WO2022237911A1 - 变压器消防灭火系统有效性评估方法及装置 - Google Patents
变压器消防灭火系统有效性评估方法及装置 Download PDFInfo
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Definitions
- the invention relates to the technical field of substation fire safety, in particular to a method and device for evaluating the effectiveness of a transformer fire extinguishing system.
- the substation plays a linking role in the power transmission and transformation system. It is a key facility for stable and effective deployment, stable transmission voltage, and continuous and safe reception and distribution of electric energy. Transformers are extremely prone to fires during severe overheating or internal short-circuit faults during operation. Insulating oil and insulating materials further increase the risk of fires, and ultimately cause very serious losses to personnel and the economy. Transformer fire protection system is an important part of substation facilities. When a fire and explosion accident occurs, it is very important whether the fire protection system works reliably and effectively.
- the technical problem to be solved by the present invention is to provide a transformer that is easy to operate and reduces computational complexity in view of the complex scoring operation process of experts in the effectiveness evaluation process of transformer fire extinguishing systems in the prior art and high requirements for expert computer skills. Methods for evaluating the effectiveness of fire suppression systems.
- a method for evaluating the effectiveness of a transformer fire extinguishing system based on natural language fuzzy analysis the specific steps include:
- Step 1 Information collection, collect information on substation design and operation information, surrounding environment information and the fire extinguishing system adopted, the collected information at least includes fire extinguishing system design parameters, equipment operation data, maintenance status and substation construction environment, etc.;
- Step 2 Construction of the fire extinguishing system effectiveness evaluation index system, by classifying the influencing factors that affect the fire extinguishing system fire extinguishing effectiveness, together constitute the fire extinguishing system effectiveness evaluation system;
- Step 3 Establish an index database, use the constructed effectiveness evaluation system as a candidate database, and compile the corresponding evaluation form and speech recognition database based on this database; the evaluation form is used for experts to directly score, and the speech recognition database is used for experts to use voice direct input;
- Step 4 Establish index natural language evaluation grades; determine the natural language evaluation grades of the fire extinguishing system effectiveness evaluation system, and use the evaluation grades as voice evaluation grades, and use fuzzy numbers to express each evaluation grade, and finally establish voice rating database;
- Step 5 Experts input the corresponding evaluation results; the input of evaluation results includes the following two methods: (1) In text form, the evaluation expert logs in to the WeChat applet, starts the evaluation result input, obtains the evaluation form, and writes the evaluation results into the evaluation form as required Just submit, the system accepts the evaluation results in the evaluation form, and establishes the expert fuzzy evaluation matrix; (2) adopts the voice method, uses the WeChat applet voice to broadcast the scoring items, the expert sends the voice evaluation content according to the prompt, the WeChat applet obtains the voice data and Carrying out voice recognition on the voice database, the system receives the evaluation index corresponding to the trigger of the preset voice input, assigns the recognition result to the corresponding evaluation index, and establishes an expert fuzzy evaluation matrix;
- Step 6 Determine the objective weight of the index, defuzzify the expert fuzzy evaluation matrix to obtain the index scoring matrix; based on the index scoring matrix, use the entropy weight method to determine the objective weight of the index, and obtain the objective weight of different indicators;
- Step 7 Establish the index subjective weight scoring database, establish the subjective weight scoring table, experts determine the relative influence of each index in the fire extinguishing system effectiveness evaluation index system, determine the weight comparison of each index, and input the relative weight of the corresponding indicators , and finally establish the subjective weight judgment matrix;
- the subjective weight input methods include the following two types: (1) In the form of text, the evaluation expert logs in to the WeChat applet, starts the evaluation result input, obtains the evaluation form, writes the evaluation result into the evaluation form and submits it as required That is, the system accepts the evaluation results in the evaluation form, and establishes a subjective weight judgment matrix; (2) adopts the voice method, uses the WeChat applet to broadcast the scoring items, and the expert sends the voice evaluation content according to the prompt, and the WeChat applet obtains the voice data and evaluates it.
- the speech database performs speech recognition, and the system receives the evaluation index corresponding to the trigger of the preset speech input, assigns the recognition result to the corresponding evaluation index, and establishes a subjective
- Step 8 Determine the subjective weight of the indicator. Based on this, construct the relative weight judgment matrix of the indicator, and conduct a consistency test on the weight judgment matrix. If it fails the test, it needs to be re-scored and evaluated by experts until it passes the consistency test; it will pass the consistency test. Calculate the weight matrix of the sex test to get the subjective weight of different indicators;
- Step 9 Judging the effectiveness of the fire extinguishing system, conduct a comprehensive evaluation according to the effectiveness indicators, and conduct a comprehensive evaluation based on the average results of the index score matrix and the subjective and objective weight vectors to determine the effectiveness level of the fire extinguishing system, and complete the evaluation if the effectiveness meets the requirements , if it does not meet the requirements, rectify according to the solutions and management suggestions put forward in the assessment conclusion, and reassess after the completion of the rectification until the assessment result is acceptable.
- the present invention adopts the above technical scheme to establish an evaluation method and device for a fire extinguishing system.
- an expert fuzzy evaluation matrix is established.
- the weight comparison of each index is determined, and the subjective weight of the index is constructed based on this.
- the defuzzification matrix is obtained by defuzzification according to the expert fuzzy evaluation matrix.
- the objective weight is obtained by using the entropy weight method.
- the comprehensive weight is obtained by combining the subjective and objective weights, and the index score matrix and the comprehensive weight are combined to complete the comprehensive evaluation of the transformer fire extinguishing system.
- step 6 use the formula Defuzzify the fuzzy comprehensive evaluation model for the effectiveness of the circulating transformer fire extinguishing system to obtain a defuzzified evaluation matrix V for the comprehensive evaluation of the effectiveness of the transformer fire extinguishing system; based on the defuzzified evaluation matrix V, use the formula Obtain information entropy, where e i is information entropy, and b i is the defuzzification evaluation value of the indicator;
- the specific process of obtaining the mutual influence relationship between the index and other indexes is: according to a certain scale, each index is relatively Based on the relative importance of other indicators, establish a judgment matrix U for evaluating the effectiveness of the fire extinguishing system of the converter substation, and obtain the mutual influence relationship between the indicators and other indicators; experts input the relative weights between the corresponding indicators, and finally establish a subjective weight judgment matrix;
- the form of subjective weight judgment matrix is shown in Table 1;
- the process of calculating the subjective weight vector in the step 8 is: according to the effectiveness evaluation judgment matrix U of the fire extinguishing system of the converter substation, using the formula Normalize the judgment matrix U by column, where u ij represents the relationship between the i-th factor and the j-th factor, and the matrix is obtained
- the process of verifying the consistency of the expert matrix is: calculating the maximum eigenvalue ⁇ max of the expert judgment matrix and the expert weighting matrix, and according to the maximum eigenvalue, using the formula Calculate the consistency check index of described expert judgment matrix, wherein n is matrix order; When described consistency check index is less than setting value, then judge that expert judgment matrix meets the requirements, has passed consistency check; When the consistency test index is not less than the set value, it is determined that the expert judgment matrix has not passed the consistency verification, and the values of the elements in the expert judgment matrix should continue to be adjusted until the expert judgment matrix passes the consistency verification.
- the present invention also provides a transformer fire extinguishing system effectiveness evaluation device based on natural language fuzzy analysis, including:
- Fire extinguishing system effectiveness index system building module used to select the characteristics of factors that affect the fire extinguishing effectiveness of the fire extinguishing system, and establish the effectiveness index system of the fire extinguishing system; use the constructed effectiveness evaluation system as a candidate database, and compile corresponding evaluation form and voice recognition database; determine the natural language evaluation level of the fire extinguishing system effectiveness evaluation system, and use the evaluation level as the voice evaluation level, and use fuzzy numbers to represent each evaluation level, and finally establish the voice evaluation level database;
- Fire extinguishing effectiveness index assignment module Experts input the evaluation grade results of the corresponding indexes and the subjective weight judgment matrix.
- Evaluation result input includes the following two methods: (1) In text form, the evaluation expert logs into the WeChat applet, starts the evaluation result input, obtains the evaluation form, writes the evaluation result into the evaluation form as required and submits it, and the system accepts the evaluation form (2) Using the voice method, using the WeChat applet voice to broadcast the scoring items, the expert sends the voice assessment content according to the prompt, the WeChat applet obtains the voice data and performs voice recognition on the voice database, The system receives the evaluation index corresponding to the trigger of the preset voice input, assigns the recognition result to the corresponding evaluation index, and establishes the expert fuzzy evaluation matrix;
- the comprehensive weight calculation module of the fire extinguishing effectiveness index used to determine the subjective and objective weights of each index in the fire extinguishing system effectiveness evaluation index system, that is, to defuzzify the index evaluation matrix, and use the entropy weight method to determine the objective weight of the index to obtain different The objective weight of each index, and then according to the relative influence of each index, determine the subjective weight comparison of each index, and obtain the subjective weight judgment matrix of relative importance according to the correlation of the index, and judge the subjective weight
- the matrix is subjected to a consistency check, and after the subjective weight passes the consistency check, the comprehensive weight of different indicators is obtained by calculating according to the subjective weight and the objective weight;
- Fire extinguishing effectiveness evaluation module evaluate the effectiveness of the transformer fire extinguishing system according to the index score matrix and comprehensive weight, determine the effectiveness level of the fire extinguishing system, and complete the evaluation if the effectiveness meets the requirements according to the evaluation results; Requirements are rectified according to the solutions and management suggestions proposed by the assessment conclusion. After the rectification is completed, return to step 3 and reassess until the assessment result is acceptable;
- the process of establishing the expert fuzzy evaluation matrix is as follows: firstly, a comment set is established for the evaluation system, using "excellent”, “good”, “general”, “poor” and “very Poor” five evaluation languages, and the evaluation language levels are recorded as L4 ⁇ L0 in turn; the effectiveness of the transformer fire extinguishing system evaluation index is processed by natural language fuzzy, and its membership function f(xi ik ) is:
- the function f(x ik ) represents the natural language fuzzification function of the k-th expert on the i-th evaluation index
- the process of calculating the subjective weight vector is: according to the effectiveness evaluation judgment matrix U of the fire extinguishing system of the converter substation, using the formula Normalize the judgment matrix U by column, where u ij represents the relationship between the i-th factor and the j-th factor, and the matrix is obtained
- the normalized judgment matrix Add by row.
- the purpose of the present invention is to propose a comprehensive, concise, highly reliable and stable transformer fire extinguishing system evaluation method and device, so as to be able to determine the fire extinguishing effectiveness of the fire extinguishing system from the perspective of the effectiveness of the fire extinguishing system and establish the effectiveness
- the evaluation criterion provides a basis for evaluating the fire extinguishing system.
- the present invention uses natural language for scoring, and uses fuzzy numbers and defuzzification methods for analysis and processing, which reduces the complexity of scoring and the difficulty of data processing, making the evaluation process more concise.
- the scoring method adopts two methods of manual input and voice input, which are more friendly to experts who are not good at operating smart phones and computers.
- the present invention adopts the above technical scheme to establish an evaluation method and device for a fire extinguishing system.
- an expert fuzzy evaluation matrix is established.
- the weight comparison of each index is determined, and the subjective weight of the index is constructed based on this.
- the defuzzification matrix is obtained by defuzzification according to the expert fuzzy evaluation matrix.
- the objective weight is obtained by using the entropy weight method.
- the comprehensive weight is obtained by combining the subjective and objective weights, and the index score matrix and the comprehensive weight are combined to complete the comprehensive evaluation of the transformer fire extinguishing system.
- an evaluation index system for the entire transformer fire extinguishing system is established. Natural language fuzzification and defuzzification method to determine the effectiveness of the fire extinguishing system. Experts input the evaluation grade results of the corresponding indicators through voice and text, and establish the expert fuzzy evaluation matrix, and use the entropy weight method to determine the objective weight of the indicators, and get Objective weighting of different indicators. According to the relative influence of each index in the fire extinguishing system effectiveness evaluation index system, the subjective weight of each index is determined. Experts input the subjective judgment matrix of the corresponding index through voice and text, and construct the comprehensive weight of the index based on the subjective and objective weights. The index score matrix and index comprehensive weight are processed to obtain the final evaluation score, determine the effectiveness level of the fire extinguishing system, and complete the comprehensive evaluation of the transformer fire extinguishing system.
- FIG. 1 is a schematic flowchart of a method for evaluating the effectiveness of a transformer fire extinguishing system provided by Embodiment 1 of the present invention
- Fig. 2 is a schematic structural diagram of an effectiveness evaluation device for a transformer fire extinguishing system provided by Embodiment 2 of the present invention.
- Fig. 1 is a schematic diagram of a method for evaluating the effectiveness of a transformer fire extinguishing system based on a natural language fuzzy analysis method provided by an embodiment of the present invention. As shown in Fig. 1, the method includes:
- Step 1 Collect information such as fire extinguishing system design parameters, equipment operation data, maintenance status, and substation construction environment.
- Step 2 Construct the effectiveness evaluation index system of the transformer fire extinguishing system.
- the main indicators include: "Fire extinguishing agent index”, “Fire extinguishing performance index”, “Fire extinguishing targeted index”, “Fire extinguishing safety index” four
- the factors affecting the first-level indicators are selected and combined into corresponding second-level indicators, and the effectiveness evaluation system of the transformer fire extinguishing system is jointly established.
- Table 2 shows the effectiveness evaluation system of the transformer fire extinguishing system established in Embodiment 1 of the present invention.
- Step 3 Build an indicator database. Take the constructed effectiveness evaluation system as a candidate database, and compile the corresponding evaluation form and speech recognition database based on this database.
- the evaluation form is used for direct scoring by experts, and the speech recognition database is used for direct input by experts using voice.
- Table 3 is a natural language assignment matrix for the effectiveness of the transformer fire extinguishing system.
- Step 4 Establish index natural language evaluation grades. Determine the natural language evaluation grades of the fire extinguishing system effectiveness evaluation system, and use the evaluation grades as voice evaluation grades, and use fuzzy numbers to represent each evaluation grade, and finally establish a voice evaluation grade database.
- Step 5 Experts input corresponding evaluation results.
- Evaluation result input includes the following two methods: (1) In text form, the evaluation expert logs into the WeChat applet, starts the evaluation result input, obtains the evaluation form, writes the evaluation result into the evaluation form as required and submits it, and the system accepts the evaluation form (2) Using the voice method, using the WeChat applet voice to broadcast the scoring items, the expert sends the voice assessment content according to the prompt, the WeChat applet obtains the voice data and performs voice recognition on the voice database, The system receives the evaluation index corresponding to the trigger of the preset voice input, assigns the recognition result to the corresponding evaluation index, and establishes an expert fuzzy evaluation matrix.
- Step 6 Determine the objective weight of the effectiveness index.
- the expert fuzzy evaluation matrix is defuzzified to obtain the index scoring matrix. Based on the index scoring matrix, the entropy weight method is used to determine the objective weight of the index, and the objective weight of different indexes is obtained.
- the expert fuzzy evaluation matrix is defuzzified to obtain the index scoring matrix. Based on the index scoring matrix, the entropy weight method is used to determine the objective weight of the index, and the objective weight of different indexes is obtained.
- Using the expert fuzzy evaluation matrix use the formula
- the fuzzy comprehensive evaluation matrix for the effectiveness of the circulating transformer fire extinguishing system is defuzzified to obtain a defuzzified matrix V for the comprehensive evaluation of the effectiveness of the transformer fire extinguishing system.
- Information entropy represents the degree of information chaos of the index. The smaller the entropy value, the more orderly the information, and vice versa.
- the effectiveness of the transformer fire extinguishing system evaluation index is processed by natural language fuzzy, and the processing function is shown in Table 4, and the fuzzy evaluation matrix is obtained.
- Step 7 Establish the index subjective weight speech scoring database.
- the subjective weight scoring table is established. According to the relative influence of each index in the fire extinguishing system effectiveness evaluation index system, experts determine the weight comparison of each index, the relative weight of the corresponding index of voice input, and finally establish the subjective weight judgment matrix.
- the subjective weight input methods include the following two methods: (1) In text form, the evaluation expert logs into the WeChat applet, starts the evaluation result input, obtains the evaluation form, writes the evaluation result into the evaluation form as required and submits it, and the system accepts the evaluation form (2) Use the voice method, use the WeChat applet voice to broadcast the scoring items, the expert sends the voice evaluation content according to the prompt, the WeChat applet obtains the voice data and performs voice recognition on the voice database, The system receives the evaluation index corresponding to the preset voice input trigger, assigns the recognition result to the corresponding evaluation index, and establishes a subjective weight judgment matrix.
- Tables 5 and 6 are scoring tables assigned by experts with subjective weights of effectiveness of the fire extinguishing system.
- Table 5 The subjective weight judgment scoring table of the first-level index weight
- Step 8 Determination of subjective weight of indicators. Based on the construction of the index relative weight judgment matrix, the consistency test of the weight judgment matrix is carried out. If it fails the test, it needs to be re-marked and evaluated by experts until it passes the consistency test. The subjective weights of different indicators are obtained by calculating the weight matrix that has passed the consistency test.
- the process of verifying the consistency of the expert matrix is: calculate the maximum eigenvalue ⁇ max of the expert judgment matrix and the expert weighting matrix, and according to the maximum eigenvalue, use the formula n is the matrix order, and the consistency check index of the expert judgment matrix is calculated.
- the final evaluation score is obtained by multiplying the defuzzification matrix V and the comprehensive weight vector W to determine the effectiveness level of the fire extinguishing system. If the effectiveness meets the requirements, the evaluation is completed. If the requirements are not met, the solution is proposed according to the evaluation conclusion. After the rectification is completed, return to step 3 for re-evaluation until the evaluation result is acceptable.
- the present invention also provides an evaluation device for the effectiveness of a transformer fire extinguishing system.
- Fig. 2 is a structural schematic diagram of an evaluation device for the effectiveness of a transformer fire extinguishing system provided by an embodiment of the present invention. As shown in Fig. 2, the device includes:
- Fire extinguishing system effectiveness index model building module for selecting the factor characteristics that affect the fire extinguishing system fire extinguishing effectiveness, and establishing the fire extinguishing system effectiveness index system, wherein, the factor characteristics include: fire extinguishing system design parameters, Equipment operation data, maintenance status and substation construction environment, etc.; use the constructed effectiveness evaluation system as a candidate database, and compile the corresponding evaluation form and speech recognition database based on this database.
- Determine the natural language evaluation grades of the fire extinguishing system effectiveness evaluation system and use the evaluation grades as voice evaluation grades, and use fuzzy numbers to represent each evaluation grade, and finally establish a voice evaluation grade database.
- Fire extinguishing effectiveness index assignment module Experts input the evaluation grade results of corresponding indexes and the subjective weight judgment matrix.
- Evaluation result input includes the following two methods: (1) In text form, the evaluation expert logs into the WeChat applet, starts the evaluation result input, obtains the evaluation form, writes the evaluation result into the evaluation form as required and submits it, and the system accepts the evaluation form (2) Using the voice method, using the WeChat applet voice to broadcast the scoring items, the expert sends the voice assessment content according to the prompt, the WeChat applet obtains the voice data and performs voice recognition on the voice database, The system receives the evaluation index corresponding to the trigger of the preset voice input, assigns the recognition result to the corresponding evaluation index, and establishes an expert fuzzy evaluation matrix.
- Fire extinguishing effectiveness index weight calculation module used to determine the subjective and objective weights of each index in the fire extinguishing system effectiveness evaluation index system, that is, to defuzzify the index evaluation matrix, and use the entropy weight method to determine the objective weight of the index, Obtain objective weights for different indicators. Aiming at the relative influence of each index in the fire extinguishing system effectiveness evaluation index system, determine the subjective weight comparison of each index, that is, the correlation of the index, and obtain the subjective weight judgment matrix of relative importance according to the correlation of the index, And carry out consistency check to described subjective weight judgment matrix, after described weight judgment matrix passes described consistency check, calculate according to described subjective weight judgment matrix and obtain the subjective weight of different indexes;
- IWCM Fire extinguishing effectiveness index weight calculation module
- Fire extinguishing effectiveness evaluation module evaluate the effectiveness of the transformer fire extinguishing system according to the index score matrix and comprehensive weight, determine the effectiveness level of the fire extinguishing system, and complete the evaluation if the effectiveness meets the requirements according to the evaluation results , if it does not meet the requirements, rectify according to the solutions and management suggestions put forward by the assessment conclusion, and reassess until the assessment result is acceptable.
- an evaluation index system for the entire transformer fire extinguishing system is established. Natural language fuzzification and defuzzification methods to determine the effectiveness of the fire extinguishing system. Experts use text or voice to input the evaluation results, and establish the expert fuzzy evaluation matrix, and use the entropy weight method to determine the objective weight of the index, and obtain the objective weight of different indicators. Weights. The comprehensive weight is obtained by combining the subjective and objective weights, and the index score matrix and the comprehensive weight are combined to complete the comprehensive evaluation of the transformer fire extinguishing system.
- the fire extinguishing system effectiveness index system establishment module (ISEM) is used for:
- the evaluation form is used for direct scoring by experts
- the speech recognition database is used for direct input by experts using voice.
- the fire extinguishing effectiveness index assignment module (ISM) is used for:
- evaluation result input includes the following two methods: (1) In text form, the evaluation expert logs into the WeChat applet, starts the evaluation result input, obtains the evaluation form, writes the evaluation result into the evaluation form as required and submits it, and the system accepts the evaluation form (2) Using the voice method, using the WeChat applet voice to broadcast the scoring items, the expert sends the voice assessment content according to the prompt, the WeChat applet obtains the voice data and performs voice recognition on the voice database, The system receives the evaluation index corresponding to the trigger of the preset voice input, assigns the recognition result to the corresponding evaluation index, and establishes an expert fuzzy evaluation matrix.
- the factor characteristics of the effectiveness of the transformer fire extinguishing system selected according to the establishment module of the fire extinguishing system effectiveness index system can be used as evaluation indicators.
- the comment set can use five evaluation languages: "excellent”, “good”, “general”, “poor” and “very poor”, and the corresponding evaluation language levels are L4 ⁇ L0.
- Table 4 of Example 1 it is the expert natural language scoring table for the effectiveness index of the transformer fire extinguishing system.
- the integrated weight calculation module (IWCM) of the fire extinguishing effectiveness index is the integrated weight calculation module (IWCM) of the fire extinguishing effectiveness index:
- Defuzzification-based evaluation matrix using the formula Obtain the information entropy, where e i is the information entropy, and b i is the defuzzification evaluation value of the indicator.
- An expert scoring table for the relative influence of each index in the fire extinguishing system effectiveness evaluation index system is established according to the fire extinguishing system effectiveness evaluation index, and the subjective weight comparison of each index is determined.
- Tables 2 and 3 in Example 1 are scoring tables assigned by experts with subjective weights for the effectiveness of the fire extinguishing system.
- each indicator relative to other indicators is established to evaluate the effectiveness evaluation judgment matrix U for the fire extinguishing system of the converter substation, and the mutual influence relationship between the indicators and other indicators is obtained.
- the process of calculating the subjective weight vector is as follows: according to the effectiveness evaluation judgment matrix U of the fire extinguishing system of the converter substation, use the formula Normalize the judgment matrix U by column, where u ij represents the relationship between the i-th factor and the j-th factor, and the matrix is obtained
- the final evaluation score is obtained by multiplying the defuzzification matrix V and the comprehensive weight vector W to determine the effectiveness level of the fire extinguishing system. If the effectiveness meets the requirements, the evaluation is completed. If the requirements are not met, the solution is proposed according to the evaluation conclusion. After the rectification is completed, re-evaluate until the evaluation result is acceptable, and complete the comprehensive evaluation of the effectiveness of the transformer fire extinguishing system.
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Abstract
一种基于自然语言模糊分析的变压器消防灭火系统有效性评估方法，建立消防灭火系统的评估方法及装置。通过消防灭火系统有效性的自然语言模糊化及去模糊化方法，建立了专家模糊评估矩阵。针对灭火系统有效性评估指标体系中每个指标的相对影响大小，确定出每个指标的权重对比，基于此构建指标主观权重。根据专家模糊评估矩阵进行去模糊化得到去模糊化矩阵，基于去模糊化矩阵，利用熵权法获得客观权重。通过结合主客观权重得到综合权重，将指标得分矩阵及综合权重进行结合完成变压器消防灭火系统的综合评估。
Description
本发明涉及变电站消防安全技术领域，具体来说是一种变压器消防灭火系统有效性评估方法及装置。
随着我国国民经济建设的不断发展以及创新，社会生产对电力的需求不断增加，电力工业迎来一段高速发展时期。在电力系统中，存在着大量的高电压、大电流、高蓄能和易燃易爆设备，如变压器、电容器、电力电缆等，这些设备一旦发生火灾，将会对电力系统的安全运行构成严重威胁，因此电力火灾及其安全防护工作意义重大。
变电站作为我国电力系统的重要组成部分，在输变电系统中起着承上启下的作用，是稳定有效的调配输送电压的稳定以及持续安全的接受和配送电能的关键设施。变压器在运营过程中极其容易在严重过热或内部短路故障状态下发生火灾，绝缘油和绝缘材料进一步加大了火灾的危险性，最终对人员和经济都会造成非常严重的损失。变压器消防系统作为变电站设施的重要组成部分，当发生火灾爆炸事故时，消防系统是否可靠有效工作是非常重要的。如何在满足规范要求的前提下，结合变压器实际情况，使系统在需要时能够有效投入使用，是变压器消防灭火系统设计选择的核心所在。对灭火系统进行评估也是预防火灾事故的一个重要措施，是借助现代化科学技术实现有效灭火的具体体现。
变压器起火机理复杂，火灾发展猛烈，针对不同类型、环境下的变压器提出有效的灭火评估体系是非常重要的。现有的消防灭火系统在扑灭变压器火灾能力评估方面还存在不足，如何针对不同等级及不同环境中选取适合的变压器防灭火系统仍存在困难，尚未有从灭火有效性的多个角度进行综合评估的方法和依据。针对不同变压器消防灭火系统的有效性评估方法及装置亟待提出。
期刊《项目管理技术》在2018年12月份的第16卷第12期发表的“基于变权重模糊理论的火灾风险评价研究”(张颜华北水利水电大学水利学院，河南郑州)一文中公开了以下内容：……本文在使用层次分析法确定权重向量(常权向量)的同时，引入变权处理的思想，在管理水平模糊综合评判过程中，对指标权重值进行进一步变权处理，提高火灾风险水平评价结果的科学性和合理性……。该文章采用层次分析法确定各个指标的主观权重，随意性较大，客观性不足，且主观评价时流程复杂，对于专家的软件操作水平要求高。
发明内容
本发明所要解决的技术问题在于针对现有技术中变压器消防灭火系统有效性评估过程中专家打分操作流程复杂、对专家计算机使用技能要求高的问题，提供一种操作简便、降低计算复杂度的变压器消防灭火系统有效性评估方法。
本发明通过以下技术手段实现解决上述技术问题的：
一种基于自然语言模糊分析的变压器消防灭火系统有效性评估方法，具体步骤包括：
步骤1：信息采集，对变电站设计运行信息、周围环境信息及其采用的消防灭火系统进行信息采集，采集的信息至少包括消防灭火系统设计参数、设备运行数据、维修情况及变电站建设环境等；
步骤2：灭火系统有效性评估指标体系的构建，通过对影响灭火系统灭火有效性的影响因素进行分类，共同构成灭火系统有效性评估体系；
步骤3：建立指标数据库，将所构建的有效性评估体系作为候选数据库，并基于此数据库编制对应的评估表格及语音识别数据库；评估表格用于专家直接进行打分，语音识别数据库用于专家使用语音直接输入；
步骤4：建立指标自然语言评价等级；确定消防灭火系统有效性评估体系的自然语言评价等级，并将所述的评价等级作为语音评价等级，并将每个评价等级使用模糊数表示，最终建立语音评价等级数据库；
步骤5：专家输入相应评价结果；评价结果输入包括以下两种方式：(1)采用文字形式，评估专家登录微信小程序，启动评估结果输入，获取评估表格，将评估结果按要求写入评估表格提交即可，系统接受评估表格中的评估结果，建立专家模糊评估矩阵；(2)采用语音方式，采用微信小程序语音播报评分项，专家根据提示发送语音评估内容，微信小程序获取语音数据并对所述语音数据库进行语音识别，系统接收预设的语音输入的触发对应的评估指标，将识别结果赋予对应的评估指标，建立专家模糊评估矩阵；
步骤6：指标客观权重的确定，将专家模糊评估矩阵进行去模糊化，得到指标评分矩阵；基于指标评分矩阵，使用熵权法来确定指标权重的客观大小，得到不同指标的客观权重；
步骤7：建立指标主观权重打分数据库，建立主观权重打分表，专家针对灭火系统有效性评估指标体系中每个指标的相对影响大小，确定出每个指标的权重对比，输入对应指标间的相对权重，最终建立主观权重判断矩阵；主观权重输入方式包括以下两种：(1)采用文字形式，评估专家登录微信小程序，启动评估结果输入，获取评估表格， 将评估结果按要求写入评估表格提交即可，系统接受评估表格中的评估结果，建立主观权重判断矩阵；(2)采用语音方式，采用微信小程序语音播报评分项，专家根据提示发送语音评估内容，微信小程序获取语音数据并对所述语音数据库进行语音识别，系统接收预设的语音输入的触发对应的评估指标，将识别结果赋予对应的评估指标，建立主观权重判断矩阵；
步骤8：指标主观权重的确定，基于此构建指标相对权重判断矩阵，并对权重判断矩阵进行一致性检验，若未通过检验，则需要经专家重新打分评估，直至通过一致性检验；将通过一致性检验的权重矩阵进行计算得到不同指标的主观权重；
步骤9：灭火系统有效性判定，按照有效性指标进行综合评估，根据指标得分矩阵及主客观权重向量的平均结果进行综合评估，确定消防灭火系统的有效性等级，若有效性符合要求则完成评估，若不符合要求则根据评估结论提出的解决措施和管理建议进行整改，整改完成后重新进行评估，直至评估结果可接受。
本发明采用上述技术方案，建立消防灭火系统的评估方法及装置。通过消防灭火系统有效性的自然语言模糊化及去模糊化方法，建立了专家模糊评估矩阵。针对灭火系统有效性评估指标体系中每个指标的相对影响大小，确定出每个指标的权重对比，基于此构建指标主观权重。根据专家模糊评估矩阵进行去模糊化得到去模糊化矩阵，基于去模糊化矩阵，利用熵权法获得客观权重。通过结合主客观权重得到综合权重，将指标得分矩阵及综合权重进行结合完成变压器消防灭火系统的综合评估。
进一步的，所述步骤4中，建立指标自然语言评价等级数据库具体过程为：首先针对评价体系建立评语集，采用“优秀”、“好”、“一般”、“差”和“很差”5种评价语言，评价语言等级依次记为L4～L0；使用自然语言模糊数对所述的评语集进行表达描述，记评价语言集为V＝{优秀，好，一般，差，很差}；设有M位专家参与变压器消防灭火系统有效性的评估，设第k位专家对第i个评价指标的等级评估值为x
ik；将变压器消防灭火系统评价指标的有效性进行自然语言模糊化处理，其自然语言模糊化函数f(x
ik)为：
其中，函数f(x
ik)表示第k位专家对第i个评价指标的自然语言模糊化函数；设第k位专家对评价指标的语言等级评价模糊矩阵为V＝[v
ik]，其自然语言模糊化函数数形式为v
ik＝(v
ik1，v
ik2，v
ik3)，将所有的专家模糊评估矩阵进行平均化处理得到
进一步的，所述步骤6中，使用公式
对所述环流变压器消防灭火系统有效性模糊综合评价模型去模糊化，得到对变压器消防灭火系统的有效性综合评估的去模糊化评估矩阵V；基于去模糊化的评估矩阵V，利用公式
获得信息熵，其中e
i为信息熵，b
i为指标的去模糊化评估值；
利用公式
获得熵权，其中w
i为权重，得到的行向量W
β＝(w
1,w
2,…,w
n)
T即为所求的客观熵权向量。
进一步的，所述步骤7中，针对所述变压器消防灭火系统有效性中的每一个指标，获取所述指标与其他指标的相互影响关系的具体过程为：根据一定的标度对每一个指标相对于其他指标的相对重要程度建立针对换流变电站消防灭火系统有效性评估判断矩阵U，获得所述指标与其他指标的相互影响关系；专家输入对应指标间的相对权重，最终建立主观权重判断矩阵；主观权重判断矩阵形式如表1；
表1主观权重判断矩阵
进一步的，所述步骤8中对所述主观权重向量计算的过程为：根据所述换流变电站消防灭火系统有效性评估判断矩阵U，利用公式
将判断矩阵U按列进行归一化，其中u
ij代表第i个因素对第j个因素影响关系，得到矩阵
利用公式，
将所述归一化后的判断矩阵
按行相加；
利用公式，
将所述行相加后的矩阵
进行正规化处理，得到的行向量W
α＝(w
1,w
2,…,w
n)
T即为所求的主观权重向量。
进一步的，所述步骤8中，对所述专家矩阵进行一致性验证的过程为：计算出所述专家判断矩阵与专家加权矩阵的最大特征值λ
max，并根据所述最大特征值，利用公式
计算所述专家判断矩阵的一致性检验指标，其中n为矩阵阶数；在所述一致性检验指标小于设定值时，则判定专家判断矩阵符合要求，通过了一致性检验；在所述一致性检验指标不小于设定值时，判定所述专家判断矩阵未通过一致性验证，应继续调整所述专家判断矩阵中的元素的值，直至所述专家判断矩阵通过一致性验证。
进一步的，所述步骤9中，将计算获得的主客观权重进行平均得到最终的综合权重向量，表示为W＝[w
1,w
2,…,w
n]
T；通过将去模糊化评估矩阵V与综合权重向量W点乘获得最终的评估分数，确定消防灭火系统的有效性等级，若有效性符合要求则完成评估，若不符合要求则根据评估结论提出的解决措施和管理建议进行整改，整改完成后重新进行评估，直至评估结果可接受。
本发明还提供一种基于自然语言模糊分析法的变压器消防灭火系统有效性评估装置，包括：
消防灭火系统有效性指标体系建立模块：用于选择影响灭火系统灭火有效性的因素特征，建立消防灭火系统有效性指标体系；将所构建的有效性评估体系作为候选数据库，并基于此数据库编制对应的评估表格及语音识别数据库；确定消防灭火系统有效性评估 体系的自然语言评价等级，并将所述的评价等级作为语音评价等级，并将每个评价等级使用模糊数表示，最终建立语音评价等级数据库；
灭火有效性指标赋分模块：专家输入相应指标的评价等级结果及主观权重判断矩阵。评价结果输入包括以下两种方式：(1)采用文字形式，评估专家登录微信小程序，启动评估结果输入，获取评估表格，将评估结果按要求写入评估表格提交即可，系统接受评估表格中的评估结果，建立专家模糊评估矩阵；(2)采用语音方式，采用微信小程序语音播报评分项，专家根据提示发送语音评估内容，微信小程序获取语音数据并对所述语音数据库进行语音识别，系统接收预设的语音输入的触发对应的评估指标，将识别结果赋予对应的评估指标，建立专家模糊评估矩阵；
灭火有效性指标综合权重计算模块：用于确定灭火系统有效性评估指标体系中每个指标的主客观权重，即将指标评估矩阵去模糊化，并使用熵权法确定指标权重的客观大小，得到不同指标的客观权重，然后针对每个指标的相对影响大小，确定出每个指标的主观权重对比，针对所述的指标关联情况，获取相对重要性的主观权重判断矩阵，并对所述主观权重判断矩阵进行一致性检验，在所述主观权重通过所述一致性检验后，根据所述主观权重与客观权重进行计算得到不同指标的综合权重；
灭火有效性评估模块：根据所述指标得分矩阵和综合权重对变压器消防灭火系统进行有效性评估，确定消防灭火系统的有效性等级，根据评估结果，若有效性符合要求则完成评估，若不符合要求则根据评估结论提出的解决措施和管理建议进行整改，整改完成后返回步骤3，重新进行评估，直到评估结果可接受；
进一步的，所述灭火有效性指标赋分模块中，建立专家模糊评估矩阵的流程为：首先针对评价体系建立评语集，采用“优秀”、“好”、“一般”、“差”和“很差”5种评价语言，评价语言等级依次记为L4～L0；将变压器消防灭火系统评价指标的有效性进行自然语言模糊化处理，其隶属度函数f(x
ik)为:
所述灭火有效性评估模块中，设第k位专家对评价指标的语言等级评价模糊矩阵为V＝[v
ik]，其自然语言模糊化函数形式为v
ik＝(v
ik1，v
ik2，v
ik3)，将所述所有的专家模糊评估矩阵进行平均化处理得到
进一步的，所述灭火有效性指标综合权重计算模块中：使用公式
对所述环流变压器消防灭火系统有效性模糊综合评价模型去模糊化，得到对变压器消防灭火系统的有效性综合评估的去模糊化矩阵V；基于去模糊化的评估矩阵，利用公式
获得信息熵，其中e
i为信息熵，b
i为指标的去模糊化评估值；利用公式
获得熵权，其中w
i为客观权重，得到向量W
β＝(w
1,w
2,…,w
n)
T即为所求的客观权重向量；
所述灭火有效性指标综合权重计算模块中，主观权重向量计算的过程为：根据所述换流变电站消防灭火系统有效性评估判断矩阵U，利用公式
将判断矩阵U按列进行归一化，其中u
ij代表第i个因素对第j个因素影响关系，得到矩阵
利用公式，
将所述归一化后的判断矩阵
按行相加。利用公式，
将所述行相加后的矩阵
进行正规化处理，得到的行向量W＝(w
1,w
2,…,w
n)
T即为所求的主观权重向量；
进一步的，灭火有效性评估模块中风险评估具体为：最终将计算获得的主客观权重进行平均得到最终的综合权重向量，表示为W＝[w
1,w
2,…,w
n]
T；通过将去模糊化矩阵V与综合权重向量W点乘获得最终的评估分数，确定消防灭火系统的有效性等级，若有效性符合要求则完成评估，若不符合要求则根据评估结论提出的解决措施和管理建议进行整改，整改完成后重新进行评估，直至评估结果可接受，完成对变压器消防灭火系统的有效性综合评估。
本发明的优点在于：
本发明的目的在于提出一种综合、简洁、可靠性高、稳定性强变压器消防灭火系统评估方法及装置，以便能够从灭火系统有效性的角度，确定消防灭火系统的灭火有效性，建立有效性的评估准则，为评估消防灭火系统提供依据，本发明采用自然语言进行打分，采用模糊数与去模糊化方式进行分析处理，降低了打分复杂程度及数据处理难度，使得评估流程更加简洁。打分方式采用手动输入和语音输入两种方式，对于不善于智能手机和计算机操作的专家较为友好。
本发明采用上述技术方案，建立消防灭火系统的评估方法及装置。通过消防灭火系统有效性的自然语言模糊化及去模糊化方法，建立了专家模糊评估矩阵。针对灭火系统有效性评估指标体系中每个指标的相对影响大小，确定出每个指标的权重对比，基于此构建指标主观权重。根据专家模糊评估矩阵进行去模糊化得到去模糊化矩阵，基于去模糊化矩阵，利用熵权法获得客观权重。通过结合主客观权重得到综合权重，将指标得分矩阵及综合权重进行结合完成变压器消防灭火系统的综合评估。
通过对影响灭火系统灭火有效性的因素进行分类，建立起整个变压器消防灭火系统评估指标体系。确定消防灭火系统有效性的自然语言模糊化及去模糊化方法，专家通过语音及文字输入相应指标的评价等级结果，并建立专家模糊评估矩阵，并使用熵权法确定指标权重的客观大小，得到不同指标的客观权重。针对灭火系统有效性评估指标体系中每个指标的相对影响大小，确定出每个指标的主观权重大小，专家通过语音及文字输入相应指标主观判断矩阵，基于主客观权重构建指标综合权重。将指标得分矩阵及指标综合权重进行处理获得最终的评估分数，确定消防灭火系统的有效性等级，完成变压器消防灭火系统的综合评估。
图1为本发明实施例一提供的变压器消防灭火系统有效性评估方法的流程示意图；
图2为本发明实施例二提供的变压器消防灭火系统有效性评估装置的结构示意图。
为使本发明实施例的目的、技术方案和优点更加清楚，下面将结合本发明实施例，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。
实施例一
图1为本发明实施例提供的一种基于自然语言模糊分析法的变压器消防灭火系统有效性评估方法的原理图，如图1所示，所述方法包括：
步骤1：采集消防灭火系统设计参数、设备运行数据、维修情况及变电站建设环境等信息。
步骤2：构建变压器灭火系统有效性评估指标体系。选择影响变压器灭火系统灭火有效性的主要指标组成评价指标体系，其中，所述主要指标包括：“灭火剂指标”、“灭火性能指标”、“灭火针对性指标”、“灭火安全性指标”四个有效性一级指标，基于文献查阅分析，选取影响一级指标的因素，组合为相应的二级指标，共同建立了变压器消防灭火系统有效性评估体系。表2为本发明实施例一中所建立的变压器消防灭火系统有效性评估体系。
表2 变压器消防灭火系统有效性评估体系
步骤3：建立指标数据库。将所构建的有效性评估体系作为候选数据库，并基于此数据库编制对应的评估表格及语音识别数据库。评估表格用于专家直接进行打分，语音识别数据库用于专家使用语音直接输入。
示例性的，表3为所述变压器消防灭火系统有效性进行自然语言赋分矩阵。
表3 变压器消防灭火系统有效性指标专家自然语言赋分矩阵
步骤4：建立指标自然语言评价等级。确定消防灭火系统有效性评估体系的自然语言评价等级，并将所述的评价等级作为语音评价等级，并将每个评价等级使用模糊数表示，最终建立语音评价等级数据库。
表4 自然语言模糊化函数
| 语言评价等级 | 含义及符号 | 自然语言模糊化函数 |
| L4 | 优秀 | (0.75，1.00，1.00) |
| L3 | 好 | (0.50，0.75，1.00) |
| L2 | 一般 | (0.25，0.50，0.75) |
| L1 | 差 | (0，0.25，0.50) |
| L0 | 很差 | (0，0，0.25) |
将所述所有的专家模糊评估矩阵进行平均化处理得到
步骤5：专家输入相应评价结果。评价结果输入包括以下两种方式：(1)采用文字形式，评估专家登录微信小程序，启动评估结果输入，获取评估表格，将评估结果按要求写入评估表格提交即可，系统接受评估表格中的评估结果，建立专家模糊评估矩阵；(2)采用语音方式，采用微信小程序语音播报评分项，专家根据提示发送语音评估内容，微信小程序获取语音数据并对所述语音数据库进行语音识别，系统接收预设的语音输入的触发对应的评估指标，将识别结果赋予对应的评估指标，建立专家模糊评估矩阵。
步骤6：有效性指标客观权重确定。将专家模糊评估矩阵进行去模糊化，得到指标评分矩阵。基于指标评分矩阵，使用熵权法来确定指标权重的客观大小，得到不同指标的客观权重。将专家模糊评估矩阵进行去模糊化，得到指标评分矩阵。基于指标评分矩阵，使用熵权法来确定指标权重的客观大小，得到不同指标的客观权重。使用所述专家模糊评估矩阵
利用公式
对所述环流变压器消防灭火系统有效性模糊综合评价矩阵去模糊化，得到对变压器消防灭火系统的有效性综合评估的去模糊化矩阵V。
信息熵代表指标的信息混乱程度，熵值越小信息越有序，反之则越无序。基于去模糊化的评估矩阵，利用公式
获得信息熵，其中ei为信息熵，b
i为指标的去模糊化评估值。利用公式
获得熵权，其中w
i为客观权重，得到的行向量W
β＝(w
1,w
2,…,w
n)
T即为所求的客观熵权向量。
将变压器消防灭火系统评价指标的有效性进行自然语言模糊化处理，处理函数如表4所示，得到模糊评估矩阵。
步骤7：建立指标主观权重语音打分数据库。建立主观权重打分表，专家针对灭火系统有效性评估指标体系中每个指标的相对影响大小，确定出每个指标的权重对比，语音输入对应指标间的相对权重，最终建立主观权重判断矩阵。主观权重输入方式包括以下两种：(1)采用文字形式，评估专家登录微信小程序，启动评估结果输入，获取评估 表格，将评估结果按要求写入评估表格提交即可，系统接受评估表格中的评估结果，建立主观权重判断矩阵；(2)采用语音方式，采用微信小程序语音播报评分项，专家根据提示发送语音评估内容，微信小程序获取语音数据并对所述语音数据库进行语音识别，系统接收预设的语音输入的触发对应的评估指标，将识别结果赋予对应的评估指标，建立主观权重判断矩阵。
示例性的，表5、6为所述消防灭火系统有效性主观权重专家进行赋分的打分表。
表5 一级指标权主观权重判断打分表
表6 二级指标主观权重判断打分表
步骤8：指标主观权重的确定。基于构建指标相对权重判断矩阵，对权重判断矩阵进行一致性检验，若未通过检验，则需要经专家重新打分评估，直至通过一致性检验。将通过一致性检验的权重矩阵进行计算得到不同指标的主观权重。
对所述专家矩阵进行一致性验证的过程为:计算出所述专家判断矩阵与专家加权矩阵的最大特征值λ
max，并根据所述最大特征值，利用公式
n为矩阵阶数，计算所述专家判断矩阵的一致性检验指标。
在所述一致性检验指标小于设定值时，则判定专家判断矩阵符合要求，通过了一致性检验。
在所述一致性检验指标不小于设定值时，判定所述专家判断矩阵未通过一致性验证，应继续调整所述专家判断矩阵中的元素的值，直至所述专家判断矩阵通过一致性验证。
步骤6，灭火有效性评估，最终将计算获得的主客观权重进行平均得到最终的综合权重向量，表示为W＝[w
1,w
2,…,w
n]
T。通过将去模糊化矩阵V与综合权重向量W点乘获得最终的评估分数，确定消防灭火系统的有效性等级，若有效性符合要求则完成评估，若不符合要求则根据评估结论提出的解决措施和管理建议进行整改，整改完成后返回步骤3进行重新评估，直至评估结果可接受。
灭火系统有效性评估的方法可以为：
(1)采用微信小程序形式，评估专家登录微信小程序，获取评估表，填写评估表提交即可；
(2)采用语音方式，对于不擅长智能手机或计算机操作的专家，采用微信小程序语音播报评分项，专家根据提示发送语音评估内容，微信小程序自动将语音信息转换成评估结果。本实施例中的语音识别技术为
实施例二
与本发明图1所示实施例一相对应，本发明还提供了一种变压器消防灭火系统有效性的评估装置。
图2为本发明实施例提供的一种变压器消防灭火系统有效性的评估装置的结构示意图，如图2所示，所述装置包括：
消防灭火系统有效性指标模型建立模块(ISEM)：用于选择影响灭火系统灭火有效性的因素特征，建立消防灭火系统有效性指标体系，其中，所述因素特征，包括：消防灭火系统设计参数、设备运行数据、维修情况及变电站建设环境等；将所构建的有效性评估体系作为候选数据库，并基于此数据库编制对应的评估表格及语音识别数据库。确定消防灭火系统有效性评估体系的自然语言评价等级，并将所述的评价等级作为语音评价等级，并将每个评价等级使用模糊数表示，最终建立语音评价等级数据库。
灭火有效性指标赋分模块(ISM)：专家输入相应指标的评价等级结果及主观权重判断矩阵。评价结果输入包括以下两种方式：(1)采用文字形式，评估专家登录微信小程序，启动评估结果输入，获取评估表格，将评估结果按要求写入评估表格提交即可，系统接受评估表格中的评估结果，建立专家模糊评估矩阵；(2)采用语音方式，采用微信小程序语音播报评分项，专家根据提示发送语音评估内容，微信小程序获取语音数据并对所述语音数据库进行语音识别，系统接收预设的语音输入的触发对应的评估指标，将识别结果赋予对应的评估指标，建立专家模糊评估矩阵。
灭火有效性指标权重计算模块(IWCM)：用于确定灭火系统有效性评估指标体系中每个指标的主客观权重，即将指标评估矩阵去模糊化，并使用熵权法确定指标权重的客观大小，得到不同指标的客观权重。针对灭火系统有效性评估指标体系中每个指标的相对影响大小，确定每个指标的主观权重对比，即指标的关联情况，针对所述的指标关联情况，获取相对重要性的主观权重判断矩阵，并对所述主观权重判断矩阵进行一致性检验，在所述权重判断矩阵通过所述一致性检验后，根据所述主观权重判断矩阵进行计算得到不同指标的主观权重；
灭火有效性评估模块(EEM)：：根据所述指标得分矩阵和综合权重对变压器消防灭火系统进行有效性评估，确定消防灭火系统的有效性等级，根据评估结果，若有效性符 合要求则完成评估，若不符合要求则根据评估结论提出的解决措施和管理建议进行整改，重新进行评估，直到评估结果可接受。
应用本发明图2所示实施例，建立消防灭火系统的评估方法及装置。通过对影响灭火系统灭火有效性的因素进行分类，建立起整个变压器消防灭火系统评估指标体系。确定消防灭火系统有效性的自然语言模糊化及去模糊化方法，专家使用文字或语音输入评估结果，并建立专家模糊评估矩阵，并使用熵权法确定指标权重的客观大小，得到不同指标的客观权重。通过结合主客观权重得到综合权重，将指标得分矩阵及综合权重进行结合完成变压器消防灭火系统的综合评估。
示例性的：
所述消防灭火系统有效性指标体系建立模块(ISEM)，用于：
根据文献查阅，现场调研等方式选择影响灭火系统灭火有效性的因素特征，建立消防灭火系统有效性指标体系。如实例一中的表1为变压器消防灭火系统有效性评估指标选取结果。
将所构建的有效性评估体系作为候选数据库，并基于此数据库编制对应的评估表格及语音识别数据库。评估表格用于专家直接进行打分，语音识别数据库用于专家使用语音直接输入。
确定消防灭火系统有效性评估体系的自然语言评价等级，并将所述的评价等级作为语音评价等级，并将每个评价等级使用模糊数表示，最终建立语音评价等级数据库。
所述灭火有效性指标赋分模块(ISM)，用于：
确定消防灭火系统有效性的自然语言模糊化方法，专家输入相应指标的评价等级结果及主观权重判断矩阵。评价结果输入包括以下两种方式：(1)采用文字形式，评估专家登录微信小程序，启动评估结果输入，获取评估表格，将评估结果按要求写入评估表格提交即可，系统接受评估表格中的评估结果，建立专家模糊评估矩阵；(2)采用语音方式，采用微信小程序语音播报评分项，专家根据提示发送语音评估内容，微信小程序获取语音数据并对所述语音数据库进行语音识别，系统接收预设的语音输入的触发对应的评估指标，将识别结果赋予对应的评估指标，建立专家模糊评估矩阵。
可以根据所述消防灭火系统有效性指标体系建立模块选择的所述变压器消防灭火系统有效性的因素特征作为评估指标。
可以将评语集采用“优秀”、“好”、“一般”、“差”和“很差”5种评价语言，其对应的评价语言等级依次为L4～L0。如实施例一中表4变压器消防灭火系统有效性指标专家自然语言打分表。根据变压器消防灭火系统有效性指标专家自然语言打分表将变压器消防灭火系统评价指标的有效性进行自然语言模糊化处理，利用自然语言模糊化函数v
ik＝(v
ik1，v
ik2，v
ik3)将所有的专家模糊评估矩阵进行平均化处理得到
所述灭火有效性指标综合权重计算模块(IWCM)：
客观权重向量计算过程：使用公式
对所述环流变压器消防灭火系统有效性模糊综合评价模型去模糊化，得到对变压器消防灭火系统的有效性综合评估的去模糊化矩阵V。
基于去模糊化的评估矩阵，利用公式
获得信息熵，其中e
i为信息熵，b
i为指标的去模糊化评估值。
利用公式
获得熵权，其中w
i为客观权重，得到的行向量W
β＝(w
1,w
2,…,w
n)
T即为所求的客观熵权向量。
根据所述灭火系统有效性评估指标建立针对灭火系统有效性评估指标体系中每个指标的相对影响大小的专家打分表，确定每个指标的主观权重对比。如实例一中表2、3为所述消防灭火系统有效性主观权重专家进行赋分的打分表。
根据一定的标度对每一个指标相对于其他指标的相对重要程度建立针对换流变电站消防灭火系统有效性评估判断矩阵U，获得所述指标与其他指标的相互影响关系。
主观权重向量计算的过程为：根据所述换流变电站消防灭火系统有效性评估判断矩阵U，利用公式
将判断矩阵U按列进行归一化，其中u
ij代表第i个因素对第j个因素影响关系，得到矩阵
利用公式，
将所述归一化后的判断矩阵
按行相加。
利用公式，
将所述行相加后的矩阵
进行正规化处理，得到的行向量W＝(w
1,w
2,…,w
n)
T即为所求的权重向量。
对所述专家矩阵进行一致性验证的过程为：
计算出所述专家判断矩阵与专家加权矩阵的最大特征值λ
max，并根据所述最大特征值，利用公式
n为矩阵阶数，计算所述专家判断矩阵的一致性检验指标。
在所述一致性检验指标小于设定值时，则判定专家判断矩阵符合要求，通过了一致性检验。
在所述一致性检验指标不小于设定值时，判定所述专家判断矩阵未通过一致性验证，应继续调整所述专家判断矩阵中的元素的值，直至所述专家判断矩阵通过一致性验证。
所述灭火有效性评估模块(EEM)，用于将计算获得的主客观权重进行平均得到最终的综合权重向量，表示为W＝[w
1,w
2,…,w
n]
T。通过将去模糊化矩阵V与综合权重向量W点乘获得最终的评估分数，确定消防灭火系统的有效性等级，若有效性符合要求则完成评估，若不符合要求则根据评估结论提出的解决措施和管理建议进行整改，整改完成后重新进行评估，直至评估结果可接受，完成对变压器消防灭火系统的有效性综合评估。
以上实施例仅用以说明本发明的技术方案，而非对其限制；尽管参照前述实施例对本发明进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本发明各实施例技术方案的精神和范围。
Claims (11)
- 一种基于自然语言模糊分析的变压器消防灭火系统有效性评估方法，其特征在于，具体步骤包括：步骤1：信息采集，对变电站设计运行信息、周围环境信息及其采用的消防灭火系统进行信息采集，采集的信息至少包括消防灭火系统设计参数、设备运行数据、维修情况及变电站建设环境等；步骤2：灭火系统有效性评估指标体系的构建，通过对影响灭火系统灭火有效性的影响因素进行分类，共同构成灭火系统有效性评估体系；步骤3：建立指标数据库，将所构建的有效性评估体系作为候选数据库，并基于此数据库编制对应的评估表格及语音识别数据库；评估表格用于专家直接进行打分，语音识别数据库用于专家使用语音直接输入；步骤4：建立指标自然语言评价等级；确定消防灭火系统有效性评估体系的自然语言评价等级，并将所述的评价等级作为语音评价等级，并将每个评价等级使用模糊数表示，最终建立语音评价等级数据库；步骤5：专家输入相应评价结果；评价结果输入包括以下两种方式：(1)采用文字形式，评估专家登录微信小程序，启动评估结果输入，获取评估表格，将评估结果按要求写入评估表格提交即可，系统接受评估表格中的评估结果，建立专家模糊评估矩阵；(2)采用语音方式，采用微信小程序语音播报评分项，专家根据提示发送语音评估内容，微信小程序获取语音数据并对所述语音数据库进行语音识别，系统接收预设的语音输入的触发对应的评估指标，将识别结果赋予对应的评估指标，建立专家模糊评估矩阵；步骤6：指标客观权重的确定，将专家模糊评估矩阵进行去模糊化，得到指标评分矩阵；基于指标评分矩阵，使用熵权法来确定指标权重的客观大小，得到不同指标的客观权重；步骤7：建立指标主观权重打分数据库，建立主观权重打分表，专家针对灭火系统有效性评估指标体系中每个指标的相对影响大小，确定出每个指标的权重对比，输入对应指标间的相对权重，最终建立主观权重判断矩阵；主观权重输入方式包括以下两种：(1)采用文字形式，评估专家登录微信小程序，启动评估结果输入，获取评估表格，将评估结果按要求写入评估表格提交即可，系统接受评估表格中的评估结果，建立主观权重判断矩阵；(2)采用语音方式，采用微信小程序语音播报评分项，专家根据提示发送语音评估内容，微信小程序获取语音数据并对所述语音数据库进行语音识别，系统接 收预设的语音输入的触发对应的评估指标，将识别结果赋予对应的评估指标，建立主观权重判断矩阵；步骤8：指标主观权重的确定，基于此构建指标相对权重判断矩阵，并对权重判断矩阵进行一致性检验，若未通过检验，则需要经专家重新打分评估，直至通过一致性检验；将通过一致性检验的权重矩阵进行计算得到不同指标的主观权重；步骤9：灭火系统有效性判定，按照有效性指标进行综合评估，根据指标得分矩阵及主客观权重向量的平均结果进行综合评估，确定消防灭火系统的有效性等级，若有效性符合要求则完成评估，若不符合要求则根据评估结论提出的解决措施和管理建议进行整改，整改完成后重新进行评估，直至评估结果可接受。
- 如权利要求1所述的基于自然语言模糊分析的变压器消防灭火系统有效性评估方法，其特征在于，所述步骤4中，建立指标自然语言评价等级数据库具体过程为：首先针对评价体系建立评语集，采用“优秀”、“好”、“一般”、“差”和“很差”5种评价语言，评价语言等级依次记为L4～L0；使用自然语言模糊数对所述的评语集进行表达描述，记评价语言集为V＝{优秀，好，一般，差，很差}；设有M位专家参与变压器消防灭火系统有效性的评估，设第k位专家对第i个评价指标的等级评估值为x ik；将变压器消防灭火系统评价指标的有效性进行自然语言模糊化处理，其自然语言模糊化函数f(x ik)为：
其中，函数f(x ik)表示第k位专家对第i个评价指标的自然语言模糊化函数；设第k位专家对评价指标的语言等级评价模糊矩阵为V＝[v ik]，其自然语言模糊化函数数形式为v ik＝(v ik1，v ik2，v ik3)，将所有的专家模糊评估矩阵进行平均化处理得到
- 如权利要求1所述的基于自然语言模糊分析的变压器消防灭火系统有效性评估方法，其特征在于，所述步骤6中，使用公式对所述环流变压器消防灭火系统有效性模糊综合评价模型去模糊化，得到对变压器消防灭火系统的有效性综合评估的去模糊化评估矩阵V；基于去模糊化的评估矩阵V，利用公式
获得信息熵，其中e i为信息熵，b i为指标的去模糊化评估值；
利用公式获得熵权，其中w i为权重，得到的行向量W β＝(w 1,w 2,…,w n) T即为所求的客观熵权向量。
- 如权利要求1所述的基于自然语言模糊分析的变压器消防灭火系统有效性评估方法，其特征在于，所述步骤7中，针对所述变压器消防灭火系统有效性中的每一个指标，获取所述指标与其他指标的相互影响关系的具体过程为：根据一定的标度对每一个指标相对于其他指标的相对重要程度建立针对换流变电站消防灭火系统有效性评估判断矩阵U，获得所述指标与其他指标的相互影响关系；专家输入对应指标间的相对权重，最终建立主观权重判断矩阵；主观权重判断矩阵形式如表1；表1主观权重判断矩阵
- 如权利要求1所述的基于自然语言模糊分析的变压器消防灭火系统有效性评估方法，其特征在于，所述步骤8中对所述主观权重向量计算的过程为：根据所述换流变电站消防灭火系统有效性评估判断矩阵U，利用公式将判断矩阵U按列进行归一化，其中u ij代表第i个因素对第j个因素影响关系，得到矩阵
利用公式，将所述归一化后的判断矩阵
按行相加；
利用公式，将所述行相加后的矩阵
进行正规化处理，得到的行向量W α＝(w 1,w 2,…,w n) T即为所求的主观权重向量。
- 如权利要求5所述的基于自然语言模糊分析的变压器消防灭火系统有效性评估方法，其特征在于，所述步骤8中，对所述专家矩阵进行一致性验证的过程为：计算出所述专家判断矩阵与专家加权矩阵的最大特征值λ max，并根据所述最大特征值，利用公式计算所述专家判断矩阵的一致性检验指标，其中n为矩阵阶数；在所述一致性检验指标小于设定值时，则判定专家判断矩阵符合要求，通过了一致性检验；在所述一致性检验指标不小于设定值时，判定所述专家判断矩阵未通过一致性验证，应继续调整所述专家判断矩阵中的元素的值，直至所述专家判断矩阵通过一致性验证。
- 如权利要求1所述的基于自然语言模糊分析的变压器消防灭火系统有效性评估方法，其特征在于，所述步骤9中，将计算获得的主客观权重进行平均得到最终的综合权重向量，表示为通过将去模糊化评估矩阵V与综合权重向量W点乘获得最终的评估分数，确定消防灭火系统的有效性等级，若有效性符合要求则完成评估，若不符合要求则根据评估结论提出的解决措施和管理建议进行整改，整改完成后重新进行评估，直至评估结果可接受。
- 基于自然语言模糊分析法的变压器消防灭火系统有效性评估装置，其特征在于，包括：消防灭火系统有效性指标体系建立模块：用于选择影响灭火系统灭火有效性的因素特征，建立消防灭火系统有效性指标体系；将所构建的有效性评估体系作为候选数据库，并基于此数据库编制对应的评估表格及语音识别数据库；确定消防灭火系统有效性评估体系的自然语言评价等级，并将所述的评价等级作为语音评价等级，并将每个评价等级使用模糊数表示，最终建立语音评价等级数据库；灭火有效性指标赋分模块：专家输入相应指标的评价等级结果及主观权重判断矩阵。评价结果输入包括以下两种方式：(1)采用文字形式，评估专家登录微信小程序，启动评估结果输入，获取评估表格，将评估结果按要求写入评估表格提交即可，系统接受评估表格中的评估结果，建立专家模糊评估矩阵；(2)采用语音方式，采用微信小程序语 音播报评分项，专家根据提示发送语音评估内容，微信小程序获取语音数据并对所述语音数据库进行语音识别，系统接收预设的语音输入的触发对应的评估指标，将识别结果赋予对应的评估指标，建立专家模糊评估矩阵；灭火有效性指标综合权重计算模块：用于确定灭火系统有效性评估指标体系中每个指标的主客观权重，即将指标评估矩阵去模糊化，并使用熵权法确定指标权重的客观大小，得到不同指标的客观权重，然后针对每个指标的相对影响大小，确定出每个指标的主观权重对比，针对所述的指标关联情况，获取相对重要性的主观权重判断矩阵，并对所述主观权重判断矩阵进行一致性检验，在所述主观权重通过所述一致性检验后，根据所述主观权重与客观权重进行计算得到不同指标的综合权重；灭火有效性评估模块：根据所述指标得分矩阵和综合权重对变压器消防灭火系统进行有效性评估，确定消防灭火系统的有效性等级，根据评估结果，若有效性符合要求则完成评估，若不符合要求则根据评估结论提出的解决措施和管理建议进行整改，整改完成后返回步骤3，重新进行评估，直到评估结果可接受；
- 如权利要求8所述的自然语言模糊分析法的变压器消防灭火系统有效性评估装置，其特征在于：所述灭火有效性指标赋分模块中，建立专家模糊评估矩阵的流程为：首先针对评价体系建立评语集，采用“优秀”、“好”、“一般”、“差”和“很差”5种评价语言，评价语言等级依次记为L4～L0；将变压器消防灭火系统评价指标的有效性进行自然语言模糊化处理，其隶属度函数f(x ik)为:函数f(x ik)表示第k位专家对第i个评价指标的自然语言模糊化函数；
所述灭火有效性评估模块中，设第k位专家对评价指标的语言等级评价模糊矩阵为V＝[v ik]，其自然语言模糊化函数形式为v ik＝(v ik1，v ik2，v ik3)，将所述所有的专家模糊评估矩阵进行平均化处理得到
- 如权利要求/8所述的自然语言模糊分析法的变压器消防灭火系统有效性评估装置，其特征在于：所述灭火有效性指标综合权重计算模块中：使用公式对所述环流变压器消防灭火系统有效性模糊综合评价模型去模糊化，得到对变压器消防灭火系统的有效性综合评估的去模糊化矩阵V；基于去模糊化的评估矩阵，利用公式
获得信息熵，其中e i为信息熵，b i为指标的去模糊化评估值；利用公式
获得熵权，其中w i为客观权重，得到向量W β＝(w 1,w 2,…,w n) T即为所求的客观权重向量；
所述灭火有效性指标综合权重计算模块中，主观权重向量计算的过程为：根据所述换流变电站消防灭火系统有效性评估判断矩阵U，利用公式将判断矩阵U按列进行归一化，其中u ij代表第i个因素对第j个因素影响关系，得到矩阵
利用公式，将所述归一化后的判断矩阵
按行相加。利用公式，
将所述行相加后的矩阵
进行正规化处理，得到的行向量W＝(w 1,w 2,…,w n) T即为所求的主观权重向量；
- 如权利要求8所述的自然语言模糊分析法的变压器消防灭火系统有效性评估装置，其特征在于：灭火有效性评估模块中风险评估具体为：最终将计算获得的主客观权重进行平均得到最终的综合权重向量，表示为通过将去模糊化矩阵V与综合权重向量W点乘获得最终的评估分数，确定消防灭火系统的有效性等级，若有效性符合要求则完成评估，若不符合要求则根据评估结论提出的解决措施和管理建议进行整改，整改完成后重新进行评估，直至评估结果可接受，完成对变压器消防灭火系统的有效性综合评估。
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| CN116089787A (zh) * | 2023-03-08 | 2023-05-09 | 中国人民解放军海军工程大学 | 基于层次分析法的船舶子系统运行状态分析方法及系统 |
| CN115907484A (zh) * | 2023-03-09 | 2023-04-04 | 泰安市特种设备检验研究院 | 一种承压特种设备安全状态在线评估方法 |
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