A data simulation-based water vapor leakage damage early warning system and method

Abstract

The application discloses a water vapor leakage damage early warning system and method based on data simulation, relates to the technical field of water vapor leakage early warning, and comprises the following steps: simulating water vapor leakage of an industrial boiler to obtain simulation data; obtaining historical design data of a historical industrial boiler, combining the design data of the industrial boiler with working data, analyzing the similarity of boiler simulation conditions between the industrial boiler and the historical industrial boiler, and obtaining a comparison historical industrial boiler; obtaining historical simulation data of the comparison historical industrial boiler, obtaining simulation data of the industrial boiler, optimizing and adjusting the simulation data of the industrial boiler based on the historical simulation data, and obtaining target simulation data; obtaining the target simulation data of the industrial boiler, obtaining equipment operation data of the industrial boiler in a current period, combining the target simulation data, formulating early warning information of the industrial boiler, and early warning the damage of water vapor leakage of the industrial boiler.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of water vapor leakage early warning, in particular to a water vapor leakage injury early warning system and method based on data simulation. BACKGROUND

[0002] At present, steam and hot water are needed in most industrial production processes, such as chemical industry, food processing, pharmaceutical industry, etc. These industries must use the heat and kinetic energy provided by the boiler, so the boiler is widely used in industrial production. However, in the actual use process, the boiler may leak water vapor due to equipment aging and improper operation, and other reasons. Water vapor leakage not only causes damage to equipment, but also may cause harm to personnel.

[0003] The existing method for early warning of water vapor leakage injury relies too much on a simplified physical model and fails to fully consider the complex physical process of the industrial boiler during water vapor leakage. Meanwhile, when analyzing and verifying the simulated water vapor early warning data of the industrial boiler, relevant historical data are not fully utilized, which makes it difficult to verify and optimize the simulation data even if the water vapor early warning data obtained by simulating the industrial boiler are obtained, thereby greatly reducing the accuracy of the simulation data and even causing personnel to be injured due to false early warning. SUMMARY

[0004] The present application aims to provide a water vapor leakage injury early warning system and method based on data simulation to solve the problems in the prior art.

[0005] To achieve the above-mentioned purpose, the present application provides the following technical scheme: a water vapor leakage injury early warning method based on data simulation, the method comprising:

[0006] Step S100: constructing a water vapor early warning cloud platform, obtaining historical water vapor leakage data and historical design data of the historical industrial boiler, constructing a water vapor leakage simulation model, obtaining preset working data and design data of the industrial boiler, simulating water vapor leakage of the industrial boiler, and obtaining simulation data;

[0007] Step S200: obtaining historical simulation data of the historical industrial boiler, obtaining historical design data of the historical industrial boiler, and combining the design data and working data of the industrial boiler to analyze the similarity degree of the boiler simulation conditions between the industrial boiler and the historical industrial boiler, and obtaining a comparison historical industrial boiler;

[0008] Step S300: obtaining the historical simulation data of the comparison historical industrial boiler, obtaining the simulation data of the industrial boiler, optimizing and adjusting the simulation data of the industrial boiler based on the historical simulation data, and obtaining target simulation data.

[0009] Step S400: obtaining target simulation data of the industrial boiler, obtaining equipment operation data of the industrial boiler in the current period, and combining the target simulation data to formulate early warning information of the industrial boiler, and performing damage early warning on water vapor leakage of the industrial boiler.

[0010] Further, step S100 comprises:

[0011] Step S101: obtaining historical water vapor leakage data of the historical industrial boiler, the historical water vapor leakage data comprising data corresponding to each accident damage parameter of the historical industrial boiler after water vapor leakage occurs and data corresponding to each operation parameter of the historical industrial boiler before water vapor leakage occurs;

[0012] Step S102: obtaining historical design data of the historical industrial boiler, the historical design data comprising data corresponding to each design parameter of the historical industrial boiler, constructing a water vapor leakage simulation model, and the specific construction process comprising: performing data normalization on the historical water vapor leakage data and the historical design data of the historical industrial boiler, and dividing the historical water vapor leakage data and the historical design data corresponding to each historical industrial boiler into a training set and a test set according to a preset proportion;

[0013] Step S103: obtaining preset input layer, hidden layer and output layer node numbers of the water vapor leakage simulation model, and obtaining an activation function f(x) of the water vapor leakage simulation model:

[0014] ,

[0015] wherein the node number of the input layer is generally the number of terms of the feature number of the input model, the node number of the output layer is generally the number of target simulation parameters to be predicted, and the node number and the layer number of the hidden layer can be determined through experiments, and the initial selection is usually 1-2 hidden layers;

[0016] The output of a neuron in the water vapor leakage simulation model is defined, wherein for the rth layer in the water vapor leakage simulation model, the calculation formula of the output a r is:

[0017] ,

[0018] wherein W r represents a weight matrix of the rth layer; b r represents a bias of the rth layer; a r-1 represents the output of the (r-1)th layer in the water vapor leakage simulation model;

[0019] The weight matrix in the above steps is usually randomly set at model initialization, and the bias is usually set to 0 or a small random value at initialization. The weight matrix can adjust the strength of the input signal, and the bias is an additional parameter in the model, which can make the model output a non-zero value without input signal. The introduction of bias makes the neural network have better fitting ability;

[0020] Step S104: Obtain the target simulation parameters preset by the water vapor leakage simulation model, and obtain the loss function L of the water vapor leakage simulation model: ,

[0021] Wherein, n represents the total number of training samples in the training set; y i represents the true value of the i-th training sample in the training set; y' i represents the predicted value of the i-th training sample in the training set;

[0022] Step S105: Calculate the gradient of the loss function, and perform layer-by-layer back propagation through the chain rule to update the weight matrix and the bias. The specific update formula is:

[0023] ,

[0024] ,

[0025] Wherein, η represents a preset learning rate; W old represents the weight matrix before updating; W new represents the weight matrix after updating; b old represents the bias before updating; b new represents the bias after updating;

[0026] Step S106: Use the training set to train the water vapor leakage simulation model, update the weight matrix and the bias of the water vapor leakage simulation model, and use the test set to verify the water vapor leakage simulation model, and obtain the verified water vapor leakage simulation model;

[0027] Step S107: Obtain the preset working data and design data of the industrial boiler. The design data includes data corresponding to each design parameter of the industrial boiler, and the working data includes data corresponding to each operating parameter of the industrial boiler.

[0028] Step S108: Input the working data and the design data into the water vapor leakage simulation model, simulate the water vapor leakage of the industrial boiler, obtain the data corresponding to each target simulation parameter of the industrial boiler, and collect the data corresponding to each target simulation parameter of the industrial boiler to obtain the simulation data of the industrial boiler.

[0029] Further, the step S200 comprises:

[0030] Step S201: obtaining historical simulation data of the historical industrial boiler, and obtaining historical working data of the historical industrial boiler input into the water vapor leakage simulation model, wherein the historical working data comprises data corresponding to each preset operating parameter of the historical industrial boiler;

[0031] Step S202: obtaining experimental verification data of the historical industrial boiler, and when the difference between the experimental verification data and the data corresponding to each target simulation parameter in the historical simulation data of the historical industrial boiler is within a preset error range, recording the historical simulation data of the historical industrial boiler as characteristic historical simulation data, retaining the historical industrial boiler with the characteristic historical simulation data, and obtaining a plurality of historical industrial boilers;

[0032] Step S203: obtaining design data of the industrial boiler, standardizing and vectorizing the design data of the industrial boiler and the historical design data in the historical industrial boiler, and obtaining a vector group;

[0033] Step S204: calculating a characteristic design similarity value P between the industrial boiler and the historical industrial boiler: ,

[0034] Wherein C represents the vector group of the design data of the industrial boiler; and D represents the vector group of the historical design data of the historical industrial boiler.

[0035] Step S205: obtaining average values of each operating parameter of the industrial boiler in the working data, and standardizing the working data of the industrial boiler and the historical working data in the historical industrial boiler, respectively;

[0036] Step S206: calculating an equipment operation similarity value H between the industrial boiler and the historical industrial boiler:

[0037] ,

[0038] Wherein E i represents the average value of the i-th operating parameter in the industrial boiler; F i represents the average value of the i-th operating parameter in the historical industrial boiler; and j represents the total number of operating parameters in the industrial boiler.

[0039] Step S207: obtaining the maximum value H max and the minimum value H min of the equipment operation similarity value between the industrial boiler and the historical industrial boiler, and calculating a characteristic equipment operation similarity value H´=(H-H min ) / (H max -H min ) between the industrial boiler and the historical industrial boiler.

[0040] Step S208: Calculate the boiler simulation condition similarity value G=(γ×P)+ (μ×H´) between the industrial boiler and the historical industrial boiler, wherein γ is a preset characteristic design coefficient, μ is a preset characteristic equipment operation coefficient, γ∈(0,1), μ∈(0,1), γ+μ=1;

[0041] Step S209: Obtain the boiler simulation condition similarity value between the industrial boiler and a plurality of historical industrial boilers, when the boiler simulation condition similarity value between the industrial boiler and a certain historical industrial boiler is greater than a preset boiler simulation condition similarity threshold value, it is determined that the boiler simulation condition similarity between the certain historical industrial boiler and the industrial boiler, and the certain historical industrial boiler is recorded as the control historical industrial boiler of the industrial boiler.

[0042] Further, step S300 includes:

[0043] Step S301: Obtain the historical simulation data of a plurality of control historical industrial boilers of the industrial boiler, and obtain the data corresponding to each target simulation parameter in the control historical industrial boilers from the historical simulation data;

[0044] Step S302: Obtain the simulation data of the industrial boiler, and calculate the characteristic deviation value of each target simulation parameter of the industrial boiler, wherein the characteristic deviation value K d of the dth target simulation parameter in the industrial boiler is calculated as follows:

[0045] ,

[0046] wherein q is the total number of the plurality of control historical industrial boilers; U d is the average value of the dth target simulation parameter in the industrial boiler; U d z is the average value of the dth target simulation parameter in the zth control historical industrial boiler of the plurality of control historical industrial boilers; U d max is the maximum value of the average value of the dth target simulation parameter in the plurality of control historical industrial boilers; U d min is the minimum value of the average value of the dth target simulation parameter in the plurality of control historical industrial boilers;

[0047] Step S303: Optimize and adjust the dth target simulation parameter in the industrial boiler, and the specific process is as follows: when the characteristic deviation value K d is greater than or equal to a preset characteristic deviation threshold value, optimize and adjust the dth target simulation parameter in the industrial boiler based on the historical simulation data of the control historical industrial boiler, and when the characteristic deviation value K dIf the feature deviation threshold is less than the feature deviation threshold, the dth target simulation parameter in the industrial boiler is not adjusted;

[0048] Step S304: optimizing and adjusting each target simulation parameter in the industrial boiler to obtain the target simulation data of the industrial boiler.

[0049] Further, step S400 comprises:

[0050] Step S401: monitoring each operation parameter of the industrial boiler in the current period to obtain the equipment operation data of the industrial boiler in the current period;

[0051] Step S402: based on the equipment operation data and in combination with the target simulation data of the industrial boiler, formulating the warning information of the industrial boiler to perform the injury warning of the water vapor leakage of the industrial boiler in the current period.

[0052] In order to better realize the above method, a water vapor leakage injury warning system based on data simulation is further provided, which comprises a simulation data module, a historical industrial boiler comparison module, a target simulation data module, and an injury warning module;

[0053] The simulation data module is used to obtain the preset working data and design data of the industrial boiler, simulate the water vapor leakage of the industrial boiler, and obtain simulation data.

[0054] The historical industrial boiler comparison module is used to analyze the similarity of the boiler simulation conditions between the industrial boiler and the historical industrial boiler to obtain the historical industrial boiler for comparison.

[0055] The target simulation data module is used to optimize and adjust the simulation data of the industrial boiler to obtain the target simulation data.

[0056] The injury warning module is used to obtain the equipment operation data of the industrial boiler, formulate the warning information of the industrial boiler, and perform the injury warning of the water vapor leakage of the industrial boiler.

[0057] Further, the simulation data module comprises a model construction unit and a data simulation unit.

[0058] The model construction unit is used to obtain the historical design data of the historical industrial boiler and construct a water vapor leakage simulation model.

[0059] The data simulation unit is used to simulate the water vapor leakage of the industrial boiler to obtain the simulation data of the industrial boiler.

[0060] Further, the historical industrial boiler comparison module comprises a boiler simulation condition similarity value unit and a historical industrial boiler comparison unit.

[0061] A boiler simulation condition similar value unit is configured to calculate a boiler simulation condition similar value between the industrial boiler and the historical industrial boiler.

[0062] A comparison historical industrial boiler unit is configured to determine a boiler simulation condition similarity between the industrial boiler and the historical industrial boiler according to the boiler simulation condition similar value, and obtain the comparison historical industrial boiler.

[0063] Further, the target simulation data module comprises a feature deviation value unit and a target simulation data unit.

[0064] The feature deviation value unit is configured to calculate a feature deviation value of each target simulation parameter of the industrial boiler.

[0065] The target simulation data unit is configured to optimize and adjust each target simulation parameter in the industrial boiler, and obtain target simulation data of the industrial boiler.

[0066] Further, the injury early warning module comprises an injury early warning unit.

[0067] The injury early warning unit is configured to monitor each operation parameter of the industrial boiler in a current period, obtain equipment operation data, combine the target simulation data of the industrial boiler, formulate early warning information of the industrial boiler, and perform injury early warning on water vapor leakage of the industrial boiler in the current period.

[0068] Compared with the prior art, the present application has the beneficial effects that: the present application realizes data simulation and intelligent early warning of water vapor leakage of the industrial boiler, first uses historical data of the historical industrial boiler to establish a water vapor leakage simulation model, performs data simulation of water vapor leakage of the industrial boiler, obtains simulation data, and considers that there may be a gap between the simulation data and actual water vapor leakage of the industrial boiler, uses simulation data of the historical industrial boiler verified by experiments to optimize and adjust the simulation data of the industrial boiler, thereby greatly increasing the accuracy of model data simulation, and further ensuring personnel safety and equipment safety. BRIEF DESCRIPTION OF DRAWINGS

[0069] Fig. 1 is a method flowchart of a water vapor leakage injury early warning system and method based on data simulation according to the present application;

[0070] Fig. 2 is a module schematic diagram of a water vapor leakage injury early warning system and method based on data simulation according to the present application. DETAILED DESCRIPTION

[0071] With reference to the accompanying drawings: the technical solutions in the embodiments of the present application will be described clearly and completely, obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0072] Embodiment: as Figs. 1-2 Indicated, the present application provides a technical scheme, a water vapor leakage damage early warning method based on data simulation, the method comprises:

[0073] Step S100: constructing a water vapor early warning cloud platform, obtaining historical water vapor leakage data and historical design data of the historical industrial boiler, constructing a water vapor leakage simulation model, obtaining preset working data and design data of the industrial boiler, simulating water vapor leakage of the industrial boiler, and obtaining simulation data;

[0074] Wherein, step S100 includes:

[0075] Step S101: obtaining the historical water vapor leakage data of the historical industrial boiler, the historical water vapor leakage data includes the data corresponding to each accident damage parameter of the historical industrial boiler after water vapor leakage, and the data corresponding to each operation parameter of the historical industrial boiler before water vapor leakage;

[0076] For example, each accident damage parameter includes the maximum distance of explosion after the historical industrial boiler leaks, the explosion area, etc.;

[0077] Step S102: obtaining the historical design data of the historical industrial boiler, the historical design data includes the data corresponding to each design parameter of the historical industrial boiler, constructing a water vapor leakage simulation model, the specific construction process is that the historical water vapor leakage data and the historical design data of the historical industrial boiler are normalized, and each historical water vapor leakage data and historical design data corresponding to each historical industrial boiler is divided into training set and test set according to the preset proportion;

[0078] For example, each design parameter includes the boiler material of the historical industrial boiler, the length of the boiler, etc.;

[0079] Step S103: obtaining the preset input layer, hidden layer and output layer node number of the water vapor leakage simulation model, obtaining the activation function f(x) of the water vapor leakage simulation model:

[0080] ,

[0081] The output of the neuron in the water vapor leakage simulation model is defined, wherein, for the rth layer in the water vapor leakage simulation model, the output ar The calculation formula is:

[0082] ,

[0083] Wherein, W r represents the weight matrix of the rth layer; b r represents the bias of the rth layer; a r-1 represents the output of the r-1th layer in the water vapor leakage simulation model;

[0084] Step S104: obtaining the target simulation parameter preset by the water vapor leakage simulation model, obtaining the loss function L of the water vapor leakage simulation model: ,

[0085] Wherein, n represents the total number of training samples in the training set; y i represents the true value of the ith training sample in the training set; y' i represents the predicted value of the ith training sample in the training set;

[0086] Step S105: calculating the gradient of the loss function, propagating back layer by layer through the chain rule, updating the weight matrix and the bias, and the specific update formula is:

[0087] ,

[0088] ,

[0089] Wherein, η represents the preset learning rate; W old represents the weight matrix before updating; W new represents the weight matrix after updating; b old represents the bias before updating; b new represents the bias after updating;

[0090] Step S106: using the training set to train the water vapor leakage simulation model, updating the weight matrix and the bias of the water vapor leakage simulation model, and using the test set to verify the water vapor leakage simulation model, obtaining the verified water vapor leakage simulation model;

[0091] Step S107: obtaining the preset working data and design data of the industrial boiler, the design data including the data corresponding to each design parameter of the industrial boiler, and the working data including the data corresponding to each operating parameter of the industrial boiler;

[0092] For example, the operating parameters include the environmental temperature of the industrial boiler during operation, the pressure in the boiler, etc.

[0093] Step S108: input the working data and the design data into the water vapor leakage simulation model, simulate the water vapor leakage of the industrial boiler, obtain data corresponding to each target simulation parameter of the industrial boiler, collect the data corresponding to each target simulation parameter of the industrial boiler, and obtain simulation data of the industrial boiler;

[0094] For example, each target simulation parameter includes a maximum threat distance of water vapor leakage of the industrial boiler, a minimum internal pressure in the boiler, etc.

[0095] Step S200: obtain historical simulation data of a historical industrial boiler, obtain historical design data of the historical industrial boiler, and analyze a similarity degree of boiler simulation conditions between the industrial boiler and the historical industrial boiler in combination with the design data and the working data of the industrial boiler, to obtain a comparison historical industrial boiler;

[0096] The step S200 includes:

[0097] Step S201: obtain historical simulation data of a historical industrial boiler, obtain historical working data of the historical industrial boiler input into a water vapor leakage simulation model, wherein the historical working data includes data corresponding to each preset operating parameter of the historical industrial boiler;

[0098] Step S202: obtain experimental verification data of the historical industrial boiler, when a difference between the experimental verification data and data corresponding to each target simulation parameter in the historical simulation data of the historical industrial boiler is within a preset error range, record the historical simulation data of the historical industrial boiler as characteristic historical simulation data, retain the historical industrial boiler with the characteristic historical simulation data, and obtain a plurality of historical industrial boilers;

[0099] Step S203: obtain design data of the industrial boiler, standardize the design data of the industrial boiler and historical design data in the historical industrial boilers, and perform vector conversion to obtain a vector group;

[0100] Step S204: calculate a characteristic design similarity value P between the industrial boiler and the historical industrial boilers: ,

[0101] C represents the vector group of the design data of the industrial boiler; and D represents the vector group of the historical design data of the historical industrial boilers.

[0102] Step S205: obtain average values of each operating parameter of the industrial boiler in the working data, and standardize the working data of the industrial boiler and the historical working data in the historical industrial boilers, respectively;

[0103] Step S206: calculate an equipment operation similarity value H between the industrial boiler and the historical industrial boilers:

[0104] ,

[0105] wherein E i represents the average value of the i-th operating parameter in the industrial boiler; F i represents the average value of the i-th operating parameter in the historical industrial boiler; j represents the total number of operating parameters in the industrial boiler;

[0106] For example, the total number of operating parameters in the industrial boiler is 3; the average value E1 of the 1st operating parameter in the industrial boiler represents 3; the average value E2 of the 2nd operating parameter in the industrial boiler represents 4; the average value E3 of the 3rd operating parameter in the industrial boiler represents 5; the average value F1 of the 1st operating parameter in the historical industrial boiler represents 4; the average value F2 of the 2nd operating parameter in the historical industrial boiler represents 5; the average value F3 of the 3rd operating parameter in the historical industrial boiler represents 7;

[0107] The equipment operation similarity value H between the industrial boiler and the historical industrial boiler is calculated as follows:

[0108] ,

[0109] Step S207: Obtain the maximum value H max and the minimum value H min of the equipment operation similarity value between the industrial boiler and the historical industrial boiler, and calculate the characteristic equipment operation similarity value H´=(H-H min ) / (H max -H min ) between the industrial boiler and the historical industrial boiler.

[0110] For example, the maximum value H max of the equipment operation similarity value between the industrial boiler and the historical industrial boiler is 10, and the minimum value H min is 0.5; the equipment operation similarity value H between the industrial boiler and the historical industrial boiler is 3.

[0111] The characteristic equipment operation similarity value H´=(H-H min ) / (H max -H min )=(3-0.5) / (10-3)≈0.36 between the industrial boiler and the historical industrial boiler is calculated as follows:

[0112] Step S208: Calculate the boiler simulation condition similarity value G=(γ×P)+(μ×H´), wherein γ is a preset characteristic design coefficient, μ is a preset characteristic equipment operation coefficient, γ∈(0,1), μ∈(0,1), and γ+μ=1.

[0113] Step S209: Obtain the boiler simulation condition similar value between the industrial boiler and a plurality of historical industrial boilers. When the boiler simulation condition similar value between the industrial boiler and a certain historical industrial boiler is greater than a preset boiler simulation condition similar threshold value, it is determined that the certain historical industrial boiler is similar to the industrial boiler in terms of the boiler simulation condition, and the certain historical industrial boiler is recorded as a comparison historical industrial boiler of the industrial boiler;

[0114] Step S300: Obtain the historical simulation data of the comparison historical industrial boiler, obtain the simulation data of the industrial boiler, and perform optimization adjustment on the simulation data of the industrial boiler based on the historical simulation data to obtain target simulation data;

[0115] The step S300 includes:

[0116] Step S301: Obtain the historical simulation data of a plurality of comparison historical industrial boilers of the industrial boiler, and obtain the data corresponding to each target simulation parameter in the comparison historical industrial boiler from the historical simulation data;

[0117] Step S302: Obtain the simulation data of the industrial boiler, and calculate the characteristic deviation value of each target simulation parameter in the industrial boiler, wherein the characteristic deviation value K d of the dth target simulation parameter in the industrial boiler is calculated as follows:

[0118] ,

[0119] wherein q is the total number of the plurality of comparison historical industrial boilers; U d is the average value of the dth target simulation parameter in the industrial boiler; U d z is the average value of the dth target simulation parameter in the zth comparison historical industrial boiler of the plurality of comparison historical industrial boilers; U d max is the maximum value of the average value of the dth target simulation parameter in the plurality of comparison historical industrial boilers; and U d min is the minimum value of the average value of the dth target simulation parameter in the plurality of comparison historical industrial boilers.

[0120] Step S303: The dth target simulation parameter in the industrial boiler is adjusted as follows. When the characteristic deviation value K d is greater than or equal to a preset characteristic deviation threshold value, the dth target simulation parameter in the industrial boiler is adjusted based on the historical simulation data of the comparison historical industrial boiler. When the characteristic deviation value K d is less than the characteristic deviation threshold value, the dth target simulation parameter in the industrial boiler is not adjusted.

[0121] Step S304: the target simulation data of the industrial boiler is obtained by optimizing and adjusting each target simulation parameter in the industrial boiler;

[0122] Step S400: the target simulation data of the industrial boiler is obtained, the equipment operation data of the industrial boiler in the current period is obtained, and the warning information of the industrial boiler is formulated by combining the target simulation data, so as to perform damage warning on the water vapor leakage of the industrial boiler;

[0123] The step S400 comprises:

[0124] Step S401: the equipment operation data of the industrial boiler in the current period is obtained by monitoring each operation parameter of the industrial boiler in the current period;

[0125] Step S402: the warning information of the industrial boiler is formulated by combining the equipment operation data and the target simulation data of the industrial boiler, so as to perform damage warning on the water vapor leakage of the industrial boiler in the current period;

[0126] In order to better realize the above method, a water vapor leakage damage warning system based on data simulation is also proposed, which comprises a simulation data module, a historical industrial boiler comparison module, a target simulation data module, and a damage warning module.

[0127] The simulation data module is used to obtain the preset working data and design data of the industrial boiler, simulate the water vapor leakage of the industrial boiler, and obtain simulation data.

[0128] The historical industrial boiler comparison module is used to analyze the similarity of the boiler simulation conditions between the industrial boiler and the historical industrial boiler, and obtain the comparison historical industrial boiler.

[0129] The target simulation data module is used to optimize and adjust the simulation data of the industrial boiler, and obtain the target simulation data.

[0130] The damage warning module is used to obtain the equipment operation data of the industrial boiler, formulate the warning information of the industrial boiler, and perform damage warning on the water vapor leakage of the industrial boiler.

[0131] The simulation data module comprises a model construction unit and a data simulation unit.

[0132] The model construction unit is used to obtain the historical design data of the historical industrial boiler, and construct a water vapor leakage simulation model.

[0133] The data simulation unit is used to simulate the water vapor leakage of the industrial boiler, and obtain the simulation data of the industrial boiler.

[0134] The control historical industrial boiler module comprises a boiler simulation condition similar value unit and a control historical industrial boiler unit.

[0135] The boiler simulation condition similar value unit is configured to calculate a boiler simulation condition similar value between the industrial boiler and the historical industrial boiler.

[0136] The control historical industrial boiler unit is configured to determine a boiler simulation condition similarity between the industrial boiler and the historical industrial boiler according to the boiler simulation condition similar value, and obtain the control historical industrial boiler.

[0137] The target simulation data module comprises a feature deviation value unit and a target simulation data unit.

[0138] The feature deviation value unit is configured to calculate a feature deviation value of each target simulation parameter of the industrial boiler.

[0139] The target simulation data unit is configured to optimize and adjust each target simulation parameter in the industrial boiler, and obtain target simulation data of the industrial boiler.

[0140] The damage early warning module comprises a damage early warning unit.

[0141] The damage early warning unit is configured to monitor each operation parameter of the industrial boiler in a current period, obtain equipment operation data, combine the target simulation data of the industrial boiler, and formulate early warning information of the industrial boiler, so as to perform damage early warning on water vapor leakage of the industrial boiler in the current period.

[0142] It is apparent for those skilled in the art that the present application is not limited to the details of the above exemplary embodiments, and the present application can be implemented in other specific forms without departing from the spirit or essential characteristics of the present application. Therefore, the embodiments should be regarded as exemplary and non-restrictive, and the scope of the present application is defined by the appended claims rather than the above description, and all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be included in the present application. Any reference signs in the claims should not be regarded as limiting the claims involved.

Claims

1. A data simulation-based water vapor leakage damage early warning method, characterized in that, The method comprises: Step S100: constructing a water vapor early warning cloud platform, obtaining historical water vapor leakage data and historical design data of a historical industrial boiler, constructing a water vapor leakage simulation model, obtaining preset working data and design data of the industrial boiler, simulating water vapor leakage of the industrial boiler, and obtaining simulation data; Step S200: obtaining historical simulation data of a historical industrial boiler, obtaining historical design data of the historical industrial boiler, and combining the design data and working data of the industrial boiler to analyze the similarity of the boiler simulation conditions between the industrial boiler and the historical industrial boiler, thereby obtaining a comparison historical industrial boiler; Step S300: obtaining historical simulation data of the comparison historical industrial boiler, obtaining simulation data of the industrial boiler, optimizing and adjusting the simulation data of the industrial boiler based on the historical simulation data, and obtaining target simulation data; Step S400: obtaining target simulation data of the industrial boiler, obtaining equipment operation data of the industrial boiler in a current period, combining the target simulation data, formulating early warning information of the industrial boiler, and performing injury early warning on water vapor leakage of the industrial boiler; The step S200 comprises: Step S201: obtaining historical simulation data of a historical industrial boiler, obtaining historical working data of the historical industrial boiler input into the water vapor leakage simulation model, wherein the historical working data comprises data corresponding to each preset operating parameter of the historical industrial boiler; Step S202: obtaining experimental verification data of the historical industrial boiler, when the difference between the experimental verification data and the data corresponding to each target simulation parameter in the historical simulation data of the historical industrial boiler is within a preset error range, recording the historical simulation data of the historical industrial boiler as characteristic historical simulation data, retaining the historical industrial boiler with the characteristic historical simulation data, and obtaining a plurality of historical industrial boilers; Step S203: obtaining design data of the industrial boiler, standardizing the design data of the industrial boiler and the historical design data in the historical industrial boiler, and performing vector conversion to obtain a vector group; Step S204: calculating a characteristic design similarity value P between the industrial boiler and the historical industrial boiler: ， Wherein C represents the vector group of the design data of the industrial boiler; D represents the vector group of the historical design data of the historical industrial boiler; Step S205: obtaining the average value of each operating parameter of the industrial boiler in the working data, and standardizing the working data of the industrial boiler and the historical working data in the historical industrial boiler, respectively; Step S206: calculating an equipment operation similarity value H between the industrial boiler and the historical industrial boiler: ， wherein E i represents the average value of the i-th operating parameter in the industrial boiler; F i represents the average value of the i-th operating parameter in the historical industrial boiler; j represents the total number of operating parameters in the industrial boiler; Step S207: obtaining a maximum value H of the equipment operation similarity value between the industrial boiler and the historical industrial boiler max , a minimum value H min , and calculating a characteristic equipment operation similarity value H´=(H-H min ) / (H max -H min ) between the industrial boiler and the historical industrial boiler; Step S208: calculating a boiler simulation condition similarity value G between the industrial boiler and the historical industrial boiler, wherein G=(γ×P)+(μ×H´), γ is a preset characteristic design coefficient, μ is a preset characteristic equipment operation coefficient, γ∈(0,1), μ∈(0,1), and γ+μ=1. Step S209: Obtain boiler simulation condition similar values between the industrial boiler and a plurality of historical industrial boilers. When a boiler simulation condition similar value between the industrial boiler and a certain historical industrial boiler is greater than a preset boiler simulation condition similar threshold value, it is determined that the certain historical industrial boiler is similar to the industrial boiler in terms of boiler simulation condition, and the certain historical industrial boiler is recorded as a control historical industrial boiler of the industrial boiler.

2. The method of claim 1, wherein, The step S100 comprises: Step S101: Obtain historical water vapor leakage data of historical industrial boilers, wherein the historical water vapor leakage data comprises data corresponding to each accident damage parameter of the historical industrial boilers after water vapor leakage and data corresponding to each operation parameter of the historical industrial boilers before water vapor leakage; Step S102: Obtain historical design data of historical industrial boilers, wherein the historical design data comprises data corresponding to each design parameter of the historical industrial boilers, and a water vapor leakage simulation model is constructed, and a specific construction process is as follows: the historical water vapor leakage data and the historical design data of the historical industrial boilers are subjected to data normalization processing, and each historical water vapor leakage data and historical design data of each historical industrial boiler is divided into a training set and a test set according to a preset proportion; Step S103: Obtain preset input layer, hidden layer and output layer node numbers of the water vapor leakage simulation model, and obtain an activation function f(x) of the water vapor leakage simulation model: ， The output of a neuron in the water vapor leakage simulation model is defined, wherein, for the rth layer in the water vapor leakage simulation model, the output a r The calculation formula is: ， wherein W r denotes a weight matrix of the rth layer; b r denotes a bias of the rth layer; a r-1 denotes an output of the r-1th layer in the water vapor leakage simulation model; Step S104: Obtain the target simulation parameters preset by the water vapor leakage simulation model, and obtain the loss function L of the water vapor leakage simulation model: , wherein n represents the total number of training samples in the training set; y i represents the true value of the i-th training sample in the training set; y' i represents the predicted value of the i-th training sample in the training set. Step S105: Calculate a gradient of the loss function, perform layer-by-layer back propagation through a chain rule, and update a weight matrix and a bias, and a specific update formula is as follows: ， ， wherein, η denotes a preset learning rate; W old denotes a weight matrix before updating; W new denotes a weight matrix after updating; b old denotes a bias before updating; b new denotes a bias after updating; Step S106: Train the water vapor leakage simulation model using the training set, update the weight matrix and the bias of the water vapor leakage simulation model, verify the water vapor leakage simulation model using the test set, and obtain a verified water vapor leakage simulation model; Step S107: Obtain preset working data and design data of the industrial boiler, wherein the design data comprises data corresponding to each design parameter of the industrial boiler, and the working data comprises data corresponding to each operation parameter of the industrial boiler; Step S108: Input the working data and the design data into the water vapor leakage simulation model, perform water vapor leakage simulation on the industrial boiler, obtain data corresponding to each target simulation parameter of the industrial boiler, and collect the data corresponding to each target simulation parameter of the industrial boiler to obtain simulation data of the industrial boiler.

3. The method of claim 2, wherein the method further comprises: The step S300 comprises: Step S301: Obtain historical simulation data of a plurality of control historical industrial boilers of the industrial boiler, and obtain data corresponding to each target simulation parameter in the control historical industrial boilers from the historical simulation data; Step S302: Obtain the simulation data of the industrial boiler, and calculate the characteristic deviation value of each target simulation parameter of the industrial boiler, wherein the characteristic deviation value K of the dth target simulation parameter in the industrial boiler is calculated according to the following formula: d : ， wherein q is the total number of the number of control historical industrial boilers; U d is the average value of the dth target simulation parameter in the industrial boiler; U d z is the average value of the dth target simulation parameter of the zth control historical industrial boiler in the number of control historical industrial boilers; U d max is the maximum value of the average value of the dth target simulation parameter in the number of control historical industrial boilers; U d min is the minimum value of the average value of the dth target simulation parameter in the number of control historical industrial boilers; Step S303: optimizing and adjusting the dth target simulation parameter in the industrial boiler. The specific process is that when the characteristic deviation value K d is greater than or equal to a preset characteristic deviation threshold, based on the historical simulation data of the historical industrial boiler, the dth target simulation parameter in the industrial boiler is optimized and adjusted; when the characteristic deviation value K d is less than the characteristic deviation threshold, the dth target simulation parameter in the industrial boiler is not adjusted. Step S304: Optimize and adjust each target simulation parameter in the industrial boiler to obtain target simulation data of the industrial boiler.

4. The method of claim 3, wherein the method further comprises: The step S400 comprises: Step S401: monitoring each operation parameter of the industrial boiler in the current period, obtaining equipment operation data of the industrial boiler in the current period; Step S402: based on the equipment operation data, and combined with the target simulation data of the industrial boiler, formulating the early warning information of the industrial boiler, and early warning the damage of the water vapor leakage of the industrial boiler in the current period.

5. A data simulation based water vapor leakage injury warning system for performing a data simulation based water vapor leakage injury warning method according to any one of claims 1 to 4, characterized by, The system comprises a simulation data module, a historical industrial boiler comparison module, a target simulation data module, and a damage early warning module; The simulation data module is configured to obtain preset working data and design data of the industrial boiler, simulate water vapor leakage of the industrial boiler, and obtain simulation data; The historical industrial boiler comparison module is configured to analyze the similarity of boiler simulation conditions between the industrial boiler and historical industrial boilers, and obtain a comparison historical industrial boiler; The target simulation data module is configured to optimize and adjust the simulation data of the industrial boiler, and obtain target simulation data; The damage early warning module is configured to obtain equipment operation data of the industrial boiler, formulate early warning information of the industrial boiler, and early warn the damage of water vapor leakage of the industrial boiler.

6. A water vapor leak hazard warning system based on data simulation according to claim 5, characterized in that, The simulation data module comprises a model construction unit and a data simulation unit; The model construction unit is configured to obtain historical design data of historical industrial boilers, and construct a water vapor leakage simulation model; The data simulation unit is configured to simulate water vapor leakage of the industrial boiler, and obtain simulation data of the industrial boiler.

7. A water vapor leak hazard warning system based on data simulation according to claim 5, wherein, The historical industrial boiler comparison module comprises a boiler simulation condition similarity value unit and a comparison historical industrial boiler unit; The boiler simulation condition similarity value unit is configured to calculate a boiler simulation condition similarity value between the industrial boiler and historical industrial boilers; The comparison historical industrial boiler unit is configured to determine the similarity of boiler simulation conditions between the industrial boiler and historical industrial boilers according to the boiler simulation condition similarity value, and obtain a comparison historical industrial boiler.

8. A data simulation based water vapor leak damage warning system as claimed in claim 5, wherein, The target simulation data module comprises a feature deviation value unit and a target simulation data unit; The feature deviation value unit is configured to calculate a feature deviation value of each target simulation parameter of the industrial boiler; The target simulation data unit is configured to optimize and adjust each target simulation parameter in the industrial boiler, and obtain target simulation data of the industrial boiler.

9. The water vapor leak hazard warning system based on data simulation according to claim 5, wherein, The damage early warning module comprises a damage early warning unit; The damage early warning unit is configured to monitor each operation parameter of the industrial boiler in the current period, obtain equipment operation data, combine the target simulation data of the industrial boiler, formulate early warning information of the industrial boiler, and early warn the damage of water vapor leakage of the industrial boiler in the current period.

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