early warning signal W for temperature field distortion is received... total At that time, based on the monitored inlet VOC concentration and outlet temperature, the temperature rise state type is determined, the switching timing adjustment amount is calculated based on the temperature rise state type, and the final switching time is obtained based on the switching timing adjustment amount. Coordinated regulation module: Before performing the switching operation, an inter-tower energy difference matrix is ​​constructed based on the two-dimensional temperature matrix of each thermal storage tower; the inter-tower energy difference matrix is ​​used to determine whether there is an inter-tower energy imbalance; if there is an inter-tower energy imbalance, the coordinated regulation mode is triggered at the same time as the final switching time.

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