Helicopter flight parameter trend analysis method

Abstract

The invention provides a helicopter flight parameter trend analysis method. The helicopter flight parameter trend analysis method comprises the following steps of 1, obtaining flight parameters of N continuous sessions; n is an integer greater than 10; 2, according to the types of the flight parameters, representative values of the flight parameters of N continuous sessions are obtained; 3, obtaining a broken line graph according to the representative values of the flight parameters of the N continuous sessions; and 4, determining the trend of the broken line graph, and determining whether fault analysis needs to be performed on the helicopter according to the trend of the broken line graph. According to the method, when parameters do not change qualitatively, trend monitoring analysis is carried out on quantitative change conditions of key parameters by using a data analysis means easy to implement, potential safety hazards are found and eliminated in advance, possible qualitative change is prevented, and the perfectness ratio of the helicopter is improved at the lowest cost. The flight parameter trend analysis method can play an important role in daily maintenance of the helicopter.

Description

Technical Field

[0001] The invention belongs to the technical field of aviation, and in particular relates to a method for analyzing the flight parameter trend of a helicopter. Background Art

[0002] At present, flight parameter analysis has become an essential means of helicopter status monitoring, providing a key guarantee for flight safety. According to flight support experience and typical fault analysis, the occurrence of faults has an evolutionary trend from quantitative change to qualitative change. At present, flight parameters follow the traditional general interpretation principle in the daily maintenance of helicopters, and can only make post-event judgments and maintenance based on qualitative changes; they focus on horizontal analysis, that is, the analysis of the relationship between parameters, and do not focus on vertical analysis, that is, the historical change analysis of the same parameter. Therefore, it is difficult for traditional methods to discover and judge in advance whether the data will undergo qualitative changes, so as to make targeted advance maintenance and restore the status of the helicopter to its best state. At present, there is a lack of working methods for the trend evolution analysis of flight parameter data and mature and intelligent software and hardware and judgment criteria. The general interpretation method lags in work, has high maintenance costs, and does not fully utilize the massive helicopter parameters. The helicopter parameter trend analysis method can just make up for its shortcomings. By analyzing the historical changes of the same parameter, it can predict the time when the data will undergo qualitative changes in advance, make advance maintenance, and restore the helicopter to its best state. Summary of the invention

[0003] The present invention provides a method for analyzing the trend of helicopter flight parameters. By using an easily achievable data analysis method, the trend monitoring and analysis of the quantitative changes of key parameters is performed, potential safety hazards are discovered and eliminated in advance, possible qualitative changes are prevented, and the helicopter's integrity rate is improved at the lowest cost. The flight parameter trend analysis method can play an important role in the daily maintenance of helicopters.

[0004] The present invention provides a helicopter flight parameter trend analysis method, comprising the following steps:

[0005] Step 1: Obtain flight parameters for N consecutive flights; N is an integer greater than 10;

[0006] Step 2: According to the type of flight parameters, obtain representative values ​​of flight parameters for N consecutive times;

[0007] Step 3: Obtain a line graph based on representative values ​​of the flight parameters of N consecutive flights;

[0008] Step 4: Determine the trend of the line graph, and determine whether it is necessary to perform a fault analysis on the helicopter based on the trend of the line graph.

[0009] Optionally, the types of flight parameters include: vibration type and non-vibration type.

[0010] Optionally, representative values ​​of flight parameters for N consecutive flights are obtained according to the type of flight parameters, including:

[0011] When the type of flight parameter is non-vibration type, the average value of the flight parameter of N consecutive times is taken as the representative value;

[0012] When the type of the flight parameter is vibration, the maximum or minimum value of the flight parameter in N consecutive sessions is taken as the representative value.

[0013] Optionally, the line chart trend includes:

[0014] Stable, rising, falling and fluctuating types;

[0015] The rising types include: obvious rising type, not obvious rising type, and steep rising type at the end;

[0016] The descending types include: obvious descending type, unobvious descending type, and steep descending type at the end;

[0017] The fluctuation types include: fluctuation tends to be stable, fluctuation with obvious increase, and fluctuation with obvious decrease.

[0018] Optionally, when the number of the same flight parameters in each session is multiple, determining whether to perform a fault analysis on the helicopter is required based on the trend of the line graph, and further including:

[0019] When the type of flight parameter is non-vibration type, when there is any of the following in the trend of multiple line graphs of the same flight parameter, or when there is a gap within the group, it is determined that the helicopter needs to be fault analyzed:

[0020] The obvious rising type, the steep rising type at the end, the obvious falling type, the steep falling type at the end, the obvious rising type during fluctuation or the obvious falling type during fluctuation.

[0021] Optionally, when the number of the same flight parameters in each session is multiple, determining whether to perform a fault analysis on the helicopter is required based on the trend of the line graph, and further including:

[0022] When the type of flight parameter is vibration, when there is any of the following trends in multiple line graphs of the same flight parameter, or when there is a gap within the group, it is determined that the helicopter needs to be analyzed for failure:

[0023] The obvious rising type, the steep rising type at the end, and the obvious rising type during fluctuation.

[0024] Determine whether a helicopter fault analysis is required based on the type of flight parameters and the trend of the line graph.

[0025] Optionally, obtain flight parameters for N consecutive flights, including:

[0026] Obtain flight parameters of N consecutive stable flight segments.

[0027] Optionally, changes in flight weight, flight altitude, and level flight attitude during the steady flight segment are within a preset range;

[0028] The flight weight is determined based on the total distance displacement, the level flight attitude and flight altitude are determined based on the radio altitude, and the flight speed is determined based on the indicated airspeed.

[0029] Optionally, the flight parameters include: A1 main rotor speed; A2 engine gas turbine speed; A3 engine power turbine speed; A4 engine inter-turbine temperature; A5 engine lubricating oil temperature; A6 engine lubricating oil pressure; A7 hydraulic pressure; A8 main reducer lubricating oil pressure; A9 main reducer lubricating oil temperature; A10 intermediate reducer lubricating oil temperature; A11 tail reducer lubricating oil temperature; A12 fuel pressure; A13 vibration value at the main rotor speed frequency; A14 vibration value at the first-order pass frequency of the main rotor; A15 vibration value at the tail rotor speed frequency; A16 vibration value at the first-order pass frequency of the tail rotor; A17 vibration value at the horizontal axis speed frequency of the tail drive shaft; A18 vibration value at the inclined axis speed frequency of the tail drive shaft.

[0030] Optional, vibration flight parameters include: A1 main rotor speed; A2 engine gas turbine speed; A3 engine power turbine speed; A4 engine turbine inter-turbine temperature; A5 engine oil temperature; A6 engine oil pressure; A7 hydraulic pressure; A8 main reducer oil pressure; A9 main reducer oil temperature; A10 intermediate reducer oil temperature; A11 tail reducer oil temperature; A12 fuel pressure;

[0031] Non-vibration flight parameters include: A13 vibration value at the main rotor speed frequency; A14 vibration value at the main rotor first-order pass frequency; A15 vibration value at the tail rotor speed frequency; A16 vibration value at the tail rotor first-order pass frequency; A17 vibration value at the tail drive shaft horizontal axis speed frequency; A18 vibration value at the tail drive shaft oblique axis speed frequency.

[0032] The present invention provides a method for analyzing the trend of helicopter flight parameters. Aiming at the deficiency that the traditional helicopter flight parameter interpretation method lacks the function of predicting the fault trend, a practical flight parameter trend analysis method is proposed, the advantages of the trend analysis method over the general interpretation method of flight parameters are introduced, the steps of using the trend analysis method are described in detail, and how to use the trend analysis method to analyze the trend changes of 18 types of key parameters that best represent the safety status of the helicopter, and determine the corresponding helicopter maintenance ideas according to the trend changes. The trend analysis method is successfully applied to predict the occurrence of the main reducer oil radiator failure and the Y-direction vibration value exceeding the limit under the tail rotor speed frequency, and correct maintenance measures are taken to restore the helicopter to a good state. It is effectively verified that the flight parameter trend analysis method can monitor and predict the safety status of the helicopter and improve the helicopter's integrity rate at the lowest cost. The promotion and popularization of the flight parameter trend analysis method will play an important application role in the daily maintenance of helicopters, and will have reference significance for the accelerated maturity of helicopter fault trend prediction software. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 Select key parameters for 12 types of flight parameters;

[0034] Figure 2 To generate trend graphs;

[0035] Figure 3 For vibration trend analysis;

[0036] Figures 4a-4d There are four types of trend trends for a single data line chart;

[0037] Figure 5a-5d There are 4 types of trend comparisons for multiple data line charts within a group;

[0038] Figure 6 Main center tail reducer oil temperature trend chart;

[0039] Figure 7 Main reducer oil problem tree

[0040] Figure 8 Trend diagram of Y-axis vibration value under tail rotor speed frequency

[0041] Fig. 9 Problem tree of large Y-axis vibration magnitude at tail rotor speed frequency

[0042] Fig.10 Application steps. DETAILED DESCRIPTION

[0043] The technical solution provided by the present invention is explained below in conjunction with the accompanying drawings.

[0044] This method selects 18 types of helicopter key parameters as research objects: A1 main rotor speed; A2 engine gas turbine speed; A3 engine power turbine speed; A4 engine turbine room temperature; A5 engine oil temperature; A6 engine oil pressure; A7 hydraulic pressure; A8 main reducer oil pressure; A9 main reducer oil temperature; A10 intermediate reducer oil temperature; A11 tail reducer oil temperature; A12 fuel pressure; A13 vibration value at the main rotor speed frequency; A14 vibration value at the main rotor first-order pass frequency; A15 vibration value at the tail rotor speed frequency; A16 vibration value at the tail rotor first-order pass frequency; A17 vibration value at the tail drive shaft horizontal axis speed frequency; A18 vibration value at the tail drive shaft oblique axis speed frequency.

[0045] The avionics system records and displays a large number of helicopter flight parameters. Practical experience shows that before the application of mature trend analysis software and hardware and criteria, it is unrealistic to comprehensively evaluate the aircraft status based on a large number of parameters, and it cannot meet the needs of intensive combat and training. Therefore, we can select a certain number of key parameters that affect flight safety, involve key components, and theoretically should be stable within a certain range or as small as possible, collect and record this part of the data, and analyze the trend evolution. In this way, we can combine the current flight parameter software functions and the actual situation of human and material resources to achieve a rapid and effective assessment of the safety status of the helicopter.

[0046] There are 18 types of key parameters that affect flight safety, involve key components, and theoretically should be stable within a certain range or as small as possible: A1 main rotor speed; A2 engine gas turbine speed; A3 engine power turbine speed; A4 engine turbine inter-turbine temperature; A5 engine oil temperature; A6 engine oil pressure; A7 hydraulic pressure; A8 main reducer oil pressure; A9 main reducer oil temperature; A10 intermediate reducer oil temperature; A11 tail reducer oil temperature; A12 fuel pressure; A13 vibration value at the main rotor speed frequency; A14 vibration value at the main rotor first-order pass frequency; A15 vibration value at the tail rotor speed frequency; A16 vibration value at the tail rotor first-order pass frequency; A17 vibration value at the tail drive shaft horizontal axis speed frequency; A18 vibration value at the tail drive shaft oblique axis speed frequency.

[0047] According to practical experience and trend analysis requirements, the flight interval parameter values ​​we selected are generally within the green zone. If they are close to the edge of the green zone or more serious, other flight intervals are likely to enter the yellow zone or red zone. At the time of the incident, they have been paid attention to and processed, and the data generally returns to normal. This method is based on the premise of generally using parameters that have not undergone qualitative changes, and predicts and prevents the occurrence of qualitative changes by analyzing and monitoring their quantitative changes.

[0048] The advantage of extreme value analysis is that data selection is simple and data expression is strong. The extreme value directly selects the maximum and minimum values ​​of a certain game or a certain period of time, and makes a trend chart in chronological order, which can intuitively display the "limit" situation of the helicopter and the trend evolution of the maximum and minimum values. The advantage of mean value analysis is that it uses a large amount of data. One mean data can truly reflect the value level of the helicopter in a stable flight state within a period of time. The trend chart generated by the mean data of multiple games can truly reflect the changes in the operating performance of a certain component of the helicopter, and can infer the time of exceeding the limit, which can be used as the basis for the need for in-depth maintenance, and the system components can be inspected and maintained in depth as soon as possible to avoid over-limit use and failure.

[0049] Among the 18 selected parameters, there are 12 flight key parameters that affect flight safety, involve key components, and theoretically should be stable within a certain range: A1~A12. The mean value analysis method can more truly reflect the state changes of the helicopter. There are 6 vibration key parameters that affect flight safety, involve key components, and theoretically should be as small as possible: A13~A18. The extreme value analysis method can better reflect the changes in the vibration level of the helicopter.

[0050] The 12 types of flight key parameters are applicable to the mean analysis method, and the 6 types of vibration key parameters are applicable to the extreme value analysis method.

[0051] Commonly used charts for expressing trends include data reports, bar charts, area charts, waterfall charts, scatter charts, line charts, etc. According to statistical principles, line charts are very convenient to reflect the trend of things changing over time or other ordered categories, and can most intuitively reflect the trend of flight parameter data changes. However, the disadvantage of line charts is that the number of broken lines cannot be too many, which will lead to poor readability of the chart. Most of the data of the preferred 18 key parameters are not similar in magnitude, and only a small part of the data is similar in magnitude. Multiple line charts can be selected for expression. Therefore, line charts are preferably a suitable trend expression method.

[0052] The 18 key parameter line graphs can be divided into 17 groups, as shown in Table 1.

[0053] Table 1 Key parameter grouping

[0054]

[0055]

[0056] Use the total displacement to determine the common flight weight, use the radio altitude to determine the common flight altitude and general level flight attitude, and use the indicated airspeed to determine the common flight speed. Based on these three criteria, select a stable flight time interval, select all the values ​​of the 12 types of key flight parameters within this interval, and use the flight parameter software or add auxiliary software to generate the average value, such as Figure 1and Table 2. Use office software to generate trend line graphs for data from more than 10 sessions, such as Figure 2 shown.

[0057] Table 2 Mean generation example

[0058] Rotor rotation Left burning rate Right burning rate Left speed Right speed Left torque May 6 212.209 86.921 87.443 102.535 102.535 34.302 May 7 212.247 85.96 86.445 102.544 102.545 31.693 May 8 212.116 86.037 87.115 102.481 102.481 31.806 May 10 212.207 85.522 86.542 102.525 102.525 30.217 May 11 212.214 85.602 86.179 102.528 102.529 31.579 May 12 212.202 86.487 87.102 102.523 102.523 34.205 May 13 212.182 86.581 87.268 102.513 102.514 33.591 May 15 212.241 85.779 86.69 102.542 102.542 32.038 May 16 212.238 86.387 87.328 102.54 102.541 33.527 May 17 212.22 87.518 88.54 102.531 102.532 34.998

[0059] Use the total displacement to determine the common flight weight, use the radio altitude to determine the common flight altitude and general level flight attitude, and use the indicated airspeed to determine the common flight speed. Based on these three criteria, select a stable flight time interval, select the maximum values ​​of the six types of key vibration parameters within this interval, and use office software to generate a trend line chart for more than 10 data, such as Figure 3 shown.

[0060] There are four types of trend trends that may appear in a single data line chart, such as Figure 4a As shown: 1) stable type; Figure 4b As shown in the figure, 2) rising type: a. obvious rising type, b. not obvious rising type, c. steep rising type at the end; Figure 4c As shown, 3) Decline type: a. obvious decline type, b. not obvious decline type, c. steep decline type at the end; Figure 4d As shown, 4) Fluctuation type: a. Fluctuation tends to be stable, b. Fluctuation with obvious increase, c. Fluctuation with obvious decrease.

[0061] There are four types of trend comparisons that may appear in multiple data line charts within a group, such as Figure 5a As shown: 1) Same superiority type: the trend of each parameter curve is good; Figure 5b As shown: 2) Same inferior type: Each parameter curve is trending in the direction of the difference; Figure 5c As shown: 3) Advantage and disadvantage type: the parameter curve has a better trend and a difference; Figure 5d As shown: 4) Gap type: The parameter comparison values ​​are very different, such as large torque difference, large temperature difference between turbines, etc.

[0062] Generally speaking, we consider five good situations: stable, not obvious rising, not obvious falling, stable fluctuation, and same good within the group. Generally speaking, we consider eight situations that need to be analyzed and paid attention to: obvious rising, steep rising at the end, obvious falling, steep falling at the end, obvious rising in fluctuation, obvious falling in fluctuation, same bad within the group, good and bad within the group, and gap within the group. In particular, for the helicopter vibration system, we also consider good situations: obvious falling, steep falling at the end, and obvious falling in fluctuation.

[0063] For example, there are 17 groups of key parameters in 18 categories. The trend impact analysis is conducted on 6 situations of the trends of the 18 key parameters in combination with the actual use and maintenance experience of helicopters and general mechanical and electrical principles, and the results are obtained. The 6 situations are: obvious rise type, steep rise type at the end, obvious decline type, steep decline type at the end, obvious rise type in fluctuation, obvious decline type in fluctuation, and intra-group gap type. The same inferior type within the group and the superior and inferior type within the group can be referenced and analyzed in the above 6 situations, as shown in Tables 3 to 18.

[0064] Table 3 Main rotor speed

[0065]

[0066] Table 4 Left and right gas turbine speeds

[0067]

[0068]

[0069] Table 5 Left and right engine turbine speed

[0070]

[0071] Table 6 Temperature between left and right turbines

[0072]

[0073] Table 7 Left and right lubricating oil temperature

[0074]

[0075] Table 8 Left and right engine oil pressure

[0076]

[0077] Table 9 Left and right hydraulic system pressure

[0078]

[0079] Table 10 Main reducer oil pressure

[0080]

[0081] Table 11 Main, middle and tail reducer oil temperature

[0082]

[0083]

[0084] Table 12 Left and right fuel pressure

[0085]

[0086] Table 13 Vibration values ​​at main rotor speed frequency

[0087]

[0088] Table 14 Vibration value of main rotor at first-order passing frequency

[0089]

[0090] Table 15 X-axis and Z-axis vibration values ​​at tail rotor speed frequency

[0091]

[0092] Table 16 Y-axis vibration value at tail rotor speed frequency

[0093]

[0094] Table 17 Vibration value of tail rotor at first-order passing frequency

[0095]

[0096] Table 17 Vibration value of tail drive shaft horizontal shaft speed frequency

[0097]

[0098] Table 18 Vibration value of tail transmission shaft at oblique axis speed frequency

[0099]

[0100] The method provided by the present invention comprises the following steps

[0101] 1. Parameter selection. Select a certain number of key parameters that affect flight safety, involve key components, and theoretically should be stable within a certain range or as small as possible. Collect, record, and analyze the trend evolution of this part of the data. This can be combined with the current flight parameter software functions and the actual human and material resources to achieve a rapid and effective assessment of the helicopter's safety status. There are 18 types of key parameters that affect flight safety, involve key components, and theoretically should be stable within a certain range or as small as possible: A1 main rotor speed; A2 engine gas turbine speed; A3 engine power turbine speed; A4 engine turbine inter-turbine temperature; A5 engine oil temperature; A6 engine oil pressure; A7 hydraulic pressure; A8 main reducer oil pressure; A9 main reducer oil temperature; A10 intermediate reducer oil temperature; A11 tail reducer oil temperature; A12 fuel pressure; A13 vibration value at the main rotor speed frequency; A14 vibration value at the main rotor first-order pass frequency; A15 vibration value at the tail rotor speed frequency; A16 vibration value at the tail rotor first-order pass frequency; A17 vibration value at the tail drive shaft horizontal axis speed frequency; A18 vibration value at the tail drive shaft oblique axis speed frequency.

[0102] 2. Selection of mathematical methods. Among the 18 selected parameters, there are 12 types of flight parameter key parameters that affect flight safety, involve key components, and theoretically should be stable within a certain range: A1~A12. The mean analysis method can more truly reflect the state changes of the helicopter. There are 6 types of vibration key parameters that affect flight safety, involve key components, and theoretically should be as small as possible: A13~A18. The extreme value analysis method can better reflect the changes in the vibration level of the helicopter. In summary, 12 types of flight parameter key parameters are suitable for the mean analysis method, and 6 types of vibration key parameters are suitable for the extreme value analysis method.

[0103] 3. Selection of trend chart: Line chart is preferably a suitable method for expressing trend.

[0104] 4. Parameter grouping of line graphs. Taking a twin-engine, twin-hydraulic helicopter as an example, the 18 types of key parameter line graphs can be divided into 17 groups, as shown in Table 1.

[0105] 5.12 steps to generate trends of key flight parameter parameters. The first step is to select the three judgment parameters of indicated airspeed, radio altitude, and collective displacement and 12 key flight parameter parameters in the flight parameter interpretation software. The second step is to generate the parameter curve, use the collective displacement to judge the common flight weight, use the radio altitude to judge the common flight altitude and the general level flight attitude, and use the indicated airspeed to judge the commonly used flight speed. After combining these three bases, select a stable flight time interval, select all the values ​​of the 12 key flight parameter parameters in this interval, and use the flight parameter software or add auxiliary software to generate the mean, such as Figure 1As shown in Table 2. The third step is to use office software to generate a trend line chart for the average data of more than 10 sessions and analyze the trend direction, such as Figure 2 shown.

[0106] 6.6 Steps to generate trends of key vibration parameters. The first step is to select the maximum values ​​of the 6 key vibration parameters of the same events as in step 5. The second step is to use office software to generate trend line graphs for the maximum value data of more than 10 events and analyze the trend direction, such as Figure 3 shown.

[0107] 7. Classification of line chart trends. There are four types of trends that may appear in a single data line chart, such as Figures 4a-4d As shown: 1) Stable type; 2) Rising type: a. Obvious rising type, b. Not obvious rising type, c. Steep rising type at the end; 3) Declining type: a. Obvious falling type, b. Not obvious falling type, c. Steep falling type at the end; 4) Fluctuating type: a. Fluctuation tends to be stable type, b. Obvious rising type in fluctuation, c. Obvious falling type in fluctuation.

[0108] There are four types of trend comparisons that may appear in multiple data line charts within a group, such as Figure 5a-5d As shown: 1) Same superior type: the trend of each parameter curve is better; 2) Same inferior type: the trend of each parameter curve is worse; 3) Superior and inferior type: the trend of parameter curves is better or worse; 4) Gap type: the parameter comparison values ​​are very different, such as large torque difference, large temperature difference between turbines, etc.

[0109] 8. Judging the good state of the line chart trend. Generally, we consider five situations as good: stable, not obvious rising, not obvious falling, stable fluctuations, and same goodness within the group. Generally, we consider eight situations that need to be analyzed and paid attention to: obvious rising, steep rising at the end, obvious falling, steep falling at the end, obvious rising in fluctuations, obvious falling in fluctuations, same badness within the group, goodness and badness within the group, and gap within the group.

[0110] In particular, for the helicopter vibration system, we consider the following conditions to be good: obvious decline type, steep decline type at the end, and obvious decline type during fluctuation.

[0111] 9. Trend result analysis method. 17 groups of key parameters in 18 categories are selected. The following 6 situations of the trends of the 18 key parameters are combined with the actual use and maintenance experience of helicopters and general mechanical and electrical principles to conduct trend impact analysis and obtain results. The 6 situations are: obvious rising type, steep rising type at the end, obvious falling type, steep falling type at the end, obvious rising type in fluctuation, obvious falling type in fluctuation, and intra-group gap type. The same inferior type within the group and the superior and inferior type within the group can be referenced and analyzed in the above 6 situations, as shown in Table 3-Table 18.

[0112] 10. Example verification of the abnormal prediction and prevention of the main reducer lubricating oil radiator. The flight parameter interpretation found that the main reducer lubricating oil temperature was slightly high but still within the universal value, not exceeding the limit and not alarming. According to the traditional flight parameter interpretation method and judgment standard, the main reducer lubricating oil temperature of this aircraft is normal and is not included in the detection and processing range, and no attention is required. However, through the trend analysis method, the trend analysis of the flight data of the aircraft in the past 15 flights was conducted, and it was found that the main reducer lubricating oil temperature trend is as follows: Figure 6 As shown, it shows a trend of gradual increase. According to the trend analysis method of "Table 11 Main, middle and tail reducer lubricating oil temperature" mentioned above, the lubricating oil temperature of the main, middle and tail reducer is related to factors such as environmental changes, oil consumption, leakage, oil contamination, temperature sensor and data transmission performance. The main reducer lubricating oil temperature is also related to factors such as the performance of the thermostatic valve and the condition of the radiator. A problem tree can be listed, such as Figure 7 As shown. Figure 8 The problem tree is analyzed and eliminated one by one: (a) After investigation, the recent changes in environmental temperature, humidity, field pressure and other factors have not been obvious. Compared with the recent trend of the lubricating oil temperature of the middle and tail reducers, which are theoretically more affected by the environment, there is no obvious change. The environmental problem can be ruled out; (b) After inspection, the oil consumption is normal, there is no leakage, and the oil test results are good, so the oil problem can be ruled out; (c) The performance of the thermostatic valve is normal, the fan assembly of the cooling system is running well, and the visible parts of the air duct, related pipelines and radiator components are checked. There are no abnormalities. There are invisible parts in the air duct, related pipelines and radiator components. They are not checked under general maintenance, and the heat dissipation problem cannot be ruled out; (d) The flight parameter interpretation data itself is recorded and displayed normally, without distortion or leakage, the sensor calibration is good, and the data line is well connected, so the data problem can be ruled out; (e) The oil analysis results are good, there is no metal chip alarm in the main reducer, and the vibration of the whole machine is good, so the main reducer problem can be ruled out. In summary, the heat dissipation problem cannot be ruled out, and further inspection of the air duct, related pipelines and radiator components is required. There are invisible parts. Further investigation revealed that there were debris such as grass fluff attached to the airway in the lubricating oil radiator assembly, which affected the smooth flow of gas and thus the heat dissipation efficiency. Moreover, because the internal airway is invisible and cannot be checked at ordinary times, the grass fluff and other debris raised during flight were sucked into the airway and accumulated more and more, resulting in a gradual decrease in heat dissipation efficiency and a gradual increase in the main reducer lubricating oil temperature. After the grass fluff and other debris were removed, the main reducer lubricating oil temperature returned to the normal level, avoiding the unpredictable risks caused by the grass fluff and other debris.

[0113] 11. Example verification of abnormal prediction and prevention of Y-direction vibration value under tail rotor speed frequency. Flight parameter interpretation found that the Y-direction vibration value of a helicopter under tail rotor speed frequency reached 0.85IPS, but it was still within the green zone of 1.0IPS specified in the manual, not exceeding the limit and not alarming. According to the traditional judgment standard, this aircraft can still participate in training normally. However, through the trend analysis method, the trend analysis of the vibration data of the aircraft in the past 15 sessions was conducted, and it was found that the trend of the Y-direction vibration value under the tail rotor speed frequency was as follows: Figure 8 As shown in the figure, it has shown a gradual upward trend in the past week. According to the trend forecast, the Y-axis vibration value at the tail rotor speed frequency will reach 1.0IPS soon, and an over-limit alarm will occur, affecting the normal training. According to the trend analysis method of "Table 16 Y-axis vibration value at tail rotor speed frequency" in the previous text, the Y-axis vibration value at the tail rotor speed frequency is mainly related to factors such as tail rotor installation, tail rotor blade condition, vibration sensor and data transmission performance. A problem tree can be listed, such as Fig. 9 shown.

[0114] right Fig. 9 The problem tree is analyzed and eliminated one by one: (a) After analysis and investigation, the flight parameter interpretation data is recorded and displayed normally, and the multi-channel comparison data is not distorted or leaked, so the data problem is eliminated; (b) The appearance inspection and knocking inspection of the tail rotor blade are in good condition, without bulging, stratification, water ingress, etc., and the tail rotor blade problem is eliminated; (c) The tail rotor blade mounting bolts are not rusted, loose, or torque loss, and the X-direction and Z-direction vibration values ​​under the tail rotor speed frequency are normal and have no upward trend. The tail rotor X-direction and Z-direction installation problems can be eliminated, but the tail rotor Y-direction installation problem cannot be eliminated. By adjusting the tail rotor blade pitch lever, re-balancing and test flying, the Y-direction vibration value level under the tail rotor speed frequency has returned to a smaller state.

[0115] The present invention selects a certain number of key parameters that affect flight safety, involve key components, and theoretically should be stable within a certain range or as small as possible for trend evolution analysis, so as to achieve a rapid and effective assessment of the safety status of the helicopter.

[0116] There are 18 types of key parameters that affect flight safety, involve key components, and theoretically should be stabilized within a certain range or as small as possible in the present invention: A1 main rotor speed; A2 engine gas turbine speed; A3 engine power turbine speed; A4 engine turbine room temperature; A5 engine lubricating oil temperature; A6 engine lubricating oil pressure; A7 hydraulic pressure; A8 main reducer lubricating oil pressure; A9 main reducer lubricating oil temperature; A10 intermediate reducer lubricating oil temperature; A11 tail reducer lubricating oil temperature; A12 fuel pressure; A13 vibration value at the main rotor speed frequency; A14 vibration value at the main rotor first-order pass frequency; A15 vibration value at the tail rotor speed frequency; A16 vibration value at the tail rotor first-order pass frequency; A17 vibration value at the tail transmission shaft horizontal axis speed frequency; A18 vibration value at the tail transmission shaft oblique axis speed frequency.

[0117] The trend graph generated by the data of multiple sessions of the present invention can truly reflect the changes in the operating performance of a certain component of the helicopter, and can infer the over-limit time, which can be used as a basis for the need for in-depth maintenance, and the system components can be deeply inspected and maintained as soon as possible to avoid over-limit use and failures.

[0118] The present invention affects flight safety, involves key components, and theoretically should be stable within a certain range. There are 12 types of flight parameter key parameters: A1~A12. The mean value analysis method can more truly reflect the state changes of the helicopter. There are 6 types of vibration key parameters that affect flight safety, involve key components, and theoretically should be as small as possible: A13~A18. The extreme value analysis method can better reflect the vibration level changes of the helicopter.

[0119] The line graph of the present invention is preferably a suitable trend expression method, and the 18 types of key parameter line graphs can be divided into 17 groups according to the value and readability.

[0120] The present invention uses the total displacement to judge the common flight weight, uses the radio altitude to judge the common flight altitude and the general level flight attitude, and uses the indicated airspeed to judge the common flight speed. Based on these three bases, a stable flight time interval is selected, and all the values ​​of the 12 types of flight parameter key parameters in this interval are selected, and the mean is generated using the flight parameter software or auxiliary software; the maximum values ​​of the 6 types of vibration key parameters in this interval are selected. The office software is used to generate a trend line chart for the data of more than 10 sessions.

[0121] The present invention considers that there are five situations in which the data trends are good: stable type, not obvious rising type, not obvious falling type, fluctuation tends to be stable type, and same good type within the group. Generally, we consider that there are eight situations that need to be analyzed and paid attention to: obvious rising type, steep rising type at the end, obvious falling type, steep falling type at the end, obvious rising type in fluctuation, obvious falling type in fluctuation, same bad type within the group, good and bad type within the group, and gap type within the group. In particular, for the helicopter vibration system, we also consider good situations as: obvious falling type, steep falling type at the end, and obvious falling type in fluctuation.

[0122] The present invention analyzes the trend impact of 6 situations of 17 groups of key parameter trends in 18 categories in total, combining the actual use and maintenance experience of helicopters and general mechanical and electrical principles, and obtains the results.

Claims

1. A method for analyzing helicopter flight parameter trends, characterized in that: The following steps are involved: Step 1: Obtain flight parameters for N consecutive flights; N is an integer greater than 10; Step 2: According to the type of flight parameters, obtain representative values ​​of flight parameters for N consecutive times; Step 3: Obtain a line graph based on representative values ​​of the flight parameters of N consecutive flights; Step 4: Determine the trend of the line graph, and determine whether it is necessary to perform a fault analysis on the helicopter based on the trend of the line graph.

2. The helicopter flight parameter trend analysis method according to claim 1, characterized in that: The types of flight parameters include: vibration type and non-vibration type.

3. The helicopter flight parameter trend analysis method according to claim 2, characterized in that: According to the type of flight parameters, obtain representative values ​​of flight parameters for N consecutive times, including: When the type of flight parameter is non-vibration type, the average value of the flight parameter of N consecutive times is taken as the representative value; When the type of the flight parameter is vibration, the maximum or minimum value of the flight parameter in N consecutive sessions is taken as the representative value.

4. The helicopter flight parameter trend analysis method according to claim 2, characterized in that: Line chart trends include: Stable, rising, falling and fluctuating types; The rising types include: obvious rising type, not obvious rising type, and steep rising type at the end; The descending types include: obvious descending type, unobvious descending type, and steep descending type at the end; The fluctuation types include: fluctuation tends to be stable, fluctuation with obvious increase, and fluctuation with obvious decrease.

5. The helicopter flight parameter trend analysis method according to claim 4, characterized in that: When there are multiple identical flight parameters in each session, determine whether the helicopter needs to be analyzed for failure based on the trend of the line graph, including: When the type of flight parameter is non-vibration type, when there is any of the following in the trend of multiple line graphs of the same flight parameter, or when there is a gap within the group, it is determined that the helicopter needs to be fault analyzed: The obvious rising type, the steep rising type at the end, the obvious falling type, the steep falling type at the end, the obvious rising type during fluctuation or the obvious falling type during fluctuation.

6. The helicopter flight parameter trend analysis method according to claim 4, characterized in that: When there are multiple identical flight parameters in each session, determine whether the helicopter needs to be analyzed for failure based on the trend of the line graph, including: When the type of flight parameter is vibration, when there are any of the following trends in multiple line graphs of the same flight parameter, or when there is a gap within the group, it is determined that the helicopter needs to be analyzed for failure: The obvious rising type, the steep rising type at the end, and the obvious rising type during fluctuation. Determine whether a helicopter fault analysis is required based on the type of flight parameters and the trend of the line graph.

7. The helicopter flight parameter trend analysis method according to claim 1, characterized in that: Get the flight parameters of N consecutive flights, including: Obtain flight parameters of N consecutive stable flight segments.

8. The helicopter flight parameter trend analysis method according to claim 7, characterized in that: The changes in flight weight, flight altitude and level flight attitude during the stable flight phase are within the preset range; The flight weight is determined based on the total distance displacement, the level flight attitude and flight altitude are determined based on the radio altitude, and the flight speed is determined based on the indicated airspeed.

9. The helicopter flight parameter trend analysis method according to claim 2, characterized in that: The flight parameters include: A1 main rotor speed; A2 engine gas turbine speed; A3 engine power turbine speed; A4 engine turbine inter-turbine temperature; A5 engine lubricating oil temperature; A6 engine lubricating oil pressure; A7 hydraulic pressure; A8 main reducer lubricating oil pressure; A9 main reducer lubricating oil temperature; A10 intermediate reducer lubricating oil temperature; A11 tail reducer lubricating oil temperature; A12 fuel pressure; A13 vibration value at the main rotor speed frequency; A14 vibration value at the first-order pass frequency of the main rotor; A15 vibration value at the tail rotor speed frequency; A16 vibration value at the first-order pass frequency of the tail rotor; A17 vibration value at the horizontal axis speed frequency of the tail drive shaft; A18 vibration value at the oblique axis speed frequency of the tail drive shaft.

10. The helicopter flight parameter trend analysis method according to claim 9, characterized in that: Vibration flight parameters include: A1 main rotor speed; A2 engine gas turbine speed; A3 engine power turbine speed; A4 engine turbine room temperature; A5 engine oil temperature; A6 engine oil pressure; A7 hydraulic pressure; A8 main reducer oil pressure; A9 main reducer oil temperature; A10 intermediate reducer oil temperature; A11 tail reducer oil temperature; A12 fuel pressure; Non-vibration flight parameters include: A13 vibration value at the main rotor speed frequency; A14 vibration value at the main rotor first-order pass frequency; A15 vibration value at the tail rotor speed frequency; A16 vibration value at the tail rotor first-order pass frequency; A17 vibration value at the tail drive shaft horizontal axis speed frequency; A18 vibration value at the tail drive shaft oblique axis speed frequency.

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