Steel production safety risk index quantification method and device

Abstract

The invention relates to the technical field of steel production safety management, and provides a steel production safety risk index quantification method and device. The method comprises the following steps: when a parameter interlock switch of equipment is turned on, calculating a risk index of the equipment according to an alarm condition of the equipment in an area; the risk index of the computing equipment is realized by using a first preset method or a second preset method; calculating a risk index of the worker according to the operation condition of the worker; determining a correction coefficient of the region according to the hidden danger rectification condition of the region; determining the comprehensive risk level of the region according to the risk index of the equipment in the region, the risk index of the staff in the region and the correction coefficient of the region; the determination of the comprehensive risk level of the area is realized by using a third preset method or a fourth preset method. According to the method, the risk level of the region is evaluated by comprehensively considering equipment, workers and hidden danger rectification conditions in the region, so that more comprehensive risk assessment can be carried out on the whole region.

Description

Technical Field

[0001] The present invention relates to the technical field of steel production safety management, and in particular to a method and device for quantifying a steel production safety risk index. Background Art

[0002] Amidst the booming steel industry, steel production safety remains a core concern for all operations. Steel production involves complex processes encompassing ironmaking, steelmaking, and rolling, each of which carries numerous risk factors, including high temperatures, high pressures, high energies, and gases.

[0003] Traditional safety risk assessment methods for steel companies suffer from numerous significant flaws. When constructing indicator systems, they often focus on a few easily observable parameters, such as the number of equipment failures, lacking a comprehensive and in-depth consideration of the entire production system. Equipment risk assessments are typically performed only after a significant equipment failure has occurred, failing to anticipate potential equipment hazards and effectively assessing the dynamic risk changes of equipment under different operating conditions.

[0004] When it comes to risk quantification, traditional methods mostly rely on qualitative descriptions or simple empirical judgments, lacking scientifically rigorous quantitative models. This makes it difficult for companies to accurately assess the true magnitude of safety risks of varying degrees, making it difficult to formulate targeted and effective preventative measures. For example, when assessing the safety risks of a rolling mill, relying solely on the operator's empirical judgment cannot accurately measure the combined impact of factors such as equipment wear, lubrication status, and electrical control system stability on safety risks.

[0005] With the continuous technological innovation and expansion of production in the steel industry, the demand for accurate, timely, and scientific safety risk assessments has become increasingly urgent. Existing safety management systems are no longer able to meet the growing safety needs of enterprises. A new, highly effective steel production safety risk index quantification method is urgently needed to fill this critical technical gap and achieve comprehensive, dynamic, and precise assessment and management of steel production safety risks, thereby ensuring the safe production of steel enterprises and promoting the sustainable development of the steel industry.

[0006] 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

[0007] The technical problem to be solved by the present invention is to provide a method and device for quantifying the safety risk index of steel production, so as to solve the problem that the existing technology cannot perform comprehensive quantitative risk assessment of a region.

[0008] The present invention adopts the following technical solutions:

[0009] A method for quantifying a safety risk index in steel production, when a parameter interlock switch of an equipment is turned on, the method comprises:

[0010] Calculating a risk index of the device according to an alarm condition of the device in the area; wherein the calculating the risk index of the device is implemented using the first preset method or the second preset method;

[0011] Calculate the risk index of the staff according to their working conditions;

[0012] Determine the correction coefficient of the area based on the hidden danger rectification situation in the area;

[0013] The comprehensive risk level of the area is determined based on the risk index of the equipment in the area, the risk index of the staff in the area and the correction coefficient of the area; wherein, the comprehensive risk level of the area is determined using the third preset method or the fourth preset method.

[0014] Preferably, when the first preset method is used, calculating the risk index of the device according to the alarm status of the device in the area specifically includes:

[0015] Determine the dynamic risk R of the device based on the highest level of alarm generated by the device in the historical period dym ;

[0016] The dynamic risk R of the equipment dym Inherent risks associated with the device sta The weighted sum between them is taken as the risk index C1 of the device.

[0017] Preferably, when the second preset method is used, calculating the risk index of the device according to the alarm status of the device in the area specifically includes:

[0018] Calculate the ratio of points with N1 or higher alarms of the corresponding level to the total number of data points within the historical period to obtain the average disturbance rate of the corresponding level of alarms. Determine the disturbance score for the corresponding level of alarm based on the average disturbance rate. Use the disturbance score of the highest level of alarm as the device's disturbance score R1, or use the maximum value of the disturbance scores of all levels of alarms as the device's disturbance score R1.

[0019] Count the number of points that generated N2 or higher alarms of the corresponding level within a historical period to obtain the number of repeated alarm points for the corresponding level. Determine the repeated alarm score for the corresponding level based on the number of repeated alarm points for the corresponding level. Use the repeated alarm score of the highest level alarm as the repeated alarm score R2 for the device, or use the maximum value of the repeated alarm scores of all levels as the repeated alarm score R2 for the device.

[0020] Calculate the ratio of the number of alarms of the corresponding level generated in the historical period to the number of collection points to obtain the average number of alarms of the corresponding level. Determine the average alarm score of the corresponding level based on the average number of alarms of the corresponding level. Use the average alarm score of the highest-level alarm as the average alarm score R3 of the device, or use the maximum value of the average alarm scores of each level as the average alarm score R3 of the device.

[0021] The average alarm extinction time of the device is obtained by dividing the total accumulated alarm duration in the historical period by the number of alarms in the historical period. Based on the average alarm extinction time, the alarm extinction time score R4 of the device is determined;

[0022] The device's timely alarm elimination rate is calculated by dividing the number of alarms eliminated within the preset time t by the number of alarms in the historical period. Based on the timely alarm elimination rate, the device's timely alarm elimination score R5 is determined.

[0023] The sum of the equipment's disturbance score R1, repeated alarm score R2, point average alarm score R3, alarm elimination time score R4, and alarm elimination timeliness score R5 is used as the equipment's risk index C1.

[0024] Preferably, the calculating of the risk index of the staff member according to the working conditions of the staff member specifically includes:

[0025] The staff's illegal operation index is obtained by dividing the sum of the risk values of illegal operations performed by the staff during the historical monitoring period by the total number of operations; the staff's illegal operation score R is determined based on the staff's illegal operation index. vio ;

[0026] The risk operation index of a worker is obtained by dividing the sum of the risk values of the risk operations performed by the worker in the historical monitoring period by the total number of operations. The risk operation score R of the worker is determined based on the risk operation index of the worker. risk ;

[0027] The average value between the staff member's illegal operation score and risky operation score is used as the staff member's risk index.

[0028] Preferably, when the third preset method is used, determining the comprehensive risk level of the area based on the risk index of the equipment in the area, the risk index of the staff in the area, and the correction coefficient of the area specifically includes:

[0029] Calculate the weighted sum of the risk index of the equipment and the risk index of the staff in the area to obtain the regional risk base;

[0030] Multiplying the risk base by the correction coefficient of the region to obtain a risk score for the region;

[0031] Determine the comprehensive risk level of the area based on the risk score of the area.

[0032] Preferably, when the fourth preset method is used, determining the comprehensive risk level of the area based on the risk index of the equipment in the area, the risk index of the staff in the area, and the correction coefficient of the area specifically includes:

[0033] Multiply the risk index of the equipment in the area by the correction factor of the area to obtain the risk base of the equipment;

[0034] The risk index of the staff in the area is multiplied by the correction factor of the area to obtain the risk base of the staff;

[0035] According to the risk base of the equipment and the risk base of the staff, they are matched with the preset risk matrix, and the matching items in the preset risk matrix are used as the comprehensive risk level of the area.

[0036] Preferably, determining the correction coefficient of a region based on the hidden danger rectification situation of the region specifically includes:

[0037] The correction coefficient corresponding to the range of the hidden danger rectification rate of the region is used as the correction coefficient of the region.

[0038] Preferably, the method further comprises:

[0039] When the parameter interlock switch of the equipment is turned off, the comprehensive risk level of the determined area is the highest level.

[0040] In a second aspect, the present invention further provides a device for quantifying the safety risk index of steel production, for implementing the method for quantifying the safety risk index of steel production described in the first aspect, the device comprising:

[0041] At least one processor; and a memory in communication with 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 steel production safety risk index quantification method described in the first aspect.

[0042] In a third aspect, 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 to complete the method described in the first aspect.

[0043] In a fourth aspect, a chip is provided, comprising: a processor and an interface, for calling and running a computer program stored in a memory, and executing any method of the first aspect.

[0044] In a fifth aspect, a computer program product comprising instructions is provided, which, when executed on a computer or a processor, causes the computer or the processor to execute any of the methods of the first aspect.

[0045] The present invention evaluates the risk level of an area by comprehensively considering the equipment, staff and hidden danger rectification in the area, thereby enabling a more comprehensive risk assessment of the entire area. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] 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.

[0047] Figure 1 This is a flow chart of a method for quantifying a steel production safety risk index provided by an embodiment of the present invention;

[0048] Figure 2 Schematic diagram of a method for quantifying a steel production safety risk index provided by an embodiment of the present invention;

[0049] Figure 3 Schematic diagram of a method for quantifying a steel production safety risk index provided by an embodiment of the present invention;

[0050] Figure 4 This is a flow chart of a method for quantifying a steel production safety risk index provided by an embodiment of the present invention;

[0051] Figure 5 This is a flow chart of a method for quantifying a steel production safety risk index provided by an embodiment of the present invention;

[0052] Figure 6 This is a flow chart of a method for quantifying a steel production safety risk index provided by an embodiment of the present invention;

[0053] Figure 7 This is a flow chart of a method for quantifying a steel production safety risk index provided by an embodiment of the present invention;

[0054] Figure 8 This is a flow chart of a method for quantifying a steel production safety risk index provided by an embodiment of the present invention;

[0055] Figure 9 This is a schematic diagram of the architecture of a device for quantifying safety risk index in steel production provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0056] 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.

[0057] 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.

[0058] 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.

[0059] 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.

[0060] 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).

[0061] 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.

[0062] Embodiment 1:

[0063] Existing steel production safety assessments often focus on only a few easily observable parameters, such as the number of simple equipment failures, without a comprehensive and in-depth consideration of the entire region, and are unable to represent the risk situation of the region. To address this issue, Example 1 of the present invention provides a method for quantifying the steel production safety risk index. When the parameter interlocking switch of the equipment is turned on, such as Figure 1 、 Figure 2 and Figure 3 As shown, the method includes:

[0064] In step 201, the risk index of the device is calculated based on the alarm status of the device in the area; wherein the risk index of the device is calculated using the first preset method or the second preset method; the alarm status includes the number of alarms and the alarm level.

[0065] In step 202, the risk index of the worker is calculated based on the worker's operating conditions; the operating conditions include the worker's illegal operations and risky operations.

[0066] In step 203, a correction coefficient for the region is determined based on the hidden danger rectification status of the region. The hidden danger rectification status can be a hidden danger rectification rate. In actual use, a person skilled in the art can predetermine multiple intervals, and the correction coefficient corresponding to the interval of the hidden danger rectification rate of the region is used as the correction coefficient for the region. In a specific application scenario, each interval and the corresponding correction coefficient are shown in the following table:

[0067] Hidden danger rectification rate range Correction coefficient β [95％,100％] 0.7 [90％,95％) 0.85 [85％,90％) 1 [80％,85％) 1.15 <80％ 1.3

[0068] In step 204, the comprehensive risk level of the area is determined based on the risk index of the equipment in the area, the risk index of the staff in the area, and the correction coefficient of the area; wherein, the determination of the comprehensive risk level of the area is achieved using the third preset method or the fourth preset method. In an optional embodiment, the comprehensive risk level of the area can be directly used for display to remind staff to pay attention to areas with higher risks. In another optional embodiment, the comprehensive risk level of the area can be used as an influencing factor affecting the alarm level displayed by the equipment in the area. For example, when the comprehensive risk level of the area is higher than the corresponding level, the level of the original alarm generated by the equipment is increased by K levels (such as upgrading a low-level alarm to a high-level alarm) to obtain an alarm to be displayed, and the alarm to be displayed is displayed to the user so that the user can increase his attention to the equipment. K is obtained by a technician in this field based on empirical analysis. It should be noted here that the alarm to be displayed is only used for display. When evaluating the comprehensive risk level of the area, the level of the original alarm is still used.

[0069] This embodiment evaluates the risk level of the region by comprehensively considering the equipment, staff and hidden danger rectification in the region, thereby being able to conduct a more comprehensive risk assessment of the region as a whole. In addition, since the alarm conditions of the equipment and the operating conditions of the staff require a period of accumulation, if only relying on the alarm conditions of the equipment and the operating conditions of the staff, then after the region is rectified, due to the update of the regional status, the historical equipment alarm conditions and the operating conditions of the staff are no longer applicable. At this time, it is necessary to accumulate new equipment alarm conditions and the operating conditions of the staff to form a basis for the quantification of the risk of the region. This will result in a long time for the quantification of the regional risk after the rectification. It is precisely to solve this problem that this embodiment introduces the hidden danger rectification situation. In this way, after the region is rectified, the historical equipment alarm conditions and the operating conditions of the staff only need to be corrected using the correction coefficient, that is, they can be applied to the risk quantification after the rectification, so there is no need to accumulate data again, which effectively shortens the time required for the quantification of the risk after the regional rectification.

[0070] In an optional embodiment, when the first preset method is used, the risk index of the device is calculated based on the alarm status of the device in the area, such as Figure 4 As shown, specifically including:

[0071] In step 301, the dynamic risk R of the device is determined based on the highest level of alarms generated by the device in the historical period. dym The duration of the historical period is obtained by those skilled in the art based on empirical analysis. For example, when the duration of the historical period is T, the historical period is [t now -T,t now ], t now is the current time.

[0072] In step 302, the dynamic risk R dym Inherent risks associated with the device sta The weighted sum between them is taken as the risk index C1 of the equipment, that is, C1 = α dym R dym +α sta R sta α dym and α sta are weight coefficients, which are obtained by those skilled in the art based on empirical analysis. In an optional embodiment, α dym =0.73,α sta =0.27, the inherent risk R sta It is obtained by technical personnel in this field based on equipment analysis. One device corresponds to an inherent risk R sta .

[0073] The dynamic risk R of the device is determined based on the highest level of alarm generated by the device in the historical period. dym Specifically, the dynamic risk value corresponding to each level of alarm is predetermined by a person skilled in the art, such as the dynamic risk value of each level of alarm is shown in the following table:

[0074]

[0075]

[0076] Among them, the first level alarm is the highest level, the fourth level alarm is the lowest level, and so on. The first level alarm is also called a high-level alarm (abbreviated as high-high alarm), the second level alarm is also called a high-level alarm (abbreviated as high alarm), the third level alarm is also called a low-level alarm (abbreviated as low alarm), and the fourth level alarm is also called a low-level alarm (abbreviated as low-low alarm).

[0077] Assume that the equipment in a region is a blast furnace, and the inherent risk R of the blast furnace is sta =7, in the historical period, the highest level of alarm generated is the low furnace top pressure alarm (i.e., level 3 alarm), then the corresponding dynamic risk R dym =5, with α dym =0.73,α sta =0.27For example, the calculated risk index of blast furnace is C1=α dym R dym +α sta R sta =0.73×5+0.27×7=5.54.

[0078] In another optional embodiment, when the second preset method is used, the risk index of the device is calculated based on the alarm status of the device in the area, such as Figure 5 As shown, specifically including:

[0079] In step 401, the proportion of the number of points with N1 or more corresponding level alarms (including N1 corresponding level alarms) in the historical period to the number of collected points is calculated to obtain the average disturbance rate of the corresponding level alarm; the disturbance score of the corresponding level alarm is determined according to the average disturbance rate of the corresponding level alarm; the disturbance score of the highest level alarm is used as the disturbance score R1 of the device, or the maximum value of the disturbance scores of each level alarm is used as the disturbance score R1 of the device; the determination of the disturbance score of the corresponding level alarm according to the average disturbance rate of the corresponding level alarm can be: the step interval and the step starting value under each level alarm are determined by those skilled in the art; if the average disturbance rate is less than the step starting value, the corresponding disturbance score is 0; otherwise, each time the average disturbance rate passes through a step interval, the preset step value is accumulated to the disturbance score until the disturbance score reaches the preset maximum disturbance score, or stops when the next step interval is no longer passed. For example, if the step starting value is 0, the step interval is 10%, the preset step value is 0.4, and the preset maximum disturbance score is 2, then for every 10% increase in the average disturbance rate, the disturbance score increases by 0.4. For example, if the average disturbance rate of the corresponding level alarm is calculated to be 32%, since it has passed through 3 step intervals (i.e., exactly greater than or equal to 3 10%), its disturbance score is 1.2.

[0080] In step 402, the number of points that generated N2 or more corresponding level alarms (including N2 corresponding level alarms) within the historical period is counted to obtain the number of repeated alarm points of the corresponding level alarm; based on the number of repeated alarm points of the corresponding level alarm, the repeated alarm score of the corresponding level alarm is determined; the repeated alarm score of the highest level alarm is used as the repeated alarm score R2 of the equipment, or the maximum value of the repeated alarm scores of each level alarm is used as the repeated alarm score R2 of the equipment; the determination of the repeated alarm score of the corresponding level alarm and the above-mentioned confirmation of the disturbance score of the corresponding level alarm are based on the same concept and are not elaborated here.

[0081] In step 403, the proportion of the number of times the corresponding level of alarm is generated in the historical period to the number of collected points is calculated to obtain the average number of point alarms of the corresponding level of alarm; based on the average number of point alarms of the corresponding level of alarm, the average point alarm score of the corresponding level of alarm is determined; the average point alarm score of the highest level of alarm is used as the point average alarm score R3 of the equipment, or the maximum value of the average point alarm scores of each level of alarm is used as the point average alarm score R3 of the equipment; the determination of the average point alarm score of the corresponding level of alarm and the above-mentioned confirmation of the disturbance score of the corresponding level of alarm are based on the same concept and will not be elaborated here.

[0082] In step 404, the total cumulative alarm duration in the historical period is divided by the number of alarms in the historical period to obtain the average alarm elimination time of the device. Based on the average alarm elimination time, the alarm elimination time score R4 of the device is determined; the determination of the alarm elimination time score R4 of the device and the disturbance score for confirming the corresponding level of alarm are based on the same concept and will not be elaborated here.

[0083] In step 405, the device's timely alarm handling rate is obtained by dividing the number of alarms cleared within a preset time t in a historical period by the number of alarms in the historical period. Based on the timely alarm handling rate, a timely alarm handling score R5 for the device is determined. The determination of the device's timely alarm handling score R5 is based on the same concept as the disturbance score for determining alarms of corresponding levels described above. The difference is that the disturbance score increases when the average disturbance rate increases, and the timely alarm handling score increases when the timely alarm handling rate decreases. For example, assuming that a person skilled in the art pre-sets an initial step value of 100%, a step interval of 5%, a preset step value of 0.2, and a preset maximum timely alarm handling score of 2, then for every 5% decrease in the timely alarm handling rate relative to 100%, 0.2 is added to the timely alarm handling score. For example, assuming that the timely alarm handling rate is 79%, since it has decreased by four 5% relative to 100%, the corresponding timely alarm handling score R5 = 4 × 0.2 = 0.8.

[0084] In step 406, the sum of the device's disturbance score R1, repeated alarm score R2, point average alarm score R3, alarm elimination time score R4, and alarm elimination timeliness score R5 is used as the device's risk index C1, that is, C1 = R1 + R2 + R3 + R4 + R5.

[0085] It should be noted that the above-mentioned use of the disturbance score of the highest level alarm as the disturbance score R1 of the device, the repeated alarm score of the highest level alarm as the repeated alarm score R2 of the device, and the point average alarm score of the highest level alarm as the point average alarm score R3 of the device all refer to the calculation of the corresponding scores using the highest level alarm. The highest level alarm here refers to the highest level alarm among the alarms of various levels that meet the corresponding score calculation conditions. For example, for the disturbance score R1 of the device, the highest The level alarm is the highest level alarm among all alarms that have N1 or more corresponding level alarms in the historical period (i.e., the average interference rate is not 0); for the repeated alarm score R2, the highest level alarm is the highest level alarm among all alarms that have N2 or more corresponding level alarms in the historical period (i.e., the number of repeated alarm points is not 0); for the point average alarm score R3, the highest level alarm is the highest level alarm among all alarms generated in the historical period (i.e., the average number of point alarms is not 0).

[0086] In an actual application scenario, N1=5, N2=2, and this embodiment also provides a more specific implementation, as shown in the following table:

[0087]

[0088]

[0089]

[0090] For example, assuming that during the historical period, the average disturbance rate for high-high alarms (i.e., level 1 alarms) was 50%, high alarms (i.e., level 2 alarms) were repeated three times, the average number of low alarms (i.e., level 3 alarms) increased by 40%, the average alarm resolution time was 0.8 hours, and the timely resolution rate was 79%, then the corresponding device's disturbance score is R1 = min(2,5×0.5) = 2, the repeated alarm score is R2 = min(2,3×0.4) = 1.2, the average alarm score for each point is R3 = min(2,2×0.2) = 0.4, the alarm resolution time is R4 = min(2,1×0.2) = 0.2, and the timely resolution score is R5 = min(2,4×0.2) = 0.8. The resulting risk index is C1 = R1 + R2 + R3 + R4 + R5 = 2 + 1.2 + 0.4 + 0.2 + 0.8 = 4.6. The "only add points for the highest risk value" in the above table means that the highest level of alarm is used to calculate the score. This is because the higher the alarm level, the greater the corresponding risk value.

[0091] In an actual application scenario, the risk index of the staff is calculated according to the staff's working conditions, such as Figure 6 As shown, specifically including:

[0092] In step 501, the total risk value of the staff member's illegal operation in the historical monitoring period is divided by the total number of operations to obtain the staff member's illegal operation index; based on the staff member's illegal operation index, the staff member's illegal operation score R is determined. vio ;

[0093] In step 502, the sum of the risk values of the risk operations performed by the staff in the historical monitoring period is divided by the total number of operations to obtain the risk operation index of the staff; based on the risk operation index of the staff, the risk operation score R of the staff is determined. risk ;

[0094] In step 503, the average value between the illegal operation score and the risk operation score of the worker is used as the risk index of the worker, that is, C2=(R vio +R risk ) / 2.

[0095] Among them, different illegal operations may correspond to different risk values, and different risk operations may correspond to different risk values. In order to facilitate calculation, in actual use, technical personnel in this field divide illegal operations into multiple categories, each category corresponds to a risk value, and the illegal operation index of the staff Among them, R i is the risk value of the i-th type of illegal operation, N i The number of times a staff member performs type i illegal operations.

[0096] Similarly, risk operations are divided into multiple categories, each category corresponds to a risk value, and the risk operation index of the staff Among them, R j is the risk value of the jth risk operation, N j The number of times the worker performs risky operations of type j.

[0097] As shown in the table below, illegal operations are divided into five categories (see the "personnel risk" item in the table below), namely no illegal behavior (corresponding risk value 1), Class C illegal operations (corresponding risk value 3), Class B illegal operations (corresponding risk value 5), Class A illegal operations (corresponding risk value 7) and prohibited illegal behaviors (corresponding risk value 10); risky operations are also divided into corresponding to the five risk values, such as no risk operation corresponds to a risk value of 1, level 1 high-altitude operation corresponds to a risk value of 3, level 2 high-altitude operation corresponds to a risk value of 5, level 3 high-altitude operation corresponds to a risk value of 7, and level 4 high-altitude operation corresponds to a risk value of 10.

[0098]

[0099]

[0100] The above table also lists the risk values corresponding to each level of alarm, as well as the impact of the interlock switch status on the risk value.

[0101] According to the staff's illegal operation index, the staff's illegal operation score R is determined. vio , and determining the risk operation score R of the staff member according to the risk operation index of the staff member risk They are all based on the same concept, that is, a number of numerical intervals are predetermined by those skilled in the art, each numerical interval corresponds to a violation score or risk score, and the violation score corresponding to the numerical interval where the violation index is located is used as the violation score R of the staff member. vio The risk operation score corresponding to the numerical range of the risk operation index is used as the risk operation score R of the staff member. vioIn a specific application scenario, the illegal operation index and the risk operation index are evaluated using a unified scale, that is, multiple identical numerical ranges and corresponding scores are set, as shown in the following table:

[0102] Numerical range Risk Score [1,3) 2 [3,5) 4 [5,7) 6 [7,10] 8.5

[0103] For example, when the calculated illegal operation index is 4.5, the corresponding illegal operation score R can be determined according to the above table. vio =4, when the calculated risk operation index is 7, confirm the corresponding risk operation score R according to the above table risk =6, and so on.

[0104] In an optional embodiment, when the third preset method is used, the comprehensive risk level of the area is determined based on the risk index of the equipment in the area, the risk index of the staff in the area and the correction coefficient of the area, such as Figure 7 As shown, specifically including:

[0105] In step 601, a weighted sum of the risk index of the equipment and the risk index of the staff in the area is calculated to obtain the regional risk base.

[0106] In step 602, the risk base is multiplied by the correction coefficient of the region to obtain a risk score of the region.

[0107] In step 603, the comprehensive risk level of the region is determined based on the risk score of the region.

[0108] Steps 601 and 602 can be understood as follows: the risk score of the region R = (α1 × C1 + α2 × C2) × β, where β is a correction factor, C1 is the risk index of the equipment, C2 is the risk index of the personnel, and α1 and α2 are weighting coefficients, which are determined by those skilled in the art based on empirical analysis. Determining the comprehensive risk level of the region based on the risk score of the region can be accomplished by presetting multiple numerical intervals by those skilled in the art, and using the risk level corresponding to the numerical interval in which the risk score of the region falls as the comprehensive risk level of the region, where each numerical interval corresponds to a comprehensive risk level.

[0109] It should be noted that the above embodiments are all described based on one device in one area. In actual use, there may be multiple devices in one area. In this case, the weighted sum of the risk index of each device in the area and the risk index of the staff is calculated to obtain the regional risk base, that is, Among them, α n,1 is the weight coefficient of the nth device in the region, which is obtained by those skilled in the art based on empirical analysis. n,1is the risk index of the nth device in the area. In addition, all workers in the area are evaluated as a whole (i.e., as one worker).

[0110] In another optional embodiment, when the fourth preset method is used, the comprehensive risk level of the area is determined based on the risk index of the equipment in the area, the risk index of the staff in the area and the correction coefficient of the area, such as Figure 8 As shown, specifically including:

[0111] In step 701, the risk index of the equipment in the area is multiplied by the correction coefficient of the area to obtain the risk base of the equipment.

[0112] In step 702, the risk index of the staff in the area is multiplied by the correction coefficient of the area to obtain the risk base of the staff.

[0113] In step 703, the risk bases of the equipment and the staff are matched with a preset risk matrix, and the matching items in the preset risk matrix are used as the comprehensive risk level of the area.

[0114] Steps 701 and 702 can be understood as follows: the risk base of the equipment, C'1, = C1 × β, and the risk base of the staff, C'2, = C2 × β. Step 703 can be understood as follows: determining a matrix index based on the risk base of the equipment and the risk base of the staff, and using the item corresponding to the matrix index in the preset risk matrix as a matching item. The matching item is the comprehensive risk level of the region. Determining the matrix index based on the risk base of the equipment and the risk base of the staff can be: determining the row subscript based on the risk base of the equipment and the column subscript based on the risk base of the staff; or determining the column subscript based on the risk base of the equipment and the row subscript based on the risk base of the staff. A matrix index includes a row subscript and a column subscript, which are used to indicate the item corresponding to the row subscript and column subscript in the risk matrix. The determination of the row subscript and column subscript is achieved by presetting multiple numerical intervals by those skilled in the art, and using the index value corresponding to the numerical interval in which the risk base is located as the row subscript and column subscript. The above implementation method is explained based on one device in one area. In actual use, there may be multiple devices in one area. At this time, the risk base of the corresponding device and the risk base of the staff responsible for the device are used to determine the matching items in the preset risk matrix, and the highest-level item among the matching items corresponding to all devices is used as the comprehensive risk level of the area.

[0115] The preset risk matrix may be:

[0116]

[0117] Taking the above table as an example, if the matrix index is determined to be (2, 3), the corresponding comprehensive risk level is level 3; among them, 2 is the row subscript and 3 is the column subscript, that is, the 2nd row and the 3rd column.

[0118] The above embodiments are all described on the premise that the parameter interlock switch of the device is turned on. In actual use, the method also includes: when the parameter interlock switch of the device is turned off, determining that the comprehensive risk level of the area is the highest level.

[0119] The following is based on the methods described in the above embodiments, combined with specific application scenarios, and uses technical descriptions in related scenarios to illustrate the implementation process of the characteristic scenarios of the present invention.

[0120] First, this embodiment uses the first preset method to calculate the risk index of the device and the third preset method to calculate the comprehensive risk level of the region as an example. Assume that there is a region with the following status:

[0121] The furnace top release interlock switch is in the open state; the furnace top pressure is underreported; the inherent risk value of the blast furnace R inherent = 7, there are 2 Class A violations, 3 Class B violations, 4 Class C violations, and no prohibited illegal operations; there are 4 Level 1 high-altitude risk operations; 6 Level 2 hot work operations; and 1 Level 1 hot work operation; the hidden danger rectification rate is between 90% and 95%, so the calculation results are:

[0122] Equipment risk index C1 = α dym R dym +α sta R sta =0.73×5+0.27×7=5.54.

[0123] Staff's illegal operation index R' vio =(7×2+5×3+3×4) / 9=4.55.

[0124] Risk work index R' of workers risk =(3×4+5×6+7×1) / 11=4.45.

[0125] Corresponding staff member's illegal operation score R vio =4, the risk score of the staff member R risk =4.

[0126] The risk index of the staff C2=(R vio +R risk ) / 2=(4+4) / 2=4.

[0127] The regional correction factor β = 0.85.

[0128] The risk score of the region R = (α1×C1+α2×C2)×β = (0.35×5.54+0.65×4)×0.85 = 3.85, and the corresponding comprehensive risk level corresponding to this risk score is determined to be level three.

[0129] This embodiment uses another application scenario to calculate the risk index of a device using the second preset method and the comprehensive risk level of a region using the fourth preset method. For example, assume that the status of a region is as follows:

[0130] The average disturbance rate of high-alarm alarms was 50%, high-alarm repeated alarms were 3 times, the average number of alarms at low-alarm points increased by 40%, the average alarm extinguishing time was 0.8 hours, and the timely extinguishing rate was 79%; there were 2 Class A violations, 3 Class B violations, 4 Class C violations, and no prohibited illegal operations; there were 4 cases of level 1 high-altitude risk operations; 6 cases of level 2 open flames; and 1 case of level 1 open flames; the hidden danger rectification rate was between 90% and 95%. The calculation results are:

[0131] The risk index of the equipment is C1 = R1 + R2 + R3 + R4 + R5 = 2 + 1.2 + 0.4 + 0.2 + 0.8 = 4.6.

[0132] Staff's illegal operation index R' vio =(7×2+5×3+3×4) / 9=4.55.

[0133] Risk work index R' of workers risk =(3×4+5×6+7×1) / 11=4.45.

[0134] Corresponding staff member's illegal operation score R vio =4, the risk score of the staff member R risk =4.

[0135] The risk index of the staff C2=(R vio +R risk ) / 2=(4+4) / 2=4.

[0136] The equipment's risk base, C'1, = C1 × β = 5.24 × 0.85 = 4.45, corresponds to a severity level of 2 and can be understood as the column subscript. The worker's risk base, C'2, = C2 × β = 4 × 0.85 = 3.4, corresponds to a severity level of 2 and can be understood as the row subscript. Using the row and column subscripts to match the preset risk matrix, the matching item is level 3, indicating a comprehensive risk level of 3 for the area.

[0137] It should be noted that the examples in the above application scenarios are all described using the tables in this embodiment as examples.

[0138] Example 2:

[0139] This embodiment is also based on the method described in the above embodiment 1, combined with specific application scenarios, and uses technical descriptions in related scenarios to illustrate the implementation process of the present invention in the characteristic scenarios.

[0140] This embodiment provides a method for quantifying the steel production safety risk index, which is carried out according to the following steps:

[0141] Step 1: Build a data acquisition and detection system.

[0142] High-precision sensors and monitoring equipment are installed in key equipment and operating areas on the steel production line to collect real-time equipment operating parameters (such as temperature, pressure, speed, vibration frequency, etc.), personnel operation behavior data (action trajectory, operation duration, illegal action identification, etc.), environmental parameters (temperature, humidity, risk gas concentration, etc.) and management process data (hidden danger inspection records, equipment maintenance cycle, etc.), to build a comprehensive multi-source data collection system, provide a rich and accurate data basis for risk assessment, and overcome the problems of single and lagging traditional assessment data.

[0143] Among them, after the sensor collects the equipment operation data, it is filtered, denoised, and cleaned to remove outliers and interference data, and then aggregated to the data processing center through a wireless or wired transmission network.

[0144] Furthermore, the sensors used are as follows:

[0145] Temperature sensors: These monitor temperature fluctuations in key areas of steel production equipment, such as blast furnaces, steelmaking furnaces, and rolling mill bearings. During the blast furnace ironmaking process, excessively high furnace temperatures can indicate severe lining erosion or abnormal furnace reactions. Temperature sensors can promptly detect these abnormal temperature fluctuations, providing critical data for equipment risk assessment.

[0146] Pressure sensors are installed in locations such as blast furnace roofs, gas pipelines, and hydraulic systems to measure gas or liquid pressure. Stable pressure at the blast furnace roof is crucial for smooth operation. Abnormal pressure fluctuations can cause damage to roof equipment or even serious accidents such as gas leaks. Pressure sensors provide real-time pressure monitoring and feedback, ensuring production safety.

[0147] Vibration sensors are primarily used in large rotating equipment and transmission devices, such as rolling mill rollers and motor rotors. By measuring equipment parameters such as vibration frequency and amplitude, they can effectively detect potential faults such as imbalance, bearing wear, and mechanical looseness. For example, if a rolling mill roller vibrates abnormally, a vibration sensor can quickly respond and transmit the data to a monitoring system, enabling timely maintenance measures and reducing the risk of equipment failure.

[0148] Gas concentration sensors: In steel production environments, they detect concentrations of hazardous gases such as carbon monoxide, sulfur dioxide, and hydrogen sulfide. Ironmaking and steelmaking processes generate large quantities of these gases. Leakage and excessive concentrations pose a serious threat to both personnel and production safety. Gas concentration sensors are located throughout key areas of the workshop, continuously monitoring gas concentrations. When concentrations reach warning levels, an alarm system is triggered to prevent accidents such as poisoning and explosions.

[0149] These sensors work together to comprehensively collect all types of data during the steel production process, laying the foundation for subsequent accurate quantitative assessment of safety risks. Compared with traditional steel production safety monitoring methods, they greatly improve the accuracy and comprehensiveness of risk monitoring.

[0150] Step 2: Quantify equipment risk based on the collected data.

[0151] Key risk monitoring indicators are determined based on equipment type and function, such as the blast furnace's top venting interlock and top pressure, and the steelmaking equipment's oxygen pressure and cooling water flow. Different alarm levels (low-low, low, high, and high-high) are set for each indicator, along with corresponding risk scores (set to 2, 4, 6, and 8, respectively). The inherent risk factor of the equipment is also considered (determined through a comprehensive assessment of historical failure data, equipment aging, and other factors, ranging from 0 to 1).

[0152] Based on this, when the device alarm occurs, the device risk value is calculated based on the risk score corresponding to the alarm level and the inherent risk coefficient. The device risk value is calculated using the following formula:

[0153] C1=α 动态 ×R 动态 +α 固有 ×R 固有

[0154] Among them, α 动态 is the dynamic risk weight, ranging from 0.6 to 0.8, R 动态 is the risk score corresponding to the alarm level, α 固有 is the inherent risk weight, ranging from 0.2 to 0.4, R 固有 is the inherent risk value of the equipment, and C1 is the equipment risk value.

[0155] Step 3: Quantify personnel risks based on personnel operation behavior classification and risk grading.

[0156] Personnel operating behaviors are classified and risk graded in detail. Violations are divided into Class A (serious safety hazards, such as illegal live-line operations), Class B (moderate risks, such as failure to operate equipment according to regulations), Class C (minor violations, such as failure to wear prescribed protective equipment), and prohibitions (absolutely prohibited behaviors, such as smoking in risk areas) according to their severity, and risk scores are assigned respectively (Class A 8, Class B 6, Class C 4, and Prohibition 10); risk operations are divided into Level 1 (such as lifting high-temperature molten metal), Level 2 (such as high-altitude hot work), Level 3 (such as general high-altitude operations), etc. according to the degree of risk, with corresponding risk scores (Level 1 7, Level 2 5, Level 3 3).

[0157] Specifically, the personnel risk value is calculated using the following formula:

[0158]

[0159] in,

[0160]

[0161] R i is the risk value of different violation behaviors, N i is the number of violations, N 总数 is the total number of monitoring times, R j is the risk value of different risk operations, N j The number of risk operations.

[0162] Step 4: Determine the safety compensation coefficient based on the hidden danger rectification rate.

[0163] First, determine the company's hidden danger rectification rate. Within the steel production safety risk assessment system, determining the hidden danger rectification rate is crucial for accurately measuring the company's safety management effectiveness and subsequent risk quantification. Typically, the hidden danger rectification rate is calculated based on the company's handling of discovered safety hazards within a specific time period. Companies must establish a comprehensive hidden danger investigation and management ledger, detailing the number, type, and time of discovery of hidden dangers detected during each investigation. After a period of time (such as monthly, quarterly, or annual), count the number of hidden dangers that have been successfully rectified. The formula for calculating the hidden danger rectification rate is: Hidden danger rectification rate = (number of hidden dangers rectified ÷ total number of hidden dangers) × 100%.

[0164] For example, during a quarter of safety management at a steel company, 100 safety hazards were discovered through routine inspections and special checks. Through the collaborative efforts of the company's safety management and production departments, 85 of these hazards were successfully rectified by the end of the quarter. Therefore, the company's hazard rectification rate for that quarter was (85 ÷ 100) × 100% = 85%. Based on the previously established safety compensation factor (β) rule, β = 0.9. This method of calculating the hazard rectification rate based on actual rectification results and associating it with the safety compensation factor effectively incentivizes companies to actively address hazards, improve overall safety management, and more accurately reflect the company's actual safety status in the quantified safety risk index.

[0165] The higher the hidden danger rectification rate, the higher the company's safety management level, and the smaller the safety compensation coefficient. Specifically, the following settings are used: when the hidden danger rectification rate is greater than 95%, β = 0.8; when the hidden danger rectification rate is between 90% and 95%, β = 0.85; when the hidden danger rectification rate is between 85% and 90%, β = 0.9; when the hidden danger rectification rate is between 80% and 85%, β = 0.95; and when the hidden danger rectification rate is less than 80%, β = 1. This coefficient is used to rationally adjust risk assessment results, incentivize companies to actively rectify hidden dangers, improve safety management effectiveness, and address the shortcomings of traditional assessments that fail to consider safety management improvement factors.

[0166] Step 5: Calculate the final safety risk index using the comprehensive risk method.

[0167] The final safety risk index is calculated using the comprehensive risk method: the specific calculation formula is as follows:

[0168] R 综合 =(α 设备 ×C1+α 人员 ×C2)×β

[0169] Among them, α 设备 is the equipment risk weight, ranging from 0.4 to 0.6, α 人员 is the personnel risk weight, ranging from 0.4 to 0.6. 综合 Determine the risk level, including safety (R 综合 <3), Level 4 (3≤R 综合 <5), Level II (7≤R 综合 <9), and (R 综合 ≥9), providing enterprises with an intuitive and clear security status classification, making it easier to take targeted security measures.

[0170] After the risk level is determined, the enterprise shall take corresponding safety measures according to different risk levels. Specifically, no special measures are required for level 4, precautions need to be strengthened, risk elimination or control is required for level 3, control measures or additional protective facilities need to be taken for level 2, and control measures and design changes need to be taken immediately for level 1.

[0171] This invention builds a comprehensive data collection network by meticulously deploying various types of sensors and monitoring equipment throughout key equipment and operating areas on a steel production line. This network continuously and in real time collects key operational parameters of the equipment, such as temperature, pressure, rotational speed, and vibration frequency. It also collects detailed data on human operator behavior, including movement trajectories, operation duration, and identification of illegal actions. It also collects environmental parameters such as temperature, humidity, and risk gas concentrations, as well as management process data such as hazard investigation records and equipment maintenance cycles. This multi-dimensional data collection approach radically overcomes the limitations of traditional assessment methods, which rely on a single data source.

[0172] In the process of risk quantification, the present invention accurately determines the key risk monitoring indicators for equipment risks based on different equipment types and functions, and sets a scientific and reasonable alarm level and corresponding risk score for each indicator. At the same time, it fully considers the inherent risk coefficient of the equipment and uses a rigorous calculation formula to accurately calculate it dynamically. For personnel risks, based on a detailed operational behavior classification and risk grading system, illegal behaviors and dangerous operations are carefully divided and assigned appropriate risk scores, and then accurately quantified through the illegal operation formula. In this way, the present invention can deeply and meticulously analyze various risk factors in the steel production process, accurately measure the degree of influence of each factor on the overall safety risk, and thus draw a highly accurate and detailed panoramic picture of the safety status for steel enterprises, effectively making up for the roughness and shortcomings of traditional assessment methods.

[0173] This invention innovatively uses the hidden danger rectification rate as the core basis for determining the safety compensation coefficient (β), establishing a dynamic incentive mechanism. When an enterprise's hidden danger rectification rate is high, such as greater than 95% (β = 0.8), it indicates that the enterprise has performed well in safety management and will receive a corresponding risk reduction reward in the final safety risk index calculation. This greatly motivates enterprises to proactively carry out hidden danger investigation and rectification work, prompting them to continuously optimize safety management processes, improve safety management levels, and form a virtuous safety management cycle. After determining the risk level, the present invention provides enterprises with clear and targeted safety measures guidance. For different risk levels, from safety level 4 (no special measures required), to level 4 (requires enhanced prevention), level 3 (requires risk elimination or control), level 2 (requires control measures or additional protective facilities), and finally level 1 (requires immediate control measures and design changes), enterprises can use these clear guidelines to develop targeted equipment maintenance plans, conduct personnel training courses, and increase hidden danger investigation and management efforts. This systematic safety management strategy enables enterprises to no longer be blind in their safety management work and to be targeted. It greatly enhances the effectiveness and initiative of enterprise safety management, effectively guarantees the safe and stable progress of steel production, and lays a solid foundation for the sustainable development of the steel industry.

[0174] Example 3:

[0175] like Figure 9 , is a schematic diagram of the structure of the steel production safety risk index quantification device according to an embodiment of the present invention. The steel production safety risk index quantification device according to this embodiment includes one or more processors 21 and a memory 22. Figure 9 A processor 21 is taken as an example.

[0176] The processor 21 and the memory 22 may be connected via a bus or other means. Figure 9 The bus connection is taken as an example.

[0177] 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 steel production safety risk index quantification method in Example 1. Processor 21 executes the steel production safety risk index quantification method by running the nonvolatile software programs and instructions stored in memory 22.

[0178] 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.

[0179] The program instructions / modules are stored in the memory 22 , and when executed by the one or more processors 21 , the steel production safety risk index quantification method in the above-mentioned embodiment 1 is executed.

[0180] 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.

[0181] 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.

[0182] 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 quantifying the safety risk index of steel production, characterized in that: When the parameter interlock switch of the device is turned on, the method includes: Calculating a risk index of the device according to an alarm condition of the device in the area; wherein the calculating the risk index of the device is implemented using the first preset method or the second preset method; Calculate the risk index of the staff according to their working conditions; Determine the correction coefficient of the area based on the hidden danger rectification situation in the area; The comprehensive risk level of the area is determined based on the risk index of the equipment in the area, the risk index of the staff in the area and the correction coefficient of the area; wherein, the comprehensive risk level of the area is determined using the third preset method or the fourth preset method.

2. The method for quantifying the steel production safety risk index according to claim 1, characterized in that: When the first preset method is used, the risk index of the device is calculated based on the alarm status of the device in the area, specifically including: Determine the dynamic risk R of the device based on the highest level of alarm generated by the device in the historical period dym ; The dynamic risk R of the equipment dym Inherent risks associated with the device sta The weighted sum between them is taken as the risk index C1 of the device.

3. The method for quantifying the steel production safety risk index according to claim 1, characterized in that: When the second preset method is used, the risk index of the device is calculated based on the alarm status of the device in the area, specifically including: Calculate the ratio of points with N1 or higher alarms of the corresponding level to the total number of data points within the historical period to obtain the average disturbance rate of the corresponding level of alarms. Determine the disturbance score for the corresponding level of alarm based on the average disturbance rate. Use the disturbance score of the highest level of alarm as the device's disturbance score R1, or use the maximum value of the disturbance scores of all levels of alarms as the device's disturbance score R1. Count the number of points that generated N2 or higher alarms of the corresponding level within a historical period to obtain the number of repeated alarm points for the corresponding level. Determine the repeated alarm score for the corresponding level based on the number of repeated alarm points for the corresponding level. Use the repeated alarm score of the highest level alarm as the repeated alarm score R2 for the device, or use the maximum value of the repeated alarm scores of all levels as the repeated alarm score R2 for the device. Calculate the ratio of the number of alarms of the corresponding level generated in the historical period to the number of collection points to obtain the average number of alarms of the corresponding level. Determine the average alarm score of the corresponding level based on the average number of alarms of the corresponding level. Use the average alarm score of the highest-level alarm as the average alarm score R3 of the device, or use the maximum value of the average alarm scores of each level as the average alarm score R3 of the device. The average alarm extinction time of the device is obtained by dividing the total accumulated alarm duration in the historical period by the number of alarms in the historical period. Based on the average alarm extinction time, the alarm extinction time score R4 of the device is determined; The device's timely alarm elimination rate is calculated by dividing the number of alarms eliminated within the preset time t by the number of alarms in the historical period. Based on the timely alarm elimination rate, the device's timely alarm elimination score R5 is determined. The sum of the equipment's disturbance score R1, repeated alarm score R2, point average alarm score R3, alarm elimination time score R4, and alarm elimination timeliness score R5 is used as the equipment's risk index C1.

4. The method for quantifying the steel production safety risk index according to claim 1, characterized in that: The risk index of the staff is calculated based on the staff's working conditions, specifically including: The staff's illegal operation index is obtained by dividing the sum of the risk values of illegal operations performed by the staff during the historical monitoring period by the total number of operations; the staff's illegal operation score R is determined based on the staff's illegal operation index. vio ; The risk operation index of a worker is obtained by dividing the sum of the risk values of the risk operations performed by the worker in the historical monitoring period by the total number of operations. The risk operation score R of the worker is determined based on the risk operation index of the worker. risk ; The average value between the staff member's illegal operation score and risky operation score is used as the staff member's risk index.

5. The method for quantifying the steel production safety risk index according to claim 1, characterized in that: When the third preset method is used, the comprehensive risk level of the area is determined based on the risk index of the equipment in the area, the risk index of the personnel in the area, and the correction factor of the area, specifically including: Calculate the weighted sum of the risk index of the equipment and the risk index of the staff in the area to obtain the regional risk base; Multiplying the risk base by the correction coefficient of the region to obtain a risk score for the region; Determine the comprehensive risk level of the area based on the risk score of the area.

6. The method for quantifying the steel production safety risk index according to claim 1, characterized in that: When the fourth preset method is used, the comprehensive risk level of the area is determined based on the risk index of the equipment in the area, the risk index of the personnel in the area, and the correction factor of the area, specifically including: Multiply the risk index of the equipment in the area by the correction factor of the area to obtain the risk base of the equipment; The risk index of the staff in the area is multiplied by the correction factor of the area to obtain the risk base of the staff; According to the risk base of the equipment and the risk base of the staff, they are matched with the preset risk matrix, and the matching items in the preset risk matrix are used as the comprehensive risk level of the area.

7. The method for quantifying the steel production safety risk index according to any one of claims 1 to 6, characterized in that: The correction coefficient of the region is determined based on the hidden danger rectification situation of the region, specifically including: The correction coefficient corresponding to the range of the hidden danger rectification rate of the region is used as the correction coefficient of the region.

8. The method for quantifying the steel production safety risk index according to any one of claims 1 to 6, characterized in that: The method also includes: When the parameter interlock switch of the equipment is turned off, the comprehensive risk level of the determined area is the highest level.

9. 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 steel production safety risk index quantification method according to any one of claims 1 to 8.

10. A device for quantifying safety risk index in steel production, characterized in that: include: 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 steel production safety risk index quantification method described in any one of claims 1-8.

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