Power plant safety production management method and device

Abstract

The invention belongs to the technical field of power production safety, and discloses a power plant safety production management method and device. The method comprises the steps of obtaining safety information data of a power plant from a database; identifying safety production risk factors existing in the power plant based on the safety information data; analyzing the safety production risk factors to determine the relevance between the safety production risk factors and each safety accident type; extracting a key safety production risk factor corresponding to each safety accident type from the safety production risk factors based on the relevance; and performing risk assessment based on the key safety production risk factors, and performing safety production management based on a risk assessment result. Through the above mode, the risk can be effectively and comprehensively detected, the problem that risk identification is not timely and accurate due to a manual management mode is avoided, and effective management of safety production of a power plant is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of power production safety, and in particular to a power plant production safety management method and device. Background Art

[0002] The current safety situation in the power industry is relatively severe, and safety accidents occur from time to time, which not only poses a safety threat to people's lives, but also brings huge losses and hidden dangers to social development.

[0003] At present, the safety management of power plant production is mainly carried out through manual inspections of potential safety hazards. However, risks are latent, accidental and variable. It is impossible to conduct effective and comprehensive risk detection through manual management. There are problems such as untimely and inaccurate risk identification, which cannot ensure effective management of power plant production safety.

[0004] The above contents are only used to assist in understanding the technical solution of the present invention and do not constitute an admission that the above contents are prior art. Summary of the invention

[0005] The main purpose of the present invention is to provide a power plant production safety management method and device, aiming to solve the technical problem that risks cannot be effectively and comprehensively detected through manual detection and effective management of power plant production safety cannot be ensured.

[0006] To achieve the above object, the present invention provides a power plant production safety management method, the power plant production safety management method comprising the following steps:

[0007] Obtain safety information data of the power plant from the database;

[0008] Identify the safety production risk factors existing in the power plant based on the safety information data;

[0009] Analyze the production safety risk factors to determine the correlation between the production safety risk factors and various types of safety accidents;

[0010] Extracting key production safety risk factors corresponding to each type of safety accident from the production safety risk factors based on the correlation;

[0011] Conduct risk assessment based on the key production safety risk factors, and carry out production safety management based on the risk assessment results.

[0012] In some embodiments, the identifying the safety production risk factors existing in the power plant based on the safety information data includes:

[0013] Performing noise data screening on the security information data to obtain first security information data;

[0014] Eliminate faulty data from the first safety information data to obtain second safety information data;

[0015] Deduplicating the second security information data to obtain third security information data;

[0016] Performing format processing on the third security information data to obtain target security information data;

[0017] The target safety information data is subjected to text segmentation, and feature extraction is performed based on the segmentation result to obtain production safety risk factors.

[0018] In some embodiments, the noise data screening is mainly to clean the interference data, abnormal data and invalid characters in the security information data, the fault data elimination is to use syntax checking, semantic checking and type checking to check and modify the error descriptions existing in the first security information data, the duplicate data deletion is to check and clear the duplicate text or fields in the second security information data, and the format processing is to remove punctuation and special symbols in the third security information data, and convert the text format corresponding to the third security information data to a preset type of text format.

[0019] In some embodiments, the analyzing the production safety risk factors includes:

[0020] Determine the frequent safety production risk factors corresponding to each type of safety accident based on historical safety accident data;

[0021] Determine the index value corresponding to the production safety risk factor and the historical index value corresponding to the frequent production safety risk factor;

[0022] The similarity between the production safety risk factor and the frequent production safety risk factor is determined according to the indicator value and the historical indicator value, and analysis is performed based on the similarity.

[0023] In some embodiments, determining the frequent production safety risk factors corresponding to each type of safety accident based on historical safety accident data includes:

[0024] Determine the set of production safety risk factors corresponding to any type of safety accident based on historical safety accident data;

[0025] Determining the support level of each production safety risk factor based on the total number of factors in the production safety risk factor set;

[0026] The production safety risk factor corresponding to the maximum support degree is taken as the frequent production safety risk factor of the corresponding safety accident type.

[0027] In some embodiments, the risk assessment based on the key production safety risk factors includes:

[0028] Determine the factor types corresponding to the key production safety risk factors;

[0029] Determine the risk level corresponding to the key production safety risk factor based on the factor type;

[0030] The weights corresponding to the various indicators of the key production safety risk factors are determined based on the risk levels, and the risk values ​​of the key production safety risk factors are calculated based on the weights and indicator values.

[0031] In some embodiments, the performing of safety production management based on risk assessment results includes:

[0032] Compare the risk value corresponding to the risk assessment result with the preset risk value;

[0033] Determine the type of safety accident corresponding to the key production safety risk factor that exceeds the preset risk value based on the comparison results;

[0034] Manage according to the type of security incident described.

[0035] In addition, to achieve the above-mentioned purpose, the present invention also proposes a power plant production safety management device, the power plant production safety management device comprising:

[0036] The acquisition module is used to obtain the safety information data of the power plant from the database;

[0037] An identification module, used to identify safety production risk factors existing in the power plant based on the safety information data;

[0038] An analysis module, used to analyze the production safety risk factors to determine the correlation between the production safety risk factors and various safety accident types;

[0039] An extraction module, used for extracting key production safety risk factors corresponding to each safety accident type from the production safety risk factors based on the correlation;

[0040] The assessment management module is used to perform risk assessment based on the key production safety risk factors and perform production safety management based on the risk assessment results.

[0041] In some embodiments, the identifying the safety production risk factors existing in the power plant based on the safety information data includes:

[0042] Performing noise data screening on the security information data to obtain first security information data;

[0043] Eliminate faulty data from the first safety information data to obtain second safety information data;

[0044] Deduplicating the second security information data to obtain third security information data;

[0045] Performing format processing on the third security information data to obtain target security information data;

[0046] The target safety information data is subjected to text segmentation, and feature extraction is performed based on the segmentation result to obtain production safety risk factors.

[0047] In some embodiments, the noise data screening is mainly to clean the interference data, abnormal data and invalid characters in the security information data, the fault data elimination is to use syntax checking, semantic checking and type checking to check and modify the error descriptions existing in the first security information data, the duplicate data deletion is to check and clear the duplicate text or fields in the second security information data, and the format processing is to remove punctuation and special symbols in the third security information data, and convert the text format corresponding to the third security information data to a preset type of text format.

[0048] In the present invention, the safety information data of the power plant is obtained from the database; based on the safety information data, the safety production risk factors existing in the power plant are identified; the safety production risk factors are analyzed to determine the correlation between the safety production risk factors and each type of safety accident; based on the correlation, the key safety production risk factors corresponding to each type of safety accident are extracted from the safety production risk factors; risk assessment is performed based on the key safety production risk factors, and safety production management is performed based on the risk assessment results. Through the above-mentioned method, risks can be effectively and comprehensively detected, avoiding the problem of untimely and inaccurate risk identification caused by human management methods, and ensuring effective management of power plant safety production. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a flow chart of the first embodiment of the power plant safety production management method of the present invention;

[0050] Figure 2 It is a structural block diagram of the first embodiment of the power plant safety production management device of the present invention.

[0051] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0052] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0053] The embodiment of the present invention provides a power plant safety production management method, referring to Figure 1 , Figure 1 It is a flow chart of a first embodiment of a power plant safety production management method of the present invention.

[0054] In this embodiment, the power plant production safety management method includes the following steps:

[0055] Step S10: Acquire the safety information data of the power plant from the database.

[0056] In this embodiment, the executor of this embodiment is a power plant safety production management device, wherein the power plant safety production management device has functions such as data processing, data communication and program running. The power plant safety production management device can be a computer terminal device or other network device, and of course it can also be other devices with similar functions, and this embodiment does not limit this.

[0057] It should be noted that the current safety management of power plant production is mainly carried out through manual inspections of potential safety hazards. However, risks are latent, accidental, and variable. It is impossible to effectively and comprehensively detect risks through manual management. There are problems with untimely and accurate risk identification, and it is impossible to ensure effective management of power plant production safety.

[0058] In order to solve the above technical problems, this embodiment obtains safety information data of the power plant from a database; identifies the safety production risk factors existing in the power plant based on the safety information data; analyzes the safety production risk factors to determine the correlation between the safety production risk factors and each type of safety accident; extracts the key safety production risk factors corresponding to each type of safety accident from the safety production risk factors based on the correlation; performs risk assessment based on the key safety production risk factors, and performs safety production management based on the risk assessment results, which can effectively and comprehensively detect risks, avoid the problem of untimely and inaccurate risk identification caused by human management methods, and ensure effective management of power plant safety production. Specifically, it can be achieved as follows.

[0059] In the specific implementation, in this embodiment, it is necessary to first obtain the safety information data of the power plant from the database. The safety information data obtained includes but is not limited to text data of the current power plant, employee feedback data, and expert opinions, etc. Among them, text data such as safety accident reports, regular safety inspection records, repair and maintenance records, employee safety training records, safety management systems and operating procedures, etc., such as potential safety hazards reported by employees, feedback on problems in safety management, and expert opinions such as third-party safety assessment reports.

[0060] Step S20: Identify the safety production risk factors existing in the power plant based on the safety information data.

[0061] The above-mentioned safety information data can be used to identify the current production safety risk factors in the power plant. Specifically, in order to accurately identify the production safety risk factors, in this embodiment, it is necessary to perform noise data screening on the safety information data to obtain first safety information data; perform fault data elimination on the first safety information data to obtain second safety information data; perform duplicate data deletion on the second safety information data to obtain third safety information data; and perform format processing on the third safety information data to obtain target safety information data, wherein the noise data screening is mainly to clean the interference data, abnormal data and invalid characters in the safety information data, the fault data elimination is to use syntax checking, semantic checking and type checking to check and modify the error descriptions in the first safety information data, the duplicate data deletion is to check and clear the repeated text or fields in the second safety information data, and the format processing is to remove punctuation marks and special symbols in the third safety information data, and convert the text format corresponding to the third safety information data to a preset type of text format.

[0062] Finally, after obtaining the target safety information data, in this embodiment, a statistical word segmentation algorithm based on the hidden Markov model (HMM) is adopted to perform text segmentation using a simple and easy-to-understand sequence labeling idea. Jieba word segmentation, SnowNLP, NLTK or HanLP and other word segmentation tools can also be used for text segmentation. According to the word segmentation results, corresponding features can be extracted, which can be keyword features, such as equipment failure, operating errors, environmental factors, management defects, etc., and the final production safety risk factors such as equipment risk, personnel operation risk, environmental risk, and management risk can also be obtained.

[0063] Step S30: Analyze the production safety risk factors to determine the correlation between the production safety risk factors and various safety accident types.

[0064] It should be understood that each type of safety accident has its corresponding production safety risk factors. For example, risk factors such as equipment aging, improper maintenance, and design defects may lead to safety accidents. For example, the corrosion of the boiler in a power plant due to long-term lack of proper maintenance may cause the boiler to explode during operation, resulting in casualties and property losses. Therefore, after obtaining the current production safety risk factors of the power plant, it is necessary to analyze the existing production safety risk factors to determine possible safety accidents.

[0065] Specifically, the process of analyzing the production safety risk factors includes: determining the frequent production safety risk factors corresponding to each type of safety accident based on historical safety accident data; determining the index value corresponding to the production safety risk factor, and the historical index value corresponding to the frequent production safety risk factor; determining the similarity between the production safety risk factor and the frequent production safety risk factor based on the index value and the historical index value, and performing analysis based on the similarity.

[0066] It should be noted that each safety risk factor may lead to a corresponding safety accident, and the same type of safety accident may be caused by different safety risk factors. For example, equipment aging, improper maintenance, and design defects may all lead to power plant boiler explosions. However, in actual situations, equipment aging is the main safety production risk factor that leads to power plant boiler explosions, and other safety production risk factors will only cause such accidents occasionally. Therefore, in this embodiment, it is necessary to determine the main safety production risk factors corresponding to each type of safety accident, that is, frequent safety production risk factors.

[0067] In some embodiments, a set of production safety risk factors corresponding to any type of safety accident can be determined based on historical safety accident data; the support level of each production safety risk factor can be determined based on the total number of factors in the production safety risk factor set; and the production safety risk factor corresponding to the maximum support level can be used as a frequent production safety risk factor for the corresponding safety accident type.

[0068] It should be noted that one type of safety accident corresponds to multiple production safety risk factors, and its corresponding production safety risk factor set can be constructed. The support is the ratio of the number of occurrences of each production safety risk factor to the total number of factors. The larger the ratio, the greater the corresponding support. Therefore, the production safety risk factor corresponding to the maximum support is also the frequent production safety risk factor.

[0069] Further, after determining the frequent production safety risk factors, since one production safety risk factor may correspond to multiple indicator values, it is necessary to determine the indicator value corresponding to the production safety risk factor and the historical indicator value corresponding to the frequent production safety risk factor in this embodiment, and then determine the similarity between the production safety risk factor and the frequent production safety risk factor based on the above indicator value and the historical indicator value. Specifically, the average values ​​between the multiple indicator values ​​can be calculated respectively, and finally the similarity is determined according to the difference in the average values. For example, the average value of the historical indicator value corresponding to the frequent production safety risk factor is A, and the average value of the indicator value corresponding to the X-type production safety risk factor is B. 1 The average value of the index value corresponding to the Y-type production safety risk factor is B 2 , the similarities are AB 1 and AB 2, further assuming that AB 1 <AB 2 , then the similarity between type X production safety risk factors and frequent production safety risk factors is greater than the similarity between type Y production safety risk factors and frequent production safety risk factors.

[0070] Step S40: extracting key production safety risk factors corresponding to each safety accident type from the production safety risk factors based on the correlation.

[0071] Through the above correlation analysis, the production safety risk factor with the greatest similarity to the frequent production safety risk factors can be used as the key production safety risk factor of the corresponding type. For example, the above-mentioned X-type production safety risk factor and Y-type production safety risk factor are both production safety risk factors corresponding to the safety accident type P. Since the similarity between the X-type production safety risk factor and the frequent production safety risk factor is relatively large, the X-type production safety risk factor is the key production safety risk factor.

[0072] Step S50: Perform risk assessment based on the key production safety risk factors, and perform production safety management based on the risk assessment results.

[0073] After obtaining the above-mentioned key production safety risk factors, in this embodiment, the factor type corresponding to the key production safety risk factor can be determined; the risk level corresponding to the key production safety risk factor can be determined based on the factor type; the weights corresponding to each indicator of the key production safety risk factor can be determined based on the risk level, and the risk value of the key production safety risk factor can be calculated based on the weight and indicator value.

[0074] It should be noted that different key production safety risk factors have their corresponding factor types, and factor types have their corresponding risk levels. The risk levels can be divided into three different levels: low, medium, and high. For example, low risk is dirt on the surface of electrical equipment, which may cause equipment overheating, medium risk is aging of electrical line insulation, which may cause short circuits, and high risk is failure of high-voltage equipment, which may cause electric shock accidents or major fires. The weight value is associated with the risk level and can be set in advance. This is not limited in this embodiment. Finally, weighted calculation based on the weight value can be performed to obtain the risk value of the key production safety risk factor.

[0075] Furthermore, the above-mentioned risk value, that is, the risk assessment result, is compared with the preset risk value. If it exceeds the preset risk value, it is determined that a safety accident corresponding to a key production safety risk factor may occur, and then corresponding management measures are taken. For example, if equipment explosion may be caused by the production safety risk factor of equipment aging, measures such as regular maintenance and inspection of the equipment or purchase of new equipment are taken to prevent the occurrence of safety accidents.

[0076] This embodiment obtains safety information data of the power plant from a database; identifies the production safety risk factors of the power plant based on the safety information data; analyzes the production safety risk factors to determine the correlation between the production safety risk factors and each type of safety accident; extracts key production safety risk factors corresponding to each type of safety accident from the production safety risk factors based on the correlation; conducts risk assessment based on the key production safety risk factors, and performs production safety management based on the risk assessment results. This allows for effective and comprehensive detection of risks, avoids the problem of untimely and inaccurate risk identification caused by human management methods, and ensures effective management of power plant production safety.

[0077] Reference Figure 2 , Figure 2 It is a structural block diagram of the first embodiment of the power plant safety production management device of the present invention.

[0078] like Figure 2 As shown, the power plant safety production management device proposed in the embodiment of the present invention includes:

[0079] The acquisition module 10 is used to obtain the safety information data of the power plant from the database;

[0080] An identification module 20, configured to identify safety production risk factors existing in the power plant based on the safety information data;

[0081] An analysis module 30, for analyzing the production safety risk factors to determine the correlation between the production safety risk factors and various safety accident types;

[0082] An extraction module 40, configured to extract key production safety risk factors corresponding to each safety accident type from the production safety risk factors based on the correlation;

[0083] The assessment management module 50 is used to perform risk assessment based on the key production safety risk factors, and to perform production safety management based on the risk assessment results.

[0084] This embodiment obtains safety information data of the power plant from a database; identifies the production safety risk factors of the power plant based on the safety information data; analyzes the production safety risk factors to determine the correlation between the production safety risk factors and each type of safety accident; extracts key production safety risk factors corresponding to each type of safety accident from the production safety risk factors based on the correlation; conducts risk assessment based on the key production safety risk factors, and performs production safety management based on the risk assessment results. This allows for effective and comprehensive detection of risks, avoids the problem of untimely and inaccurate risk identification caused by human management methods, and ensures effective management of power plant production safety.

[0085] In some embodiments, the identification module 20 is used to filter the safety information data for noise data to obtain first safety information data;

[0086] Eliminate faulty data from the first safety information data to obtain second safety information data;

[0087] Deduplicating the second security information data to obtain third security information data;

[0088] Performing format processing on the third security information data to obtain target security information data;

[0089] The target safety information data is subjected to text segmentation, and feature extraction is performed based on the segmentation result to obtain production safety risk factors.

[0090] In some embodiments, the noise data screening is mainly to clean the interference data, abnormal data and invalid characters in the security information data, the fault data elimination is to use syntax checking, semantic checking and type checking to check and modify the error descriptions existing in the first security information data, the duplicate data deletion is to check and clear the duplicate text or fields in the second security information data, and the format processing is to remove punctuation and special symbols in the third security information data, and convert the text format corresponding to the third security information data to a preset type of text format.

[0091] In some embodiments, the analysis module 30 is used to determine the frequent production safety risk factors corresponding to each type of safety accident based on historical safety accident data;

[0092] Determine the index value corresponding to the production safety risk factor and the historical index value corresponding to the frequent production safety risk factor;

[0093] The similarity between the production safety risk factor and the frequent production safety risk factor is determined according to the indicator value and the historical indicator value, and analysis is performed based on the similarity.

[0094] In some embodiments, the analysis module 30 is used to determine a set of production safety risk factors corresponding to any type of safety accident based on historical safety accident data;

[0095] Determining the support level of each production safety risk factor based on the total number of factors in the production safety risk factor set;

[0096] The production safety risk factor corresponding to the maximum support degree is taken as the frequent production safety risk factor of the corresponding safety accident type.

[0097] In some embodiments, the assessment management module 50 is used to determine the factor type corresponding to the key production safety risk factor;

[0098] Determine the risk level corresponding to the key production safety risk factor based on the factor type;

[0099] The weights corresponding to the various indicators of the key production safety risk factors are determined based on the risk levels, and the risk values ​​of the key production safety risk factors are calculated based on the weights and indicator values.

[0100] In some embodiments, the assessment management module 50 is used to compare the risk value corresponding to the risk assessment result with a preset risk value;

[0101] Determine the type of safety accident corresponding to the key production safety risk factor that exceeds the preset risk value based on the comparison results;

[0102] Manage according to the type of security incident described.

[0103] An embodiment of the present application also provides a power plant safety production management device, including a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus, and the memory is used to store the power plant safety production management program; the processor is used to implement the above-mentioned power plant safety production management method when executing the program stored in the memory.

[0104] The communication bus mentioned in the above power plant safety production management equipment can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus can be divided into an address bus, a data bus, a control bus, etc.

[0105] The communication interface is used for communication between the above-mentioned power plant safety production management equipment and other equipment.

[0106] The memory may include a random access memory (RAM) or a non-volatile memory (NVM), such as at least one disk memory. Optionally, the memory may also be at least one storage device located away from the aforementioned processor.

[0107] The above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, and discrete hardware components.

[0108] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive Solid State Disk (SSD)), etc.

[0109] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0110] Each embodiment in this specification is described in a related manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0111] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

[0112] It should be understood that the above is only an example and does not constitute any limitation on the technical solution of the present invention. In specific applications, technicians in this field can make settings as needed, and the present invention does not limit this.

[0113] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of the present invention. In practical applications, technicians in this field can select part or all of them according to actual needs to achieve the purpose of the present embodiment, and no limitation is made here.

[0114] In addition, for technical details that are not described in detail in this embodiment, reference can be made to the power plant safety production management method provided in any embodiment of the present invention, and will not be repeated here.

[0115] In addition, it should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0116] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0117] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as a read-only memory (ROM) / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0118] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

[0119] It is understandable that the system provided by the embodiment of the present invention corresponds to the method provided by the embodiment of the present invention, and the explanation, examples and beneficial effects of the relevant contents can refer to the corresponding parts in the above method.

Claims

1. A power plant production safety management method, characterized in that: The power plant production safety management method comprises: Obtain safety information data of the power plant from the database; Identify the safety production risk factors existing in the power plant based on the safety information data; Analyze the production safety risk factors to determine the correlation between the production safety risk factors and various types of safety accidents; Extracting key production safety risk factors corresponding to each type of safety accident from the production safety risk factors based on the correlation; Conduct risk assessment based on the key production safety risk factors, and carry out production safety management based on the risk assessment results.

2. The power plant production safety management method according to claim 1, characterized in that: The identifying the safety production risk factors existing in the power plant based on the safety information data includes: Performing noise data screening on the security information data to obtain first security information data; Eliminate faulty data from the first safety information data to obtain second safety information data; Deduplicating the second security information data to obtain third security information data; Performing format processing on the third security information data to obtain target security information data; The target safety information data is subjected to text segmentation, and feature extraction is performed based on the segmentation result to obtain production safety risk factors.

3. The power plant production safety management method according to claim 2, characterized in that: The noise data screening is mainly to clean the interference data, abnormal data and invalid characters in the security information data, the fault data elimination is to use syntax checking, semantic checking and type checking to check and modify the error descriptions in the first security information data, the duplicate data deletion is to check and clear the duplicate text or fields in the second security information data, and the format processing is to remove punctuation and special symbols in the third security information data, and convert the text format corresponding to the third security information data to a preset type of text format.

4. The power plant production safety management method according to claim 1, characterized in that: The analysis of the production safety risk factors includes: Determine the frequent safety production risk factors corresponding to each type of safety accident based on historical safety accident data; Determine the index value corresponding to the production safety risk factor and the historical index value corresponding to the frequent production safety risk factor; The similarity between the production safety risk factor and the frequent production safety risk factor is determined according to the indicator value and the historical indicator value, and analysis is performed based on the similarity.

5. The power plant production safety management method according to claim 4, characterized in that: Determining the frequent production safety risk factors corresponding to each type of safety accident based on historical safety accident data includes: Determine the set of production safety risk factors corresponding to any type of safety accident based on historical safety accident data; Determining the support level of each production safety risk factor based on the total number of factors in the production safety risk factor set; The production safety risk factor corresponding to the maximum support degree is taken as the frequent production safety risk factor of the corresponding safety accident type.

6. The power plant production safety management method according to claim 1, characterized in that: The risk assessment based on the key production safety risk factors includes: Determine the factor types corresponding to the key production safety risk factors; Determine the risk level corresponding to the key production safety risk factor based on the factor type; The weights corresponding to the various indicators of the key production safety risk factors are determined based on the risk levels, and the risk values ​​of the key production safety risk factors are calculated based on the weights and indicator values.

7. The power plant production safety management method according to claim 6, characterized in that: The safety production management based on the risk assessment results includes: Compare the risk value corresponding to the risk assessment result with the preset risk value; Determine the type of safety accident corresponding to the key production safety risk factor that exceeds the preset risk value based on the comparison results; Manage according to the type of security incident described.

8. A power plant production safety management device, characterized in that: The power plant production safety management device comprises: The acquisition module is used to obtain the safety information data of the power plant from the database; An identification module, used to identify safety production risk factors existing in the power plant based on the safety information data; An analysis module, used to analyze the production safety risk factors to determine the correlation between the production safety risk factors and various safety accident types; An extraction module, used for extracting key production safety risk factors corresponding to each safety accident type from the production safety risk factors based on the correlation; The assessment management module is used to perform risk assessment based on the key production safety risk factors and perform production safety management based on the risk assessment results.

9. The power plant production safety management device according to claim 8, characterized in that: The identifying the safety production risk factors existing in the power plant based on the safety information data includes: Performing noise data screening on the security information data to obtain first security information data; Eliminate faulty data from the first safety information data to obtain second safety information data; Deduplicating the second security information data to obtain third security information data; Performing format processing on the third security information data to obtain target security information data; The target safety information data is subjected to text segmentation, and feature extraction is performed based on the segmentation result to obtain production safety risk factors.

10. The power plant production safety management device according to claim 9, characterized in that: The noise data screening is mainly to clean the interference data, abnormal data and invalid characters in the security information data, the fault data elimination is to use syntax checking, semantic checking and type checking to check and modify the error descriptions in the first security information data, the duplicate data deletion is to check and clear the duplicate text or fields in the second security information data, and the format processing is to remove punctuation and special symbols in the third security information data, and convert the text format corresponding to the third security information data to a preset type of text format.

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