CN114021864A - Method for identifying major risks and evaluating real-time dynamic risks of ammonia-related refrigeration enterprises - Google Patents
Method for identifying major risks and evaluating real-time dynamic risks of ammonia-related refrigeration enterprises Download PDFInfo
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Abstract
The invention discloses a method for identifying major risks and evaluating real-time dynamic risks of ammonia-related refrigeration enterprises. The steps consist in S1 data collection; s2, analyzing data; s3 risk identification, namely dividing risk units according to the ammonia-related refrigeration enterprise process system, and taking the serious accidents of the induction units as risk points; identifying inherent risk factors of risk points from high-risk articles, high-risk equipment, high-risk processes, high-risk places and high-risk operations; compiling the inherent factor identification result of each risk point into a unit inherent risk list; s4 risk assessment grading; s5 risk aggregation. The invention provides theoretical and technical guidance for enterprise safety risk management and control work, is beneficial to improving the safety management level of ammonia-related refrigeration enterprises, and prevents serious accidents.
Description
Technical Field
The invention belongs to the technical field of safety risk classification management and control in enterprise safety production, and particularly relates to a method for identifying major risks and evaluating real-time dynamic risks of ammonia-related refrigeration enterprises.
Background
The serious accident of ammonia refrigeration enterprises occurs occasionally, and the safe production situation is still severe. The control of major risks is the key for preventing major accidents, the possible accident risks are comprehensively identified, evaluated in real time and controlled in a grading manner, and the accident prevention effect is achieved with half the effort.
The risk identification and assessment technology is accompanied by the theoretical development of safety system engineering. The risk identification method comprises an expert investigation method, a safety inspection table, danger and operability research, accident tree analysis and the like; common risk assessment methods include preliminary risk analysis, accident tree analysis, risk and operability research, failure type and influence analysis, operation condition risk evaluation method, risk matrix method, accident consequence simulation evaluation method, DOW chemical company (DOW) method, empire chemical company (ICI) mond method, japan labor province "chemical plant six-step safety evaluation method", russian chemical process risk evaluation method, and the like, and a risk-based inspection method (RBI) suitable for the safety field of special equipment.
On the basis of statistical analysis of a large number of major fire, explosion and poison leakage poisoning accident data, the evaluation of the major hazard is divided into inherent risk evaluation and actual risk evaluation, wherein the inherent risk evaluation starts from material risk and process risk, analyzes the cause and condition of major accident occurrence, and evaluates the influence range of the accident, casualties and economic loss; the actual risk evaluation considers process equipment, safety management and personnel quality offset factors, and reflects subjective initiative of people for controlling accident occurrence and accident consequence expansion. The project establishes a damage model library in accident severity evaluation, and adopts a quantitative calculation method to enable the research of the industrial safety evaluation method in China to enter a quantitative evaluation stage from qualitative evaluation.
The method for daily adoption of the enterprise comprises a safety check list method, an LEC method, a risk matrix method, an MES method, pre-risk analysis, fault type and influence analysis, risk and operability analysis, event tree analysis and accident tree analysis. The assessment method is simple to operate, mainly qualitatively or semi-quantitatively, and widely applied to safety management work of enterprises at home and abroad. When the evaluation of specific accident risks such as fire explosion, poisoning and the like is involved, a fire explosion index method of the United states channel (DOW) chemical company, a Mond evaluation method of a Mond factory of the British empire chemical company and an evaluation method of a flammable and explosive toxic major hazard source have obvious advantages. In addition, safety risk evaluation specially aiming at petrochemical enterprises also comprises a Japanese six-stage risk evaluation method and a Chinese risk degree grading method.
The academic community risk assessment is mainly based on quantitative evaluation and can be divided into probability evaluation, injury range evaluation and system comprehensive evaluation. With the introduction of fuzzy mathematics, grey system theory, Markov, Bayesian theory, machine learning, deep learning and complex system theory, the risk assessment model is also gradually diversified.
(1) The existing risk identification lacks a method for identifying major risks, the risk identification objects are not comprehensive enough, and the identification of external risk factors of the system is lacked;
(2) the existing risk evaluation index is single and fixed, the possibility and consequence indexes in the safety risk definition are considered, and the objective attribute of the dynamic change of the risk is ignored;
(3) in the existing risk assessment, a risk metric value of an evaluation object at a certain moment is taken as a stable risk level of the evaluation object, and an assessment result is not accurate enough;
(4) the existing risk evaluation model is a general and macroscopic evaluation model, and strict scientific demonstration is not shown according to the theory, the modeling principle and the index quantification method.
The key problem of ammonia refrigeration enterprises is the safety problem, and from a batch of ammonia refrigeration system refrigerators originally built in China to date, the ammonia refrigeration system refrigerators have been operated for more than sixty years. Most of the refrigeration house equipment is old, the pipeline is aged, and the valve gasket is aged, so that a plurality of accident potential hazards exist. Meanwhile, as the center of a refrigeration house of an ammonia-related refrigeration enterprise, an ammonia refrigeration system relates to a plurality of refrigeration devices, safety accessories and protection devices, and often forms a major hazard source, and once the ammonia refrigeration system fails or breaks down, major accidents are very easy to happen.
The rapid increase of the scale and the number of the ammonia refrigeration cold storage and the frequent occurrence of serious accidents of an ammonia refrigeration system put higher requirements on the safety production of ammonia-related refrigeration enterprises, and the management idea of preventing the serious accidents with the industry as the key point can not adapt to the actual safety production of the ammonia-related refrigeration enterprises. How to establish a set of risk identification and evaluation method with accuracy, systematicness and comprehensiveness aiming at prevention of serious accidents related to ammonia refrigeration enterprises is a problem to be solved urgently.
Disclosure of Invention
The invention aims to provide a method for identifying the major risk and evaluating the real-time dynamic risk of an ammonia-related refrigeration enterprise aiming at the defects in the prior art, and solves the problems of major safety risk identification, unit dynamic risk evaluation grading and enterprise risk aggregation in the safety risk grading management and control work of the ammonia-related refrigeration enterprise.
In order to realize the purpose of the invention, the technical scheme of the invention is as follows: a method for identifying and dynamically evaluating major risks and real-time risks of ammonia-related refrigeration enterprises comprises the following steps:
s1 data collection, the collected data comprising:
s1.1, relating to typical accident cases of ammonia refrigeration enterprises;
s1.2, analyzing typical accident modes of ammonia-related refrigeration enterprises;
s1.3, relating to typical production process principles, related material characteristics, equipment principles and monitoring facility requirements of ammonia refrigeration enterprises;
s1.4, an ammonia refrigeration enterprise safety standardization evaluation report is involved;
s1.5 related laws, standards and regulations of ammonia refrigeration enterprises;
s2 data analysis, based on the process principle and material characteristics, combined with several typical accident modes, to analyze possible accident causes, and to compare and expand the accident causes in the existing accident case; on the basis of accident reason analysis, material, equipment, facility, process, operation and place information related to typical accident occurrence of ammonia refrigeration enterprises are extracted, and risk factors related to accidents are induced;
s3 risk identification
S3.1, dividing risk units according to the ammonia-related refrigeration enterprise process system, and taking the serious accident of the induction unit as a risk point;
s3.2 intrinsic risk factor identification
S3.2.1 identifying intrinsic risk factors for risk points from high risk items, high risk equipment, high risk processes, high risk locations, high risk operations;
s3.2.2, compiling the inherent factor identification results of each risk point into unit inherent risk lists;
s3.3 management Risk factor identification
The management risk factor identification is to identify and acquire the security management level, namely the security standardization level, of a unit or an enterprise;
s3.4 dynamic risk factor identification
S3.4.1 identifying dynamic risk factors from key monitoring data, accident potential data, natural environment characteristics, Internet of things accident big data, special periods and the like;
s3.4.2, organizing and compiling the identification result of the dynamic risk factor into a dynamic risk list of the unit;
s4 Risk assessment grading
S4.1, establishing a risk evaluation index system of '5 +1+ X', specifically covering;
s4.1.1, the 'five-high' inherent risk index '5' of the risk point comprises an article inherent risk index, an equipment inherent risk index, a process inherent risk index, an operation inherent risk index and a place inherent risk index;
s4.1.2 Unit management and control index "1";
s4.1.3 risk dynamic index X including high risk monitoring index, accident hidden danger dynamic index, special period index, Internet of things accident big data index, natural environment index, etc.;
s4.2, quantifying risk evaluation indexes, wherein the quantification form comprises:
s4.2.1 the quantitative form of the inherent risk index of the equipment is the equipment risk index, and the index is measured according to the intrinsic safety level of the equipment; the quantitative form of the inherent risk index of the article is a material risk index which is measured by the characteristics of fire, explosion, toxicity, energy and the like and the quality; the inherent risk index of the process is characterized by the average level of the failure rate of the monitoring and controlling facilities in the unit; the measurement of the inherent risk index of the operation is determined by the number of high-risk operation types in the unit, including the types of dangerous operations, the operation of special equipment and the number of special operations; the quantitative form of the site inherent risk index is a site personnel exposure index, and the site inherent risk index is determined according to the number of exposed personnel in the site;
s4.2.2, quantifying risk management indexes into enterprise safety management levels, and measuring by the reciprocal of the unit safety production standardized score percentage;
s4.2.3, the quantitative form of the risk dynamic index is the disturbance degree of the dynamic risk index to the risk, the key monitoring index and the accident hidden danger dynamic index are dynamic correction to the risk value, and the special time index, the natural environment index, the Internet of things accident big data index and the like directly disturb the unit risk level;
s4.3 Risk assessment
S4.3.1 calculating the risk inherent to the risk point, the inherent risk of the unit, the initial risk of the unit and the real-time dynamic risk of the unit 5+1+ X on the basis of the risk evaluation index system 5+1+ X according to the measurement mathematical model;
s4.3.2 risk classification criteria;
according to an ALARP principle and a pareto rule, a risk comparability principle and a risk difference principle are provided;
s4.3.3 Risk level determination
Judging the risk level of the unit according to a risk classification criterion;
risk aggregation of S5
And on the basis of unit risk evaluation, coupling the real-time dynamic risk of the unit into the actual risk of the enterprise according to a risk aggregation rule.
According to the embodiment of the invention, the step S3.1 of dividing risk units according to the process comprises a refrigeration unit, a quick-freezing unit, a processing workshop unit and a storage tank area unit; the risk points determined in the risk unit in said step S3.1 include fire explosion accident risk points and toxic accident risk points.
According to the embodiment of the invention, the step S3.2 of identifying the inherent risk factors identifies high-risk articles, equipment, processes, operations and places;
the high-risk articles refer to flammable and explosive articles, dangerous chemicals and other articles which can cause serious accidents;
the high-risk process refers to a process which can cause serious accidents due to the out-of-control of the process;
high risk equipment refers to equipment facilities which can cause serious accidents in the process of running out of control, such as an ammonia refrigeration system;
the high risk place refers to a place which can cause serious accident consequences once an accident occurs, such as a serious hazard source and a labor-intensive place;
high risk operation refers to operation that may cause serious accidents by mistake, such as special operation, dangerous operation, special equipment operation, etc.
According to the embodiment of the invention, in the step S3.4, dynamic risk factor identification is carried out, and the high risk dynamic monitoring data including temperature, pressure, flow and the like are extracted from the existing monitoring system of the ammonia-related refrigeration enterprise;
the accident potential dynamic data is obtained from a potential troubleshooting system, and accident potential influencing the unit accident is selected; the natural environment dynamic factors are obtained from a meteorological system, and meteorological and geological disaster data which have influences on the unit accident are selected;
the Internet of things big data dynamic factor is extracted from a national security big data platform, and the same type of accident data related to the risk of the unit is selected;
the dynamic factors in the special period are obtained from a government affair network and a national calendar, and a national large conference, a national legal festival, a holiday, a major activity and the like are selected as dynamic data.
According to the embodiment of the invention, the "5 +1+ X" risk evaluation index system in step S4.1 includes characteristic indexes representing the severity of the risk of 5 types of inherent and relatively stable objects such as substances, equipment, processes, operations and places, safety management indexes representing the frequency, and 5 types of disturbance indexes including an internet of things monitoring index, an accident potential index, an accident big data index, a special period index and a natural environment index.
According to the embodiment of the present invention, the risk assessment model of step S4.3.1 includes a risk point risk assessment model, an element inherent risk assessment model, an element initial risk assessment model, and an element real-time dynamic risk assessment model;
wherein the risk assessment inherent to the risk point is a cumulative multiplication based on the inherent risk indicator of "five high", and the risk assessment mathematical model is as follows:
h＝hsMEK1K2
in the formula:
hs-high risk equipment risk index;
m-substance hazard index;
e-site personnel exposure index;
K1-monitoring the monitored failure rate correction factor;
K2-high risk job risk correction factor;
the unit intrinsic risk is a weighted average of the intrinsic risks of each risk point in the unit over the exposition person index, and the risk assessment mathematical model is as follows:
in the formula:
hi-the ith risk point in the cell has an inherent risk index;
Ei-the exposure index of personnel at the ith risk point site within the cell;
f, cumulative value of exposure index of personnel at each risk point and place in the unit;
n-number of risk points within a unit;
the unit initial risk is the cumulative multiplication of the unit inherent risk and the management and control index, and the risk assessment mathematical model is as follows:
R0＝100H/Ms
in the formula:
h-inherent risk of the unit;
MS-initial safe production normalized score;
the real-time dynamic risk of the unit is the correction of the initial risk of the unit under the disturbance of a dynamic index, and the risk assessment mathematical model is as follows:
RN-real-time dynamic risk of the unit;
R0-a unit initial high risk safety risk value;
MS-initial safe normalized score;
K3-a key monitoring index disturbance coefficient;
K4-accident potential dynamic indexA disturbance coefficient;
Mi-the ith risk point material risk index;
Ei-the ith risk point site personnel exposure index;
f is the cumulative value of the exposure indexes of personnel at each risk point and place in the unit.
According to the embodiment of the present invention, the risk classification rule of step S4.3.2, according to the comparability principle of the trial calculation result, makes the unit risk classification standard as follows:
according to the embodiment of the present invention, in step S5, risk aggregation, the unit risk to enterprise risk aggregation mathematical model is as follows:
in the formula:
r-enterprise realistic risk;
max(RNj) The maximum value of the real-time dynamic risk values of all the units of the enterprise;
ave(RNj) -average value of real-time dynamic risk values of the units of the enterprise.
According to the embodiment of the invention, the unit real-time dynamic risk classification standard is suitable for enterprise risk classification.
The invention has the technical effects that: (1) the method comprises the steps of identifying inherent risk factors, management and control factors and identifying dynamic risk factors based on five-high; (2) compiling and summarizing a unit high-risk list of ammonia-related refrigeration enterprises, providing basis and reference for later-stage risk evaluation, being beneficial to determining an analysis object, reducing the blindness of major safety risk control and realizing targeted perception; (3) establishing a '5 +1+ X' risk evaluation index system, and on the basis, providing a risk evaluation model based on a safety control theory, so that real-time dynamic evaluation of risks is realized, and the barrier of traditional risk static evaluation is broken through; (4) a risk aggregation method from a unit to an enterprise is provided, and uncertainty and roughness brought by traditional enterprise risk macroscopic evaluation are distinguished; (5) the risk identification method and the evaluation model are applied by combining related technical data related to ammonia refrigeration enterprise research, and are contrastively analyzed with the researched technical data and the field investigation result, so that the effectiveness of the risk identification method and the feasibility of the evaluation model are verified; (6) theoretical and technical guidance is provided for enterprise safety risk management and control work, the safety management level of ammonia-related refrigeration enterprises is improved, and serious accidents are prevented.
Drawings
FIG. 1 is a flow chart of a method for identifying security risks and evaluating real-time dynamic risks of ammonia-related refrigeration enterprises.
FIG. 2 is a quantitative graph of the risk assessment index "5 +1+ X".
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples.
Referring to fig. 1, the present invention provides a method for identifying a major risk and evaluating a real-time dynamic risk of an ammonia-related refrigeration enterprise, comprising the steps of:
s1 data collection, the collected data comprising:
s1.1, relating to typical accident cases of ammonia refrigeration enterprises;
s1.2, analyzing typical accident modes of ammonia-related refrigeration enterprises;
s1.3, relating to typical production process principles, related material characteristics, equipment principles and monitoring facility requirements of ammonia refrigeration enterprises;
s1.4, an ammonia refrigeration enterprise safety standardization evaluation report is involved;
s1.5 related laws, standards and regulations of ammonia refrigeration enterprises;
s2 data analysis, based on the process principle and material characteristics, combined with several typical accident modes, to analyze possible accident causes, and to compare and expand the accident causes in the existing accident case; on the basis of accident reason analysis, material, equipment, facility, process, operation and place information related to typical accident occurrence of ammonia refrigeration enterprises are extracted, and risk factors related to accidents are induced;
s3 risk identification
S3.1, dividing risk units according to the ammonia-related refrigeration enterprise process system, and taking the serious accident of the induction unit as a risk point;
s3.2 intrinsic risk factor identification
S3.2.1 identifying intrinsic risk factors for risk points from high risk items, high risk equipment, high risk processes, high risk locations, high risk operations;
s3.2.2, compiling the inherent factor identification results of each risk point into unit inherent risk lists;
s3.3 management Risk factor identification
The management risk factor identification is used for identifying and acquiring the security management level, namely the security standardization level, of a unit or an enterprise.
S3.4 dynamic risk factor identification
S3.4.1, identifying dynamic risk factors from key monitoring data, accident potential data, natural environment characteristics, Internet of things accident big data, special periods and the like.
S3.4.2 compile the dynamic risk factor recognition result into dynamic risk list of the unit.
S4 Risk assessment grading
S4.1, establishing a risk evaluation index system of '5 +1+ X', specifically covering;
s4.1.1, the 'five-high' inherent risk index '5' of the risk point comprises an article inherent risk index, an equipment inherent risk index, a process inherent risk index, an operation inherent risk index and a place inherent risk index;
s4.1.2 Unit management and control index "1";
s4.1.3 risk dynamic index X includes high risk monitoring index, accident hidden danger dynamic index, special period index, Internet of things accident big data index, natural environment index, etc.
S4.2, quantifying risk evaluation indexes, wherein the quantification form comprises:
s4.2.1 the quantitative form of the inherent risk index of the equipment is the equipment risk index, and the index is measured according to the intrinsic safety level of the equipment; the quantitative form of the inherent risk index of the article is a material risk index which is measured by the characteristics of fire, explosion, toxicity, energy and the like and the quality; the inherent risk index of the process is characterized by the average level of the failure rate of the monitoring and controlling facilities in the unit; the measurement of the inherent risk index of the operation is determined by the number of high-risk operation types in the unit, including the types of dangerous operations, the operation of special equipment and the number of special operations; the quantitative form of the site inherent risk index is a site personnel exposure index which is determined according to the number of exposed personnel of the site.
S4.2.2 Risk management indicators are quantified as enterprise safety management levels, measured as the inverse of the percentage of the standardized score for unit safety production.
S4.2.3 the quantitative form of the risk dynamic index is the disturbance degree of the dynamic risk index to the risk, the key monitoring index and the accident hidden danger dynamic index are dynamic amendments to the risk value, and the special time index, the natural environment index, the internet of things accident big data index and the like directly disturb the unit risk level.
S4.3 Risk assessment
S4.3.1 calculating the risk inherent to the risk point, the inherent risk of the unit, the initial risk of the unit and the real-time dynamic risk of the unit 5+1+ X on the basis of the risk evaluation index system 5+1+ X according to the measurement mathematical model;
s4.3.2 risk classification criteria. According to ALARP principle and pareto's rule, the risk classification rule is given with the principle of comparability and difference of risk.
S4.3.3 risk level determination. And judging the risk level of the unit according to the risk classification criterion.
S5 risk aggregation. And on the basis of unit risk evaluation, coupling the real-time dynamic risk of the unit into the actual risk of the enterprise according to a risk aggregation rule.
The invention relates to ammonia refrigeration enterprises which are mainly distributed in vegetable bases of various fruits, vegetables, meat products, poultry, aquatic products, cold drinks and dairy product main production areas, suburban areas of large and medium cities and important cold chain transportation ports.
As shown in fig. 1, different from the conventional risk identification and evaluation method, on the basis of the collection and analysis of the existing data, the invention provides a unit-to-risk point risk identification method, which establishes a risk evaluation model based on a "5 +1+ X" evaluation index system, and proposes the risk aggregation rule of the ammonia-related refrigeration enterprise to meet the requirements of the ammonia-related refrigeration enterprise on major risk identification and real-time dynamic risk evaluation classification.
Data collection and analysis. The accident reasons are refined and analyzed and risk factors related to the accidents are induced by means of on-site investigation, accident case collection, literature reference, standard comparison and the like.
The risk evaluation unit refers to the division experience of the safety production standardization unit, takes a relatively independent process system as an inherent risk identification evaluation unit, and generally divides the ammonia refrigeration enterprises into evaluation units by workshop division, which is shown in table 1.
The risk points are in the area of the unit, and the possibly induced serious accident of the unit is taken as the risk point, see table 1.
TABLE 1 division of units and Risk Point selection for Ammonia refrigeration enterprises
Example (b): and (3) carrying out risk identification, index quantitative value taking and real-time dynamic risk assessment grading method application and explanation by taking the refrigeration unit as an implementation example.
The refrigeration unit has many fire explosion and toxic accidents, and the two accidents are taken as typical accident risk points of the unit.
Because two types of accident risk points belong to the same set of production device, when only carrying out high risk place, personnel exposure index has the difference, and the inherent risk identification difference of other involved categories is not big.
The amount of stored ammonia in the refrigeration unit production device is an energy source of an accident and belongs to a high risk item;
the refrigerating unit is provided with a whole set of refrigerating system which comprises equipment facilities such as a compressor, a condenser, an evaporator, a storage tank, a pipeline and the like, and the production process has pressure cyclic variation and belongs to high-risk equipment;
the integrity of process monitoring devices (such as a pressure gauge, a liquid level meter, an ammonia concentration detector and the like) of the refrigeration unit reflects the reliability of the enterprise on the control of key indexes, and the process is a high-risk process;
the ammonia-related unit comprises refrigeration and air-conditioning operation, patrol maintenance of a pressure pipeline, operation of a fixed pressure container and the like, and the operation compliance influences the probability and the severity of accidents, so that the ammonia-related unit is used as high-risk operation;
the degree of exposure of personnel in a factory area and the vicinity thereof determines casualty consequences possibly caused by accidents, and belongs to a high-risk place;
after the inherent risk factors of five high are identified, the inherent risk factor identification results of all risk points are compiled into a unit inherent risk list and are updated in time according to regulations.
The refrigeration unit fire explosion accident risk points are inherently provided with a risk list shown in table 2.
The identification of the management and control risk factors of the refrigeration units is to identify and acquire the safety management level of the units, and generally takes the safety standardized scores of the whole ammonia-related refrigeration enterprises as data sources.
The basic standard of standardization for enterprise safety production (GB/T33000-.
And identifying dynamic risk factors from key monitoring data, accident potential data, natural environment characteristics, Internet of things accident big data, special periods and the like.
Extracting high-risk dynamic monitoring data from the existing monitoring system of an ammonia-related refrigeration enterprise, wherein the high-risk dynamic monitoring data comprises temperature, pressure, flow and the like; acquiring accident potential dynamic data from a potential troubleshooting system, and selecting general accident potential and major accident potential which have influence on the unit accident;
acquiring a natural environment dynamic factor from a meteorological system, and selecting meteorological and geological disaster data which influence the unit accident;
extracting the big data dynamic factor of the Internet of things from a national security big data platform, and selecting the same type of accident data related to the risk of the unit;
the dynamic factors in the special period are obtained from a government affair network and a national calendar, and a national large conference, a national legal festival, a holiday, a major activity and the like are selected as dynamic data.
After the refrigeration unit dynamic risk is identified, a dynamic risk list of the unit is compiled and updated in time according to the regulations. The refrigeration unit dynamic risk list is shown in table 3 and table 4.
Table 3 refrigeration unit dynamic risk list.
Table 4 refrigeration unit dynamic risk list.
And constructing an inherent risk index system and analyzing index elements and characteristic values according to the inherent risk factors of the high-risk articles, the high-risk process, the high-risk equipment, the high-risk places and the high-risk operation.
And constructing unit risk management and control indexes, wherein the unit high-risk management and control frequency indexes are represented according to the current situation of enterprise safety management.
And constructing a unit dynamic risk index system according to the unit dynamic risk factors, and analyzing the index elements and the characteristic values.
The measurement of the inherent risk index mainly comprises measurement of high-risk articles, high-risk equipment, high-risk processes, high-risk operations and high-risk places.
The metering method of high-risk equipment is characterized by the intrinsic safety level of the equipment.
The method is mainly considered from qualification conditions, use conditions, safety accessory allocation conditions of a pressure relief pipe, a check valve and the like of main refrigeration equipment such as an ammonia compressor, a circulating barrel and the like, installation and use conditions of main protection devices such as an ammonia concentration alarm device and the like and objective production environment layout conditions, and the implementation condition of each technical measure corresponds to different fault types and represents different safety levels.
TABLE 5 Risk points Equipment intrinsic hazard index dereferencing Standard
In the embodiment, the intrinsic risk index hs of the equipment at the fire explosion accident risk point and the toxic accident risk point is 1.2.
The method of metering high-risk items is characterized by the risk factor M of the substance.
And determining the M value by using the M value of the product of the ratio of the actual existing quantity of the high-risk articles to the critical quantity and the danger characteristic correction coefficient of the corresponding articles as a grading index according to the grading result.
According to the identification of major hazard sources of hazardous chemicals (GB18218-2018), the critical amount Q of ammonia is 10 t; the correction coefficient β is 2. The classification result R of the fire explosion accident risk point and the toxic accident risk point of the refrigerating unit is calculated as follows.
m＝q/5
In the formula, q represents the actual amount of ammonia present in the refrigeration system, t
And determining the grade of the high-risk articles with high risk points according to the calculated M value and a table 6, and determining a corresponding material index M.
TABLE 6 correspondence between high-risk point high-risk item classes and material risk factors M
In the examples, the actual amount of stored ammonia was 25t, and M was calculated to be 5 and M to be 3.
The metering method of the high-risk process is to monitor the correction coefficient K of the failure rate of the monitoring facility1Characterized by the following metering method:
K1＝1+l
in the formula, l: monitoring the average value of failure rate of the monitoring facility.
The high risk process of a refrigeration unit is gauged by the average level of failure rates of monitoring facilities such as pressure gauges, thermometers, flow meters, ammonia concentration detectors, level meters, etc. on the refrigeration compressor, refrigeration equipment and piping.
In the embodiment, the average value of the failure rates of the process monitoring and controlling facilities at the risk points is 0.02, and then the failure rate correction coefficient K of the process monitoring and controlling facilities is obtained1＝1.02。
The measurement of the inherent risk index of the high-risk operation is quantitatively represented by a high-risk operation risk correction coefficient, and the high-risk operation risk correction coefficient K is converted into a high-risk operation risk correction coefficient by measuring the number of the types of the high-risk operation2，K2The metering method comprises the following steps:
K2＝1+0.05t
in the formula, t: the risk points relate to the number of high-risk operation categories
The fire explosion accident risk point and the toxic risk point of the refrigeration unit relate to defrosting operation, routine equipment inspection and maintenance operation, pressure pipeline inspection and maintenance D1, fixed pressure container operation R1, safety accessory maintenance operation, refrigeration and air conditioning operation and the like.
In the embodiment, if there are 6 high-risk jobs at the risk point, the correction coefficient K of the high-risk job2＝1.3。
The personnel exposure index for high risk locations is determined primarily by the number of exposed personnel at the risk point, according to table 7.
The number of exposed personnel at the fire and explosion accident risk points involving the ammonia refrigeration unit includes the personnel operating the entire cold storage area; the exposure personnel of the toxic accident risk point comprise the operators in the reservoir area and the personnel within the range of 1km around the reservoir area.
Table 7 correspondence between exposure number and site personnel exposure index.
The unit security risk management and control indexes refer to the representation of the enterprise security management level, and are measured by the reciprocal of the security standardization score, and the metering formula is as follows:
G＝100/Ms
in the formula: g-final unit high risk management and control index value;
Ms-an initial safe production normalized score.
In the embodiment, the safety standardization level is two grades, the score Ms is 85 scores, and G is 1.176.
The quantification of the key monitoring index is dynamic correction of the unit risk value, and the pre-alarm condition of the key monitoring index is quantified into a disturbance coefficient K of the key monitoring index3And is used to correct the initial risk value of the unit.
The on-line monitoring index real-time alarm condition is divided into a first-level alarm (low alarm), a second-level alarm (middle alarm) and a third-level alarm (high alarm).
Through calculation and calculation, the disturbance coefficient K is calculated when the alarm is not given31, disturbance coefficient K in first-level alarm31.2, two-stage alarm disturbance coefficient K31.5, three-level alarm disturbance coefficient K3＝2.5。
The high-risk monitoring characteristic index of the refrigeration unit takes the highest early warning condition of dynamic safety production on-line monitoring indexes such as pressure, liquid level, flow, concentration and the like of the refrigeration unit as a dynamic correction index;
in the embodiment, the highest alarm level of the key monitoring indexes of the refrigeration unit is first-level alarm, and the disturbance coefficient K is3＝ 1.2
The quantification of the accident hidden danger dynamic index is dynamic correction of a unit risk value, and mainly comprises disturbance of two sub-elements of an accident hidden danger level and an accident hidden danger rectification rate on the risk value, and the disturbance is converted into an accident hidden danger dynamic index correction coefficient K4；
Accident potential grade (I)1) The accident potential is divided into general hidden dangers and major hidden dangers, and the corresponding scores of the accident potential of different grades are shown in a table 8.
Table 8 different levels of accident potential correspond to scores.
Accident potential grade I1The metering method comprises the following steps:
I1＝B1b1+B2b2
in the formula:
I1calculation of the potential hazard level
B1-corresponding number of major hidden troubles
B2-number of corresponding general hidden troubles
b1-major hidden danger corresponding score
b2The general hidden danger corresponds to the score.
In the embodiment, 1 major hidden danger exists in the refrigeration unit, the number of the common hidden dangers is 4, and I is calculated1＝2.2。
Accident potential correction rate value I2And is related to the level and the rectification degree of the accident potential.
Table 9 corresponding scores for different hidden danger rectification rates.
Accident potential correction rate value I2The metering method comprises the following steps:
in the formula:
I2calculation result of hidden danger rectification rate
In the embodiment, 1 major hidden danger of the refrigeration unit and all major hidden dangers are rectified and improved, the number of the common hidden dangers is 4, the rectification rate is 80 percent, and I is calculated2＝0.24。
The risk correction of the accident hidden danger dynamic index mainly comprises the correction of risk values by two types of factors, namely accident hidden danger grade and accident hidden danger rectification rate, and the proportion and the weight of different factors are shown in a table 10.
Table 10 shows the weight scores corresponding to different dynamic indicators of accident risks.
And establishing a mathematical model through the index quantization value and the index weight thereof. Dynamic correction coefficient K for accident hidden trouble4The metering formula is as follows:
K4＝I1W1+I2W2
K4-accident potential dynamic correction coefficients;
Wn-each index corresponds to a weight, n ═ 1, 2
In the embodiment, the accident potential grade score I12.2, accident potential modification rate score value I2If 0.24, the accident potential dynamic correction times K4＝2.2*0.4+0.6*0.24＝1.024。
And (4) carrying out upgrading correction on the unit risk level by using the natural environment dynamic indexes, and upgrading two grades at most.
And (4) carrying out upgrading correction on the unit risk level by using the Internet of things accident big data index, and upgrading the unit risk level to the highest level.
And (4) carrying out upgrading correction on the unit risk level by the dynamic indexes in the special period, and upgrading the unit risk level to the highest level.
The risk assessment inherent to the risk point is a cumulative multiplication based on the "five high" inherent risk indicator, and the risk assessment mathematical model is as follows:
h＝hsMEK1K2
in the formula:
hs-high risk equipment risk index;
m-substance hazard index;
e-site personnel exposure index;
K1-monitoring the monitored failure rate correction factor;
K2-high risk job risk correction factor.
In an embodiment, it is calculated that:
risk inherent to fire accident risk point h1＝hsMEK1K2＝1.2*3*5*1.02*1.3＝23.868；
Risk inherent to a toxic accident risk point h2＝hsMEK1K2＝1.2*3*9*1.02*1.3＝42.962。
The unit intrinsic risk is a weighted average of the intrinsic risks of each risk point in the unit over the exposition person index, and the risk assessment mathematical model is as follows:
in the formula:
hi-the ith risk point in the cell has an inherent risk index;
Ei-the exposure index of personnel at the ith risk point site within the cell;
f, cumulative value of exposure index of personnel at each risk point and place in the unit;
n-number of risk points within a unit.
In the embodiment, the refrigerating unit comprises two risk points of fire explosion and poisoning, the inherent risk of the unit is calculated according to the weighted average of the number of exposed persons,
the initial risk of the unit is the cumulative multiplication of the inherent risk of the unit and the control index, and the mathematical model is as follows:
R0＝100H/Ms
in the formula:
h-inherent risk of the unit;
ms — initial safe production normalized score.
In the example, Ms is 85 minutes, unit intrinsic risk H is 36.143, and refrigeration unit initial risk value R0 is 42.521.
The real-time dynamic risk of the unit is the correction of the initial risk of the unit under the disturbance of a dynamic index, and the risk assessment mathematical model is as follows: rN＝R0×K3×K4
In the formula:
RN-real-time dynamic risk of the unit;
R0-a unit initial high risk safety risk value;
K3-a key monitoring index disturbance coefficient;
K4the disturbance coefficient of the accident potential dynamic index.
In the examples, K3＝1.2，K41.024, then madeCold unit realistic risk RN＝R0×K3×K4＝ 52.25。
TABLE 11 Unit real-time dynamic Risk Classification
And according to the risk classification standard, the risk grade of the refrigeration unit is a secondary risk, and orange early warning is performed.
In comparison with other methods, the evaluation results under the evaluation index of "5 +1+ X" were compared with other methods.
According to a major hazard source grading method in 'identification of major hazard source of hazardous chemicals' (GB18218-2018), the ratio of the actual existing amount of various hazardous chemicals in a refrigeration unit to the specified critical amount of the hazardous chemicals is adopted, and the sum of the ratios corrected by a correction coefficient is used as a grading index.
In the examples, the ammonia storage amount is 25t
The refrigeration unit in the embodiment belongs to three-level major hazard sources according to the major hazard source classification standard.
In the invention, the refrigerating unit actual (dynamic risk) risk value calculated by adopting the '5 +1+ N' risk assessment method is 52.228, and belongs to secondary risk.
The unit intrinsic risk value without considering the dynamic data influence is 36.143, which belongs to three levels of risk under the existing risk classification standard, and the classification result is relatively consistent with that of the major hazard source.
In the invention, because the real-time dynamic risk of the unit considers the influence of dynamic data, the risk level is increased reasonably.
Risk aggregation. The unit risk to enterprise risk aggregation model is as follows:
in the formula:
r-enterprise realistic risk;
max(RNj) The maximum value of the real-time dynamic risk values of all the units of the enterprise;
ave(RNj) -average value of real-time dynamic risk values of the units of the enterprise.
The present invention is not limited to the above-described embodiments, and it will be apparent to those skilled in the art that various modifications and improvements can be made without departing from the principle of the present invention, and such modifications and improvements are also considered to be within the scope of the present invention. Details not described in this specification are within the skill of the art that are well known to those skilled in the art.
Claims (9)
1. A method for identifying and dynamically evaluating major risks of ammonia-related refrigeration enterprises in real time is characterized by comprising the following steps:
s1 data collection, the collected data comprising:
s1.1, relating to typical accident cases of ammonia refrigeration enterprises;
s1.2, analyzing typical accident modes of ammonia-related refrigeration enterprises;
s1.3, relating to typical production process principles, related material characteristics, equipment principles and monitoring facility requirements of ammonia refrigeration enterprises;
s1.4, an ammonia refrigeration enterprise safety standardization evaluation report is involved;
s1.5 related laws, standards and regulations of ammonia refrigeration enterprises;
s2 data analysis, based on the process principle and material characteristics, combined with several typical accident modes, to analyze possible accident causes, and to compare and expand the accident causes in the existing accident case; on the basis of accident reason analysis, material, equipment, facility, process, operation and place information related to typical accident occurrence of ammonia refrigeration enterprises are extracted, and risk factors related to accidents are induced;
s3 risk identification
S3.1, dividing risk units according to the ammonia-related refrigeration enterprise process system, and taking the serious accident of the induction unit as a risk point;
s3.2 intrinsic risk factor identification
S3.2.1 identifying intrinsic risk factors for risk points from high risk items, high risk equipment, high risk processes, high risk locations, high risk operations;
s3.2.2, compiling the inherent factor identification results of each risk point into unit inherent risk lists;
s3.3 management Risk factor identification
The management risk factor identification is to identify and acquire the security management level, namely the security standardization level, of a unit or an enterprise;
s3.4 dynamic risk factor identification
S3.4.1 identifying dynamic risk factors from key monitoring data, accident potential data, natural environment characteristics, Internet of things accident big data, special periods and the like;
s3.4.2, organizing and compiling the identification result of the dynamic risk factor into a dynamic risk list of the unit;
s4 Risk assessment grading
S4.1, establishing a risk evaluation index system of '5 +1+ X', specifically covering;
s4.1.1, the 'five-high' inherent risk index '5' of the risk point comprises an article inherent risk index, an equipment inherent risk index, a process inherent risk index, an operation inherent risk index and a place inherent risk index;
s4.1.2 Unit management and control index "1";
s4.1.3 risk dynamic index X including high risk monitoring index, accident hidden danger dynamic index, special period index, Internet of things accident big data index, natural environment index, etc.;
s4.2, quantifying risk evaluation indexes, wherein the quantification form comprises:
s4.2.1 the quantitative form of the inherent risk index of the equipment is the equipment risk index, and the index is measured according to the intrinsic safety level of the equipment; the quantitative form of the inherent risk index of the article is a material risk index which is measured by the characteristics of fire, explosion, toxicity, energy and the like and the quality; the inherent risk index of the process is characterized by the average level of the failure rate of the monitoring and controlling facilities in the unit; the measurement of the inherent risk index of the operation is determined by the number of high-risk operation types in the unit, including the types of dangerous operations, the operation of special equipment and the number of special operations; the quantitative form of the site inherent risk index is a site personnel exposure index, and the site inherent risk index is determined according to the number of exposed personnel in the site;
s4.2.2, quantifying risk management indexes into enterprise safety management levels, and measuring by the reciprocal of the unit safety production standardized score percentage;
s4.2.3, the quantitative form of the risk dynamic index is the disturbance degree of the dynamic risk index to the risk, the key monitoring index and the accident hidden danger dynamic index are dynamic correction to the risk value, and the special time index, the natural environment index, the Internet of things accident big data index and the like directly disturb the unit risk level;
s4.3 Risk assessment
S4.3.1 calculating the risk inherent to the risk point, the inherent risk of the unit, the initial risk of the unit and the real-time dynamic risk of the unit 5+1+ X on the basis of the risk evaluation index system 5+1+ X according to the measurement mathematical model;
s4.3.2 risk classification criteria;
according to an ALARP principle and a pareto rule, a risk comparability principle and a risk difference principle are provided;
s4.3.3 Risk level determination
Judging the risk level of the unit according to a risk classification criterion;
risk aggregation of S5
And on the basis of unit risk evaluation, coupling the real-time dynamic risk of the unit into the actual risk of the enterprise according to a risk aggregation rule.
2. The method for identifying the major risk and evaluating the real-time dynamic risk of the ammonia-related refrigeration enterprise according to claim 1, wherein the step S3.1 of dividing risk units according to the process comprises a refrigeration unit, a quick-freezing unit, a processing workshop unit and a storage tank area unit; the risk points determined in the risk unit in said step S3.1 include fire explosion accident risk points and toxic accident risk points.
3. The method for identifying the major risk and evaluating the real-time dynamic risk of the ammonia-related refrigeration enterprise according to claim 1, wherein the step S3.2 of identifying the inherent risk factor identifies high-risk articles, equipment, processes, operations and places;
the high-risk articles refer to flammable and explosive articles, dangerous chemicals and other articles which can cause serious accidents;
the high-risk process refers to a process which can cause serious accidents due to the out-of-control of the process;
high risk equipment refers to equipment facilities which can cause serious accidents in the process of running out of control, such as an ammonia refrigeration system;
the high risk place refers to a place which can cause serious accident consequences once an accident occurs, such as a serious hazard source and a labor-intensive place;
high risk operation refers to operation that may cause serious accidents by mistake, such as special operation, dangerous operation, special equipment operation, etc.
4. The method for identifying the major risk and evaluating the real-time dynamic risk of the ammonia-related refrigeration enterprise according to claim 1, wherein in the step S3.4, the dynamic risk factor is identified, and the high-risk dynamic monitoring data is extracted from the existing monitoring system of the ammonia-related refrigeration enterprise, and comprises temperature, pressure, flow and the like;
the accident potential dynamic data is obtained from a potential troubleshooting system, and accident potential influencing the unit accident is selected; the natural environment dynamic factors are obtained from a meteorological system, and meteorological and geological disaster data which have influences on the unit accident are selected;
the Internet of things big data dynamic factor is extracted from a national security big data platform, and the same type of accident data related to the risk of the unit is selected;
the dynamic factors in the special period are obtained from a government affair network and a national calendar, and a national large conference, a national legal festival, a holiday, a major activity and the like are selected as dynamic data.
5. The method for identifying the major risk and evaluating the real-time dynamic risk of the ammonia-related refrigeration enterprise according to claim 1, wherein the risk evaluation index system of "5 +1+ X" in the step S4.1 includes a characteristic index for characterizing the severity of the risk of 5 types of intrinsic and relatively stable objects in a substance, equipment, a process, an operation and a place, a safety management index for characterizing the frequency, and 5 types of disturbance indexes including an internet of things monitoring index, an accident potential risk index, an accident big data index, a special period index and a natural environment index.
6. The method according to claim 1, wherein the risk assessment models of step S4.3.1 include a risk point risk assessment model, a unit intrinsic risk assessment model, a unit initial risk assessment model, and a unit real-time dynamic risk assessment model;
wherein the risk assessment inherent to the risk point is a cumulative multiplication based on the inherent risk indicator of "five high", and the risk assessment mathematical model is as follows:
h＝hsMEK1K2
in the formula:
hs-high risk equipment risk index;
m-substance hazard index;
e-site personnel exposure index;
K1-monitoring the monitored failure rate correction factor;
K2-high risk job risk correction factor;
the unit intrinsic risk is a weighted average of the intrinsic risks of each risk point in the unit over the exposition person index, and the risk assessment mathematical model is as follows:
in the formula:
hi-the ith risk point in the cell has an inherent risk index;
Ei-the exposure index of personnel at the ith risk point site within the cell;
f, cumulative value of exposure index of personnel at each risk point and place in the unit;
n-number of risk points within a unit;
the unit initial risk is the cumulative multiplication of the unit inherent risk and the management and control index, and the risk assessment mathematical model is as follows:
R0＝100H/Ms
in the formula:
h-inherent risk of the unit;
ms — initial safe production normalized score;
the real-time dynamic risk of the unit is the correction of the initial risk of the unit under the disturbance of a dynamic index, and the risk assessment mathematical model is as follows:
RN-real-time dynamic risk of the unit;
R0-a unit initial high risk safety risk value;
MS-an initial safe normalized score;
K3-a key monitoring index disturbance coefficient;
K4-accident potential dynamic index disturbance coefficient;
Mi-the ith risk point material risk index;
Ei-the ith risk point site personnel exposure index;
f is the cumulative value of the exposure indexes of personnel at each risk point and place in the unit.
7. The method according to claim 1, wherein the step S4.3.2 of risk classification rule, according to the comparability rule of trial calculation results, defines unit risk classification criteria as:
8. the method for identifying the significant risk and dynamically evaluating the risk of the ammonia-related refrigeration enterprise in real time according to claim 1, wherein the risk is aggregated in step S5, and the mathematical model for aggregating the unit risk into the enterprise risk is as follows:
in the formula:
r-enterprise realistic risk;
max(RNj) The maximum value of the real-time dynamic risk values of all the units of the enterprise;
ave(RNj) -average value of real-time dynamic risk values of the units of the enterprise.
9. The method for identifying the significant risk and evaluating the real-time dynamic risk of the ammonia-related refrigeration enterprise according to claim 7, wherein the unit real-time dynamic risk classification standard is applicable to enterprise risk classification.
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