Dynamic risk assessment method and device for gas unit of metallurgical enterprise

Abstract

The invention relates to the technical field of gas unit risk assessment, and provides a method and a device for dynamically assessing the risk of a gas unit of a metallurgical enterprise. The method comprises the following steps: constructing a risk evaluation index system influencing a gas unit to obtain an evaluation index; determining an evaluation weight of each evaluation index; according to the risk level of the evaluation index in each historical time period, using the evaluation weight of each evaluation index to predict the prediction risk connection degree of the gas unit in the next time period; according to the predicted risk connection degree, determining a safety level change trend of the gas unit; according to the safety level change trend, calculating the safety level score of the gas unit, and solving the problems that a single evaluation method cannot comprehensively and accurately evaluate the overall risk of the gas unit, cannot effectively capture the safety level change trend, and is poor in practicability and low in accuracy.

Description

Technical Field

[0001] The present invention relates to the technical field of gas unit risk assessment, and in particular to a method and device for dynamic risk assessment of a gas unit in a metallurgical enterprise. Background Art

[0002] Currently, safety risk assessments for gas units in metallurgical enterprises primarily employ methods such as neural networks, Bayesian networks, Hazard and Operability (HAZOP) analysis, or risk matrices. However, using only these single assessment methods for gas unit risk assessments presents numerous limitations, resulting in poor practicality and low accuracy. On the one hand, single assessment methods cannot comprehensively and accurately assess the overall risk of a gas unit, nor can they fully consider the interrelationships and synergies between various assessment indicators. On the other hand, single assessment methods cannot effectively capture the dynamic trends of safety risks, thus failing to provide timely and accurate risk warnings and management decision-making for enterprises.

[0003] In view of this, overcoming the defects of the prior art is an urgent problem to be solved in this technical field. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method and device for dynamically assessing the risks of gas units in metallurgical enterprises. The purpose is to construct a risk evaluation index system affecting gas units, calculate the evaluation weights of various evaluation indicators and the correlation between them and the predicted risks of the next time period, and combine multiple evaluation methods to effectively capture the dynamic changing trends of safety risks. This solves the problems that a single evaluation method cannot comprehensively and accurately assess the overall risk of the gas unit, cannot effectively capture the changing trends of the safety level, and has poor practicality and low accuracy.

[0005] The present invention adopts the following technical solutions:

[0006] In a first aspect, the present invention provides a method for dynamically assessing the risk of a gas unit in a metallurgical enterprise, comprising:

[0007] Constructing a risk assessment index system affecting the gas unit to obtain assessment indicators; determining the assessment weight of each assessment indicator;

[0008] According to the risk level of the evaluation indicators in each historical period, using the evaluation weight of each evaluation indicator, predicting the predicted risk connection degree of the gas unit in the next period;

[0009] Determining a safety level change trend of the gas unit according to the predicted risk connection degree;

[0010] The safety level score of the gas unit is calculated based on the safety level change trend.

[0011] Furthermore, the risk connection degree of the gas unit in the next period is predicted based on the risk level of the evaluation indicator in each historical period and using the evaluation weight of each evaluation indicator, including:

[0012] Obtain the risk level of the evaluation indicator in each historical period;

[0013] Processing the evaluation weights of the evaluation indicators according to the changes in the risk levels of the evaluation indicators in each historical period to generate a current probability matrix for each historical period;

[0014] averaging each element in the current probability matrix to obtain an average probability matrix;

[0015] The average risk connection degree is solved using the average probability matrix; and the risk connection degree under a stable state is predicted according to the average probability matrix and the average risk connection degree to obtain a predicted risk connection degree.

[0016] Furthermore, processing the evaluation weights of the evaluation indicators according to the changes in the risk levels of the evaluation indicators in each historical period to generate the current probability matrix for each historical period includes:

[0017] During the historical period, for each risk level, determining a first type of evaluation indicator for the risk level to remain in the same state, determining a second type of evaluation indicator for the risk level to shift to a different state, and determining a third type of evaluation indicator for the risk level to shift to an opposing state;

[0018] The first, second and third evaluation indicators corresponding to the risk levels are used to calculate the current probability of each risk level in the historical period respectively; the current probability of each risk level is used as an element to form a current probability matrix for the historical period.

[0019] Furthermore, the using the first type evaluation indicator, the second type evaluation indicator, and the third type evaluation indicator corresponding to the risk level to calculate the current probability of each risk level in the historical period includes:

[0020] Determine the sum of the evaluation weights of all the first-category evaluation indicators as a first weight sum;

[0021] Determine the sum of the evaluation weights of all the first-category evaluation indicators and the second-category evaluation indicators as a second weighted sum;

[0022] Determine the sum of the evaluation weights of all the first-category evaluation indicators, the second-category evaluation indicators, and the third-category evaluation indicators as a third weighted sum;

[0023] The current probability of the evaluation indicator of each risk level within the historical period is determined according to the first weight sum, the second weight sum, or the third weight sum.

[0024] Furthermore, determining the current probability of the evaluation indicator of each risk level within the historical period based on the first weight sum, the second weight sum, or the third weight sum includes:

[0025] Determine an evaluation indicator whose risk level at the beginning of the historical period is the first level, and determine the sum of the evaluation weights of the determined evaluation indicators as a fourth weighted sum;

[0026] Determine the ratio of the first weighted sum to the fourth weighted sum as the current probability that the evaluation indicator of the first level remains in the same state during the historical period;

[0027] Determine the ratio of the second weight sum to the fourth weight sum as the current probability that the evaluation indicator of the first level turns to a difference state within the historical period;

[0028] The ratio of the third weighted sum to the fourth weighted sum is determined as the current probability that the evaluation indicator of the first level turns to an antagonistic state within the historical period.

[0029] Furthermore, the using the average probability matrix to solve the average risk connection degree; predicting the risk connection degree in a stable state according to the average probability matrix and the average risk connection degree to obtain the predicted risk connection degree includes:

[0030] Use the state coefficients of the average risk connection degree to be solved to construct the matrix to be solved;

[0031] Determine the difference between the unit matrix and the average probability matrix as an intermediate value matrix; solve for the state coefficient values that can make the sum of the state coefficients equal to one and the product of the matrix to be solved and the intermediate value matrix equal to zero; and use the values of the state coefficients obtained to determine the average risk connection degree;

[0032] A risk status matrix is constructed using the coefficients of the average risk connection degree; and the product of the average probability matrix, the risk status matrix and a preset coefficient matrix is calculated to obtain a predicted risk connection degree.

[0033] Furthermore, determining the safety level change trend of the gas unit according to the predicted risk connection degree includes:

[0034] Obtaining a coefficient of the predicted risk connection degree, and determining the obtained coefficient as a predicted state transition probability corresponding to the risk level;

[0035] Comparing the magnitude relationships between the respective predicted state transition probabilities; when the predicted state transition probability of the first level is greater than the predicted state transition probability of the third level, determining that the main change trend is the same trend; when the predicted state transition probability of the first level is equal to the predicted state transition probability of the third level, determining that the main change trend is balanced trend; when the predicted state transition probability of the first level is less than the predicted state transition probability of the third level, determining that the main change trend is countertrend;

[0036] According to the size relationship between the second-level predicted state transition probability and the first-level predicted state transition probability and the third-level predicted state transition probability, as well as the determined main change trend, the degree of change in the safety level is obtained to determine the trend of change in the safety level.

[0037] Furthermore, the risk evaluation index system affecting the gas unit is constructed to obtain evaluation indicators; and the evaluation weight of each evaluation indicator is determined, including:

[0038] Determining dimensional indicators that affect the gas unit, and determining evaluation indicators belonging to each of the dimensional indicators to obtain the risk evaluation indicator system;

[0039] Scoring each dimension indicator in pairs to obtain a first judgment matrix; scoring each evaluation indicator in pairs to obtain a second judgment matrix;

[0040] Calculating a first maximum eigenvalue and a first weight vector of the first judgment matrix; performing a consistency check on the first judgment matrix using the first maximum eigenvalue; calculating a second maximum eigenvalue and a second weight vector of the second judgment matrix; performing a consistency check on the second judgment matrix using the second maximum eigenvalue;

[0041] When the first maximum eigenvalue causes the first judgment matrix to pass the consistency test, and the second maximum eigenvalue causes the second judgment matrix to pass the consistency test, the product of the first weight vector and the second weight vector is determined as the target weight vector, and the elements in the target weight vector are used as the evaluation weights of the corresponding evaluation indicators.

[0042] In a second aspect, the present invention further provides a device for dynamically assessing the risk of a gas unit in a metallurgical enterprise, comprising:

[0043] At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the processor to execute the method for dynamically assessing the risk of a coal gas unit in a metallurgical enterprise as described in the first aspect.

[0044] In a third aspect, the present invention further provides a non-volatile computer storage medium, which stores computer-executable instructions, and the computer-executable instructions are executed by one or more processors to complete the dynamic risk assessment method for gas units in metallurgical enterprises described in the first aspect.

[0045] In a fourth aspect, a computer program product comprising instructions is provided, which, when executed on a computer or a processor, causes the computer or processor to execute the method for dynamic risk assessment of a coal gas unit in a metallurgical enterprise as described in the first aspect.

[0046] In the fifth aspect, the present invention also provides a metallurgical enterprise gas unit risk dynamic assessment system, including a metallurgical enterprise gas unit risk dynamic assessment device as in the second aspect, and using the metallurgical enterprise gas unit risk dynamic assessment method as described in the first aspect to complete the interaction of the metallurgical enterprise gas unit risk dynamic assessment device of the second aspect.

[0047] Different from the prior art, the present invention has at least the following beneficial effects:

[0048] The present invention first constructs a risk evaluation index system affecting the gas unit, then determines the evaluation weight of each evaluation index, and predicts the predicted risk connection degree of the gas unit in the next time period according to the risk level of the evaluation index in each historical time period and the evaluation weight of each evaluation index, and then determines the safety level change trend of the gas unit, evaluates the safety level change trend of the gas unit risk, so as to more accurately define the safety level score, and finally calculates the safety level change trend corresponding to each evaluation index respectively, comprehensively and accurately evaluates the overall risk of the gas unit, and can fully consider the relationship and synergy between each evaluation index; combines the calculation of the evaluation weight with the prediction of the predicted risk connection degree of the next time period, and uses multiple evaluation methods to effectively capture the dynamic change trend of the safety risk, thereby providing enterprises with timely and accurate risk warnings and management decision-making basis, solving the problems that a single evaluation method cannot comprehensively and accurately evaluate the overall risk of the gas unit, cannot effectively capture the safety level change trend, and has poor practicality and low accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments of the present invention. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort.

[0050] Figure 1 This is a flow chart of a method for dynamically assessing the risk of a gas unit in a metallurgical enterprise provided by an embodiment of the present invention;

[0051] Figure 2 is a schematic diagram of a specific example of a risk assessment indicator system provided by an embodiment of the present invention;

[0052] Figure 3 is a flow chart of step 10 provided in an embodiment of the present invention;

[0053] Figure 4 is a flow chart of step 20 provided in an embodiment of the present invention;

[0054] Figure 5 is a flow chart of step 202 provided by an embodiment of the present invention;

[0055] Figure 6 is a flow chart of step 204 provided by an embodiment of the present invention;

[0056] Figure 7 is a flow chart of step 30 provided in an embodiment of the present invention;

[0057] Figure 8 The present invention provides a schematic diagram of the architecture of a device for dynamically assessing the risk of a gas unit in a metallurgical enterprise. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0059] Unless the context requires otherwise, throughout the specification and claims, the term "including" is to be interpreted as meaning open inclusion, that is, "including, but not limited to". In the description of the specification, the terms "one embodiment", "some embodiments", "exemplary embodiments", "example", "specific example" or "some examples" and the like are intended to indicate that the specific features, structures, materials or characteristics associated with the embodiment or example are included in at least one embodiment or example of the present disclosure. The schematic representation of the above terms does not necessarily refer to the same embodiment or example. In addition, the specific features, structures, materials or characteristics may be included in any one or more embodiments or examples in any appropriate manner, that is, although they may be carried in the embodiments or examples of the above terms due to reasons such as the order and position of appearance, it is not limited to that they can be carried in combination by one embodiment or example.

[0060] In the description of the present invention, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings, and are only for the convenience of describing the present disclosure and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present disclosure.

[0061] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of the present disclosure, unless otherwise specified, "multiple" means two or more. In addition, for example, the description may also use the method of adding "A" and "B" at the end to describe the same type of nouns as two independent individuals. In this case, the corresponding features defined as "A" and "B" are only used to distinguish the description purposes of the same type of individuals, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated.

[0062] When describing some embodiments, the expressions “coupled”, “coupled” and “connected” and their derivatives may be used. For example, when describing some embodiments, the term “connected” may be used to indicate that two or more components are in direct physical or electrical contact with each other. For another example, when describing some embodiments, the term “coupled” may be used to indicate that two or more components are in direct physical or electrical contact. However, the term “connected” or “coupled” may also mean that two or more components are not in direct contact with each other, but still cooperate or interact with each other, such as “optical coupling”, “wireless connection”, etc. The embodiments disclosed herein are not necessarily limited to the contents of the present invention.

[0063] In the description of the present invention, the expression "A and / or B" (where A and B are used to formally represent specific characteristic contents) will be involved, and the corresponding expressions include the following three combinations: only A, only B, and a combination of A and B.

[0064] As used herein, "about," "substantially," or "approximately" includes the stated value and an average value that is within an acceptable range of deviation from the particular value as determined by one of ordinary skill in the art taking into account the measurements in question and the errors associated with the measurement of the particular quantity (i.e., the limitations of the measurement system).

[0065] In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0066] Embodiment 1:

[0067] In order to solve the above problems, Figure 1 As shown, an embodiment of the present invention provides a method for dynamically assessing the risk of a gas unit in a metallurgical enterprise, comprising:

[0068] Step 10: Construct a risk assessment index system affecting the gas unit to obtain assessment indicators; and determine the assessment weight of each assessment indicator.

[0069] In one embodiment, if Figure 2 As shown, multiple dimensional indicators and multiple evaluation indicators under each dimensional indicator can be constructed for the two-level influencing factors affecting the gas unit; and the evaluation weight of the evaluation indicator corresponding to each secondary influencing factor can be determined, so that the evaluation weight can be used subsequently in combination with other evaluation methods to comprehensively evaluate the impact of each evaluation indicator on the gas unit; wherein, the method of determining the evaluation weight of each evaluation indicator is selected by technical personnel in this field according to the specific usage scenario; in an optional embodiment, the hierarchical analysis method can be used to calculate the evaluation weight of each evaluation indicator.

[0070] Step 20: Based on the risk level of the evaluation indicators in each historical period, the evaluation weight of each evaluation indicator is used to predict the predicted risk connection degree of the gas unit in the next period.

[0071] Among them, the method of determining the risk level of each evaluation indicator in each historical time period is selected by technical personnel in this field according to the specific usage scenario; in an optional embodiment, the risk level of each evaluation indicator can be divided by expert scoring; and the risk level of each evaluation indicator in each historical time period is determined according to historical data. Through the risk level and evaluation weight of each evaluation indicator, combined with multiple evaluation methods, the predicted risk connection degree of the gas unit in the next time period is calculated as a whole.

[0072] Step 30: Determine the safety level change trend of the gas unit according to the predicted risk connection degree.

[0073] Each specific evaluation indicator is paired with the risk level of the gas unit as a safety assessment set. The uncertainty of the gas unit overall system is quantified by predicting risk connections to estimate the changing trend of the safety level.

[0074] Step 40: Calculate the safety grade score of the gas unit according to the safety level change trend.

[0075] In actual application scenarios, existing technologies often directly score the safety level of gas units, and the scoring results often fall near the score limit, making the determination of the level more subjective.

[0076] Currently, the industry's assessment of gas unit safety risks is primarily subjective, lacking a scientific methodology to comprehensively evaluate dynamically changing gas units. Consequently, effective safety ratings cannot be obtained, resulting in an inability to fully and accurately assess the safety status of gas units. To more scientifically and objectively assess safety levels, the present embodiment, in accordance with steps 10 through 30 above, combines the comprehensive management level of an enterprise's gas units in recent years to assess the changing trends in the safety level of gas unit risks, thereby more accurately defining the safety rating of an enterprise's gas units.

[0077] In one embodiment, the enterprise may score the safety level of the gas unit according to a risk assessment index system.

[0078] If the difference between the obtained security level score and the lower limit of the corresponding risk level range is greater than the preset value, the risk level within which the obtained security level score falls is directly used as the final security assessment result. The preset value is selected by those skilled in the art based on the specific usage scenario and is not limited here. For example, if the obtained security level score is 96 points, the preset value is 3, and the security level score range corresponding to the risk level "safe" is [90, 100], and the difference between the obtained security level score of 96 points and the lower limit of 90 points of [90, 100] is greater than the preset value of 3, then 96 points is directly used as the final security assessment result.

[0079] If the difference between the obtained safety level score and the lower limit of the corresponding risk level range is less than or equal to the preset value, the original risk level of the safety level score is first determined. If the safety level change trend is "increasing", the risk level of the previous level of the original risk level is determined, and the previous level of risk level is determined as the final safety assessment result. If the safety level change trend is "no increasing trend", the original risk level is directly used as the final safety assessment result. If the safety level change trend is "decreasing trend", the risk level of the next level of the original risk level is determined, and the next level of risk level is determined as the final safety assessment result.

[0080] For example, the obtained security level score is 88 points, the preset value is 3, and the security level score value range corresponding to the risk level of "safe" is [90, 100], and the security level score value range corresponding to the risk level of "general safety" is [70, 90]; at this time, the original risk level of the security level score is general safety; the upper risk level of the original risk level is safe; and the lower risk level of the original risk level is dangerous.

[0081] When the trend of change in safety level is "there is an improving trend", the safety is determined as the final safety assessment result; when the trend of change in safety level is "there is no improving trend", general safety is directly taken as the final safety assessment result; when the trend of change in safety level is "there is a decreasing trend", danger is determined as the final safety assessment result.

[0082] The present invention first constructs a risk evaluation index system affecting the gas unit, then determines the evaluation weight of each evaluation index, and predicts the predicted risk connection degree of the gas unit in the next time period according to the risk level of the evaluation index in each historical time period and the evaluation weight of each evaluation index, and then determines the safety level change trend of the gas unit, evaluates the safety level change trend of the gas unit risk, so as to more accurately define the safety level score, and finally calculates the safety level change trend corresponding to each evaluation index respectively, comprehensively and accurately evaluates the overall risk of the gas unit, and can fully consider the relationship and synergy between each evaluation index; combines the calculation of the evaluation weight with the prediction of the predicted risk connection degree of the next time period, and uses multiple evaluation methods to effectively capture the dynamic change trend of the safety risk, thereby providing enterprises with timely and accurate risk warnings and management decision-making basis, solving the problems that a single evaluation method cannot comprehensively and accurately evaluate the overall risk of the gas unit, cannot effectively capture the safety level change trend, and has poor practicality and low accuracy.

[0083] In order to illustrate the process of obtaining the evaluation index and the evaluation weight, in one embodiment, as Figure 3 As shown, the step 10 includes:

[0084] Step 101: Determine dimensional indicators that affect the gas unit, and determine evaluation indicators belonging to each of the dimensional indicators to obtain the risk evaluation indicator system.

[0085] In an optional embodiment, the four dimensional indicators affecting the gas unit can be determined based on the actual management experience of the enterprise, such as Figure 2As shown, it includes: Equipment and Facility A1, Safety Accessories and Protection A2, Personnel and Operation Management A3, and Emergency Rescue A4. Among them, Equipment and Facility A1 includes four evaluation indicators: design and installation compliance and rationality B1, equipment operation B2, equipment inspection and testing B3, and equipment and facility protection distance compliance B4. Safety Accessories and Protection A2 includes three evaluation indicators: safety accessory integrity and compliance B5, safety protection facility integrity and compliance B6, and gas area explosion-proof electrical compliance B7. Personnel and Operation Management A3 includes three evaluation indicators: gas-related operator evidence collection B8, equipment and facility inspection and maintenance system and implementation B9, and relevant laws and regulations acquisition, identification, and application B10. Emergency Rescue A4 includes three evaluation indicators: emergency plan system B11, emergency drills B12, and accident rescue implementation B13.

[0086] Among them, each evaluation indicator corresponds to different evaluation content. In a specific example, the risk evaluation indicator system is shown in the following table:

[0087]

[0088]

[0089] Step 102: Score each dimension indicator in pairs to obtain a first judgment matrix; score each evaluation indicator in pairs to obtain a second judgment matrix.

[0090] Using the analytic hierarchy process, domestic metallurgical industry experts were invited to score each dimension indicator and evaluation indicator. For example, according to the 1-9 scale, each dimension indicator and its corresponding evaluation indicator were scored in pairs. The first judgment matrix and the second judgment matrix were both m rows and n columns in size, that is, A = (aij)m×n.

[0091] Step 103: Calculate the first maximum eigenvalue and the first weight vector of the first judgment matrix; use the first maximum eigenvalue to perform a consistency check on the first judgment matrix; calculate the second maximum eigenvalue and the second weight vector of the second judgment matrix; use the second maximum eigenvalue to perform a consistency check on the second judgment matrix.

[0092] A consistency test is performed on each of the first and second judgment matrices. During the test, the corresponding consistency index (CI) is calculated, the random consistency index (RI) is determined, and the consistency ratio (CR) is calculated. If the CR value is less than 0.1, the corresponding judgment matrix passes the consistency test. If the CR value is greater than 0.1, the corresponding judgment matrix is inconsistent and fails the consistency test. The judgment matrix that fails the consistency test is appropriately adjusted and then retested until it passes.

[0093] Step 104: When the first maximum eigenvalue causes the first judgment matrix to pass the consistency check, and the second maximum eigenvalue causes the second judgment matrix to pass the consistency check, the product of the first weight vector and the second weight vector is determined as the target weight vector, and the elements in the target weight vector are used as the evaluation weights of the corresponding evaluation indicators.

[0094] For example, the specific examples of evaluation weights of various evaluation indicators in a risk assessment indicator system are as follows:

[0095]

[0096] In order to illustrate the process of obtaining the predicted risk connection degree, Figure 4 As shown, the step 20 includes:

[0097] Step 201: Obtain the risk level of the evaluation indicator in each historical period.

[0098] Among them, the risk levels can be divided into safe (S), generally safe (G) and dangerous (U).

[0099] In one embodiment, the risk level of each assessment indicator in the past five years can be determined by interviews based on the actual safety status of the gas unit, as shown in the following table:

[0100]

[0101]

[0102] Step 202: Processing the evaluation weights of the evaluation indicators according to the changes in the risk levels of the evaluation indicators in each historical period to generate a current probability matrix for each historical period.

[0103] The situation where all evaluation indicators perform well is taken as the standard set, that is, the standard set is a set composed of all evaluation indicators that are fully qualified. The set actually required to be evaluated in the embodiment of the present invention is compared with the standard set one by one for set pair analysis, and the characteristics obtained by the analysis are described as similarities, differences, and opposites, that is, which characteristics of the two sets are identical, which characteristics are opposite, and which characteristics are neither identical nor opposite (difference). In one embodiment, when defining identity, opposition, and difference, if the points that meet the standards in a certain evaluation indicator of the spot check account for more than 90% or are equal to the total number of spot check points, then the evaluation indicator is identical to the evaluation indicator in the standard set. If the points that meet the standards in a certain evaluation indicator of the spot check account for less than 75% of the total number of spot check points, then the evaluation indicator is opposite to the evaluation indicator in the standard set. The indicator in the middle is a difference indicator, thereby establishing the risk assessment connection degree μ, which is expressed as follows:

[0104]

[0105] Among them, N is the total number of evaluation indicators in the standard set; S is the total number of evaluation indicators in the set to be evaluated that are identical to the standard set; P is the total number of evaluation indicators in the set to be evaluated that are opposite to the standard set; Q is the total number of evaluation indicators in the set to be evaluated that are different from the standard set; i is the difference coefficient, which can be taken as [-1,1], which is used to reflect the uncertainty of the risk assessment indicator system under study. The closer i is to 0, the greater the uncertainty information contained in the risk assessment indicator system; j is the opposition coefficient, which can be set to -1.

[0106] Since each characteristic contributes differently to the target, the embodiment of the present invention also considers the weight w i The influence of w i for Rearrange the N evaluation indicators so that they are arranged in the order of same, different, and reverse. The first S are the total number of identity indicators, P is the total number of difference indicators, and Q is the total number of opposition indicators. The risk assessment connection degree μ at this time is as follows:

[0107]

[0108] Based on the above expression, let Among them, a+b+c=1, then μ=a+bi+cj.

[0109] According to the above analysis, the embodiment of the present invention generates a current probability matrix for each historical period according to the risk assessment connection degree of each historical period, which will be described in detail below.

[0110] Step 203: Calculate the average value of each element in the current probability matrix to obtain an average probability matrix.

[0111] In one embodiment, the current probability matrix in the [1, 2] historical period is:

[0112]

[0113] Similarly, the current probability matrices in the historical periods [2,3], [3,4], and [4,5] are:

[0114]

[0115] When the weights of the current probability matrices of each historical period are the same, the average value of each element in the current probability matrix of each period is calculated. For example, for P 1-2 The first element in 0.68, P 2-3 The first element in 0.415, P3-4 The first element 0 and P in 4-5 The first element 0 in the matrix is averaged to get (0.68+0.415+0+0) / 4≈0.273. Similarly, the average of each element at the same position is calculated to get the average probability matrix

[0116]

[0117] Since the weights of the current probability matrices of each historical period are the same, the current probability matrix P of the [1,2] historical period is 1-2 、[2,3] Current probability matrix P of historical period 2-3 、[3,4] Current probability matrix P of historical period 3-4 、[4,5] Current probability matrix P of historical period 4-5 Adding and taking the mean, the average probability matrix calculated can be:

[0118]

[0119] Step 204: using the average probability matrix to solve the average risk connection degree; predicting the risk connection degree in a stable state according to the average probability matrix and the average risk connection degree to obtain a predicted risk connection degree.

[0120] Since the overall gas unit system will eventually stabilize after the safety risk status has shifted over multiple cycles, and the risk connection degree in the stable state conforms to a specific expression, this expression is used to solve the equation to calculate the average risk connection degree of the gas unit for all time periods. Based on this, the risk status of the gas unit in the next time period is predicted to obtain the predicted risk connection degree. This process will be explained below. An average risk connection degree can be: The corresponding predicted risk connection can be:

[0121]

[0122] In order to illustrate the process of generating the current probability matrix, as shown in Figure 5 As shown, step 202 includes:

[0123] Step 2021: During the historical period, for each risk level, determine the first type of evaluation indicators for the risk level to remain in the same state, determine the second type of evaluation indicators for the risk level to turn to a different state, and determine the third type of evaluation indicators for the risk level to turn to an opposing state.

[0124] The embodiment of the present invention is based on the problem of connectivity analyzed from a static perspective. Dynamic factors should be considered when conducting risk assessment of gas units, that is, the random process with no aftereffect of the transition between states of a certain event. Therefore, it is necessary to analyze the future change law of random events and possible results. In one embodiment, after assigning weights to each evaluation indicator, the set to be evaluated is compared with the standard set, and then divided into three levels as three states, namely, "excellent performance", "average performance", and "unqualified performance". "Excellent performance" is the first level, "average performance" is the second level, and "unqualified performance" is the third level. In one embodiment, the first level can be "safe", the second level can be "generally safe", and the third level can be "dangerous".

[0125] For example, at time period t, S evaluation indicators have a risk level of safe. For the risk level "safe," during time period t + Δt, the risk level of the evaluation indicators will evolve from "safe" and may change. If S1 evaluation indicators still have a risk level of safe, then these S1 evaluation indicators are considered first-category evaluation indicators; if S2 evaluation indicators change to a risk level of generally safe, then these S2 evaluation indicators are considered second-category evaluation indicators; if S3 evaluation indicators change to a risk level of dangerous, then these S3 evaluation indicators are considered third-category evaluation indicators; and S1 + S2 + S3 = S.

[0126] Step 2022: Use the first type of evaluation indicators, the second type of evaluation indicators and the third type of evaluation indicators corresponding to the risk level to calculate the current probability of each risk level in the historical period respectively; use the current probability of each risk level as an element to form a current probability matrix for the historical period.

[0127] Based on step 2021, the embodiment of the present invention introduces the probability of time, and the expression of the risk assessment connection degree of the gas unit in time period t is:

[0128]

[0129] Among them, N is the total number of evaluation indicators in the standard set, S t is the total number of indicators that are identical between the set to be evaluated and the standard set, P t is the total number of contradictory indicators in the set to be evaluated and the standard set, S is the total number of first-category evaluation indicators, P is the total number of second-category evaluation indicators, and Q is the total number of third-category evaluation indicators.

[0130] Based on the above expression, the current probability of each risk level in the historical period is calculated respectively. The following example uses the calculation of the current probability of the evaluation indicator with the first risk level in the historical period as an example to illustrate:

[0131] For example, among the S evaluation indicators whose risk level is the first level at the beginning of the historical period t, S1 is still at the first level in the period t+1, S2 turns to the difference state, and S3 turns to the opposition state, where S=S1+S2+S3; then first determine the sum of the weights of each type of evaluation indicators, that is, the sum of the evaluation weights of all the first type of evaluation indicators Determine as the first weighted sum; wherein the risk level of a certain evaluation indicator in time period t is state i; the sum of the evaluation weights of all the first category evaluation indicators and the second category evaluation indicators Determine as the second weight sum; the sum of the evaluation weights of all the first category evaluation indicators, the second category evaluation indicators and the third category evaluation indicators Determined as the third weighted sum.

[0132] Then, the current probability of the evaluation indicator of each risk level in the historical period is determined based on the first weight sum, the second weight sum, or the third weight sum.

[0133] Among them, for the first-level evaluation indicators, determine the S evaluation indicators with the risk level of the first level at the beginning of the historical period t, and sum the evaluation weights of the determined evaluation indicators The ratio of the first weighted sum to the fourth weighted sum is determined as Determine the current probability that the evaluation indicator of the first level remains in the same state during the historical period; Determine the current probability of the evaluation indicator of the first level turning to a different state within the historical period; The current probability of the evaluation indicator of the first level turning into an antagonistic state within the historical period is determined.

[0134] Similarly, the current probability of calculating the evaluation indicators with risk levels of the second and third levels within the historical period will not be repeated here.

[0135] Finally, the current probability matrix is constructed using the current probability corresponding to each risk level.

[0136] Therefore, with p ij It indicates the possibility of the risk level of a certain evaluation indicator transferring from state i to state j from period t to period t+1, that is:

[0137] P={x n+1 =|x n =i}=p ij (i,j=1,2,…,n)

[0138] Here, n is the number of types of state j. For example, when the risk level includes three states: "safe", "generally safe" and "dangerous", n is 3.

[0139] The current probability matrix P of the gas unit evaluation index in the t+T period is:

[0140]

[0141] The embodiment of the present invention uses the concept of connection degree to construct a dynamic risk assessment model for gas units based on the risk assessment connection degree of each gas unit and the current probability matrix. During the time period t+T, the current risk assessment connection degree of the gas unit is:

[0142] μ(t+T)=a(t+T)+b(t+T)i+c(t+T)j=[a(t+T),b(t+T),c(t+T)]·P·(1,i,j) T

[0143] In one embodiment, the current risk assessment connectivity of the gas unit over the past five years can be determined, and the assessment is conducted based on the current risk assessment connectivity over the past five years. The 13 evaluation indicators are ranked according to the three levels of safety (S), general safety (G), and danger (U), and the current risk assessment connectivity of the gas unit over five different time periods is calculated as follows:

[0144] μ1=0.303+0.547i+0.15j

[0145] μ2=0.771+0.181i+0.048j

[0146] μ3=0.382+0.499i+0.119j

[0147] μ4=0.048+0.707i+0.245j

[0148] μ5=0.194+0.399i+0.407j

[0149] After determining the current risk assessment connection degree of each historical period, in order to explain the process of generating the predicted risk connection degree, as shown in the following example: Figure 6 As shown, step 204 includes:

[0150] Step 2041: Construct a matrix to be solved using the state coefficients of the average risk connection degree to be solved.

[0151] As mentioned above, one expression of the average risk connection degree to be solved is:

[0152]

[0153] Among them, each state coefficient is a, b and c; in one embodiment, an expression of the matrix to be solved can be (a, b, c).

[0154] Step 2042: Combine the identity matrix I with the average probability matrix The difference is determined as the intermediate value matrix The solution can make the sum of the state coefficients equal to one, that is, satisfy a+b+c=1, and can make the matrix to be solved (a, b, c) equal to the intermediate value matrix The product of the state coefficients is zero; the average risk connection degree is determined using the values of the state coefficients obtained by solving.

[0155] In one embodiment, when the entire gas unit system tends to be stable, a, b, and c in the predicted risk correlation of the stable state meet the following relationship:

[0156]

[0157] Among them, a,b,c>0.

[0158] The average risk connection degree can be obtained by solving the equation

[0159] Step 2043: construct a risk status matrix using the coefficients of the average risk connection degree; calculate the product of the average probability matrix, the risk status matrix and the preset coefficient matrix to obtain the predicted risk connection degree.

[0160] In an optional embodiment, the preset coefficient matrix may be (1, i, j) T .

[0161] For example, when the state coefficient a is 0.34, b is 0.466, and c is 0.194, the risk state matrix is (0.34, 0.466, 0.194), and the predicted risk connection degree of the gas unit in the next period is:

[0162]

[0163] In order to illustrate the process of determining the trend of safety level, such as Figure 7 As shown, the step 30 includes:

[0164] Step 301: Obtain the coefficient of the predicted risk connection degree, and determine the obtained coefficient as the predicted state transition probability corresponding to the risk level.

[0165] For example, the predicted risk connection degree can be: μ6=0.313+0.449i+0.238j.

[0166] The predicted state transition probability for the first risk level (i.e., safe) is coefficient a, i.e., 0.313; the predicted state transition probability for the second risk level (i.e., generally safe) is coefficient b, i.e., 0.449; and the predicted state transition probability for the third risk level (i.e., dangerous) is coefficient c, i.e., 0.238.

[0167] Step 302: Compare the size relationships between the various predicted state transition probabilities; when the predicted state transition probability of the first level is greater than the predicted state transition probability of the third level, determine that the main change trend is the same trend; when the predicted state transition probability of the first level is equal to the predicted state transition probability of the third level, determine that the main change trend is balanced; when the predicted state transition probability of the first level is less than the predicted state transition probability of the third level, determine that the main change trend is the opposite trend.

[0168] In one embodiment, a comparison table for determining the trend of dynamic risk changes is shown below. The table is obtained by sorting the dynamic risk change situations of the gas unit according to the relevant information of the three risk levels (S, G, U) of the evaluation indicators; wherein the first level is safety (S), the second level is general safety (G), and the third level is danger (U). When the number of evaluation indicators with a risk level of safety (S) is greater than the number of evaluation indicators with a risk level of danger (U), that is, S>U, it is called the same trend; when the number of evaluation indicators with a risk level of safety (S) is equal to the number of evaluation indicators with a risk level of danger (U), that is, S=U, it is called equilibrium; when the number of evaluation indicators with a risk level of safety (S) is less than the number of evaluation indicators with a risk level of danger (U), it is called countertrend.

[0169]

[0170] According to the above table, it can be concluded that the main change trend in the next period is the same trend, that is, the same trend exists but the degree of change in the safety level is slight.

[0171] Step 303: According to the size relationship between the second-level predicted state transition probability and the first-level predicted state transition probability and the third-level predicted state transition probability, as well as the determined main change trend, the degree of change of the safety level is obtained to determine the change trend of the safety level.

[0172] According to the above table, based on the size relationship between a, b and c, it can be concluded that the safety level change procedure for the next period is generally safe.

[0173] In one embodiment, the security level change trends include: an improving trend, a non-improving trend, and a decreasing trend.

[0174] Since μ5=0.194+0.399i+0.407j in the previous period, compared with the predicted μ6=0.313+0.449i+0.238j in this period, a increased from 0.194 to 0.313, so the safety level change trend of the enterprise's gas unit is: there is an improving trend.

[0175] Subsequently, according to step 40, when the difference between the obtained security level score and the lower limit of the value range of the corresponding risk level is greater than the preset value, the risk level to which the obtained security level score falls is directly used as the final security assessment result; or, when the difference between the obtained security level score and the lower limit of the value range of the corresponding risk level is less than or equal to the preset value, the upper-level risk level of the original risk level is determined, and the upper-level risk level is determined as the final security assessment result.

[0176] Example 2:

[0177] like Figure 8 FIG. 1 is a schematic diagram of an architecture of a device for dynamically assessing the risk of a gas unit in a metallurgical enterprise according to an embodiment of the present invention. The device for dynamically assessing the risk of a gas unit in a metallurgical enterprise according to this embodiment includes one or more processors 21 and a memory 22. Figure 8 A processor 21 is taken as an example.

[0178] The processor 21 and the memory 22 may be connected via a bus or other means. Figure 8 The bus connection is taken as an example.

[0179] Memory 22, as a nonvolatile computer-readable storage medium, can be used to store nonvolatile software programs and nonvolatile computer-executable programs, such as the method for dynamically assessing the risk of a metallurgical enterprise's coal gas unit in this embodiment. Processor 21 executes the method for dynamically assessing the risk of a metallurgical enterprise's coal gas unit by running the nonvolatile software program and instructions stored in memory 22.

[0180] The memory 22 may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state memory device. In some embodiments, the memory 22 may optionally include a memory remotely located relative to the processor 21, and such remote memory may be connected to the processor 21 via a network. Examples of such networks include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0181] The program instructions / modules are stored in the memory 22. When executed by the one or more processors 21, the method for dynamically assessing the risk of a coal gas unit in a metallurgical enterprise in the above-mentioned embodiment is executed, for example, each step of the method for dynamically assessing the risk of a coal gas unit in a metallurgical enterprise in the embodiment of the present invention described above is executed.

[0182] An embodiment of the present invention further provides a non-volatile computer storage medium, wherein the computer storage medium stores computer executable instructions, and the computer executable instructions are executed by one or more processors, for example Figure 8 A processor 21 can enable the above one or more processors to execute the metallurgical enterprise gas unit risk dynamic assessment method in the specific embodiment of the present invention, for example, to execute the various steps of the metallurgical enterprise gas unit risk dynamic assessment method described above in the embodiment of the present invention; it can also realize Figure 8 The various modules and units described above; or executing the metallurgical enterprise gas unit risk dynamic assessment method in the specific embodiment of the present invention, for example, executing the various steps of the metallurgical enterprise gas unit risk dynamic assessment method of the embodiment of the present invention described above; it can also be realized Figure 8 The various modules and units described.

[0183] It is worth noting that the information interaction, execution process, etc. between the modules and units within the above-mentioned devices and systems are based on the same concept as the processing method embodiment of the present invention. The specific content can be found in the description of the method embodiment of the present invention and will not be repeated here.

[0184] Those skilled in the art will understand that all or part of the steps in the various methods of the embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium, which may include: read-only memory (ROM), random access memory (RAM), a disk or an optical disk, etc.

[0185] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for dynamic risk assessment of gas units in metallurgical enterprises, characterized in that: include: Construct a risk assessment index system affecting the gas unit and obtain the assessment index; Determining the evaluation weight of each of the evaluation indicators; According to the risk level of the evaluation indicators in each historical period, using the evaluation weight of each evaluation indicator, predicting the predicted risk connection degree of the gas unit in the next period; Determining a safety level change trend of the gas unit according to the predicted risk connection degree; The safety level score of the gas unit is calculated based on the safety level change trend.

2. The method for dynamic risk assessment of a metallurgical enterprise gas unit according to claim 1, characterized in that: include: Obtain the risk level of the evaluation indicator in each historical period; Processing the evaluation weights of the evaluation indicators according to the changes in the risk levels of the evaluation indicators in each historical period to generate a current probability matrix for each historical period; averaging each element in the current probability matrix to obtain an average probability matrix; Using the average probability matrix to solve the average risk connection degree; According to the average probability matrix and the average risk connection degree, the risk connection degree in a stable state is predicted to obtain a predicted risk connection degree.

3. The method for dynamic risk assessment of a metallurgical enterprise gas unit according to claim 2, characterized in that: include: During the historical period, for each risk level, determining a first type of evaluation indicator for the risk level to remain in the same state, determining a second type of evaluation indicator for the risk level to shift to a different state, and determining a third type of evaluation indicator for the risk level to shift to an opposing state; Using the first, second, and third evaluation indicators corresponding to the risk levels, respectively calculate the current probability of each risk level in the historical period; The current probability of each risk level is used as an element to form a current probability matrix for the historical period.

4. The method for dynamic risk assessment of a metallurgical enterprise gas unit according to claim 3, characterized in that: include: Determine the sum of the evaluation weights of all the first-category evaluation indicators as a first weight sum; Determine the sum of the evaluation weights of all the first-category evaluation indicators and the second-category evaluation indicators as a second weighted sum; Determine the sum of the evaluation weights of all the first-category evaluation indicators, the second-category evaluation indicators, and the third-category evaluation indicators as a third weighted sum; The current probability of the evaluation indicator of each risk level within the historical period is determined according to the first weight sum, the second weight sum, or the third weight sum.

5. The method for dynamic risk assessment of a metallurgical enterprise gas unit according to claim 4, characterized in that: include: Determine an evaluation indicator whose risk level at the beginning of the historical period is the first level, and determine the sum of the evaluation weights of the determined evaluation indicators as a fourth weighted sum; Determine the ratio of the first weighted sum to the fourth weighted sum as the current probability that the evaluation indicator of the first level remains in the same state during the historical period; Determine the ratio of the second weight sum to the fourth weight sum as the current probability that the evaluation indicator of the first level turns to a difference state within the historical period; The ratio of the third weighted sum to the fourth weighted sum is determined as the current probability that the evaluation indicator of the first level turns to an antagonistic state within the historical period.

6. The method for dynamic risk assessment of a gas unit in a metallurgical enterprise according to claim 2, characterized in that: include: Use the state coefficients of the average risk connection degree to be solved to construct the matrix to be solved; Determine the difference between the unit matrix and the average probability matrix as an intermediate value matrix; solve for the state coefficients that can make the sum of the state coefficients equal to one and the product of the matrix to be solved and the intermediate value matrix equal to zero; Using the values of each state coefficient obtained by solving, the average risk connection degree is determined; Using the coefficients of the average risk connection degree, constructing a risk status matrix; The product of the average probability matrix, the risk state matrix and the preset coefficient matrix is calculated to obtain the predicted risk connection degree.

7. The method for dynamic risk assessment of a metallurgical enterprise gas unit according to claim 1, characterized in that: include: Obtaining a coefficient of the predicted risk connection degree, and determining the obtained coefficient as a predicted state transition probability corresponding to the risk level; Comparing the magnitude relationships between the respective predicted state transition probabilities; when the predicted state transition probability of the first level is greater than the predicted state transition probability of the third level, determining that the main change trend is the same trend; when the predicted state transition probability of the first level is equal to the predicted state transition probability of the third level, determining that the main change trend is balanced trend; when the predicted state transition probability of the first level is less than the predicted state transition probability of the third level, determining that the main change trend is countertrend; According to the size relationship between the second-level predicted state transition probability and the first-level predicted state transition probability and the third-level predicted state transition probability, as well as the determined main change trend, the degree of change in the safety level is obtained to determine the trend of change in the safety level.

8. The method for dynamic risk assessment of a gas unit in a metallurgical enterprise according to any one of claims 1 to 7, characterized in that: include: Determining dimensional indicators that affect the gas unit, and determining evaluation indicators belonging to each of the dimensional indicators to obtain the risk evaluation indicator system; Scoring each dimension indicator in pairs to obtain a first judgment matrix; scoring each evaluation indicator in pairs to obtain a second judgment matrix; Calculating a first maximum eigenvalue and a first weight vector of the first judgment matrix; and performing a consistency check on the first judgment matrix using the first maximum eigenvalue; Calculating a second maximum eigenvalue and a second weight vector of the second judgment matrix; and performing a consistency check on the second judgment matrix using the second maximum eigenvalue; When the first maximum eigenvalue causes the first judgment matrix to pass the consistency test, and the second maximum eigenvalue causes the second judgment matrix to pass the consistency test, the product of the first weight vector and the second weight vector is determined as the target weight vector, and the elements in the target weight vector are used as the evaluation weights of the corresponding evaluation indicators.

9. A dynamic risk assessment device for gas units in metallurgical enterprises, characterized in that: The device for dynamically assessing the risk of a gas unit in a metallurgical enterprise includes at least one processor and a memory, wherein the at least one processor and the memory are connected via a data bus, and the memory stores instructions that can be executed by the at least one processor. After being executed by the processor, the instructions are used to implement the method for dynamically assessing the risk of a gas unit in a metallurgical enterprise as described in any one of claims 1 to 8.

10. A non-volatile computer storage medium, characterized in that The computer storage medium stores computer-executable instructions, which are executed by one or more processors to complete the method for dynamic risk assessment of a gas unit in a metallurgical enterprise according to any one of claims 1 to 8.

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