Cockpit microenvironment comfort evaluation method

Abstract

The invention relates to the field of cockpit microenvironment evaluation, in particular to a cockpit microenvironment comfort evaluation method. A relatively complete cockpit microenvironment comfort evaluation system is established; an evaluation result can be quantitatively given in the micro-environment comfort evaluation of the cockpit, which is mostly single-factor evaluation at present; the tedious steps in the evaluation process are simplified, the time required for evaluation is greatly shortened, and the evaluation result can be quickly obtained.

Description

Technical Field

[0001] The present invention relates to the field of cockpit microenvironment evaluation, and in particular to a cockpit microenvironment comfort evaluation method. Background Art

[0002] The cockpit is the most prominent and concentrated place of the aircraft human-machine interface. The pilot, cockpit and cabin environment form a complex human-machine-environment system. The design of the human-machine-environment system generally includes steps such as determining system goals and constraints, human-machine function analysis and allocation, software and hardware and human-machine interface design, and system comprehensive evaluation. Among them, microenvironment comfort evaluation is an indispensable and important link. In this regard, on the basis of the single factor analysis of comfort of each microenvironment in China, an integrated quantitative analysis of the cockpit microenvironment comfort evaluation is carried out. The evaluation results can provide a decision-making basis for the layout and structural design of the cabin equipment, and can timely discover and feedback problems and optimize them, so that pilots can be more comfortable and efficient when performing flight missions, thereby ensuring the safe operation of the aircraft. In addition, the existing cockpit microenvironment comfort evaluation in China generally only includes a single indicator evaluation of one of the categories such as heat and humidity, vibration, and noise. The usual evaluation method is difficult to comprehensively and accurately consider the many factors in the evaluation index system. At the same time, most of the evaluation systems are incomplete and the steps are cumbersome, and are usually only applicable to specific models of aircraft. Therefore, a universal, fast and simple evaluation method is urgently needed in this field. Summary of the invention

[0003] In response to the above problems, the purpose of this application is to conduct a systematic evaluation, refer to domestic and foreign comfort analysis cases, combine relevant standard requirements, medical research results and human physiological needs, based on the impact of different environments on human comfort, and target the different environments in which crew members are located. The improved Delphi-improved hierarchical analysis-fuzzy comprehensive evaluation method is used to conduct a comprehensive evaluation of the cockpit microenvironment comfort, while simplifying the evaluation process.

[0004] To this end, the first technical solution of the present application provides a cockpit microenvironment comfort evaluation method, comprising the following steps:

[0005] Establish a comfort evaluation index system: determine the factors affecting cockpit microenvironment comfort and subdivide them to obtain evaluation indicators, and construct a cockpit microenvironment comfort evaluation index system through the improved Delphi method;

[0006] Calculate the weight of evaluation index: Analyze the weight of each influencing factor based on the improved hierarchical method and expert group weight construction method, adjust each weight through the local penalty-incentive variable weight vector function, and obtain the weight of evaluation index;

[0007] Determine the evaluation index value: evaluate each index through the test evaluation scale method, etc., and perform normalization.

[0008] Determine the index membership function and fuzzy comprehensive evaluation: construct the index membership function and obtain the fuzzy comprehensive evaluation matrix based on it, and then combine it with the weight matrix to obtain the cockpit microenvironment comfort evaluation result through fuzzy comprehensive evaluation.

[0009] Furthermore, the factors affecting the cockpit microenvironment comfort are temperature, humidity, pressure, ventilation, vibration, noise, and lighting.

[0010] Furthermore, the improved Delphi method is to ask experts to rank the degree of influence of evaluation indicators on comfort through questionnaires, calculate the concentration and dispersion of expert opinions, return to the experts to repeat the above steps, compare the coordination coefficients of the two rounds of evaluation results, and then screen and determine the cockpit microenvironment comfort evaluation index system through the threshold method.

[0011] Furthermore, the improved hierarchical method compares the mutual importance of evaluation indicators in pairs, determines the basic weight of each indicator according to the relative importance, and then introduces a local penalty-incentive variable weight vector function to adjust the indicator weight to obtain the evaluation indicator weight.

[0012] Furthermore, the methods for determining the values ​​of evaluation indicators include test evaluation scale method, virtual simulation evaluation method, expert review method, model test method, actual operation measurement method, investigation evaluation method, observation and analysis evaluation method, and inference calculation method, and a linear function is constructed for the indicator value as a membership function.

[0013] Furthermore, the fuzzy comprehensive evaluation includes single-level fuzzy comprehensive evaluation and multi-level fuzzy comprehensive evaluation.

[0014] The beneficial effects of the present application are as follows: the present application establishes a relatively complete cockpit microenvironment comfort evaluation system; it can quantitatively give evaluation results in the current cockpit microenvironment comfort evaluation which is mostly a single-factor evaluation; it simplifies the cumbersome steps in the evaluation process, greatly reduces the time required for the evaluation, and can quickly obtain the evaluation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A schematic diagram of some evaluation indicators preliminarily selected according to an embodiment of the present invention;

[0016] Figure 2 A schematic diagram of a process for evaluating cockpit microenvironment comfort provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0017] The present invention will be further described in detail below in conjunction with the accompanying drawings. The following specific implementation steps can enable technicians in this professional field to more fully understand the present invention. The flow chart is as follows Figure 2 The present invention is not limited in any way.

[0018] Example 1 A cockpit microenvironment comfort evaluation method

[0019] Step 1. Establish a comfort evaluation index system: determine the factors affecting cockpit microenvironment comfort and subdivide them to obtain evaluation indicators, and construct a cockpit microenvironment comfort evaluation index system through the improved Delphi method.

[0020] In this embodiment, the cockpit microenvironment comfort influencing factors are based on the systematic principle (the index system can fully reflect the various elements of the cockpit microenvironment comfort and the relationship between them), the comparability principle (the index system can fully reflect the various elements of the cockpit microenvironment comfort and the relationship between them), the representative principle (the selected indicators must be representative so as to fully and systematically reflect the objective situation of the cockpit microenvironment comfort), the independence principle (each indicator in the evaluation index set must not only have a scientific concept, simple and clear, but also the characteristics reflected by each indicator cannot be repeated and conflicting), the prospective principle (the comprehensive evaluation must reflect the current status and indicate the future development trend by expressing the relationship between the past and the current status) and the objectivity principle, combined with relevant standards, medical physiological needs of the human body, analysis of the comfort impact of relevant factors, and the environment in which the crew members are located, etc., to select evaluation indicators that can reflect the cockpit microenvironment comfort. After analysis, temperature, humidity, pressure, ventilation, vibration, noise, and lighting are used as the main factors affecting the cockpit microenvironment comfort. It should be noted that in this embodiment, other microenvironmental factors can also be added according to actual conditions.

[0021] These seven factors were then refined. The temperature factors mainly include temperature range, temperature uniformity, automatic temperature control ability, time for temperature to reach a stable state, reliability of temperature control device, physical activity, mental activity (such as Figure 1 Humidity factors mainly include humidity variation range and humidity automatic control capability; pressure factors mainly include pressure variation range, pressurization rate and decompression rate; ventilation factors mainly include ventilation volume, air flow rate, inlet and outlet layout, ventilation nozzle gas temperature, air supply cleanliness and air age; vibration factors mainly include vibration frequency and vibration intensity; lighting factors mainly include lighting intensity, lighting color, lighting brightness, light leakage, reflection and glare, dimming and lighting contrast; noise factors mainly include the impact of noise on communication voice clarity and noise intensity frequency.

[0022] Each detailed factor is further refined, and an index system is constructed based on these specific details as shown in Table 1.

[0023] Table 1 Evaluation index system of fighter cockpit environment comfort

[0024]

[0025]

[0026] Step 2: By improving the Delphi method and using a questionnaire, experts were asked to make corresponding choices on the importance of each indicator. The questionnaire was scored using the Likert scale, where very important represented 5 points, important represented 4 points, average represented 3 points, unimportant represented 2 points, and very unimportant represented 1 point. They were also asked to give modification opinions and confidence levels. The collected questionnaires were analyzed, and the concentration, dispersion, and coordination of expert opinions were calculated respectively: the concentration can be expressed as the average value E and the full score frequency K i The degree of dispersion can be expressed by the standard deviation σ. The smaller the value, the less the experts’ opinions on the evaluation results of index i are dispersed. The degree of coordination can be expressed by the coefficient of variation V i After the statistics are completed, the results are fed back to the experts for a second round of consultation. The statistical parameters of the consultation results are shown in Table 2.

[0027] Table 2 Statistical parameters of the first round of indicators

[0028]

[0029]

[0030] Among them, P33 represents the consensus of the expert consultation results, which means that no less than 2 / 3 of the experts believe that the indicator level should be greater than the value of this level. GCR represents the confidence of the expert group in judging the level of influence of the indicator on pilot comfort.

[0031] The collected expert consultation forms from the first round were statistically processed and analyzed, and the consensus, average and distribution of the expert group's judgment results on each indicator were fed back to each expert in the second round, and the experts re-evaluated each indicator.

[0032] Table 3 shows the statistical parameter results of each indicator obtained after the second round of expert consultation using the improved Delphi method.

[0033] Table 3 Statistical parameters of the second round of indicators

[0034]

[0035]

[0036] Step 3: Based on the statistical results of the two rounds of expert consultation, the coordination coefficient was compared and the χ 2 The test method tests the significance of the coordination coefficient and evaluates the credibility of the conclusion.

[0037] According to the degrees of freedom and significance level, we can get 2Find the critical value X in the distribution table α 2 , if X R 2 >X α 2 , indicating that the coordination number is significant, the coordination degree of expert opinions is good, and the result is desirable; on the contrary, X R 2 The smaller the value, the higher the probability that the expert opinions are coordinated by chance. When the confidence level is 95%, if P>0.05, it means that the credibility of the evaluation conclusion is poor and the result is not desirable. Table 4 is a comparison table of the coordination coefficients of the expert opinions of the two rounds of Delphi method.

[0038] Table 4 Comparison of coordination coefficients of expert opinions in two rounds of Delphi method

[0039]

[0040] After comparison, it can be found that the coordination coefficient increased from 0.138 in the first round to 0.262 in the second round, indicating that the experts' understanding of the importance of the indicators tends to be consistent. The P value of the coordination coefficient test is less than 0.05. When the confidence level is 95%, the expert opinions are well coordinated and the results are acceptable.

[0041] Step 4: Based on the statistical results of the two rounds of expert consultation, the threshold method was used to screen indicators. The evaluation indicators were screened by calculating the threshold values ​​of the full score frequency, mean value, and coefficient of variation of the impact score of each indicator. The threshold value of the full score frequency and mean value was A1, defined as the difference between the arithmetic mean and the standard deviation, and the indicators with scores higher than the threshold value were screened out; the threshold value of the coefficient of variation was A2, defined as the sum of the arithmetic mean and the standard deviation, and the indicators with scores lower than the threshold value were screened out.

[0042]

[0043] The cut-off values ​​of the screening indicators in the two rounds of expert consultation are shown in the following table.

[0044] Table 5 Critical values ​​of screening indicators in two rounds of expert consultation

[0045]

[0046] In order to ensure the comprehensiveness and comprehensiveness of the index system, the indicators that do not meet the requirements of the above three measurement scales are eliminated; the indicators that do not meet the requirements are retained; the indicators that do not meet the requirements need to be considered comprehensively in combination with expert opinions, and the selection is made after repeated weighing. Alternatively, the screening criteria can be used: the expert consensus is P33, and the confidence of the expert group is greater than 3. The index system obtained by the evaluation indicators screened by the threshold method is shown in Table 6.

[0047] Table 6 Fighter cockpit environment comfort index system

[0048]

[0049]

[0050] Step 5, using the improved hierarchical analysis method combined with the expert group weighting method, through the questionnaire method, ask experts to make pairwise comparisons on the mutual importance of evaluation indicators, and process the data according to the credibility of the experts to calculate the weight coefficient w of each indicator. The weight coefficients of each indicator are shown in Table 7.

[0051] w1=[0.2300.1600.1330.1920.0950.0950.095];

[0052] w 11 =[0.1330.1570.1110.1330.1110.1330.1110.111];

[0053] w 12 =[0.5000.500];

[0054] w 13 =[0.3760.3120.312];

[0055] w 14 =[0.2670.1690.1410.1410.1410.141];

[0056] w 15 =[0.5000.500];

[0057] w 16 =[0.2500.2500.2500.250];

[0058] w 17 =[0.5000.500].

[0059] Table 7 Evaluation index weight coefficient

[0060]

[0061]

[0062] Step 6. The previous article used the improved hierarchical analysis method to analyze the cockpit microenvironment comfort evaluation, decomposed the overall goal into multiple sub-factors, and determined the weight of each factor, forming a multi-level indicator system aggregated at different levels. According to the established evaluation indicator system, the influencing factor set is established as follows.

[0063] Cockpit microenvironment comfort U = {temperature U1, humidity U2, pressure U3, ventilation U4, vibration U5, lighting U6, noise U7};

[0064] Temperature U1 = {temperature range U11, temperature uniformity U12, automatic temperature control capability U13, time for temperature to reach a stable state U14, reliability of temperature control device U15, physical activity U16, mental activity U17, solar radiation U18};

[0065] Humidity U2 = {humidity variation range U21, humidity automatic control capability U22};

[0066] Pressure U3 = {pressure change range U31, pressure increase rate U32, pressure reduction rate U33};

[0067] Ventilation U4 = {ventilation volume U41, air flow rate U42, inlet and outlet layout U43, ventilation nozzle gas temperature U44, air supply cleanliness U45, air age U46};

[0068] Vibration U5 = {vibration frequency U51, vibration intensity U52};

[0069] Lighting U6 = {lighting intensity U61, lighting color U62, dimming U63, lighting contrast U64};

[0070] Noise U7 = {noise impact on communication voice clarity U71, noise intensity frequency U72};

[0071] Step 7, taking the evaluation of the index U1 temperature as an example, adopt the test evaluation scale method, virtual simulation evaluation method, expert review method, model test method, actual operation measurement method, investigation evaluation method, observation analysis evaluation method, inference calculation method, etc. to obtain the index value of each index and normalize the index. Table 8 shows the specific index value of U1 temperature.

[0072] Table 8 Specific index values ​​of U1 temperature

[0073]

[0074] Step 8, construct the indicator membership function. For the preprocessed indicator values, use a linear function as the indicator membership function. Suppose the evaluation set is V = {v1, v2, ···, v5}, v1, v2, ···, v5 represent excellent, good, medium, poor, and very poor, respectively. The membership function is as follows.

[0075]

[0076]

[0077] The calculated membership degrees are shown in Table 9.

[0078] Table 9 U1 temperature membership

[0079]

[0080] Step 9: For the comprehensive evaluation of cockpit microenvironment comfort, a local penalty-incentive variable weight function is introduced to adjust the index weights, which can more sensitively reflect the impact of degradation indicators on overall comfort. The local penalty-incentive variable weight vector function Si(x) constructed by Duan Shuqiao et al. is used as shown below.

[0081]

[0082] Where: x i is the evaluation value of the ith indicator; m is the total number of projects; w i is the variable weight of the i-th indicator factor; w i (0) is the constant weight of the i-th indicator factor; Si(x) is a smooth, continuous and differentiable function in the interval [0, 1], α is the penalty level, β is the incentive level, (λ, α) is the initial penalty stage, (μ, λ] is the strong penalty stage, (0, μ] is the veto stage, and 0<μ<λ<α<β<1, 0 <C<c1<c2<1。

[0083] Considering the actual situation of cockpit comfort evaluation, in order to reflect its "barrel nature", the magnitude of punishment should be much greater than the magnitude of incentive. When the evaluation value of a certain indicator is poor, its weight is increased significantly, so that the comprehensive evaluation result is more in line with the actual situation. Considering that the design must comply with the requirements of the national military standard, when indicator i does not meet the minimum requirements stipulated in relevant regulations (i.e. x i =0), w i (x i )=1, the overall evaluation is 0 points. i When ≠0, take β=0.9, α=0.7, λ=0.5, μ=0.2, C2=0.8, C1=0.5, C=0.4, K=2, and construct the penalty variable weight vector function Si(x) as follows.

[0084]

[0085] Where: x i is the evaluation value of the ith indicator; m is the total number of projects; w i is the variable weight of the i-th indicator factor; w i (0) is the constant weight of the ith indicator factor, and the calculated variable weights are shown in Table 10.

[0086] Table 10U1 temperature index evaluation

[0087]

[0088] Step 10: According to the obtained membership vectors, the corresponding fuzzy comprehensive evaluation matrix can be obtained:

[0089]

[0090] The weights and variable weights of each factor are:

[0091] w 11 (0) =[0.1330.1570.1110.1330.1110.1330.1110.111];

[0092] w 11 =[0.14990.11330.07700.10520.17360.09230.15010.1386];

[0093] The above matrix operations can be used to perform fuzzy comprehensive evaluation, which are:

[0094] B 11 (0) =w 11 (0) R 11 =[0.15540.277350.19580.233850.1376];

[0095] B 11 =w 11 R 11 =[0.230140.3445850.1616950.168120.09546];

[0096] By analogy, we can get the fuzzy comprehensive evaluation of other factors and finally get the comprehensive evaluation result:

[0097]

[0098] B1=w1R1.

[0099] Step 11, the result obtained by fuzzy comprehensive evaluation is only a matrix, which cannot clearly and intuitively reflect the final result of cockpit environment comfort evaluation. Therefore, it will be defuzzified to make the result clearer.

[0100] The use of multi-level fuzzy comprehensive evaluation can give quantitative evaluation results. Let the membership set of the evaluation criteria be μ;

[0101] μ={μ1μ2···μ n}

[0102] The standard membership set of cockpit comfort results is taken as:

[0103] μ = {5 (excellent) 4 (good) 3 (average) 2 (poor) 1 (very poor)};

[0104] Total score is S:

[0105] S=B×μ T ;

[0106] According to the established fuzzy comprehensive evaluation model, the basic weights are used to calculate:

[0107] B 11 (0) =w 11 (0) R 11 =[0.1554 0.27735 0.1958 0.23385 0.1376], the total score is 2.9209 points, calculated with variable weights 11 =w 11 R 11 =[0.230140.3445850.1616950.168120.09546], the total score is 2.554175 points. According to the maximum membership principle, the evaluation levels are all "medium", but the total scores calculated by variable weights are significantly lower than the total scores calculated by basic weights. It can be seen that the established variable weight comprehensive evaluation model can more sensitively reflect the impact of degradation indicators on the overall comfort level, and the evaluation results are more accurate.

[0108] Note: The actual scope of the present invention includes not only the specific embodiments disclosed above, but also all equivalent solutions that implement or perform the present invention under the claims.

Claims

1. A cockpit microenvironment comfort evaluation method, characterized in that: The steps include: Establish a comfort evaluation index system: determine the factors affecting cockpit microenvironment comfort and subdivide them to obtain evaluation indicators, and construct a cockpit microenvironment comfort evaluation index system through the improved Delphi method; Calculate the weight of evaluation index: Analyze the weight of each influencing factor based on the improved hierarchical method and expert group weight construction method, adjust each weight through the local penalty-incentive variable weight vector function, and obtain the weight of evaluation index; Determine the evaluation index value: evaluate each index through the test evaluation scale method, etc., and perform normalization. Determine the index membership function and fuzzy comprehensive evaluation: construct the index membership function and obtain the fuzzy comprehensive evaluation matrix based on it, and then combine it with the weight matrix to obtain the cockpit microenvironment comfort evaluation result through fuzzy comprehensive evaluation.

2. The evaluation method according to claim 1, characterized in that: The factors affecting cockpit microenvironment comfort are temperature, humidity, pressure, ventilation, vibration, noise and lighting.

3. According to the evaluation method of claim 1, the improved Delphi method is to ask experts to classify the degree of influence of evaluation indicators on comfort through questionnaires, calculate the concentration and dispersion of expert opinions, return to the experts to repeat the above steps, compare the coordination coefficients of the two rounds of evaluation results, and then screen and determine the cockpit microenvironment comfort evaluation index system through the threshold method.

4. The evaluation method according to claim 1, characterized in that: The improved hierarchical method is to compare the mutual importance of evaluation indicators in pairs, determine the basic weight of each indicator according to the relative importance, and then introduce a local penalty-incentive variable weight vector function to adjust the indicator weight to obtain the evaluation indicator weight.

5. The evaluation method according to claim 1, characterized in that: The methods for determining the values ​​of evaluation indicators include experimental evaluation scale method, virtual simulation evaluation method, expert review method, model test method, actual operation measurement method, investigation evaluation method, observation and analysis evaluation method, and inference calculation method. A linear function is constructed for the indicator value as a membership function.

6. The evaluation method according to claim 1, characterized in that: The fuzzy comprehensive evaluation includes single-level fuzzy comprehensive evaluation and multi-level fuzzy comprehensive evaluation.

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