Gasification furnace soft measurement method and system based on mechanism model and electronic equipment

Abstract

The invention discloses a gasification furnace soft measurement method and system based on a mechanism model and electronic equipment, and relates to the technical field of industrial automation. According to the method, after a first target parameter including the specific enthalpy of cooling water before entering the water cooling wall of the gasification furnace, the specific enthalpy of water or a water-vapor mixture after cooling and total reaction heat obtained through a mechanism model of the gasification furnace is obtained, the first target parameter is input into a wall surface heat exchange model established based on the energy conservation relation of the water cooling wall; and the wall surface heat loss coefficient of the gasification furnace is obtained, and then the obtained wall surface heat loss coefficient is input into the mechanism model so as to enable the mechanism model to determine the working state of the gasification furnace. Therefore, the problems that when the working state of the gasification furnace is determined by adopting a mechanism model, the wall surface heat loss coefficient is estimated through experimental data or an empirical model, so that an estimation result is easy to distort, and production is difficult to effectively guide are solved.

Description

Technical Field

[0001] The present application relates to the technical field of industrial automation, and more specifically, to a soft measurement method, system and electronic device for a gasifier based on a mechanism model. Background Art

[0002] Compared with fixed beds and fluidized beds, entrained flow gasification technology has better coal type adaptability. However, the gasifier adopts a liquid slag discharge method, which requires the coal ash to have good melting characteristics and has high requirements for the temperature distribution of the syngas. For example: when the reaction temperature of the gasifier is too high, the wall temperature is too high, which will cause the viscosity of the coal slag layer to be too low, and it is impossible to effectively form a slag layer, thereby shortening the service life of the refractory brick or water-cooled wall, affecting long-term stable operation and reducing the effective gas production; when the temperature of the gasifier is too low, the coal slag cannot melt, which may lead to difficult slag discharge, even blockage, and the coal consumed to produce the same amount of effective gas will also increase. However, the reaction process inside the gasifier is rapid and the relationship is complex. The highest point and average temperature are too high, and conventional temperature sensors are difficult to operate in the harsh environment of high temperature inside the gasifier for a long time. Therefore, it is usually necessary to establish a soft measurement instrument for the temperature of the gasifier to guide the optimization control of production.

[0003] Soft measurement instruments can usually be established through data-driven models or mechanism models. Among them, because the mechanism model has good transparency and interpretability, and generally can always reflect the conservation relationship of the system, it is more suitable for on-site applications. However, considering the complex and changeable on-site environment and the current situation of actual on-site instruments, the heat exchange relationships of different gasifier devices vary greatly, and the heat exchange situation of the same gasifier is also affected by various factors. At the same time, when calculating the mechanism, the heat loss coefficient of the gasifier has a great influence on the reaction rate and temperature distribution. Therefore, when actually applying the mechanism model, it is necessary to solve the calibration and online estimation problems of the heat loss coefficient. However, the existing technology usually estimates this parameter through experimental data or empirical models, which will cause the results estimated by the mechanism model to be easily distorted, and thus it is difficult to effectively guide production. Summary of the Invention

[0004] In view of this, the embodiments of the present application are committed to providing a soft measurement method, system and electronic device for a gasifier based on a mechanism model, so as to solve the problem that when determining the working state of the gasifier by using a mechanism model, the estimation results are easily distorted due to estimating the wall heat loss coefficient through experimental data or empirical models, and thus it is difficult to effectively guide production.

[0005] In a first aspect, the present invention provides a soft measurement method for a gasifier based on a mechanism model, including:

[0006] Obtain a first target parameter, where the first target parameter includes: the specific enthalpy of the cooling water before entering the water-cooled wall of the gasifier, the specific enthalpy of the cooled water or water-vapor mixture, and the total reaction heat obtained from the mechanism model of the gasifier;

[0007] Input the first target parameter into the wall heat transfer model to obtain the wall heat loss coefficient of the gasifier;

[0008] Input the wall heat loss coefficient into the mechanism model to enable the mechanism model to determine the working state of the gasifier;

[0009] Wherein, the wall heat transfer model is established based on the energy conservation relationship of the water-cooled wall.

[0010] In a possible implementation manner, the soft measurement method of the gasifier based on the mechanism model further includes:

[0011] Obtain a second target parameter, where the second target parameter includes: the process parameters of the feedstock entering the furnace, the quality parameters of the coal entering the furnace, and the elemental composition of the syngas at the outlet of the gasifier;

[0012] Based on the second target parameter, determine the elemental composition of the coal entering the furnace;

[0013] Input the elemental composition of the coal entering the furnace into the mechanism model to enable the mechanism model to determine the working state of the gasifier.

[0014] In a possible implementation manner, the determining the elemental composition of the coal entering the furnace based on the second target parameter includes:

[0015] Input the second target parameter into a preset coal element conservation model to obtain the elemental composition of the coal entering the furnace output by the coal element conservation model;

[0016] Wherein, the coal element conservation model is established based on the conservation relationship between the elements contained in the feedstock entering the furnace and the corresponding elements contained in the syngas at the outlet.

[0017] In a possible implementation manner, after obtaining the second target parameter, it further includes:

[0018] Obtain the predicted elemental composition of the syngas at the outlet corresponding to the elemental composition of the syngas at the outlet output by the mechanism model according to a preset time lag;

[0019] Based on the elemental composition of the syngas at the outlet and the predicted elemental composition of the syngas at the outlet, correct the mechanism model;

[0020] Wherein, the preset time lag is determined based on the time lag relationship between the outlet and the inlet of the gasifier.

[0021] In a possible implementation manner, the soft sensor method for a gasifier based on a mechanism model further includes:

[0022] Obtaining an estimated value of the elemental composition of the coal entering the furnace and an actual value of the elemental composition of the coal entering the furnace; wherein, the estimated value of the elemental composition is obtained from the mechanism model;

[0023] Based on the actual value and the estimated value of the elemental composition, correcting the mechanism model.

[0024] In a possible implementation manner, the soft sensor method for a gasifier based on a mechanism model further includes:

[0025] Obtaining each third target parameter and a confidence interval preset for each third target parameter, where the third target parameter is measured by a monitoring module arranged on the gasifier;

[0026] Based on the confidence interval preset for each third target parameter, determining the final value of each third target parameter;

[0027] Inputting the final value of each third target parameter into the mechanism model for the mechanism model to determine the working state of the gasifier.

[0028] In a possible implementation manner, the determining the final value of each third target parameter based on the confidence interval preset for each third target parameter includes:

[0029] Obtaining the value of the same third target parameter measured by the monitoring module arranged at different measuring points;

[0030] Based on the confidence interval preset for the corresponding third target parameter, performing weighted calculation on the value of the third target parameter to obtain the final value of the third target parameter.

[0031] In a possible implementation manner, before inputting the wall heat loss coefficient into the mechanism model, it further includes:

[0032] Based on a preset threshold range, performing filtering processing on the wall heat loss coefficient.

[0033] In a second aspect, the present invention provides a soft sensor system for a gasifier based on a mechanism model, including:

[0034] A parameter acquisition unit for obtaining first target parameters, where the first target parameters include: the specific enthalpy of the cooling water before entering the water-cooled wall of the gasifier, the specific enthalpy of the water or water-vapor mixture after cooling, and the total reaction heat obtained from the mechanism model of the gasifier;

[0035] A parameter processing unit, configured to input the first target parameter into a wall heat transfer model to obtain a wall heat loss coefficient of the gasifier;

[0036] A state estimation unit, configured to input the wall heat loss coefficient into a mechanism model to enable the mechanism model to determine the working state of the gasifier;

[0037] Wherein, the wall heat transfer model is established based on the energy conservation relationship of the water wall.

[0038] In a third aspect, the present invention provides an electronic device, which includes:

[0039] A processor;

[0040] A memory for storing executable instructions of the processor;

[0041] The processor is configured to execute the soft measurement method for the gasifier based on the mechanism model provided in the first aspect of the present invention.

[0042] According to the soft measurement method for the gasifier based on the mechanism model provided by the present invention, after obtaining the first target parameter including the specific enthalpy of the cooling water before entering the water wall of the gasifier, the specific enthalpy of the cooled water or water vapor mixture, and the total reaction heat obtained from the mechanism model of the gasifier, first input the first target parameter into the wall heat transfer model established based on the energy conservation relationship of the water wall to obtain the wall heat loss coefficient of the gasifier, and then input the obtained wall heat loss coefficient into the mechanism model to enable the mechanism model to determine the working state of the gasifier. Thus, based on the energy conservation relationship of the water wall, the dynamic calculation of the wall heat loss coefficient of the gasifier under complex field conditions is realized, overcoming the limitation of the fixed wall heat loss coefficient in the existing method, and further improving the accuracy of the wall heat loss coefficient, and thus improving the accuracy of the working state of the gasifier determined by the mechanism model. Description of the Drawings

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only the embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained according to the provided drawings without creative efforts.

[0044] Figure 1 The unreacted shrinking core model adopted in the embodiment of the present invention is shown;

[0045] Figure 2 The schematic diagram of the axial chamber segmentation of the entrained flow gasifier is shown;

[0046] Figure 3The figure shows a schematic diagram of the temperature and flow rate of the gas phase and solid phase at various locations when the material flows from chamber n-1 into chamber n;

[0047] Figure 4 The figure shows a flowchart of a soft measurement method for a gasifier based on a mechanism model provided by an embodiment of the present invention;

[0048] Figure 5 The figure shows a comprehensive mechanism model obtained by integrating the traditional mechanism model of the gasifier with a wall heat transfer model and a coal element conservation model provided by an embodiment of the present invention;

[0049] Figure 6 The figure shows a structural diagram of a soft measurement system for a gasifier based on a mechanism model provided by an embodiment of the present invention;

[0050] Figure 7 The figure shows a structural diagram of another soft measurement system for a gasifier based on a mechanism model provided by an embodiment of the present invention;

[0051] Figure 8 The figure shows a schematic structural diagram of an electronic device provided by an embodiment of the present invention. Detailed implementation manners

[0052] Unless otherwise defined, the technical terms or scientific terms used in the embodiments of this specification should have the ordinary meanings understood by those of ordinary skill in the art to which this specification belongs. The "first", "second" and similar terms used in the embodiments of this specification do not denote any order, quantity or importance, but are only used to avoid confusion of components.

[0053] Unless otherwise required by the context, throughout this specification, "a plurality" means "at least two", and "including" is interpreted as an open, inclusive meaning, that is, "including, but not limited to". In the description of the specification, the terms "an embodiment", "some embodiments", "exemplary embodiments", "examples", "specific examples" or "some examples", etc. are intended to indicate that specific features, structures, materials or characteristics related to the embodiment or example are included in at least one embodiment or example of this specification. The schematic representations of the above terms do not necessarily refer to the same embodiment or example.

[0054] Next, the technical solutions in the embodiments of this specification will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of this specification. Obviously, the described embodiments are only a part of the embodiments of this specification, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in this specification without creative efforts belong to the scope protected by this specification.

[0055] It can be understood that, due to the complex and variable on-site environment in which the gasifier is applied, the soft measurement instrument for the gasifier using a mechanism model needs to overcome the following problems:

[0056] 1. Considering the cost and technical implementation difficulty, most of the current gasifier devices are not equipped with an on-line elemental analyzer for the coal fed into the furnace. The elemental analysis of coal usually needs to be obtained through laboratory tests. The on-site coal blending ratio relationship in the furnace is greatly affected by the source of coal supply;

[0057] 2. The heat exchange relationships of different gasifier devices vary greatly. The heat exchange situation of the same gasifier is also affected by various factors. At the same time, in the mechanism calculation, the heat loss coefficient of the gasifier has a great influence on the reaction rate and temperature distribution. The actual application of the mechanism model needs to solve the calibration and on-line estimation problems of the heat loss coefficient, and the existing technology usually estimates this parameter through experimental data or empirical models;

[0058] 3. The accuracy of the mechanism model results depends on many parameters. When the measured value of a certain parameter deviates due to measurement deviation or communication problems, the results estimated by the mechanism model are likely to be distorted, and the distorted results are difficult to effectively guide production in actual applications.

[0059] The present invention aims to solve the above problems and improve the reliability of the soft measurement instrument based on the mechanism model by improving the accuracy of parameters such as the wall heat transfer coefficient, the elemental composition of the coal fed into the furnace, and the temperature after quench that are input into the mechanism model.

[0060] Furthermore, the gasifier soft measurement method based on the mechanism model provided by the present invention is executed on an electronic device, which can be a network-side server or an intelligent terminal such as a smart phone or a laptop computer.

[0061] Even further, in order to make the gasifier soft measurement method based on the mechanism model provided by the present invention easier to understand, the commonly used mechanism models of the gasifier will be introduced first below:

[0062] Specifically, the mechanism models of the gasifier include: a sectional reaction model, an unreacted shrinking core model, and a chamber model.

[0063] Among them, it can be understood that in the gasifier, oxygen, steam, pulverized coal, and carbon dioxide are sprayed into the furnace from the burner of the gasifier and a series of reactions start. Due to the high concentration of oxygen mixed at the burner and the combustion of volatile substances rapidly pyrolyzed in a high-temperature environment, the gas phase temperature near the burner is extremely high. And the feed moving along the reactor undergoes pyrolysis, combustion, and gasification in sequence. Therefore, the gasification process can be divided into three regions: A. Pyrolysis and volatile combustion region; B. Combustion and gasification region; C. Gasification region.

[0064] Based on this, a zoned reaction model can be established based on the main chemical reaction processes in each region:

[0065] A. Pyrolysis and volatile combustion zone

[0066]

[0067] Among them, α i , β i , γ i , δ i and ∈ i are respectively the molar ratios of carbon, hydrogen, oxygen, nitrogen, and sulfur in raw coal excluding ash in a statistical sense. α, β, γ, δ, and ∈ are respectively the molar ratios of carbon, hydrogen, oxygen, nitrogen, and sulfur in coal after pyrolysis excluding ash in a statistical sense.

[0068] B. Combustion and gasification zone

[0069] Coal-oxygen reaction:

[0070]

[0071] Coal-steam reaction:

[0072]

[0073] Coal-carbon dioxide reaction:

[0074]

[0075] Hydrogen combustion:

[0076]

[0077] Carbon monoxide combustion:

[0078]

[0079] C. Gasification zone

[0080] The burned gas flows into the gasification zone, where heterogeneous reactions occur together with the water-gas shift reaction. Therefore, in the gasification zone, in addition to the coal-steam reaction and coal-carbon dioxide reaction corresponding to formulas (3) and (4) respectively, three other reactions will also occur, namely:

[0081]

[0082] CO + H2O → CO2 + H2 (8)

[0083] CH4 + H2O → CO + 3H2 (9)

[0084] For the unreacted shrinking core model, inside the gasifier, due to the relatively high operating temperature, the gas-solid heterogeneous reaction mainly considers the reaction between the gas and the solid on the surface. Since the proportion of solids in the gasifier is small, the probability of particle collision is low. Therefore, it can be assumed that the ash layer will remain on the surface of the fuel particles during the reaction process. Then, the heterogeneous gas-solid reaction rate is estimated through the unreacted shrinking core model. In addition to chemical reactions, ash layer diffusion and gas film diffusion effects should also be considered. Therefore, the total reaction rate k rate is as follows:

[0085]

[0086] where k dg is the gas film diffusion constant, k dash is the ash diffusion constant, k s is the surface reaction constant, r is the radius of the unreacted core, as Figure 1 shown, R is the radius of the coal ash particle including the ash layer, and δP i is the effective partial pressure of the gas considering the reverse reaction effect.

[0087] For the compartment model, during the calculation of the mechanism model, the gasifier can be axially divided into several compartments in the form shown in Figure 2 and Figure 3 . Then, the heterogeneous reaction and flow process in each compartment are considered, and the axial flow process is considered in units of compartments. At the same time, the height difference of each compartment is dynamically divided automatically according to the preset criteria according to the severity of the reaction and heat transfer, that is, when the flow or heat transfer process in a certain area is relatively complex, it will be automatically subdivided to obtain a good simulation effect.

[0088] Specifically, in each compartment, the mass change of the inlet and outlet materials is calculated according to the mass conservation equation:

[0089]

[0090] where W is the mass flow rate (kg / s), A t is the cross-sectional area of the reactor (m 2 ), z is the height (m 2 ), v ik is the stoichiometric parameter of the i-th component gas in the k-th gas reaction, and r k is the rate factor of the k-th reaction.

[0091] The energy conservation relationship of each compartment:

[0092]

[0093] where c pwhere \(C_p\) is the specific heat capacity (J / kg / K), \(T\) is the temperature (K), \(a\) is the contact area between the reactor solids and gas per unit volume (1 / m), \(r\) j is the rate factor for the \(j\)th solid reaction, \(H\) is the specific enthalpy (J / kg), \(H\) loss,g→w is the total heat loss from the gas to the wall (J / m).

[0094] In summary, by using the mechanism model of the gasifier, information such as the gas phase temperature, solid phase temperature, syngas composition, and flow velocity of each chamber can be dynamically solved based on the input furnace parameters. At the same time, the elemental composition of the syngas at the outlet of the gasifier can also be estimated.

[0095] Based on the above content, referring to Figure 4 , Figure 4 is a flowchart of a soft sensor method for a gasifier based on a mechanism model provided by an embodiment of the present invention. As Figure 4 shown, the process of this method may include:

[0096] S100. Obtain the first target parameter.

[0097] Among them, the first target parameter includes: the specific enthalpy of the cooling water before entering the water-cooled wall of the gasifier, the specific enthalpy of the cooled water or water-vapor mixture, and the total reaction heat obtained from the mechanism model of the gasifier.

[0098] Specifically, the specific enthalpy of the cooling water before entering the water-cooled wall of the gasifier can be determined according to the inlet cooling water temperature and pressure of the water-cooled wall; the specific enthalpy of the cooled water or water-vapor mixture can be determined according to parameters such as the density at the outlet of the water-cooled wall and the drum pressure.

[0099] S110. Input the first target parameter into the wall heat transfer model to obtain the wall heat loss coefficient of the gasifier.

[0100] Among them, the wall heat transfer model is established based on the energy conservation relationship of the water-cooled wall.

[0101] Specifically, as can be seen from formula (12), by multiplying the specific enthalpy difference between the cooling water before entering the water-cooled wall of the gasifier and the cooled water or water-vapor mixture by the cooling water flow rate, the power of the heat loss of the cooling water in the gasifier can be obtained. By dividing this power by the total reaction heat obtained from the mechanism model of the gasifier, the wall heat loss coefficient of the gasifier can be obtained.

[0102] S120. Input the wall heat loss coefficient into the mechanism model to enable the mechanism model to determine the working state of the gasifier.

[0103] It should be noted that under the complex and changeable operating conditions of the on-site gasifier, the heat exchange process between the syngas in the gasifier and the water-cooled wall is complex and affected by various factors such as the flow characteristics of coal ash, the gas flow process, the boundary layer thickness, and the water-cooling flow rate. The heat exchange process will change slowly over time.

[0104] Based on this, in order to adapt to this complex heat exchange condition, in this embodiment, based on the energy conservation relationship of the water-cooled wall, the wall heat loss coefficient of the gasifier is dynamically calculated, thereby realizing the automatic calibration of the wall heat loss coefficient, and further improving the accuracy of the mechanism model, that is, improving the reliability of determining the working state of the gasifier.

[0105] Furthermore, because the heat exchange process changes slowly over time, the wall heat loss coefficient is also a parameter that changes slowly. Therefore, in order to avoid deviation of the wall heat loss coefficient determined based on the first target parameter due to short-term measurement errors, in an optional embodiment, before inputting the wall heat loss coefficient into the mechanism model, it further includes:

[0106] Filter the wall heat loss coefficient based on a preset threshold range.

[0107] Specifically, by filtering the wall heat loss coefficient based on a preset threshold range, smoothing of the wall heat loss coefficient can be achieved, thereby avoiding heat exchange calculation deviation caused by short-term measurement errors.

[0108] It can be understood that, as mentioned above, considering cost and technical implementation difficulties, there is usually a lack of on-line analysis of the coal quality of the coal entering the furnace on site.

[0109] Based on this, in an optional embodiment, the soft measurement method of the gasifier based on the mechanism model further includes:

[0110] Obtain a second target parameter.

[0111] Wherein, the second target parameter includes: the process parameters of the material entering the furnace, the quality parameters of the coal entering the furnace, and the elemental composition of the syngas at the outlet of the gasifier.

[0112] Specifically, the process parameters of the material entering the furnace include parameters such as the mass flow rate, temperature, and pressure of the material; the quality parameters of the coal entering the furnace include the ash content and moisture content of the coal quality.

[0113] More specifically, the process parameters of the material entering the furnace, the quality parameters of the coal entering the furnace, and the elemental composition of the syngas at the outlet of the gasifier can all be detected by corresponding monitoring devices. For example, the material temperature can be detected by a temperature sensor.

[0114] Based on the second target parameter, determine the elemental composition of the coal entering the furnace.

[0115] Input the elemental composition of the coal charged into the furnace into the mechanism model to enable the mechanism model to determine the operating state of the gasifier.

[0116] Specifically, after obtaining the second target parameters, namely the parameters such as the mass flow rate, temperature, and pressure of the materials entering the gasifier, as well as the ash content and moisture content of the coal quality, and the elemental composition of the outlet syngas, the elemental composition of the coal charged into the furnace can be calculated by back-calculation through elemental conservation.

[0117] More specifically, after back-calculating the elemental composition of the coal charged into the furnace and inputting it into the mechanism model, the accuracy of the elemental composition of the coal charged into the furnace input into the mechanism model is improved, thereby further improving the reliability of the operating state of the gasifier obtained through the mechanism model.

[0118] Furthermore, in an optional embodiment, based on the second target parameters, determining the elemental composition of the coal charged into the furnace includes:

[0119] Input the second target parameters into a preset coal elemental conservation model to obtain the elemental composition of the coal charged into the furnace output by the coal elemental conservation model;

[0120] Among them, the coal elemental conservation model is established based on the conservation relationship between the elements contained in the materials charged into the furnace and the corresponding elements contained in the outlet syngas.

[0121] Specifically, establishing the coal elemental conservation model based on the conservation relationship between the elements contained in the materials charged into the furnace and the corresponding elements contained in the outlet syngas includes:

[0122] For the gasifier, the carbon in the coal charged into the furnace is equal to the carbon in the outlet syngas:

[0123]

[0124] Among them, is the number of moles of carbon in the coal charged into the furnace, n CO , and are the number of moles of CO, CO2, and CH4 in the outlet syngas respectively.

[0125] The hydrogen in the coal charged into the furnace and the hydrogen in the steam are equal to the hydrogen in the outlet gas:

[0126]

[0127] Among them, and are the number of moles of hydrogen in the coal charged into the furnace and the water in the steam at the inlet respectively, and are the number of moles of hydrogen in the outlet syngas and the water in the steam at the outlet respectively.

[0128] The oxygen in the coal charged into the furnace, oxygen, and steam is equal to the oxygen in the outlet gas:

[0129]

[0130] wherein, and are the number of moles of the coal charged into the furnace and oxygen respectively.

[0131] Conservation of nitrogen in nitrogen and coal:

[0132]

[0133] wherein, and are the number of moles of nitrogen in the coal charged into the furnace and nitrogen at the inlet respectively, is the number of moles of nitrogen in nitrogen at the outlet.

[0134] The number of moles of sulfur in the coal is equal to that of H2S:

[0135]

[0136] Therefore, based on the above coal element conservation model, the element composition of the coal charged into the furnace can be inversely deduced using the least squares method.

[0137] In a possible embodiment, after obtaining the second target parameter, it further includes:

[0138] Obtaining the predicted elemental composition of the outlet syngas corresponding to the elemental composition of the outlet syngas output by the mechanism model according to a preset time lag;

[0139] Calibrating the mechanism model based on the elemental composition of the outlet syngas and the predicted elemental composition of the outlet syngas;

[0140] wherein, the preset time lag is determined based on the time lag relationship between the outlet and inlet of the gasifier.

[0141] It can be understood that after the coal charged into the furnace enters the gasifier, it needs to go through a series of processes such as pyrolysis, combustion, and gasification before syngas can be obtained from the outlet. Therefore, it takes a certain amount of time to obtain the outlet syngas corresponding to the coal charged into the furnace.

[0142] Based on this, in this embodiment, by determining the preset time lag based on the time lag relationship between the outlet and inlet of the gasifier, and then according to this preset time lag, the predicted elemental composition of the outlet syngas output by the obtained mechanism model can be aligned with the elemental composition of the outlet syngas obtained from the outlet of the gasifier in time. Furthermore, by comparing the elemental composition of the outlet syngas and the predicted elemental composition of the outlet syngas, the calibration of the mechanism model can be realized.

[0143] It can be understood that during the actual production process, the coal fed into the furnace is usually regularly sent for inspection and testing to determine the actual elemental composition of the coal fed into the furnace. And the elemental composition of the coal fed into the furnace is also an intermediate parameter of the mechanism model that can be derived.

[0144] Based on this, in a possible embodiment, the soft sensor method for the gasifier based on the mechanism model further includes:

[0145] Obtain the estimated value of the elemental composition of the coal fed into the furnace and the actual value of the elemental composition of the coal fed into the furnace;

[0146] Among them, the estimated value of the elemental composition is obtained from the mechanism model;

[0147] Based on the actual value and the estimated value of the elemental composition, correct the mechanism model.

[0148] That is, in this embodiment, by comparing the elemental composition of the coal fed into the furnace obtained from the mechanism model, that is, the estimated value of the elemental composition, with the elemental composition of the coal fed into the furnace obtained from the results of regular inspection and testing, that is, the actual value of the elemental composition, the mechanism model of the gasifier can be corrected, thereby further improving the accuracy of the mechanism model.

[0149] In summary, as Figure 5 shown, the soft sensor method for the gasifier based on the mechanism model provided by the embodiment of the present invention, after fusing the traditional mechanism model of the gasifier with the wall heat transfer model and the coal element conservation model, obtains a comprehensive mechanism model, thereby making full use of the key conservation relationships in the production process of the gasifier. Starting from the first principles, through measurable information such as the steam drum pressure, temperature, and feed water flow rate, relatively real outlet effective components, yields, carbon conversion ratios, and temperature distributions of the synthesis gas of the gasifier are obtained, thereby effectively guiding the real-time optimization direction and real-time control.

[0150] It can be understood that the parameters input into the mechanism model are obtained through measurement. When there are errors in the measurement of a certain or certain parameters, it will affect the output result of the mechanism model, that is, reduce the accuracy of the mechanism model.

[0151] At the same time, considering that at the implementation site, multiple measuring points are usually set for some parameters, that is, for the same parameter, monitoring modules are respectively set at different positions for measurement, or monitoring modules of different manufacturers or types are set for measurement.

[0152] Based on this, in a possible embodiment, the soft sensor method for the gasifier based on the mechanism model further includes:

[0153] Obtain each third target parameter and the confidence interval preset for each third target parameter.

[0154] Among them, the third target parameter is measured by the monitoring module arranged on the gasifier;

[0155] Determine the final values of the third target parameters based on the confidence intervals preset for each third target parameter;

[0156] Input the final values of the third target parameters into the mechanism model to enable the mechanism model to determine the working state of the gasifier.

[0157] Specifically, the setting of the confidence interval can be flexibly set by the user based on their own needs. For example: preset based on the variance of the parameters obtained through different measurement points, that is, the degree of volatility; preset based on the accuracy differences of the monitoring modules arranged at different measurement points, etc., which are not specifically limited here.

[0158] In this embodiment, by presetting different confidence intervals for the third target parameters, that is, redundant measurement values, and then determining the final values of each third target parameter based on the preset confidence intervals, when one of the measurement points deviates too much, relatively accurate measurement values can also be obtained according to other measurement points, thus establishing data fusion of the measurement values. Furthermore, when the final values of each third target parameter are input into the mechanism model to enable the mechanism model to determine the working state of the gasifier, by combining as much measurable parameter information as possible and outputting multiple real-time parameters that can be cross-validated, even if there is a measurement error in a single parameter pre-input into the mechanism model, the output result will not show significant fluctuations and can still represent the relatively real working state of the gasifier.

[0159] Further, in a possible embodiment, determining the final values of the third target parameters based on the confidence intervals preset for each third target parameter includes:

[0160] Obtain the values of the same third target parameter measured by the monitoring modules arranged at different measurement points;

[0161] Based on the confidence interval preset for the corresponding third target parameter, perform weighted calculation on the value of the third target parameter to obtain the final value of the third target parameter.

[0162] Specifically, taking the measurement of the temperature after quench as an example, assume that there are 3 temperature measurement points on site and different real-time monitoring instruments are used for measurement. Through weighted calculation based on the confidence interval, the fused temperature data is obtained. The fused temperature data makes full use of the information of the 3 measurement points, and when one of the temperature measurement points deviates too much, relatively accurate temperature measurement values can also be obtained according to other temperature measurement points.

[0163] In this embodiment, by fusing various on-site measurement data and performing weighted calculation based on the confidence intervals preset for redundant measurement values, the robustness of the mechanism model is improved and the influence of single-parameter errors on the output result is reduced.

[0164] In summary, the soft measurement method for gasifiers based on a mechanism model provided in the above embodiments of the present invention, through basic conservation relations, on the premise of accurately depicting the internal energy, mass changes, and material exchange relations in the gasifier, makes full use of the data information collected by existing instruments to establish an overall mechanism model with multi-data fusion. Through the element conservation relation, by analyzing the components of the syngas at the outlet and combining the time-delay information at the inlet and outlet of the gasifier, the elemental composition of the coal entering the furnace is estimated online in real time to ensure the correct input of the mechanism model. In addition, to solve the problem of automatic calibration of the heat loss coefficient of the gasifier, a wall heat transfer model for dynamically calculating the heat loss coefficient is established through the energy conservation relation of the water-cooled wall. Through the combination of the above methods, integrating multiple data sources improves the robustness of the mechanism model and reduces the problem that the output deviates severely from the real physical process due to fluctuations in a single parameter.

[0165] In summary, by applying the soft measurement method for gasifiers based on a mechanism model provided in the above embodiments of the present invention, a real-time soft measurement instrument is established for the gasifier, effectively solving the problems of missing online analysis of elements, lack of online estimation of heat loss calculation, and distortion of results due to interference when determining the working state of the gasifier through the mechanism model of the gasifier. That is, it solves various difficulties that may occur in the practical engineering application of the mechanism model of the gasifier, improves the applicable range and accuracy of the soft measurement instrument based on the mechanism model. The real-time estimation of the internal state of the gasifier by the soft measurement method for gasifiers based on a mechanism model provided in the above embodiments of the present invention can provide effective production optimization guidance to ensure the stable operation of the gasifier and the effective gas production.

[0166] Next, a soft measurement system for gasifiers based on a mechanism model provided in an embodiment of the present invention will be introduced. The soft measurement system for gasifiers based on a mechanism model described below can be considered as a module architecture for implementing the soft measurement method for gasifiers based on a mechanism model provided in an embodiment of the present invention; the content described below can be referred to each other with the above content.

[0167] See Figure 6 , Figure 6 which is a structural block diagram of a soft measurement system for gasifiers based on a mechanism model provided in an embodiment of the present invention. The system may include:

[0168] A parameter acquisition unit 10, configured to acquire first target parameters, where the first target parameters include: the specific enthalpy of the cooling water before entering the water-cooled wall of the gasifier, the specific enthalpy of the cooled water or water-vapor mixture, and the total reaction heat obtained from the mechanism model of the gasifier;

[0169] A parameter processing unit 20, configured to input the first target parameters into the wall heat transfer model to obtain the wall heat loss coefficient of the gasifier;

[0170] A state estimation unit 30, configured to input a wall heat loss coefficient into a mechanism model, so that the mechanism model determines the working state of the gasifier;

[0171] Among them, the wall heat transfer model is established based on the energy conservation relationship of the water-cooled wall.

[0172] Optionally, the parameter acquisition unit 10 is further configured to acquire second target parameters, where the second target parameters include: process parameters of the feedstock entering the furnace, quality parameters of the coal entering the furnace, and elemental composition of the syngas at the outlet of the gasifier;

[0173] The parameter processing unit 20 is further configured to determine the elemental composition of the coal entering the furnace based on the second target parameters;

[0174] The state estimation unit 30 is further configured to input the elemental composition of the coal entering the furnace into the mechanism model, so that the mechanism model determines the working state of the gasifier.

[0175] Optionally, the parameter processing unit 20 is specifically configured to input the second target parameters into a preset coal element conservation model, and obtain the elemental composition of the coal entering the furnace output by the coal element conservation model;

[0176] Among them, the coal element conservation model is established based on the conservation relationship between the elements contained in the feedstock entering the furnace and the corresponding elements contained in the syngas at the outlet.

[0177] Optionally, refer to Figure 7 , Figure 7 shown in the structure block diagram of another soft measurement system for a gasifier based on a mechanism model provided by an embodiment of the present invention. On the basis of the embodiment shown in Figure 6 shown in the embodiment, the system further includes:

[0178] A model correction unit 40, configured to obtain predicted elemental composition of the syngas corresponding to the elemental composition of the syngas at the outlet output by the mechanism model according to a preset time delay;

[0179] Based on the elemental composition of the syngas at the outlet and the predicted elemental composition of the syngas at the outlet, correct the mechanism model;

[0180] Among them, the preset time delay is determined based on the time delay relationship between the outlet and the inlet of the gasifier.

[0181] Optionally, the model correction unit 40 is further configured to obtain an estimated value of the elemental composition of the coal entering the furnace and an actual value of the elemental composition of the coal entering the furnace; among them, the estimated value of the elemental composition is obtained from the mechanism model;

[0182] Based on the actual value of the elemental composition and the estimated value of the elemental composition, correct the mechanism model.

[0183] Optionally, the parameter acquisition unit 10 is further configured to obtain each third target parameter and the confidence interval preset for each third target parameter, where the third target parameter is measured by a monitoring module arranged on the gasifier;

[0184] The parameter processing unit 20 is further configured to determine the final value of each third target parameter based on the confidence interval preset for each third target parameter;

[0185] The state estimation unit 30 is further configured to input the final value of each third target parameter into the mechanism model, so that the mechanism model determines the working state of the gasifier.

[0186] Optionally, the parameter processing unit 20 is specifically configured to obtain the values of the same third target parameter measured by the monitoring modules arranged at different measurement points;

[0187] Based on the confidence interval preset for the corresponding third target parameter, perform weighted calculation on the value of the third target parameter to obtain the final value of the third target parameter.

[0188] Optionally, the parameter processing unit 20 is further configured to perform filtering processing on the wall heat loss coefficient based on a preset threshold range.

[0189] Next, with reference to Figure 8 The electronic device provided in the embodiment of the present application will be described. The electronic device provided in this embodiment may include: at least one processor 100, at least one communication interface 200, at least one memory 300, and at least one communication bus 400;

[0190] In the embodiment of the present invention, the number of the processor 100, the communication interface 200, the memory 300, and the communication bus 400 is at least one, and the processor 100, the communication interface 200, and the memory 300 complete mutual communication through the communication bus 400; obviously, Figure 8 The communication connection schematic diagram of the processor 100, the communication interface 200, the memory 300, and the communication bus 400 shown is only optional;

[0191] Optionally, the communication interface 200 may be an interface of a communication module, such as an interface of a GSM module; the processor 100 may be a central processing unit CPU, or a specific integrated circuit ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiment of the present invention.

[0192] The memory 300 may include a high-speed RAM memory, and may also include a non-volatile memory, such as at least one disk memory.

[0193] Among them, the processor 100 is specifically configured to execute the application programs in the memory to implement the steps of the above-mentioned soft measurement method for the gasifier based on the mechanism model.

[0194] The basic principles of the present application have been described above in conjunction with specific embodiments. However, it should be noted that the advantages, benefits, effects, etc. mentioned in the present application are only examples and not limitations. It cannot be considered that these advantages, benefits, effects, etc. are essential for each embodiment of the present application. In addition, the above-disclosed specific details are only for the purposes of illustration and easy understanding, rather than limitations. The above details do not limit the present application to necessarily adopt the above specific details for implementation.

[0195] The block diagrams of the devices, apparatuses, equipment, and systems involved in the present application are only illustrative examples and do not intend to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "including", "comprising", "having", etc. are open-ended terms, meaning "including but not limited to", and can be used interchangeably with each other. The words "or" and "and" used herein refer to the word "and / or", and can be used interchangeably with each other, unless the context clearly indicates otherwise. The word "such as" used herein refers to the phrase "such as but not limited to", and can be used interchangeably with each other.

[0196] It should also be noted that in the devices, equipment, and methods of the present application, each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent solutions of the present application.

[0197] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present application. Various modifications to these aspects will be very apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of the present application. Therefore, the present application is not intended to be limited to the aspects shown herein, but rather to the broadest scope consistent with the principles and novel features disclosed herein.

[0198] It should be understood that the qualifiers "first", "second", "third", "fourth", "fifth", and "sixth" used in the description of the embodiments of the present application are only used to more clearly elaborate the technical solutions and cannot be used to limit the protection scope of the present application.

[0199] The above description has been given for purposes of illustration and description. In addition, this description is not intended to limit the embodiments of the present application to the forms disclosed herein. Although multiple example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions, and sub-combinations thereof.

Claims

1. A gasifier soft-sensing method based on a mechanism model, characterized in that: include: Acquiring first target parameters, the first target parameters including: specific enthalpy of cooling water before entering the water-cooled wall of the gasifier, specific enthalpy of water or water vapor mixture after cooling, and total reaction heat obtained from a mechanism model of the gasifier; Inputting the first target parameter into a wall heat exchange model to obtain a wall heat loss coefficient of the gasifier; Inputting the wall heat loss coefficient into a mechanism model so as to enable the mechanism model to determine the working state of the gasifier; Wherein, the wall heat exchange model is established based on the energy conservation relationship of the water-cooled wall.

2. The method according to claim 1, characterized in that Also includes: Acquiring second target parameters, the second target parameters including: process parameters of the incoming materials, quality parameters of the incoming coal, and elemental components of the outlet synthesis gas of the gasifier; Determining the elemental composition of the incoming coal based on the second target parameter; The elemental composition of the coal fed into the furnace is input into the mechanism model so as to enable the mechanism model to determine the working state of the gasifier.

3. The method according to claim 2, characterized in that The step of determining the elemental composition of the incoming coal based on the second target parameter comprises: Inputting the second target parameter into a preset coal element conservation model to obtain the element composition of the incoming coal output by the coal element conservation model; The coal element conservation model is established based on the conservation relationship between the elements contained in the input materials and the corresponding elements contained in the outlet synthesis gas.

4. The method according to claim 2, characterized in that: After obtaining the second target parameter, the method further includes: Obtaining a predicted elemental composition of the outlet syngas corresponding to the elemental composition of the outlet syngas output by the mechanism model according to a preset time delay; calibrating the mechanistic model based on the elemental composition of the outlet syngas and the predicted elemental composition of the outlet syngas; Wherein, the preset time delay is determined based on the time delay relationship between the outlet and the inlet of the gasifier.

5. The method according to claim 2, characterized in that: Also includes: Obtaining an estimated value of the elemental composition of the coal fed into the furnace and an actual value of the elemental composition of the coal fed into the furnace; wherein the estimated value of the elemental composition is obtained by the mechanism model; The mechanism model is calibrated based on the actual value of the element composition and the estimated value of the element composition.

6. The method according to claim 1 or 2, characterized in that: Also includes: Acquire each third target parameter and a confidence interval preset for each third target parameter, wherein the third target parameter is measured by a monitoring module arranged on the gasifier; Determining a final value of each of the third target parameters based on a confidence interval preset for each of the third target parameters; The final value of each of the third target parameters is input into the mechanism model so as to enable the mechanism model to determine the working state of the gasifier.

7. The method according to claim 6, characterized in that Determining the final value of each of the third target parameters based on the confidence interval preset for each of the third target parameters comprises: Acquire the value of the same third target parameter measured by the monitoring modules arranged at different measuring points; Based on the confidence interval preset for the corresponding third target parameter, a weighted calculation is performed on the value of the third target parameter to obtain a final value of the third target parameter.

8. The method according to claim 1, characterized in that Before inputting the wall heat loss coefficient into the mechanism model, the method further includes: Based on a preset threshold range, filtering is performed on the wall heat loss coefficient.

9. A gasifier soft measurement system based on a mechanism model, characterized in that: include: A parameter acquisition unit, used to obtain a first target parameter, wherein the first target parameter includes: a specific enthalpy of cooling water before entering the water-cooled wall of the gasifier, a specific enthalpy of water or water vapor mixture after cooling, and a total reaction heat obtained from a mechanism model of the gasifier; A parameter processing unit, used for inputting the first target parameter into a wall heat exchange model to obtain a wall heat loss coefficient of the gasifier; A state estimation unit, used for inputting the wall heat loss coefficient into a mechanism model, so as to enable the mechanism model to determine the working state of the gasifier; Wherein, the wall heat exchange model is established based on the energy conservation relationship of the water-cooled wall.

10. An electronic device, characterized in that: The electronic device comprises: processor; a memory for storing instructions executable by the processor; The processor is used to execute the method according to any one of claims 1 to 8.

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