CN113610338A - Rail transit signal system safety risk evaluation and risk early warning method and device - Google Patents
Rail transit signal system safety risk evaluation and risk early warning method and device Download PDFInfo
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Abstract
The invention relates to a rail transit signal system safety risk evaluation and risk early warning method and a device, wherein the method comprises the following steps: step S1: identifying the constituent elements of a safety risk early warning system; step S2: determining a dynamic monitoring factor set; step S3: real-time dynamic monitoring; step S4: constructing a risk quantitative evaluation model; step S5: multi-dimensional dynamic risk early warning is realized; step S6: and (5) carrying out link hidden trouble investigation and treatment. Compared with the prior art, the method has the advantages of ensuring the safety of the on-orbit running signal equipment and the like.
Description
Technical Field
The invention relates to a train signal control system, in particular to a method and a device for safety risk evaluation and risk early warning of a rail transit signal system.
Background
The signal system is an important means for ensuring the safe operation of rail transit, and serious driving accidents can be caused by the failure of the dangerous side of the signal system, so that huge life and property losses are caused. Therefore, according to requirements of EN50126 and EN50129 standards, rail transit signal systems must avoid systematic failures by means of quality management, safety management and technical measures, and prove that the dangerous failure rate is reduced to an acceptable level by means of technical measures and quantitative evaluation, so as to ensure that the safety of the system reaches the expected safety integrity level requirement.
However, even though the safety system is proved, occasional safety faults still occur after the system is operated on line, and some safety accidents even are caused, which brings great negative effects to the society and greatly reduces the confidence of users and the public to rail transit. Therefore, a more active and prospective risk management method is adopted for the rail transit signal system, the risk state of the system is dynamically evaluated, the possible hazard events/accidents of the system are predicted in advance, and management and control measures are taken in time to avoid risks.
From the beginning of this century, by taking the experience in the fields of chemical engineering and aerospace into account, the rail transit signal industry of China begins to explore and establish an early warning system suitable for the characteristics of the industry. However, due to the limitations of management boundaries and data bases, most of the existing early warning systems start with post-event monitoring data or fault data, and do not identify and cover the risk source of the rail transit signal system in the whole process and all around, so that the risk evaluation and risk early warning have certain limitations.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a method and a device for evaluating the safety risk and early warning the risk of a rail transit signal system.
The purpose of the invention can be realized by the following technical scheme:
according to a first aspect of the invention, a rail transit signal system safety risk evaluation and risk early warning method is provided, which comprises the following steps:
step S1: identifying the constituent elements of a safety risk early warning system;
step S2: determining a dynamic monitoring factor set;
step S3: real-time dynamic monitoring;
step S4: constructing a risk quantitative evaluation model;
step S5: multi-dimensional dynamic risk early warning is realized;
step S6: and (5) carrying out link hidden trouble investigation and treatment.
Preferably, the components in step S1 include human factors, equipment factors, environmental factors, and administrative factors.
As a preferred technical solution, the factor set in step S2 includes a post-monitoring factor set and a pre-monitoring factor set, where the post-monitoring factor set includes an explicit event or accident occurring on site, a site potential safety hazard and its corrective measure, an execution situation of a preventive measure, a site device alarm situation, and a timely handling situation; the prior monitoring factor set comprises process performance conditions of research and development, production, test, installation and debugging processes, unsafe problem conditions discovered by test, and risk conditions of safety-related left-over opening items.
As a preferred technical solution, the specific implementation process of step S3 is as follows:
establishing a safety management informatization system to realize the online development of hazard analysis, safety verification, safety audit and safety evaluation activities;
and constructing a data interface of a demand management system Polarion, a hazard management system CentraLog and a change management system ClearQuest, calling relevant hazard information, safety non-conformity item information and hazard information at any time, and realizing online dynamic monitoring of safety relevant data.
As a preferred technical solution, the specific implementation process of step S4 is as follows:
step S41, a model formula is constructed as follows:
d ═ D person + D environment + D management + D device ≈ α D device + β D device + γ D device + D device ═ (1+ θ) D device;
wherein D is the calculated risk value, D is the risk caused by human factors, D is the risk caused by environmental factors, D is the risk caused by administrative factors, D is the risk caused by equipment factors, and D is the risk caused by equipment factors, wherein alpha is the ratio of human factors to equipment factors, and beta is the ratio of environmental factors to equipment factors; γ is the ratio of factors of management to equipment factors; θ is the ratio of other factors than equipment to equipment factors;
step S42, the D device is calculated as follows:
d device ═ Σ DaijWherein a isijFor all dynamic monitoring factors, i represents the type of the monitoring factor and j represents the number of the monitoring event.
As a preferred technical solution, the specific implementation process of step S5 is as follows:
step S51: comparing the risk value D calculated in the step 4 with a risk threshold value, and carrying out risk early warning;
step S52: before the signal system is put into use, the signal system must be ensured to be in a low risk state, otherwise, the signal system must not be put into use; with long-time field operation, if a hidden safety problem or an unsafe event possibly occurs, dynamically updating the risk value and carrying out corresponding early warning;
step S53: the method comprises the steps of setting three lines according to the point mean value and the standard variance of the previous monitoring period, wherein the three lines are the sum of the mean value and 1 time, and the sum of the standard variance deviation of 2 times and 3 times; in the monitoring period, any one of the following situations occurs, and then an alarm is displayed:
if any 1 point is higher than 3 times of the standard deviation value, carrying out major risk early warning;
2 times of standard deviation value appears at 2 continuous points, and large risk early warning is carried out;
and (5) carrying out general risk early warning when the continuous 3-point initial selection is higher than 1 time of standard deviation value.
According to a second aspect of the invention, a rail transit signal system safety risk evaluation and risk early warning device is provided, which comprises:
the component element module is used for identifying the component elements of the safety risk early warning system;
the factor set determining module is used for determining a dynamic monitoring factor set;
the dynamic monitoring module is used for real-time dynamic monitoring;
the model construction module is used for constructing a risk quantitative evaluation model;
the risk early warning module is used for realizing multi-dimensional dynamic risk early warning;
and the hidden danger troubleshooting module is used for carrying out linkage hidden danger troubleshooting and treatment.
According to a third aspect of the invention, there is provided an electronic device comprising a memory having stored thereon a computer program and a processor implementing the method when executing the program.
According to a fourth aspect of the invention, a computer-readable storage medium is provided, on which a computer program is stored which, when being executed by a processor, carries out the method.
Compared with the prior art, the invention has the following advantages:
1) the invention monitors a series of processes from research and development, testing, installation and debugging to on-line operation and maintenance by establishing and implementing a whole-process and omnibearing safety management information system, and realizes quantitative evaluation of system safety risks from the back to the front, from theory to concrete, and from local to the whole, thereby integrally measuring the safety level of a rail transit signal system;
2) according to the invention, through the development direction of the monitoring and fitting state of affairs of data, with the help of the risk early warning module, the serious danger condition which possibly occurs is reported, and the risk avoiding measure can be implemented in advance, so that the safety of the on-orbit operation signal equipment is further ensured;
3) the invention collects all process data from research and development to production, then to installation and debugging processes, and brings the data into a risk assessment model, so that the risk early warning is early warned in advance from a later report;
4) the invention constructs a method for evaluating the working quality of a person through process data so as to reflect the equipment risk, and opens up a new visual angle of human factor evaluation;
5) the invention also considers the influence of the management level factors on the equipment safety, so that the risk evaluation is more real and standard.
Drawings
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a schematic diagram of the structure of the apparatus of the present invention;
FIG. 3 is a schematic diagram of a hazard causing factor of a rail transit signal system;
FIG. 4 is a schematic diagram of a dynamic monitoring factor set;
FIG. 5 is a schematic diagram of risk trend prediction in an embodiment.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, shall fall within the scope of protection of the present invention.
As shown in fig. 1, the method of the present invention comprises the following steps:
step S101: and identifying the structural elements of the safety risk early warning system. Referring to the classification and codes of risks and harmful factors in the GB/T13861-2009 production process, the risk factors of the rail transit signal system are divided into: four major categories of human, device, environmental and administrative. As shown in fig. 1, wherein secondary causative factors are by way of example only. Human factors, environmental factors and management factors are all management categories of signal system users and can be brought into the operation risk of the whole rail transit signal system; however, the present document focuses on the risk evaluation that is common to the management systems of rail transit signal system suppliers, so that only human, environmental and management ease of implementation is considered as a factor in the present model, and the factor is considered in the risk evaluation model (see step 4 for details).
Step S102: a set of dynamic monitoring factors is determined. In order to comprehensively evaluate the risk of the equipment, data collection and monitoring are respectively carried out from the aspects of post and early, wherein the post monitoring comprises the execution conditions of dominant events/accidents occurring on site, site potential safety hazards, corrective measures and preventive measures thereof, the alarm condition of the site equipment and the timely handling condition; the prior monitoring includes process performance of research and development, production, test, installation and debugging processes, unsafe problem conditions found by the test, risk conditions of safety-related opening items, and the like, which are shown in fig. 2 in detail.
Step S103: and (5) real-time dynamic monitoring. Establishing a safety management informatization system to realize the online development of hazard analysis, safety verification, safety audit, safety evaluation activities and the like; and the system can realize data interfaces with a demand management system Polarion, a hazard management system CentraLog and a change management system ClearQuest, and can call related hazard information, safety non-conforming item information, hazard information and the like at any time to realize online dynamic monitoring of safety related data.
Step S104: and constructing a risk quantitative evaluation model. Hainrichi's Law states that: behind each serious accident there must be 29 minor accidents and 300 signs of failure and 1000 accidents. The principle of wrong iceberg reveals: dominant errors are much fewer than recessive errors. According to Hainrichi's rule and error iceberg principle, and combining with the safety production risk evaluation (D ═ L ×. E ×. C) method, inviting experts to score experience, setting severity and exposure index parameters for each monitoring factor, and combining with dynamic monitoring data, calculating to obtain the overall risk value of the signal system. The specific steps are as follows:
step S41: the security accident risk is composed of human factors, equipment factors, environmental factors and administrative factors as shown in fig. 1; the human factor, the environmental factor and the management factor are the management category of the signal system user, and are determined by the environment, the human operation and the management level after the system is delivered to operate. Therefore, as a supplier of the signal system, the risk parameter is estimated by considering the difficulty degree of the requirements of people, environment and management from the viewpoint of the output limit of the signal system, and the calculation formula is as follows:
d ═ D person + D environment + D management + D device ≈ α D device + β D device + γ D device + D device ═ 1+ θ) D device, where D is a calculated risk value, D person is a risk due to a human factor, D environment is a risk due to a factor of environment, D management is a risk due to a factor of management, D device is a risk due to a factor of device,
step S42: the risk of the device comes from the dynamic monitoring of the set of critical factors of the device. Parameters of frequency of occurrence, exposure index and severity were established for each accident/event according to the safety production risk assessment (D ═ L × E × C) method. Wherein the number of monitored factors is used as the frequency of risk; determining a severity index for each type of monitoring factor by referring to Haienlixi's Law, and ' Classification and code of dangerous and harmful factors in production Process ' (GB/T13861-2009) and TEM management framework; an exposure index is determined for each monitored event based on the path of the fault propagation.
The D device is calculated as follows:
d device ═ Σ DaijWherein a isijFor all dynamic monitoring factors, i represents the type of the monitoring factor and j represents the number of the monitoring event.
Step S105: and multi-dimensional dynamic risk early warning is realized. The system can perform overall risk early warning of a signal system, and can also perform multi-angle early warning of the operation risk of field equipment, the technical risk of product safety, the risk of process safety management and the like by grading objects in stages. And according to possible consequences caused by harm, the emergency degree and the development situation of risks, the early warning level is divided into three levels of important, larger and common hidden dangers.
Step S51: comparing the risk value calculated in the step 4 with a risk threshold value, and carrying out risk early warning:
risk rating (D ═ L × E × C) criteria
| D value | Risk rating |
| ＞60 | A major risk |
| ＞30 | B greater risk |
| ＞20 | C general risk |
| ≤20 | D Low Risk |
Step S52: before the signal system is put into use, the signal system must be ensured to be in a low risk state, otherwise, the signal system must not be put into use; with long-time field operation, hidden safety problems or unsafe events may occur, and then the risk value should be dynamically updated and corresponding early warning is performed. When the opening item is modified for a certain safety problem or unsafe event, the exposure index of the item can only be reduced, and the risk item cannot be eliminated. Only after double zeroing can the risk term be cleared.
Step S53: in addition to providing early warning of overall system risk, the process performance indicators may also be evaluated and early warned, including taking past (e.g., previous) monitoring periods as reference objects in a given monitoring period (year or quarter), i.e., based on the point mean and standard deviation of the previous monitoring period. Three lines were set up, which are the sum of the mean and 1, 2, and 3 standard deviation deviations, respectively. Calculation formula of standard deviation:
wherein X is the value of each data point, N is the total amount of data, and u is the mean of all data;
during the monitoring period, an alarm (abnormal, unacceptable risk) is displayed if any of the following conditions occur:
if any 1 point is higher than 3 times of the standard deviation value, carrying out major risk early warning;
2 times of standard deviation value appears at 2 continuous points, and large risk early warning is carried out;
primarily selecting the standard deviation value which is higher than 1 time from 3 continuous points, and carrying out general risk early warning;
step S106: and (5) carrying out linkage hidden trouble investigation and treatment process. Making a correction measure and a prevention measure for each hidden danger of early warning, and automatically turning to a hidden danger troubleshooting and treatment module for tracking, verifying and closing; and after the hidden danger troubleshooting and treatment process is finished, feeding the information back to the risk evaluation module to update the risk value. The warning may be released until after the risk has decreased to an acceptable level.
The invention has the following characteristics:
1. on the basis of a safety management mode based on management system compliance, forming a safety management mode based on process safety performance, which comprises the following steps: the method comprises a demand stage, an application design stage, a software design stage, a hardware design stage, a tool design stage, a test stage and an installation, debugging and operation maintenance stage.
2. And (3) forming a series of efficient and easy-to-operate safety management programs, such as a safety verification program, a safety audit program and the like, checking the stages in the step (1), and calculating process safety performance indexes of each stage, so that the capability and efficiency of controlling process safety risks are improved.
3. A set of overall-process and omnibearing comprehensive safety management system is established for actively monitoring and collecting data information of the overall process to form a safety management mode based on data driving.
4. And constructing an effective risk evaluation model, scientifically identifying, quantitatively evaluating and uniformly grading the safety risk of the signal system, and predicting the risk trend so that the risk control is changed from passive protection to active control.
5. An internal regular monitoring, evaluating and auditing system is formulated, closed-loop operation and continuous improvement of safety management are promoted, and the long-acting mechanism of better fulfilling the safety responsibility of a main body and healthy self supervision, self auditing and self perfection is facilitated.
DETAILED DESCRIPTION OF EMBODIMENT (S) OF INVENTION
The present invention will be described in detail below with reference to a CBTC system as an example.
1. The accident cause factor theta of the CBTC system is selected, the system is considered to be a full-automatic unmanned system, requirements for human factors and operation and maintenance procedures are not high, the CBTC system is installed in plain areas of China, and the natural environment is good, so that the selected theta is 0.1.
2. The obtained dynamic monitoring factor set is as follows:
where SPI is the security-related non-compliance that has been identified per thousand requirements, at various stages of system development.
3. Selecting severity and exposure indexes:
order to
Respectively, representing the severity of unsafe events, potential field safety hazards, and process non-compliance. Severity can be assessed separately for each overt incident/event and process non-compliance, and for simplicity of the process, a uniform severity index is selected for each major category (see the rule of hainmei).
Take G ═ {30, 3, 0.3 }.
Let E { E1, E2, E3} represent exposure indices of unsafe events, site safety hazards, and process non-compliance items, respectively. The exposure index may be evaluated separately for each dominant fault/event and process non-compliance, and for simplicity of the process, a uniform exposure index is chosen for each large class (taking into account the path of fault propagation).
Take G ═ {1, 0.5, 0.25 }.
Note that the above parameters are initial parameters. Along with the accumulation of data, the influence of each factor on the risk can be fitted through the analysis of big data, and therefore the selection of each parameter value is adjusted in real time. And if a safety accident occurs on the site, directly reporting the safety and not carrying out risk early warning.
When an unsafe accident/event or a site safety hazard occurs and is corrected, after the correction measures are completed, the exposure index can be reduced to the exposure index of the non-conforming item, namely 0.25.
4. And dynamically calculating the overall risk value of the system in real time, and fitting a curve to predict the trend.
The risk value of month 1 was calculated as:
d (1+ θ) D device 1.2 (Σ 1 month process non-compliance term 0.25 0.3+1 month field safety hazard quantity 0.5 x 3+1 month unsafe problem quantity 0.5 x 3) 11.6325
The risk value for month 2 is calculated as:
d (1+ θ) D equipment 1.2 (Σ (1 month-2 month) process non-compliance item 0.25 0.3+1 month field safety hazard quantity 0.5 3+1 month unsafe problem quantity 0.5) 16.7475
And so on. The third month the development process is completed, the risk value is 19.965, the risk is acceptable and the system can be delivered.
And thirdly, the potential safety hazard of the site in the 6 th month is generated, and the risk value is calculated as follows:
d (1+ θ) D equipment 1.2 (Σ (1 month-6 month) process non-conformity item 0.25 0.3+1 month field safety hidden trouble quantity 0.5 x 3+1 month unsafe problem quantity 0.5 ═ 21.45
Fourthly, if the potential safety hazards in the field are corrected in the 7 th month, the quantity of the potential safety hazards in the field is not calculated in the 7 th month; however, the root cause of the 6-month field safety hazard analysis should be regarded as the number statistics of the 7-month process non-conforming items. The risk value is calculated as:
d (1+ θ) D equipment 1.2 (Σ (1 month-6 month) process non-compliance item 0.25 0.3+1 month field safety hazard quantity 0.5 3+1 month unsafe problem quantity 0.5) 19.8825
At month 7, although the potential safety hazard in the field was corrected and the risk dropped, the risk still exceeded 20 by curve fitting, suggesting "double zeroing". The risk can be completely reduced only by carrying out double zero resetting of management and technology, the defect of non-conformity in the early process is eliminated, and the accumulated risk of safety accident events is displayed.
In this example, double zeroing is not performed, and so on. In the 8 th month, the potential safety hazard of the site is generated, and the risk value is increased.
Obtaining the risk value of the system according to the calculation formula, and predicting the risk trend as shown in figure 5.
The above is a description of method embodiments, and the embodiments of the present invention are further described below by way of apparatus embodiments.
As shown in fig. 2, the apparatus 100 includes:
the component element module is used for identifying the component elements of the safety risk early warning system;
the factor set determining module is used for determining a dynamic monitoring factor set;
the dynamic monitoring module is used for real-time dynamic monitoring;
the model construction module is used for constructing a risk quantitative evaluation model;
the risk early warning module is used for realizing multi-dimensional dynamic risk early warning;
and the hidden danger troubleshooting module is used for carrying out linkage hidden danger troubleshooting and treatment.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process of the described module may refer to the corresponding process in the foregoing method embodiment, and is not described herein again.
The electronic device of the present invention includes a Central Processing Unit (CPU) that can perform various appropriate actions and processes according to computer program instructions stored in a Read Only Memory (ROM) or computer program instructions loaded from a storage unit into a Random Access Memory (RAM). In the RAM, various programs and data required for the operation of the device can also be stored. The CPU, ROM, and RAM are connected to each other via a bus. An input/output (I/O) interface is also connected to the bus.
A plurality of components in the device are connected to the I/O interface, including: an input unit such as a keyboard, a mouse, etc.; an output unit such as various types of displays, speakers, and the like; storage units such as magnetic disks, optical disks, and the like; and a communication unit such as a network card, modem, wireless communication transceiver, etc. The communication unit allows the device to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.
The processing unit executes the respective methods and processes described above, for example, methods S101 to S106. For example, in some embodiments, methods S101-S106 may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as a storage unit. In some embodiments, part or all of the computer program may be loaded and/or installed onto the device via ROM and/or the communication unit. When the computer program is loaded into RAM and executed by the CPU, one or more of the steps of methods S101-S106 described above may be performed. Alternatively, in other embodiments, the CPU may be configured to perform methods S101-S106 by any other suitable means (e.g., by way of firmware).
The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), an Application Specific Standard Product (ASSP), a system on a chip (SOC), a load programmable logic device (CPLD), and the like.
Program code for implementing the methods of the present invention may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present invention, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
While the invention has been described with reference to specific embodiments, the invention is not limited thereto, and various equivalent modifications and substitutions can be easily made by those skilled in the art within the technical scope of the invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A rail transit signal system safety risk evaluation and risk early warning method is characterized by comprising the following steps:
step S1: identifying the constituent elements of a safety risk early warning system;
step S2: determining a dynamic monitoring factor set;
step S3: real-time dynamic monitoring;
step S4: constructing a risk quantitative evaluation model;
step S5: multi-dimensional dynamic risk early warning is realized;
step S6: and (5) carrying out link hidden trouble investigation and treatment.
2. The method for rail transit signal system safety risk assessment and risk early warning according to claim 1, wherein the components in step S1 include human factors, equipment factors, environmental factors and administrative factors.
3. The method for rail transit signal system safety risk assessment and risk early warning according to claim 1, wherein the factor set in step S2 includes a post monitoring factor set and a pre-monitoring factor set, the post monitoring factor set includes a dominant event or accident occurring on site, a site safety hazard and its corrective action, an execution situation of preventive action, a site equipment alarm situation and a timely handling situation; the prior monitoring factor set comprises process performance conditions of research and development, production, test, installation and debugging processes, unsafe problem conditions discovered by test, and risk conditions of safety-related left-over opening items.
4. The rail transit signal system safety risk evaluation and risk early warning method according to claim 1, wherein the step S3 is implemented as follows:
establishing a safety management informatization system to realize the online development of hazard analysis, safety verification, safety audit and safety evaluation activities;
and constructing a data interface of a demand management system Polarion, a hazard management system CentraLog and a change management system ClearQuest, calling relevant hazard information, safety non-conformity item information and hazard information at any time, and realizing online dynamic monitoring of safety relevant data.
5. The rail transit signal system safety risk evaluation and risk early warning method according to claim 1, wherein the step S4 is implemented as follows:
step S41, a model formula is constructed as follows:
d ═ D person + D environment + D management + D device ≈ α D device + β D device + γ D device + D device ═ (1+ θ) D device;
wherein D is the calculated risk value, D is the risk caused by human factors, D is the risk caused by environmental factors, D is the risk caused by administrative factors, D is the risk caused by equipment factors, and D is the risk caused by equipment factors, wherein alpha is the ratio of human factors to equipment factors, and beta is the ratio of environmental factors to equipment factors; γ is the ratio of factors of management to equipment factors; θ is the ratio of other factors than equipment to equipment factors;
step S42, the D device is calculated as follows:
d device ═ Σ DaijWherein a isijFor all dynamic monitoring factors, i represents the type of the monitoring factor and j represents the number of the monitoring event.
6. The rail transit signal system safety risk evaluation and risk early warning method according to claim 1, wherein the step S5 is implemented as follows:
step S51: comparing the risk value D calculated in the step 4 with a risk threshold value, and carrying out risk early warning;
step S52: before the signal system is put into use, the signal system must be ensured to be in a low risk state, otherwise, the signal system must not be put into use; with long-time field operation, if a hidden safety problem or an unsafe event possibly occurs, dynamically updating the risk value and carrying out corresponding early warning;
step S53: the method comprises the steps of setting three lines according to the point mean value and the standard variance of the previous monitoring period, wherein the three lines are the sum of the mean value and 1 time, and the sum of the standard variance deviation of 2 times and 3 times; in the monitoring period, any one of the following situations occurs, and then an alarm is displayed:
if any 1 point is higher than 3 times of the standard deviation value, carrying out major risk early warning;
2 times of standard deviation value appears at 2 continuous points, and large risk early warning is carried out;
and (5) carrying out general risk early warning when the continuous 3-point initial selection is higher than 1 time of standard deviation value.
7. The rail transit signal system safety risk evaluation and risk early warning method according to claim 1, wherein the step S6 specifically comprises:
making a correction measure and a prevention measure for each hidden danger of early warning, and automatically turning to a hidden danger troubleshooting and treatment module for tracking, verifying and closing; after the hidden danger troubleshooting and treatment process is completed, feeding the information back to the risk evaluation module to update the risk value; the warning may be released until after the risk has decreased to an acceptable level.
8. The utility model provides a rail transit signal system safety risk evaluation and risk early warning device which characterized in that, the device includes:
the component element module is used for identifying the component elements of the safety risk early warning system;
the factor set determining module is used for determining a dynamic monitoring factor set;
the dynamic monitoring module is used for real-time dynamic monitoring;
the model construction module is used for constructing a risk quantitative evaluation model;
the risk early warning module is used for realizing multi-dimensional dynamic risk early warning;
and the hidden danger troubleshooting module is used for carrying out linkage hidden danger troubleshooting and treatment.
9. An electronic device comprising a memory and a processor, the memory having stored thereon a computer program, wherein the processor, when executing the program, implements the method of any of claims 1-7.
10. A computer-readable storage medium, on which a computer program is stored, which program, when being executed by a processor, carries out the method according to any one of claims 1 to 7.
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