Equipment exposure environment factor classification method

Abstract

The invention relates to an equipment exposure environment factor classification method. The method comprises the following steps: S1, determining N types of natural environment factors forming an equipment environment spectrum; s2, performing causal analysis on every two environmental factors in the environmental spectrum to obtain a causal relationship between the environmental factors; s3, constructing a directed graph G = (N, E) of N types of environmental factors; s4, determining the coupling degree CD of the N types of environmental factors; s5, judging whether the N types of environmental factors are tightly coupled or not, and if yes, entering the next step; s6, establishing a relation matrix A among the environmental factors; s7, calculating an adjacent matrix A '; s8, calculating a reachable matrix R; and S9, establishing a hierarchical structure diagram of the N types of environmental factors according to the reachable matrix so as to obtain the input of an environmental prediction model. Based on the environmental effect of equipment, the coupling degree of environmental factors is quantitatively evaluated by adopting a directed graph theory, the hierarchical relationship of tight coupling environmental factors is determined by adopting an attribution analysis method, and a basis is provided for subsequently selecting a proper environmental prediction method.

Description

Technical Field

[0001] The invention belongs to the field of environmental engineering, and in particular relates to a method for classifying environmental factors exposed to equipment. Background Art

[0002] When in service, equipment will be adversely affected by external climate, chemistry and other environmental factors. To study this impact, it is necessary to establish a corresponding environmental spectrum. The environmental spectrum is an important input for equipment environmental adaptability assessment and verification and life determination and extension. It is based on different types of environmental data. Through statistical and conversion methods, it gives the stress value, action time, number of actions and proportion of environmental factors that have a significant impact on the equipment, and quantitatively describes the environmental action process that the equipment has experienced during the mission cycle.

[0003] The stress value in the environmental spectrum represents the situation in which the equipment is subjected to the extreme environment, but the environmental data actually used to compile the environmental spectrum usually does not include the extreme state, so it is necessary to use the environmental prediction method to extrapolate and calculate the stress value corresponding to the extreme state. Due to the different regions where the equipment is located, the corresponding environmental factors that constitute the environmental spectrum are also different, and the mutual influence between different environmental factors cannot be ignored. For example, the two environmental factors of sand and dust and corrosive media in the air do not affect each other and can be predicted separately; as for relative humidity, it is significantly affected by solar radiation and temperature. Solar radiation will cause the temperature to rise, and the temperature increase will cause the saturated vapor pressure of humid air to increase, which will lead to a decrease in relative humidity. Therefore, the relative humidity needs to be predicted by considering the three environmental factors comprehensively. However, for multiple environmental factors with strong coupling, the key premise for carrying out environmental prediction is to clarify the causal relationship between the environmental factors, so as to accurately define the input parameters and output parameters in the environmental prediction model, otherwise it will lead to difficulties in solving the prediction model or non-convergence of the calculation, and the error of the prediction result is large, which cannot support the compilation of the environmental spectrum. Summary of the invention

[0004] In view of the shortcomings of the prior art, the present invention provides a method for classifying equipment exposure environmental factors, which can first use directed graph theory to quantitatively evaluate the coupling degree of environmental factors in the environmental spectrum, and then use attribution analysis methods to establish a hierarchical relationship between various factors, thereby providing a basis for the subsequent selection of appropriate environmental prediction methods and determination of prediction model inputs and outputs.

[0005] To achieve the above object, the present invention discloses the following technical solution:

[0006] Specifically, the present invention provides a method for classifying equipment exposure environmental factors, which comprises the following steps:

[0007] S1. According to the environmental profile during the equipment life cycle, combined with the composition structure and functional performance requirements of the equipment, screen the environmental factors that have an impact on the equipment, and determine the N types of natural environmental factors that constitute the equipment environmental spectrum;

[0008] S2. Based on the physical mechanisms that form each environmental factor, conduct a causal analysis between all pairs of environmental factors in the environmental spectrum to obtain the causal relationships between environmental factors. The analysis criteria are as follows:

[0009] When the change of environmental factor A will synchronously cause the change of environmental factor B, then it is determined that environmental factor A is the cause and environmental factor B is the effect, and it is represented by the unidirectional symbol →; when the change of environmental factor A synchronously causes the change of environmental factor B and the change of environmental factor B synchronously causes the change of environmental factor A, then it is determined that the two environmental factors are mutually causal, and it is represented by the bidirectional symbol is used for representation;

[0010] S3. According to the causal relationships between the environmental factors determined in step S2, construct a directed graph G=(N, E) of the N types of environmental factors, where: E represents the total sum of the causal relationships between the environmental factors, and the unidirectional symbol → is counted as 1, and the bidirectional symbol is counted as 2;

[0011] S4. Use the density of the counts of the directed conformations representing the causal relationships of each environmental factor in the directed graph G to characterize the coupling degree CD of the N types of environmental factors. When all pairs of the N types of environmental factors are represented by bidirectional symbols symbols, at this time, the coupling degree of the N types of environmental factors is the highest, and the total sum of their causal relationships is expressed by the permutation formula Therefore, the calculation formula for defining the coupling degree CD is defined as:

[0012]

[0013] S5. Set the b value as the critical threshold representing the coupling tightness. When b < CD, the set of N types of environmental factors is tightly coupled, otherwise it is loosely coupled. If the judgment result is tightly coupled, then proceed to the next step;

[0014] S6. When the set of N types of environmental factors is tightly coupled, establish a relationship matrix A between the environmental factors. Among them, if the matrix element a ij =1, it means that environmental factor F i has a direct impact on environmental factor F j , and if a ij =0, it means that environmental factor F i has no impact on environmental factor F j ;

[0015] S7. Calculate the adjacency matrix A′. The calculation formula for the adjacency matrix A′ is:

[0016] A′=A+I

[0017] Among them, A is the relationship matrix, I is the identity matrix;

[0018] S8. Calculate the power of the adjacency matrix A′ until convergence, and obtain the reachable matrix R; according to the reachable matrix R, decompose the N types of environmental factors into different levels, and establish a hierarchical structure diagram of the N types of environmental factors. In the hierarchical structure diagram of the N types of environmental factors, the environmental factors in the next layer are the causes of the previous layer, and the top layer is the overall goal, that is, the environmental factors in the next layer are independent variables, and the environmental factors in the previous layer are dependent variables;

[0019] S9. According to the hierarchical structure diagram of N types of environmental factors, when predicting a certain environmental factor, all environmental factors at all levels below the environmental factor and related to the environmental factor are used as inputs of the environmental prediction model, and the samples corresponding to the inputs of the determined environmental prediction model are used to solve the environmental prediction model parameters and output as the prediction result of the environmental factor.

[0020] Preferably, when the coupling degree is close to 1, it indicates that the environmental factors tend to be tightly coupled and the coupling degree is high; when the coupling degree is close to 0, it indicates that the environmental factors tend to be weakly coupled and the coupling degree is low.

[0021] Preferably, the equipment life cycle environmental profile refers to a profile consisting of the environment experienced by the equipment and the environmental combination / integration and its time sequence description.

[0022] Preferably, the environmental effect refers to the phenomenon that the equipment's materials, components and structural parts are fatigued, worn, corroded, aged, degraded or downgraded due to various single or comprehensive / combined environmental effects during its life cycle, resulting in a decline in equipment performance or even loss of function.

[0023] Preferably, the unit matrix I refers to a matrix with the same size as the relationship matrix and whose diagonal elements are 1 and other elements are 0.

[0024] Preferably, the environmental factors in step S1 are temperature, relative humidity, solar radiation, wind, sand and dust, and acidic media in the atmosphere.

[0025] Compared with the prior art, the present invention has the following beneficial effects:

[0026] (1) The method of the present invention aims to solve the problem of lack of analysis on the coupling degree of each environmental factor when compiling the environmental spectrum. Based on the environmental effect of the equipment, the method adopts directed graph theory to quantitatively evaluate the coupling degree of environmental factors, which provides a basis for the subsequent selection of appropriate environmental prediction methods. When the environmental factors are tightly coupled, this method is selected to determine the input parameters of the environmental prediction model, and the samples corresponding to the input environmental factors are clearly used as the input to solve the model output, and the final environmental prediction model is determined to ensure the accuracy of the output results. The method can be applied to the prediction of environmental factors of various equipment during specific exposure and use, and can be applied to the classification of equipment exposure environmental factors in multiple fields.

[0027] (2) The method of the present invention targets multiple environmental factors with strong coupling, adopts the attribution analysis method to perform structural analysis on all environmental factors, establishes the hierarchical relationship of all environmental factors, clarifies the input-output relationship between all environmental factors, and according to the hierarchical structure diagram of N types of environmental factors, when predicting a certain environmental factor, all environmental factors of all levels below the environmental factor and related to it are used as the input of the environmental prediction model, and the corresponding input environmental data samples are used to solve the prediction model parameters and output as the environmental prediction result, which can well support the analysis and calculation work of the environmental prediction model. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a specific flow chart of the present invention;

[0029] Figure 2 is a directed graph in an embodiment of the present invention;

[0030] Figure 3 4 is a hierarchical structure diagram of environmental factors in an embodiment of the present invention.

[0031] Figure 4 This is a diagram showing the predicted results of the relative humidity environment in an embodiment of the present invention. DETAILED DESCRIPTION

[0032] The exemplary embodiments, features and aspects of the present invention will be described in detail below with reference to the accompanying drawings. The same reference numerals in the accompanying drawings represent elements with the same or similar functions. Although various aspects of the embodiments are shown in the accompanying drawings, the drawings are not necessarily drawn to scale unless otherwise specified.

[0033] Specifically, the present invention provides a method for classifying equipment exposure environmental factors, which comprises the following steps:

[0034] S1. Based on the environmental profile of the equipment during its life cycle, combined with the equipment's composition structure and functional performance requirements, screen the environmental factors that have a significant impact and effect on the equipment, and determine the N types of natural environmental factors that constitute the equipment's environmental spectrum.

[0035] Among them, the environmental profile of the equipment life cycle refers to the profile composed of the environment and environmental combination / combination and its time sequence description that the equipment is subjected to. Environmental effects refer to the phenomenon that the equipment's materials, components and structural parts are fatigued, worn, corroded, aged, and their performance degraded or downgraded under the influence of various single or comprehensive / combined environments during its life cycle, resulting in equipment performance degradation or even loss of function.

[0036] In specific applications, the determination process is based on the environmental effects of the equipment. For example, the equipment consists of electronic components, so it is sensitive to temperature and humidity; the equipment consists of metal materials, so it is sensitive to corrosive media; the equipment consists of polymer materials such as rubber and plastic, so it is sensitive to solar radiation.

[0037] Among them, environmental factors include temperature, relative humidity, solar radiation, wind, dust and acidic media in the atmosphere.

[0038] S2. Based on the physical mechanism that forms each environmental factor, a causal analysis is performed between all environmental factors in the environmental spectrum to obtain the causal relationship between environmental factors. The analysis criteria are as follows:

[0039] When the change of a certain environmental factor A will cause the change of a certain environmental factor B at the same time, and the change of environmental factor B will not cause the change of environmental factor A, that is, only the change of one environmental factor can cause the change of the other environmental factor, then environmental factor A is determined to be the cause and environmental factor B is the effect, and the one-way symbol → is used to represent it; when the change of environmental factor A causes the change of environmental factor B at the same time, and the change of environmental factor B causes the change of environmental factor A at the same time, that is, the two environmental factors can cause each other's changes when they change, then the two environmental factors are determined to be causal, and the two-way symbol → is used to represent it; To express.

[0040] S3. According to the causal relationship between the environmental factors determined in step S2, a directed graph G = (N, E) of N types of environmental factors is constructed, where: E represents the sum of the causal relationships between the environmental factors, where the one-way symbol → counts as 1, and the two-way symbol The count is 2.

[0041] S4. The density of the counts of the directed matches representing the causal relationship of each environmental factor in the directed graph G is used to represent the coupling degree CD of N types of environmental factors. When the symbol is represented, the coupling degree of N types of environmental factors is the highest, and the sum of their causal relationships is expressed by the arrangement formula Therefore, the calculation formula for defining the degree of coupling CD is:

[0042]

[0043] S5. Set the b value as the critical threshold representing the tightness of coupling. When b < CD, the N sets of environmental factors are tightly coupled; otherwise, they are loosely coupled. If the judgment result is tight coupling, proceed to the next step. If it is judged as loose coupling, since the input and output of environmental data are relatively clear, the input of the environmental factor prediction model can be directly predicted.

[0044] In specific applications, in practical applications, the coupling degree is distinguished by the values 0 and 1. When the value is closer to 1, it indicates that the environmental factors tend to be tightly coupled with a high coupling degree; when the value is close to 0, it indicates that the environmental factors tend to be weakly coupled with a low coupling degree. If it is determined that the environmental factors are tightly coupled, proceed to the next step.

[0045] S6. When the N sets of environmental factors are tightly coupled, establish the relationship matrix A between the environmental factors. Among them, the matrix element a ij = 1 indicates that the environmental factor F i has a direct impact on the environmental factor F j ; a ij = 0 indicates that the environmental factor F i has no impact on the environmental factor F j .

[0046] S7. Calculate the adjacency matrix A′. The calculation formula for the adjacency matrix A′ is:

[0047] A′ = A + I

[0048] where A is the relationship matrix and I is the identity matrix; in specific applications, the identity matrix I refers to a matrix with the same size as the relationship matrix, with diagonal elements being 1 and other elements being 0.

[0049] S8. Calculate the power of the adjacency matrix A′ until convergence to obtain the reachability matrix R; according to the reachability matrix R, decompose the N sets of environmental factors into different levels and establish the hierarchical structure diagram of the N sets of environmental factors. In the hierarchical structure diagram of the N sets of environmental factors, the environmental factors in the lower layer are the reasons for the upper layer, and the top layer is the overall goal, that is, the environmental factors in the lower layer are independent variables and the environmental factors in the upper layer are dependent variables; in specific applications, the attribution analysis method is used to conduct a structural analysis of all environmental factors, establish the hierarchical relationship of all environmental factors, and clarify the input and output relationship between all environmental factors.

[0050] S9. According to the hierarchical structure diagram of the N sets of environmental factors, when predicting a certain environmental factor, use all the environmental factors in all the lower levels and related to this environmental factor as the input of the environmental prediction model, and solve the prediction model parameters with the corresponding input environmental data samples and output them as the environmental prediction result.

[0051] Another aspect of the present invention further provides an equipment exposure environmental factor classification system, which includes a natural environmental factor determination unit, a causal relationship analysis unit, a directed graph construction unit, a coupling degree calculation unit, a coupling degree judgment unit, a relationship matrix construction unit, an adjacency matrix calculation unit, a reachability matrix calculation unit, and an environmental prediction model input determination unit.

[0052] The natural environmental factor determination unit is used to determine N types of natural environmental factors that make up the equipment environmental spectrum; the causal relationship analysis unit conducts a causal analysis between all environmental factors in the environmental spectrum pairwise to obtain the causal relationships between environmental factors; the directed graph construction unit is used to construct a directed graph G=(N, E) of N types of environmental factors; the coupling degree calculation unit is used to determine the coupling degree CD of N types of environmental factors; the coupling degree judgment unit judges whether N types of environmental factors are tightly coupled. If so, proceed to the next step; in this unit, set the b value as the critical threshold representing the tightness of coupling. When b < CD, the set of N types of environmental factors is tightly coupled, otherwise it is loosely coupled. If the judgment result is tightly coupled, proceed to the next step. If it is judged to be loosely coupled, since the input and output of environmental data are relatively clear, the input of the environmental factor prediction model can be directly predicted. The relationship matrix construction unit is used to establish a relationship matrix A between each environmental factor; the adjacency matrix calculation unit is used to calculate the adjacency matrix A'; the reachability matrix calculation unit is used to calculate the reachability matrix R, and based on the reachability matrix R, decompose N types of environmental factors into different levels and establish a hierarchical structure diagram of N types of environmental factors. In the hierarchical structure diagram of N types of environmental factors, the environmental factors in the lower layer are the reasons for the upper layer, and the top layer is the overall goal, that is, the environmental factors in the lower layer are independent variables, and the environmental factors in the upper layer are dependent variables; the environmental prediction model input determination unit is used to, according to the hierarchical structure diagram of N types of environmental factors, when predicting a certain environmental factor, use all the environmental factors in all levels below this environmental factor and related to this environmental factor as the input of the environmental prediction model, and solve the prediction model parameters using the corresponding input environmental data samples and output as the environmental prediction result.

[0053] Meanwhile, the present invention also provides a computer device, on which the above-mentioned equipment exposure environmental factor classification system is installed.

[0055] An embodiment of the present invention provides a method for classifying helicopter equipment exposure environmental factors, specifically including the following steps:

[0056] S1. A certain type of helicopter is deployed in a certain area. Since the life of a certain type of helicopter is mainly parking, the natural environment spectrum of the parking stage of a certain type of helicopter is compiled. A certain area is a coastal industrial area. The atmosphere contains acidic atmosphere formed by acidic media generated by industrial activities. The environmental effects of all natural environmental factors on a certain type of helicopter are analyzed, and it is determined that the parking environment spectrum of a certain type of helicopter consists of 6 types of environmental factors: temperature, relative humidity, solar radiation, wind, sand and dust, and acidic media in the atmosphere.

[0057] S2. Define 6 types of environmental factors as F1 to F6. Based on the physical mechanism of each environmental factor, conduct causal analysis between all N types of environmental factors in the environmental spectrum, as follows:

[0058] a) Solar radiation will cause the temperature to rise, which is represented by "F1→F2";

[0059] b) Changes in temperature, solar radiation, relative humidity and wind speed will lead to changes in dust concentration, which are indicated by "F1→F5", "F2→F5", "F3→F5" and "F4→F5";

[0060] c) Changes in temperature and wind speed will lead to changes in relative humidity, which are indicated by "F4→F2" or "F2→F3";

[0061] d) Changes in wind speed will cause changes in the concentration of acidic media in the atmosphere, which is represented by "F4→F6".

[0062] S3. According to the dependency relationship of the six types of environmental factors in the environmental spectrum, a directed graph G = (6, E) is constructed, where E represents the dependency relationship between the environmental factors and the number of edges is |E|. Figure 1 As shown, where |E|=8.

[0063] S4. Calculate the coupling degree CD of the six types of environmental factors. The formula is as follows:

[0064]

[0065] S5. Define the critical threshold b=0.2 of the tightness of coupling of environmental factors. Since CD=0.27>0.2, the six types of environmental factors are tightly coupled.

[0066] S6. Establish the relationship matrix A between the six types of environmental factors, as shown below:

[0067] A=[0 1 0 0 10; 0 0 1 0 10; 0 0 0 1 10; 0 0 0 0 1 1; 0 0 0 0 0 0; 0 0 00 00]

[0068] Add the relationship matrix A to the identity matrix I to obtain the adjacency matrix A′, that is:

[0069] A′=[1 1 0 0 1 0; 01 1 0 1 0; 0 0 1 1 1 0; 0 0 0 1 1 1; 0 0 0 0 1 0; 0 0 00 0 1]

[0070] S7. Calculate the power of the adjacency matrix A′ until convergence, and obtain the reachable matrix R, that is:

[0071] R=[1 1 1 1 1 1; 01 1 1 1 1; 0 01 1 1 1; 0 0 0 1 1 1; 0 0 0 0 1 0; 0 0 0 00 1]

[0072] S8. According to the reachable matrix R, the six types of environmental factors are decomposed into different levels and a hierarchical structure diagram of the six types of environmental factors is established, with a total of five levels, as shown in the attached figure. Figure 2 shown.

[0073] S9. For the six types of environmental factors that constitute a hierarchical structure diagram, when predicting a certain environmental factor, all environmental factors at all levels below the environmental factor and related to it are used as the input of the environmental prediction model, and the corresponding input environmental data samples are used to solve the prediction model parameters and output as the environmental prediction result.

[0074] Predict the relative humidity inside the cockpit of a certain type of helicopter. According to the hierarchical diagram, relative humidity is at the third level. The fourth and fifth level environmental factors are temperature and solar radiation, respectively. Therefore, temperature and solar radiation are the input parameters for relative humidity prediction.

[0075] The relative humidity environment in the cabin is modeled and predicted using the Elman neural network method. The external solar radiation intensity, external atmospheric temperature, external relative humidity and cabin temperature are selected as the input matrix X(t), and the cabin relative humidity is selected as the output matrix Y(t). When establishing the network model, the network topology is set to 4-5-1 based on the number of input and output variables and engineering experience, that is, the number of input layer nodes is 4, the number of hidden layer nodes is 5, and the number of output layer nodes is 1.

[0076] The measured data obtained was used to train the network, and the number of iterations was set to 10000. As the number of training times increased, the gradient of the cost function decreased rapidly, and by the time the network training was completed, it had dropped to 0.1. At this time, the learning rate was 0.01, which had reached a relatively small value. The mean square error of the training was 2.62.

[0077] Environmental data not involved in modeling are selected to verify the accuracy of the model. Input the outside air temperature, outside relative humidity and cabin air temperature, and the output is the relative humidity in the cockpit. The relative humidity environment prediction result for a certain day is as shown in the attached figure. Figure 4 shown.

[0078] The embodiment of the present invention targets a variety of highly coupled environmental factors, adopts an attribution analysis method to perform a structural analysis on all environmental factors, establishes a hierarchical relationship among all environmental factors, clarifies the input-output relationship among all environmental factors, and according to a hierarchical structure diagram of N types of environmental factors, when predicting a certain environmental factor, all environmental factors of all levels below the environmental factor and related to it are used as inputs to the environmental prediction model, and the corresponding input environmental data samples are used to solve the prediction model parameters and output as the environmental prediction results, which can well support the analysis and calculation work of the environmental prediction model.

[0079] The embodiments described above are only descriptions of the preferred implementation modes of the present invention, and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. A method for classifying equipment exposure environmental factors, characterized by: It includes the following steps: S1. According to the environmental profile during the equipment life cycle, combined with the composition structure and functional performance requirements of the equipment, screen out the environmental factors that have an impact on and act on the equipment, and determine N types of natural environmental factors that constitute the equipment environmental spectrum; S2. Based on the physical mechanisms forming each environmental factor, conduct causal analysis between all pairs of environmental factors in the environmental spectrum to obtain the causal relationships between environmental factors. The analysis criteria are as follows: When the change of environmental factor A causes the change of environmental factor B at the same time, then environmental factor A is determined to be the cause and environmental factor B is the effect, and the one-way symbol → is used to represent it; when the change of environmental factor A causes the change of environmental factor B at the same time and the change of environmental factor B causes the change of environmental factor A at the same time, then the two environmental factors are determined to be mutually causal, and the two-way symbol To express; S3. According to the causal relationship between the environmental factors determined in step S2, a directed graph G = (N, E) of N types of environmental factors is constructed, where: E represents the sum of the causal relationships between the environmental factors, where the one-way symbol → counts as 1, and the two-way symbol The count is 2; S4. The density of the counts of the directed matches representing the causal relationship of each environmental factor in the directed graph G is used to represent the coupling degree CD of N types of environmental factors. When the symbol is represented, the coupling degree of N types of environmental factors is the highest, and the sum of their causal relationships is expressed by the arrangement formula Therefore, the calculation formula for defining the degree of coupling CD is: S5. Set the value of b as the critical threshold representing the tightness of coupling. When b < CD, the set of N types of environmental factors is tightly coupled; otherwise, it is loosely coupled. If the judgment result is tight coupling, proceed to the next step; S6. When the N types of environmental factors are tightly coupled, a relationship matrix A between the environmental factors is established, where the matrix element a ij = t represents the environmental factor F i Environmental factors j Has a direct impact, a ij =0 means environmental factor F i Environmental factors j No impact; S7. Calculate the adjacency matrix A′. The calculation formula for the adjacency matrix A′ is: A′ = A + I where A is the relationship matrix and I is the identity matrix; S8. Calculate the adjacency matrix A ′ The power of is obtained until convergence, and the reachable matrix R is obtained; according to the reachable matrix R, the N types of environmental factors are decomposed into different levels, and a hierarchical structure diagram of the N types of environmental factors is established. In the hierarchical structure diagram of the N types of environmental factors, the environmental factors in the next layer are the causes of the previous layer, and the top layer is the overall goal, that is, the environmental factors in the next layer are independent variables, and the environmental factors in the previous layer are dependent variables; S9. According to the hierarchical structure diagram of N types of environmental factors, when predicting a certain environmental factor, use all the environmental factors at all levels below this environmental factor and related to the environmental factor as the input of the environmental prediction model. Solve the parameters of the environmental prediction model using the samples corresponding to the input of the determined environmental prediction model and output them as the prediction result of this environmental factor.

2. The method for classifying equipment exposure environmental factors according to claim 1, characterized in that: Regarding the coupling degree, when the value is close to 1, it indicates that each environmental factor tends to be tightly coupled and the coupling degree is high; when the value is close to 0, it indicates that each environmental factor tends to be weakly coupled and the coupling degree is low.

3. The method for classifying equipment exposure environmental factors according to claim 1, characterized in that: The environmental profile during the equipment life cycle refers to the profile composed of the environment and environmental combinations / syntheses experienced by the equipment and their chronological descriptions.

4. The method for classifying equipment exposure environmental factors according to claim 3, characterized in that: The environmental effect refers to the phenomenon that under the action of various single or combined / composite environments during the equipment life cycle, the materials, components, and structural parts of the equipment are fatigued, worn, corroded, aged, their performance degrades or deteriorates, resulting in a decline in the equipment performance and even the loss of its functions.

5. The method for classifying equipment exposure environmental factors according to claim 1, characterized in that: The identity matrix I refers to a matrix with the same size as the relationship matrix, with diagonal elements being 1 and other elements being 0.

6. The method for classifying equipment exposure environmental factors according to claim 1, characterized in that: In step S1, the environmental factors are temperature, relative humidity, solar radiation, wind, sand and dust, and acidic media in the atmosphere.

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