Hydropower station operation risk level dynamic study and judgment method and system

Abstract

The invention discloses a hydropower station operation risk level dynamic research and judgment method and system, and the method comprises the steps: obtaining risk work task data of hydropower station operation from an external system through setting a timed task, and building a risk task form; traversing the acquired hydropower station operation risk work task data, judging whether the data are in an operation risk historical library, and if so, recording and assigning the risk level and the disposal measure of the corresponding risk work task in the operation risk historical library to the risk level and the disposal measure of the current risk work task; otherwise, the names of the risk work tasks are subjected to word splitting, matching is conducted in a work risk historical library, and the names with the high matching rate serve as risk levels and disposal measures recommended preferentially; and forming a hydropower station operation risk research and judgment report based on the risk level and the disposal measure of the risk work task. According to the invention, a uniform safety risk research and judgment mechanism and rule can be formed, and non-uniform research and judgment results and wrong results caused by human factors are avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of hydropower station monitoring, and in particular to a method and system for dynamically evaluating the risk level of hydropower station operations. Background Art

[0002] The smooth and safe operation of a hydropower station not only has a direct impact on the economic benefits of the power plant, but also has a decisive impact on production and life in the vicinity of the power station and in the upstream and downstream reservoir areas. The power plant has a wide variety of equipment and a complex working area.

[0003] The main work of a power plant includes daily maintenance of various equipment and other construction operations. Before the operation is carried out, it is necessary to manually identify the risk level of the operation content and formulate corresponding control measures, clarify the operation risk level of the risk operation and clarify the corresponding control measures, so as to ensure that when carrying out construction operations or equipment maintenance, construction workers can clearly know the risks of the operation and the necessary control measures. In addition, the management department can also summarize the data to judge the development trend of risk operations within a certain period of time and do corresponding management and prevention work.

[0004] However, the existing technology has the following problems:

[0005] 1. It is necessary to manually assess the level of risk tasks and control measures in the business system.

[0006] 2. It is impossible to conduct real-time data analysis and manual analysis is inefficient, and there are no unified analysis standards and rules.

[0007] 3. Unable to form systematic reports and data summaries of operating trends. Summary of the invention

[0008] In order to solve the above problems, the present invention proposes a method and system for dynamically evaluating the risk level of hydropower station operations, which can form a real-time unified safety risk evaluation mechanism and rules, avoiding inconsistent and erroneous evaluation results caused by human factors.

[0009] The technical solution adopted by the present invention is as follows:

[0010] On the one hand, the present invention proposes a method for dynamically evaluating the risk level of a hydropower station operation, comprising:

[0011] By setting up scheduled tasks, the risk work task data of the hydropower station operation is obtained from the external system; a risk task form is established, including the risk level and disposal measures for each risk work task data, and each risk level and disposal measure is initialized to empty;

[0012] Traverse the acquired hydropower station operation risk task data to determine whether it is in the operation risk history database. If so, record the risk level and disposal measures of the corresponding risk task in the operation risk history database and assign them to the risk level and disposal measures of the current risk task; otherwise, split the risk task name into words and match them in the operation risk history database, and take the risk level and disposal measures with the highest matching rate as the priority recommendation;

[0013] A hydropower station operation risk assessment report is formed based on the risk level and disposal measures of risk work tasks.

[0014] Furthermore, the word splitting of the risk task name and matching in the operation risk history library includes:

[0015] The risk work task name is split into words, and the binary tree search algorithm is used to search and match the keywords obtained in the operation risk history database: the operation risk history database is regarded as a binary tree. If the keyword is successfully matched at the parent node of the binary tree, it will continue to match at the child node. The number of matches of the keyword will increase by 1 for each successful match; if the match at the parent node is unsuccessful, it will exit directly and continue to match the next keyword; finally, the risk level and disposal measures of the risk work task corresponding to the keyword with the most matches will be recorded and assigned to the risk level and disposal measures of the current risk work task.

[0016] Furthermore, the word splitting of the risk work task name includes:

[0017] Obtain risk work task data as text to be segmented;

[0018] Selecting a preset word segmentation method combination, the preset word segmentation method combination comprising a basic word segmentation method, a word segmentation disambiguation optimization method, and a proper noun optimization method, wherein the proper noun comprises an alias-type proper noun;

[0019] Use the selected preset word segmentation method combination to segment the text.

[0020] Furthermore, the method of using the selected preset word segmentation method combination to segment the text to be segmented includes:

[0021] Segment the text to be segmented according to the basic segmentation method to obtain a basic segmentation result;

[0022] Obtaining intersecting word tuples and non-intersecting word tuples included in the basic word segmentation results according to the word segmentation disambiguation optimization method; determining non-intersecting word tuple combinations in each intersecting word tuple; determining non-ambiguous word tuples according to the word formation probability of each word tuple in the non-intersecting word tuple combination; using the word tuples in the non-intersecting word tuple group and the non-ambiguous word tuples as the primary word segmentation results of the text to be segmented;

[0023] According to the proper nouns in the preset proper word library, determining non-proprietary word unit combinations and proper word unit combinations in the primary word segmentation results;

[0024] According to the alias-type proper words in the preset alias-type proper word library, a non-alias-type proper word combination is determined in the proper word combination, including: determining a first proper noun and a second proper noun in the proper word combination, wherein the word length of the second proper noun is less than the length of the first proper noun and is included in the first proper noun; performing a circular matching between the second proper noun and the alias-type proper words in the preset alias-type proper word library to obtain a non-alias-type proper word combination, wherein the alias-type proper word library includes the alias-type proper words of the first proper noun, and the non-alias-type proper word combination includes the second proper noun that does not match the alias-type proper word of the first proper noun;

[0025] The word-grams in the non-proprietary word-gram combination and the word-grams in the proprietary word-gram combination other than the word-grams in the proprietary word-gram combination are taken as the word segmentation results of the text to be segmented.

[0026] Furthermore, if the keyword match obtained by word splitting is unsuccessful, it means that the risk work task is not in the operation risk history library. At this time, the keywords obtained by word splitting are matched in the risk level and disposal measures library of the operation risk history library, and the matching results with more matching keywords are used as the risk level and disposal measures of the current risk work task.

[0027] On the other hand, the present invention provides a system for dynamically evaluating the risk level of hydropower station operations, comprising:

[0028] The data acquisition module is configured to obtain risk work task data of hydropower station operations from an external system by setting a scheduled task; and to establish a risk task form, including establishing a risk level and disposal measures for each risk work task data, and initializing each risk level and disposal measure to be empty;

[0029] The risk judgment module is configured to traverse the acquired hydropower station operation risk work task data to determine whether it is in the operation risk history database. If so, the risk level and disposal measures of the corresponding risk work task in the operation risk history database are recorded and assigned to the risk level and disposal measures of the current risk work task; otherwise, the risk work task name is decomposed and matched in the operation risk history database, and the risk level and disposal measures with a high matching rate are used as the priority recommended risk level;

[0030] The report generation module is configured to form a hydropower station operation risk assessment report based on the risk level and disposal measures of the risk work tasks.

[0031] Furthermore, in the risk judgment module, the risk task name is decomposed into words and matched in the operation risk history library, including:

[0032] The risk work task name is split into words, and the binary tree search algorithm is used to search and match the keywords obtained in the operation risk history database: the operation risk history database is regarded as a binary tree. If the keyword is successfully matched at the parent node of the binary tree, it will continue to match at the child node. The number of matches of the keyword will increase by 1 for each successful match; if the match at the parent node is unsuccessful, it will exit directly and continue to match the next keyword; finally, the risk level and disposal measures of the risk work task corresponding to the keyword with the most matches will be recorded and assigned to the risk level and disposal measures of the current risk work task.

[0033] Furthermore, in the risk judgment module, decomposing the risk work task name includes:

[0034] Obtain risk work task data as text to be segmented;

[0035] Selecting a preset word segmentation method combination, the preset word segmentation method combination comprising a basic word segmentation method, a word segmentation disambiguation optimization method, and a proper noun optimization method, wherein the proper noun comprises an alias-type proper noun;

[0036] Use the selected preset word segmentation method combination to segment the text.

[0037] Furthermore, the method of using the selected preset word segmentation method combination to segment the text to be segmented includes:

[0038] Segment the text to be segmented according to the basic segmentation method to obtain a basic segmentation result;

[0039] Obtaining intersecting word tuples and non-intersecting word tuples included in the basic word segmentation results according to the word segmentation disambiguation optimization method; determining non-intersecting word tuple combinations in each intersecting word tuple; determining non-ambiguous word tuples according to the word formation probability of each word tuple in the non-intersecting word tuple combination; using the word tuples in the non-intersecting word tuple group and the non-ambiguous word tuples as the primary word segmentation results of the text to be segmented;

[0040] According to the proper nouns in the preset proper word library, determining non-proprietary word unit combinations and proper word unit combinations in the primary word segmentation results;

[0041] According to the alias-type proper words in the preset alias-type proper word library, a non-alias-type proper word combination is determined in the proper word combination, including: determining a first proper noun and a second proper noun in the proper word combination, wherein the word length of the second proper noun is less than the length of the first proper noun and is included in the first proper noun; performing a circular matching between the second proper noun and the alias-type proper words in the preset alias-type proper word library to obtain a non-alias-type proper word combination, wherein the alias-type proper word library includes the alias-type proper words of the first proper noun, and the non-alias-type proper word combination includes the second proper noun that does not match the alias-type proper word of the first proper noun;

[0042] The word-grams in the non-proprietary word-gram combination and the word-grams in the proprietary word-gram combination other than the word-grams in the proprietary word-gram combination are taken as the word segmentation results of the text to be segmented.

[0043] Furthermore, in the risk judgment module, if the keyword match obtained by word splitting is unsuccessful, it means that the risk work task is not in the operation risk history library. At this time, the keywords obtained by word splitting are matched in the risk level and disposal measures library of the operation risk history library, and the matching results with more matching keywords are used as the risk level and disposal measures of the current risk work task.

[0044] The beneficial effects of the present invention are:

[0045] The present invention can form a real-time unified safety risk assessment mechanism and rules through dynamic assessment of hydropower station operation risks, thus avoiding inconsistent and erroneous assessment results caused by human factors; at the same time, due to the use of automatic task docking, risk data is directly stored from other systems into this system, which greatly improves data entry efficiency; after the assessment is completed, the system will automatically generate an assessment report on risk operation data, so that the management department can timely and effectively grasp the recent work task status of the power plant and the distribution of safe operations, which can more effectively improve management efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 The present invention is a flow chart of a method for dynamically evaluating the risk level of a hydropower station operation. DETAILED DESCRIPTION

[0047] In order to have a clearer understanding of the technical features, purposes and effects of the present invention, the specific implementation methods of the present invention are now described. 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, that is, the embodiments described are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present invention.

[0048] Example 1

[0049] This embodiment provides a method for dynamically evaluating the risk level of a hydropower station operation, including:

[0050] By setting up scheduled tasks, the risk work task data of the hydropower station operation is obtained from the external system; a risk task form is established, including the risk level and disposal measures for each risk work task data, and each risk level and disposal measure is initialized to empty;

[0051] Traverse the acquired hydropower station operation risk task data to determine whether it is in the operation risk history database. If so, record the risk level and disposal measures of the corresponding risk task in the operation risk history database and assign them to the risk level and disposal measures of the current risk task; otherwise, split the risk task name into words and match them in the operation risk history database, and take the risk level and disposal measures with the highest matching rate as the priority recommendation;

[0052] A hydropower station operation risk assessment report is formed based on the risk level and disposal measures of risk work tasks.

[0053] like Figure 1 As shown, the method for dynamically evaluating the risk level of hydropower station operations implemented in this embodiment can be implemented by the following steps.

[0054] S1. Obtain risk work data and establish a risk task form, including the following sub-steps:

[0055] S1-1. Obtain risk work task data from the external system by setting a scheduled task. The risk work task data includes risk name, risk operation area, work person in charge, planned working time, number of workers, equipment code, responsible department, and work status. Only work tasks with a work status of started or not started are obtained.

[0056] S1-2. Create a risk task form based on the acquired data: create a risk level and disposal measure for each risk work task data, and initialize each risk level and disposal measure to empty;

[0057] S2. Traverse the acquired risk work task data to determine whether each risk work task data is in the operation risk history library, including the following sub-steps:

[0058] S2-1. Match directly in the operation risk history database by the name of the risk work task. If the match is successful, the risk level and disposal measures of the corresponding risk work task in the operation risk history database are recorded and assigned to the risk level and disposal measures of the current risk work task;

[0059] S2-2. If S2-1 fails to match successfully, the risk work task name will be split into words, and the binary tree search algorithm will be used to search and match the keywords obtained from the split words in the operation risk history library. The specific method is: regard the operation risk history library as a binary tree. If the keyword is successfully matched at the parent node of the binary tree, continue to match at the child node. For each successful match, the number of matches of the keyword is increased by 1; if the match at the parent node is unsuccessful, exit directly and continue to match the next keyword; finally, record the risk level and disposal measures of the risk work task corresponding to the keyword with the most matches and assign them to the risk level and disposal measures of the current risk work task.

[0060] Preferably, the specific method of decomposing the risk work task name is:

[0061] S2-2-1. Obtain risk work task data as text to be segmented;

[0062] S2-2-2, selecting a preset word segmentation method combination, wherein the preset word segmentation method combination includes a basic word segmentation method, a word segmentation disambiguation optimization method, and a proper noun optimization method, and the proper noun includes an alias-type proper noun;

[0063] S2-2-3. Use the selected preset word segmentation method combination to segment the text to be segmented. The specific method is:

[0064] Use the basic word segmentation method to segment the text to be segmented and obtain the basic word segmentation result;

[0065] The word segmentation disambiguation optimization method is as follows: obtaining intersecting word tuples and non-intersecting word tuples included in the basic word segmentation results; determining non-intersecting word tuple combinations in the intersecting word tuples for each intersecting word tuple; determining non-ambiguous word tuples according to the word formation probability of each word tuple in the non-intersecting word tuple combination; using the word tuples in the non-intersecting word tuples and the non-ambiguous word tuples as the primary word segmentation results of the text to be segmented;

[0066] The method for optimizing proper nouns is as follows: according to the proper nouns in the preset proper word library, non-proprietary word unit combinations and proper word unit combinations are determined in the primary word segmentation results;

[0067] According to the alias-type proper words in the preset alias-type proper word library, a non-alias-type proper word combination is determined in the proper word combination, including: determining a first proper noun and a second proper noun in the proper word combination, wherein the word length of the second proper noun is less than the length of the first proper noun and is included in the first proper noun; performing a cyclic matching between the second proper noun and the alias-type proper words in the preset alias-type proper word library to obtain a non-alias-type proper word combination, wherein the alias-type proper word library includes the alias-type proper word of the first proper noun, and the non-alias-type proper word combination includes the second proper noun that does not match the alias-type proper word of the first proper noun;

[0068] The word-grams in the non-proprietary word-gram combination and the word-grams in the proprietary word-gram combination other than the word-grams in the proprietary word-gram combination are taken as the word segmentation results of the text to be segmented.

[0069] It should be noted that the parent node of the binary tree is the user-defined data of high importance, and the child nodes are the data associated with the parent node; each search is first searched in the parent node of high importance, and if the match is successful, then the child node associated with the parent node is searched (the data of the child node may only appear under certain circumstances of the parent node). If the match is unsuccessful at the parent node, there is no need to search the child node again, which can shorten the matching time and improve the matching efficiency. The structure of the binary tree is as follows:

[0070] S2-2-1, the number of non-empty binary tree leaf nodes = the number of nodes with degree 2 + 1, that is, N0 = N2 + 1;

[0071] S2-2-2. There are at most 2K-1 nodes on the Kth level of a non-empty binary tree, K ≥ 1;

[0072] S2-2-3. A binary tree with a height of H has at most 2H-1 nodes, H ≥ 1;

[0073] S2-2-4. The height of a complete binary tree with N nodes is:

[0074] [log2(N+1)][log2(N+1)] or [log2N]+1[log2N]+1, N>0;

[0075] S2-2-5. Number the complete binary tree 1, 2, ..., N from top to bottom and from left to right, and then we have the following relationship:

[0076] ① When i>1i>1, the parent node of node ii is numbered [i / 2][i / 2], that is, when ii is an even number, its parent node is numbered i / 2i / 2, and it is the left child of the parent node; when ii is an odd number, its parent node is numbered (i-1) / 2(i-1) / 2, and it is the right child of the parent node;

[0077] ②When 2i≤N2i≤N, the left child of node i is numbered 2i2i, otherwise there is no left child;

[0078] ③When 2i+1≤N2i+1≤N, the right child of node i is numbered 2i+12i+1, otherwise there is no right child;

[0079] ④The level (depth) of node ii is [log2i]+1[log2i]+1; (assuming the root node is at the first level).

[0080] S2-3. If the keyword match obtained by word splitting fails, it means that the risk work task is not in the operation risk history database, and the following processing is performed:

[0081] S2-3-1. Use the LEC method to determine the risk level;

[0082] S2-3-2. The keywords obtained by decomposing the words in S2-2 are matched in the disposal measure library of the operation risk history library, and the matching results with more matching keywords are used as the disposal measures for the current risk work task.

[0083] S3. Prepare a risk assessment report, including the risk level and disposal measures for each pre-risk work task data.

[0084] Example 2

[0085] This embodiment provides a system for dynamically evaluating the risk level of a hydropower station operation, including:

[0086] The data acquisition module is configured to obtain risk work task data of hydropower station operations from an external system by setting a scheduled task; and to establish a risk task form, including establishing a risk level and disposal measures for each risk work task data, and initializing each risk level and disposal measure to be empty;

[0087] The risk judgment module is configured to traverse the acquired hydropower station operation risk work task data to determine whether it is in the operation risk history database. If so, the risk level and disposal measures of the corresponding risk work task in the operation risk history database are recorded and assigned to the risk level and disposal measures of the current risk work task; otherwise, the risk work task name is decomposed and matched in the operation risk history database, and the risk level and disposal measures with a high matching rate are used as the priority recommended risk level;

[0088] The report generation module is configured to form a hydropower station operation risk assessment report based on the risk level and disposal measures of the risk work tasks.

[0089] Preferably, in the risk judgment module, the risk work task name is decomposed into words and matched in the operation risk history library, including:

[0090] The risk work task name is split into words, and the binary tree search algorithm is used to search and match the keywords obtained in the operation risk history database: the operation risk history database is regarded as a binary tree. If the keyword is successfully matched at the parent node of the binary tree, it will continue to match at the child node. The number of matches of the keyword will increase by 1 for each successful match; if the match at the parent node is unsuccessful, it will exit directly and continue to match the next keyword; finally, the risk level and disposal measures of the risk work task corresponding to the keyword with the most matches will be recorded and assigned to the risk level and disposal measures of the current risk work task.

[0091] Preferably, in the risk judgment module, decomposing the risk work task name includes:

[0092] Obtain risk work task data as text to be segmented;

[0093] Selecting a preset word segmentation method combination, the preset word segmentation method combination includes a basic word segmentation method, a word segmentation disambiguation optimization method, and a proper noun optimization method, wherein the proper noun includes an alias-type proper noun;

[0094] Use the selected preset word segmentation method combination to segment the text.

[0095] Preferably, the selected preset word segmentation method combination is used to segment the text to be segmented, including:

[0096] Segment the text to be segmented according to the basic segmentation method to obtain a basic segmentation result;

[0097] Obtaining intersecting word tuples and non-intersecting word tuples included in the basic word segmentation results according to the word segmentation disambiguation optimization method; determining non-intersecting word tuple combinations in each intersecting word tuple; determining non-ambiguous word tuples according to the word formation probability of each word tuple in the non-intersecting word tuple combination; using the word tuples in the non-intersecting word tuple group and the non-ambiguous word tuples as the primary word segmentation results of the text to be segmented;

[0098] According to the proper nouns in the preset proper word library, determining non-proprietary word unit combinations and proper word unit combinations in the primary word segmentation results;

[0099] According to the alias-type proper words in the preset alias-type proper word library, a non-alias-type proper word combination is determined in the proper word combination, including: determining a first proper noun and a second proper noun in the proper word combination, wherein the word length of the second proper noun is less than the length of the first proper noun and is included in the first proper noun; performing a cyclic matching between the second proper noun and the alias-type proper words in the preset alias-type proper word library to obtain a non-alias-type proper word combination, wherein the alias-type proper word library includes the alias-type proper word of the first proper noun, and the non-alias-type proper word combination includes the second proper noun that does not match the alias-type proper word of the first proper noun;

[0100] The word-grams in the non-proprietary word-gram combination and the word-grams in the proprietary word-gram combination other than the word-grams in the proprietary word-gram combination are taken as the word segmentation results of the text to be segmented.

[0101] Preferably, in the risk judgment module, if the keyword match obtained by word splitting is unsuccessful, it means that the risk work task is not in the operation risk history library. At this time, the keywords obtained by word splitting are matched in the risk level and disposal measures library of the operation risk history library, and the matching results with more matching keywords are used as the risk level and disposal measures of the current risk work task.

[0102] Example 3

[0103] This embodiment is based on embodiment 1:

[0104] This embodiment provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the method for dynamically evaluating the risk level of hydropower station operations in embodiment 1 are implemented. The computer program may be in source code form, object code form, executable file, or some intermediate form.

[0105] Example 4

[0106] This embodiment is based on embodiment 1:

[0107] This embodiment provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the method for dynamically evaluating the risk level of hydropower station operations in Embodiment 1. The computer program may be in source code form, object code form, executable file, or some intermediate form, etc. The storage medium includes: any entity or device capable of carrying computer program code, recording medium, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content contained in the storage medium may be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the storage medium does not include electric carrier signals and telecommunication signals.

[0108] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity of description, they are expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the order of the actions described, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

Claims

1. A method for dynamically evaluating the risk level of hydropower station operations, characterized in that: include: By setting up scheduled tasks, we can obtain risk task data of hydropower station operations from external systems; Create a risk task form, including establishing risk levels and treatment measures for each risk work task data, and initialize each risk level and treatment measure to empty; Traverse the acquired hydropower station operation risk task data to determine whether it is in the operation risk history database. If so, record the risk level and disposal measures of the corresponding risk task in the operation risk history database and assign them to the risk level and disposal measures of the current risk task; otherwise, split the risk task name into words and match them in the operation risk history database, and take the risk level and disposal measures with the highest matching rate as the priority recommendation; A hydropower station operation risk assessment report is formed based on the risk level and disposal measures of risk work tasks.

2. A method for dynamically evaluating the risk level of a hydropower station operation according to claim 1, characterized in that: The risk task name is decomposed into words and matched in the operation risk history library, including: The risk work task name is split into words, and the binary tree search algorithm is used to search and match the keywords obtained in the operation risk history database: the operation risk history database is regarded as a binary tree. If the keyword is successfully matched at the parent node of the binary tree, it will continue to match at the child node. The number of matches of the keyword will increase by 1 for each successful match; if the match at the parent node is unsuccessful, it will exit directly and continue to match the next keyword; finally, the risk level and disposal measures of the risk work task corresponding to the keyword with the most matches will be recorded and assigned to the risk level and disposal measures of the current risk work task.

3. A method for dynamically evaluating the risk level of a hydropower station operation according to claim 1, characterized in that: The word splitting of the risk task name includes: Obtain risk work task data as text to be segmented; Selecting a preset word segmentation method combination, the preset word segmentation method combination comprising a basic word segmentation method, a word segmentation disambiguation optimization method, and a proper noun optimization method, wherein the proper noun comprises an alias-type proper noun; Use the selected preset word segmentation method combination to segment the text.

4. A method for dynamically evaluating the risk level of a hydropower station operation according to claim 3, characterized in that: The method of using the selected preset word segmentation method combination to segment the text to be segmented includes: Segment the text to be segmented according to the basic segmentation method to obtain a basic segmentation result; Obtaining intersecting word tuples and non-intersecting word tuples included in the basic word segmentation results according to the word segmentation disambiguation optimization method; determining non-intersecting word tuple combinations in each intersecting word tuple; determining non-ambiguous word tuples according to the word formation probability of each word tuple in the non-intersecting word tuple combination; using the word tuples in the non-intersecting word tuple group and the non-ambiguous word tuples as the primary word segmentation results of the text to be segmented; According to the proper nouns in the preset proper word library, determining non-proprietary word unit combinations and proper word unit combinations in the primary word segmentation results; According to the alias-type proper words in the preset alias-type proper word library, a non-alias-type proper word combination is determined in the proper word combination, including: determining a first proper noun and a second proper noun in the proper word combination, wherein the word length of the second proper noun is less than the length of the first proper noun and is included in the first proper noun; performing a circular matching between the second proper noun and the alias-type proper words in the preset alias-type proper word library to obtain a non-alias-type proper word combination, wherein the alias-type proper word library includes the alias-type proper words of the first proper noun, and the non-alias-type proper word combination includes the second proper noun that does not match the alias-type proper word of the first proper noun; The word-grams in the non-proprietary word-gram combination and the word-grams in the proprietary word-gram combination other than the word-grams in the proprietary word-gram combination are taken as the word segmentation results of the text to be segmented.

5. A method for dynamically evaluating the risk level of a hydropower station operation according to claim 1, characterized in that: If the keyword match obtained by word splitting is unsuccessful, it means that the risk work task is not in the operation risk history library. At this time, the keywords obtained by word splitting are matched in the risk level and disposal measures library of the operation risk history library, and the matching results with more matching keywords are used as the risk level and disposal measures of the current risk work task.

6. A dynamic assessment system for the risk level of hydropower station operations, characterized in that: include: The data acquisition module is configured to obtain risk work task data of the hydropower station operation from the external system by setting a scheduled task; And establish a risk task form, including establishing risk levels and disposal measures for each risk work task data, and initializing each risk level and disposal measure to empty; The risk judgment module is configured to traverse the acquired hydropower station operation risk work task data to determine whether it is in the operation risk history database. If so, the risk level and disposal measures of the corresponding risk work task in the operation risk history database are recorded and assigned to the risk level and disposal measures of the current risk work task; otherwise, the risk work task name is decomposed and matched in the operation risk history database, and the risk level and disposal measures with a high matching rate are used as the priority recommended risk level; The report generation module is configured to form a hydropower station operation risk assessment report based on the risk level and disposal measures of the risk work tasks.

7. A hydropower station operation risk level dynamic analysis system according to claim 6, characterized in that: In the risk judgment module, the risk task name is decomposed and matched in the operation risk history library, including: The risk work task name is split into words, and the binary tree search algorithm is used to search and match the keywords obtained in the operation risk history database: the operation risk history database is regarded as a binary tree. If the keyword is successfully matched at the parent node of the binary tree, it will continue to match at the child node. The number of matches of the keyword will increase by 1 for each successful match; if the match at the parent node is unsuccessful, it will exit directly and continue to match the next keyword; finally, the risk level and disposal measures of the risk work task corresponding to the keyword with the most matches will be recorded and assigned to the risk level and disposal measures of the current risk work task.

8. A hydropower station operation risk level dynamic analysis system according to claim 6, characterized in that: In the risk judgment module, the risk work task name is decomposed into words including: Obtain risk work task data as text to be segmented; Selecting a preset word segmentation method combination, the preset word segmentation method combination comprising a basic word segmentation method, a word segmentation disambiguation optimization method, and a proper noun optimization method, wherein the proper noun comprises an alias-type proper noun; Use the selected preset word segmentation method combination to segment the text.

9. A hydropower station operation risk level dynamic analysis system according to claim 8, characterized in that: The method of using the selected preset word segmentation method combination to segment the text to be segmented includes: Segment the text to be segmented according to the basic segmentation method to obtain a basic segmentation result; Obtaining intersecting word tuples and non-intersecting word tuples included in the basic word segmentation results according to the word segmentation disambiguation optimization method; determining non-intersecting word tuple combinations in each intersecting word tuple; determining non-ambiguous word tuples according to the word formation probability of each word tuple in the non-intersecting word tuple combination; using the word tuples in the non-intersecting word tuple group and the non-ambiguous word tuples as the primary word segmentation results of the text to be segmented; According to the proper nouns in the preset proper word library, determining non-proprietary word unit combinations and proper word unit combinations in the primary word segmentation results; According to the alias-type proper words in the preset alias-type proper word library, a non-alias-type proper word combination is determined in the proper word combination, including: determining a first proper noun and a second proper noun in the proper word combination, wherein the word length of the second proper noun is less than the length of the first proper noun and is included in the first proper noun; performing a circular matching between the second proper noun and the alias-type proper words in the preset alias-type proper word library to obtain a non-alias-type proper word combination, wherein the alias-type proper word library includes the alias-type proper words of the first proper noun, and the non-alias-type proper word combination includes the second proper noun that does not match the alias-type proper word of the first proper noun; The word-grams in the non-proprietary word-gram combination and the word-grams in the proprietary word-gram combination other than the word-grams in the proprietary word-gram combination are taken as the word segmentation results of the text to be segmented.

10. A hydropower station operation risk level dynamic analysis system according to claim 6, characterized in that: In the risk judgment module, if the keyword match obtained by word splitting is unsuccessful, it means that the risk work task is not in the operation risk history library. At this time, the keywords obtained by word splitting are matched in the risk level and disposal measures library of the operation risk history library, and the matching results with more matching keywords are used as the risk level and disposal measures of the current risk work task.

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