Zieja Mariusz, Barszcz Piotr: Determination of time intervals between subsequent corrosion inspections based on the example of the TS-11 „ISKRA” aircraft. Wyznaczanie okresów wykonywania przeglądów korozyjnych na przykładzie samolotu TS-11 „ISKRA”.

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DETERMINATION OF TIME INTERVALS BETWEEN

SUBSEQUENT CORROSION INSPECTIONS BASED ON

THE EXAMPLE OF THE TS-11 ‘ISKRA’ AIRCRAFT

WYZNACZANIE OKRESÓW WYKONYWANIA

PRZEGLĄDÓW KOROZYJNYCH NA PRZYKŁADZIE

SAMOLOTU TS-11 „ISKRA”

Mariusz Zieja, Piotr Barszcz

Air Force Institute of Technology mariusz.zieja@itwl.pl; piotr.barszcz@itwl.pl

Abstract: When the operation is driven by the actual technical condition of the equipment with current monitoring of the reliability level the problem appears how to schedule inspections intended for restoring sound technical condition of aircrafts with regard to corrosion protective coatings and keep them permanently available for operation with determination of maintenance jobs that must be carried out in the plane. The methods that enable estimation how frequently inspections for detection of corrosion traces should be carried out include the method of characteristic sets, the Fourier spectral analysis as well as the methods of indices that reflect the process of the aircraft operation. Each of the foregoing methods is suitable for the equipment operation but the only method that takes into account the conditions that occurred during operation of the specific aircraft unit is the method of indices that reflects the process of the aircraft operation.

Keywords: corrosion inspection, condition-driven operation, fault, defect.

Streszczenie: Problemem do rozwiązania przy eksploatacji według stanu technicznego z kontrolowanym poziomem niezawodności jest wyznaczenie okresów wykonywania przeglądów przywracających zdatność samolotu pod kątem korozji i stanu pokryć ochronnych oraz wyznaczeniu zakresu prac, które należy wykonać na samolocie. Metodami pozwalającymi na szacowanie częstości wykonywania przeglądów korozyjnych są metoda charakterystycznych zbiorów, analiza widmowa Fouriera oraz metoda wskaźników charakteryzujących proces eksploatacji. Każda z metod jest przydatna w eksploatacji, jednak metodą, która uwzględnia warunki, w jakich był eksploatowany określony egzemplarz samolotu jest metoda wskaźników charakteryzujących proces eksploatacji. Słowa kluczowe: przegląd korozyjny, eksploatacja według stanu, uszkodzenie, niesprawność.

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1. Introduction

The scheduled and preventive method of maintenance and services (according to overhaul lives) assumes that a specific program of prophylactic operations must be carried out after a predefined period of calendar time or operation time expires, regardless the condition of the system and the aircraft. On the contrary, the condition-driven method is in place when milestones of the operation lifetime are determined according to the actual technical status of the equipment. The condition-driven operation can be subdivided into two basis groups: with monitoring of the reliability level and with monitoring of operational parameters of the equipment. Maintenance and overhauls driven by the equipment condition with monitoring of the reliability level consists in acquisition, processing and analyzing of information related to reliability and efficiency of a set of products classified to a single, common type, where results of that procedures serve as a basis for taking decisions on the scope of necessary prophylactic and maintenance jobs for the entire set of products or for specific groups included into the product set. Each item of the product is replaced after such a defect that presents no harm to the overall functional system. The method that assumes condition-driven execution of maintenance and service operations with monitoring of the equipment parameters entails continuous or periodic checks and measurements of parameters that are crucial for technical condition of both the functional system and the product. The decision to replace or to restore the operability of the product is made when values of monitored parameters approach critical thresholds. When the condition-driven method of maintenance and service with monitoring of the reliability level is applied it is necessary to select the indices that dependably depict the process of equipment operation, which, in consequence, leads to the need of appropriate classification of all the events that may occur during the aircraft operation.

Correct classification of faults and deficiencies enables to eliminate errors that may be made when operability indices of fault tolerance are calculated with the use of formulas offered by the theory of reliability. Instead, actual operability indices of fault tolerance are assessed on the basis of results from examinations and operational parameters of avionic products.

In order to unify the approach to the analyses of processes occurring during operation of aircraft equipment, the term ‘fault’ shall be understood as any deviation from the fault-free status whilst the general operability of the aircraft is maintained. Defects of certain devices not always lead to inoperability of the overall system the device is included in. If the device is duplicated or during the specific flight the system has already completed the operations the device is involved it means that the system in fact is faulty. On one hand, when the aircraft comes back and successful completion of its task during the flight is reported it means that its major systems were operable during the essential part of the flight. Nevertheless, during the after-flight inspection a number of failures or deficiencies of individual devices are detected and eventually the overall aircraft should be classified as faulty.

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2. Parameter of fault flux

One of major indices that define the process of equipment operation is the parameter of fault flux. That parameter was calculated on the basis of the totalized flying time expressed in hours and totalized number of faults that happened to TS-11 ‘Iskra’ aircrafts during the analyzed time period.

The method for calculation of average statistical parameters was derived from the following assumptions:

 the totalized flying time of the TS-11 ‘Iskra’ aircrafts for a specific period of time is known and is calculated as a simple sum of flying time values for individual units:



  n i i t T 1 (1) where:

ti – flying time of the ith unit of TS-11 ‘Iskra’ aircraft;

n – number of aircraft units.

 the total number of faults is known and is calculated as a simple sum of faults that happened to individual units of the TS-11 ‘Iskra’ aircraft:



  n i i N N 1 (2) where:

Ni – number of faults that happened to an individual unit of the TS-11 ‘Iskra’

aircraft:

For calculation of average statistical indices the following designations were adopted:

Tn – average flying time per a single fault:

N

T

N

t

T

_n i i n i i n





  1 1 (3)

The flux of faults for an aircraft (which is a repairable device) is understood as a number of faults that happened to a specific aircraft during a time unit. The parameters of the fault flux shall be denoted as ωn. Therefore the following is true:

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n n i i n i i n T N t 1 1 1 1  



 



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The average value of the fault flux parameter for a large number of aircrafts representing various manufacturing series of equipment, operated under diverse climatic conditions and maintained by various technical staff is the parameter that sufficiently objectively defines the fault-tolerance level of an aircraft design. It has been found out that the more defects are detected on the ground during technical maintenance of aircrafts, the less number of faults happens during aircraft flights. The parameter of fault flux reflects the amount of work carried out by the engineering and aircraft staff with the aim to restore operability of aircrafts. Fault fluxes for basic systems are then added up to obtain the fault flux for the aircraft as a whole. Therefore, the sum of values for fault flux associated with basic systems is equal with the value of fault flux assigned to the whole aircraft. The analysis of how the value of the fault flux varies in time (years of the aircraft operation) makes it possible to estimate effectiveness of individual measures undertaken to improve fault tolerance. It is typically observed that for aircrafts with the design featuring the high degree of unification with the design properties of its predecessors, the parameter value of fault flux is usually diminished during first years of the aircraft operation. It is associated with application of well proven, perfectly tuned and highly reliable design solutions. On the contrary, for aircrafts with great part of subassemblies and modules designed completely anew with essential novelty of technical solutions, a rapid jump in the fault flux parameter is usually recorded. Such an estimation of the fault flux parameter enables to make comparison between the achieved level of the aircraft fault tolerance and the requirements of the relevant technical specification (WTT).

3. Method of characteristic sets

Fig. 1 presents graphs that demonstrate how the value of the fault flux parameter depends on both the flying time and age of the population of aircrafts that comprises TS-11 ‘Iskra’ aircrafts subjected to the analysis.

In order to distinguish characteristic sets of TS-11 ‘Iskra’ aircrafts and taking account for parameter values of the fault flux, the sets were grouped with the use of the method of squares, where groups are compiled of single squares that incorporate elements of the populations.

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Wiek = 371,2548-0,0417*x Nalot = 2010,849-0,7136*x 0 50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800 850 900 950 1000 1050 1100 1150 1200 1250 1300 1350 1400 1450 1500 1550 1600

Parametr strumienia niesprawności ωn samolotu TS-11 "Iskra" [1/h] 0 150 300 450 600 750 900 1050 1200 1350 1500 1650 1800 1950 2100 2250 2400 2550 2700 2850 3000 3150 3300 3450 Nalot [h] 0 150 300 450 600 750 900 1050 1200 1350 1500 1650 1800 1950 2100 2250 2400 2550 2700 2850 3000 3150 3300 3450 Wiek [mies. ] Wiek Nalot

Fig. 1 The interrelationships between the parameter of fault flux against the flying time and age of the analyzed population comprising TS-11 ‘Iskra’ aircrafts.

ωn = 428,3803-0,7124*x 2 6 5 2 7 0 2 7 5 2 8 0 2 8 5 2 9 0 2 9 5 3 0 0 3 0 5 3 1 0 3 1 5 3 2 0 3 2 5 3 3 0 3 3 5 3 4 0 3 4 5 3 5 0 3 5 5 3 6 0 3 6 5 3 7 0 3 7 5 3 8 0 3 8 5 3 9 0 3 9 5 4 0 0 4 0 5 4 1 0 4 1 5 4 2 0 4 2 5 4 3 0 Wiek 0 70 140 210 280 350 420 490 560 630 700 770 840 910 980 1050 1120 1190 1260 1330 1400 1470 1540 Pa ra m etr st ru m ie ni a n ie sp ra w no śc i ω [ 1 /h ] 49 87 35 17 1409 1615 1232

Fig. 2 Relationship between age of the TS-11 ‘Iskra’ aircraft and the parameter of fault flux

Pa ra m et er o f fa u lt f lu x  [ 1 /h ] Age Age Flying time Age Flying time A g e [mo n th s] Fl y in g t ime [ h ]

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As it is shown in Fig. 2 and Fig. 3, the time of airframe operation for the population of the TS-11 ‘Iskra’ aircrafts falls within the limits from 153÷49 months, i.e. 13÷8 years, whilst the flying time between the characteristic sets is 2096÷210 hours. According to such an approach, the safe flying time for TS-11 ‘Iskra’ aircrafts operated by Armed Forces of Polish Republic is 210 hours with 49 months of continuous operation. According to observations, it was the period of time when no fault flux was recorded. Therefore, one can say that the inspection intended to restore technical operability of the airframe with regard to corrosion and deterioration of protective coating should be carried out after each 49 months of operation or 210 hours of flying time.

ωn = 334,3732-0,0875*x 7 00 770 840 910 980 1 050 1120 1190 1260 1330 1400 1470 5401 1610 1680 1750 1820 1890 1960 2030 1002 2170 2240 2310 2380 2450 2520 2590 2660 2730 2800 2870 2940 3010 3080 3150 Nalot [h] 0 70 140 210 280 350 420 490 560 630 700 770 840 910 980 1050 1120 1190 1260 1330 1400 1470 1540 Par ametr strumi en ia nie sp raw nośc i ωn [1/h] 1148 210

Fig. 3 Relationship between flying time of the TS-11 ‘Iskra’ aircraft and the parameter of fault flux.

4. Method of fourier spectral analysis

In order to illustrate the approach to the problem of determining the frequency of inspection and maintenance operations intended to restore technical operability of aircrafts, the TS-11 ‘Iskra” aircrafts with their numbers 1232, 1615 and 1409 were selected for the examination.

The investigation was carried out on the basis of information collected about operational defects recorded by means of the SAMANTA system with further processing of the data with the use of the Fourier transformation.

The Fourier transformation is an integral transformation of time-dependant functions from the time domain to the frequency domain. It obtained its name in honour of Jean Baptiste Joseph Fourier. The Fourier transform results from the

P ar ame te r o f fa u lt f lu x n [1 /h ] Flying time [h]

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Fourier transformation (the transform is a function whilst transformation is an operation with the function where the transform is obtained as the result of transformation). The Fourier transformation decomposes the specific function into a series of periodic functions in such a way that the obtained transform clearly indicates which frequencies are included in the primary function.

The analysis of frequency of carrying out wide-scope inspections of the TS-11 aircraft ‘Iskra’ No. 1232

Fig. 4 presents the graph that demonstrates how the flux of faults varied during subsequent years of the aircraft operation.

Fig. 4. Parameter of fault flux for the TS-11 ‘Iskra’ aircraft No. 1232 during subsequent years

The maximum values of frequency demonstrate cyclical variability, no trend is visible and the average value for that series exceeds zero. Fig. 5 presents the graph for the periodogram. As one can see in Fig. 5, one clear maximum is visible that occurs for the frequency of about 0.43. All the values for the periodogram are summarized in the table below.

The frequency means a number of cycles per a time unit, where the time unit is understood as the time period between two subsequent observations. Therefore, the frequency of 0.42 corresponds to the period of 2. The maximum values of the fault frequency demonstrate clear periodic cycle with the frequency of 2 years. It is reasonable to make the periodogram smoother, remove random deviations and obtain assessment for the spectral density.

Pa ra m et er o f fa u lt f lu x n [1 /h ] fo r th e TS -1 1 ‘Isk ra ’ ai rc ra ft N o. 1 23 2 Years

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0 ,0 0 0 ,0 2 0 ,0 4 0 ,0 6 0 ,0 8 0 ,1 0 0 ,1 2 0 ,1 4 0 ,1 6 0 ,1 8 0 ,2 0 0 ,2 2 0 ,2 4 0 ,2 6 0 ,2 8 0 ,3 0 0 ,3 2 0 ,3 4 0 ,3 6 0 ,3 8 0 ,4 0 0 ,4 2 0 ,4 4 0 ,4 6 0 ,4 8 0 ,5 0 Częstotliwość 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000 55000 60000 65000 70000 75000 80000 85000 90000 95000 1E5 1,05E51,1E5 1,15E5 1,2E5 Wa rto śc i p er io do gr am u

Fig. 5 The graph of periodogram Table 1

Spectral analysis: ω : =(1/(v1/v2))*1000 (Inspections TS-11No.1232.STA) No. of obs.: 14

Frequency Period Coeff. Coeff. Periodog. Density Hamming 0 0.000000 1.2045 0.0000 10.2 28264.97 0.035714 1 0.071429 14.00000 -12.4324 -81.1893 47223.9 42238.59 0.241071 2 0.142857 7.00000 103.9719 13.1683 76885.0 53600.66 0.446429 3 0.214286 4.66667 54.8842 -26.8067 26116.1 42979.22 0.241071 4 0.285714 3.50000 77.7617 -18.4132 44701.5 35359.92 0.035714 5 0.357143 2.80000 24.0675 26.6714 9034.2 44095.65 6 0.428571 2.33333 124.7974 -34.0977 117159.2 61002.94 7 0.500000 2.00000 -20.9561 0.0000 3074.1 58505.15 Frequency P erio d o g ra m v al u es

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Fig. 6 Spectral density

One of the maximum peaks is more significant. Fig. 7 presents the spectral density as the function of period.

Wagi Hamminga: ,0357 ,2411 ,4464 ,2411 ,0357 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Okres 20000 22000 24000 26000 28000 30000 32000 34000 36000 38000 40000 42000 44000 46000 48000 50000 52000 54000 56000 58000 60000 62000 64000 66000 68000 70000 72000 74000 76000 78000 80000 Gę st ość wid m owa

Again, it is seen that maximum peaks of fault intensity for the PS-11 ‘Iskra’ aircraft No. 1232 demonstrate the clear two-year long cycle.

Hamming weight coefficients .0357 .2411 .4464 .2411 .0357

Period Sp ec tr al d en sity

Hamming weight coefficients .0357 .2411 .4464 .2411 .0357 Frequency Spect ra l den si ty

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The analysis of frequency of carrying out wide-scope inspections of the TS-11 ‘Iskra’ aircraft No. 1409

1 9 9 7 1 9 9 8 1 9 9 9 2 0 0 0 2 0 0 1 2 0 0 2 2 0 0 3 2 0 0 4 2 0 0 6 2 0 0 7 2 0 0 8 2 0 0 9 2 0 1 0 Rok 0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102 108 114 120 126 132 138 144 150 156 Pa ra m etr st ru m ie ni a n ie sp ra w no śc i ωn [ 1 /h ] s a m o lo tu T S -1 1 " Is k ra " N r 1 4 0 9

Fig. 8 Parameter of fault flux for the TS-11 ‘Iskra’ aircraft No. 1409 during subsequent years

0 ,00 0,02 0,04 0,06 0,08 0,10 0,12 0,14 0,16 0,18 0,20 0,22 _{Częstotliwość},240 0,26 ,280 ,300 0,32 0,34 0,36 ,380 0,40 0,42 0,44 0,46 0,48 0,50 0 300 600 900 1200 1500 1800 2100 2400 2700 3000 3300 3600 3900 4200 4500 4800 5100 5400 5700 6000 6300 6600 6900 7200 7500 7800 Wartoś ci periodog ramu

Fig. 9 The graph of periodogram

P ara m eter o f fa u lt flu x n [1 /h ] fo r th e TS -1 1 ‘Isk ra ’ aircra ft No . 1 40 9 Years Per io d o g ra m v alu es Frequency

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Again, the peak values of frequency show cyclicality with no trend and the average value for that series is greater than zero. The periodogram is shown in Fig. 9. As one can see in Fig. 9, only one clear maximum peak occurs at the frequency of 0.25. Below is the table with all the values of the periodogram.

Table 2

Spectral analysis: Ů : =(1/(v1/v2))*1000 (Inspections TS-11No.1409 Oblicz.STA) No. of obs.: 12

Frequency Period Coeff. Coeff. Periodog. Density Hamming 0 0.000000 6.4803 0.0000 251.963 1436.935 0.035714 1 0.083333 12.00000 -10.0266 -16.6037 2257.288 2201.567 0.241071 2 0.166667 6.00000 -0.1123 23.4718 3305.632 3813.120 0.446429 3 0.250000 4.00000 34.1237 -5.3250 7156.715 4507.622 0.241071 4 0.333333 3.00000 13.2160 -10.0208 1650.471 2837.222 0.035714 5 0.416667 2.40000 2.3564 12.9755 1043.503 1193.771 6 0.500000 2.00000 -5.0697 0.0000 154.208 689.851

The frequency means a number of cycles per a time unit, where the time unit is understood as the time period between two subsequent observations. Therefore, the frequency of 0.25 corresponds to the period of 4. The maximum values of the fault frequency demonstrate clear periodic cycle with the frequency of 4 years. It is reasonable to make the periodogram smoother, remove random deviations and obtain assessment for the spectral density.

Wagi Hamminga: ,0357 ,2411 ,4464 ,2411 ,0357 0 ,00 0,02 0,04 0,06 0,08 0,10 0,12 0,14 0,16 0,18 0,20 0,22 _{Częstotliwość},240 0,26 ,280 ,300 0,32 0,34 0,36 ,380 0,40 0,42 0,44 0,46 0,48 0,50 600 800 1000 1200 1400 1600 1800 2000 2200 2400 2600 2800 3000 3200 3400 3600 3800 4000 4200 4400 4600 4800 5000 Gęstość widmowa

Hamming weight coefficients .0357 .2411 .4464 .2411 .0357 Frequency Sp ec tr al d en sity

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152

One of the maximum peaks is now more evident. Fig. 11 presents the spectral density as a function of time period.

Wagi Hamminga: ,0357 ,2411 ,4464 ,2411 ,0357 0 1 2 3 4 5 6 7 8 9 10 11 12 13 Okres 600 800 1000 1200 1400 1600 1800 2000 2200 2400 2600 2800 3000 3200 3400 3600 3800 4000 4200 4400 4600 4800 5000 Gęstość widmow a

Again, one can see that fault intensity for the PS-11 ‘Iskra’ aircraft No. 1409 is a periodic function with clearly visible 4-year long cycle.

The analysis of frequency of carrying out wide-scope inspections of the TS-11 ‘Iskra’ aircraft

1 9 9 4 1 9 9 5 1 9 9 6 1 9 9 7 1 9 9 8 1 9 9 9 2 0 0 0 2 0 0 1 2 0 0 2 2 0 0 3 2 0 0 4 2 0 0 5 2 0 0 6 2 0 0 7 2 0 0 8 2 0 0 9 Rok 0 30 60 90 120 150 180 210 240 270 300 330 360 390 420 450 480 510 540 570 600 630 660 690 720 750 780 Pa ra m etr st ru m ie ni a n ie sp ra w ωn [ 1 /h ] s a m o lo tu T S -11 " Is k ra "

Fig. 12 Parameter of fault flux for the TS-11 ‘Iskra’ aircraft during subsequent years

Period Sp ec tr al d en sity P ar am eter o f fa u lt f lu x n [1 /h ] fo r th e T S -1 1 ‘I sk ra’ air cr af t Years

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Again, the peak values of frequency show cyclicality with no trend and the average value for that series is greater than zero. The periodogram is shown in Fig. 13.

0 ,0 0 0 ,0 2 0 ,0 4 0 ,0 6 0 ,0 8 0 ,1 0 0 ,1 2 0 ,1 4 0 ,1 6 0 ,1 8 0 ,2 0 0 ,2 2 0 ,2 4 0 ,2 6 0 ,2 8 0 ,3 0 0 ,3 2 0 ,3 4 0 ,3 6 0 ,3 8 0 ,4 0 0 ,4 2 0 ,4 4 0 ,4 6 0 ,4 8 0 ,5 0 Częstotliwość 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000 55000 60000 65000 70000 75000 80000 85000 90000 95000 1E5 1,05E5 1,1E5 1,15E5 1,2E5 W ar to śc i p er io do gr am u

Fig. 13 The graph of periodogram

As one can see in Fig. 13, only one clear maximum peak occurs at the frequency of about 0.06. All the figures used in the periodogram are summarized in the table below.

Table 3 Spectral analysis: ωn (Table2TS-11.STA) Number of observations: 16

Frequency Period Coeff. Coeff. Periodog. Density Hamming 0 0.000000 -0.0000 0.00000 0.0 62811.05 0.035714 1 0.062500 16.00000 118.1567 20.93852 115195.4 82659.60 0.241071 2 0.125000 8.00000 104.6589 42.06861 101786.0 92492.34 0.446429 3 0.187500 5.33333 86.9241 38.45367 72275.9 74671.42 0.241071 4 0.250000 4.00000 72.3625 35.60000 52029.5 53387.82 0.035714 5 0.312500 3.20000 59.9096 25.46414 33900.6 37393.26 6 0.375000 2.66667 53.6411 19.34361 26012.4 28211.50 7 0.437500 2.28571 54.3096 8.64898 24194.7 24111.60 8 0.500000 2.00000 50.7375 0.00000 20594.4 22717.25

The frequency means a number of cycles per a time unit, where the time unit is understood as the time period between two subsequent observations. Therefore, the frequency of 0.06 corresponds to the period of 16. The maximum values of the fault

Per io d o g ra m v alu es Frequency

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frequency demonstrate clear periodic cycle with the frequency of 16 years (or, perhaps, some longer). It is reasonable to make the periodogram smoother, remove random deviations and obtain assessment for the spectral density.

Wagi Hamminga: ,0357 ,2411 ,4464 ,2411 ,0357 0 ,00 0,02 0,04 0,06 0,08 0,10 0,12 0,14 0,16 0,18 0,20 0,22 _{Częstotliwość},240 0,26 ,280 ,300 0,32 0,34 0,36 ,380 0,40 0,42 0,44 0,46 0,48 0,50 20000 25000 30000 35000 40000 45000 50000 55000 60000 65000 70000 75000 80000 85000 90000 95000 1E5 Gęstość widmow a

One of the maximum peaks is now better visible. Spectral density as a function of time period is shown in Fig. 15.

Wagi Hamminga: ,0357 ,2411 ,4464 ,2411 ,0357 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Okres 20000 25000 30000 35000 40000 45000 50000 55000 60000 65000 70000 75000 80000 85000 90000 95000 1E5 Gęstość widmow a

Period Sp ec tr al d en sity

Frequency Sp ec tr al d en sity

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The graph serves as the next evidence that maxima peaks of fault intensities for the TS-11 ‘Iskra’ aircraft occur within the time period of 8 years.

For the TS-11 ‘Iskra’ aircraft with the number 1615 it was infeasible to find out the period for the maximum intensity of faults as the Fourier spectral analysis requires at least 10 observations, which could not been fulfilled for the specific plane.

5. Method of indices that determine the operation process

To reasonably schedule all the jobs intended for identification of the deterioration degree of protective coatings and corrosion failures the model was proposed that should enable determination of frequency of corrosion inspections.

The interval coefficient for execution of corrosion inspections for such types of aircrafts is to be calculated from the formula (5):







   10 1 i type i type i type cor F wt K 5

The interval coefficient for execution of corrosion inspections for any specific unit of aircrafts is to be calculated from the formula (6) with slight modifications as below:







   10 1 i unit i unit i unit cor F wt K 6

The method is based on determination of the maximum, minimum and average age of airframes that guarantee safe operation of them. These three characteristic parameters are used to plot an exponential curve. When the interval coefficient Kcor

is known, it is possible to find out the individual period for execution of inspections. Based on available data acquired for the set of TS-11 ‘Iskra’ aircrafts operated by Polish Armed Forces the exponential curve was plotted. That curve is useful to set up individual schedules for execution of inspections intended for detection of corrosion spots and deterioration of protective coatings.

The interval coefficient for execution of corrosion inspections is to be determined on the basis of the aircraft age expressed in months, the flying time expressed in the number of hours the specific aircraft travelled in air during its operation lifetime, the average flying time per year, intensity of operation, category of corrosivity typical for the region where assignments are to be executed, operation vulnerability to development of corrosion processes, effect of destructive processes during operation of airframes on their condition, technical wear of airframe components, total number of takeoff/landing operations and average number of takeoff/landing operations per year.

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Pkortyp = 1,8879E5*exp(-0,2847*x) 24, 8 24, 9 25, 0 25, 1 25, 2 25, 3 25, 4 25, 5 25, 6 25, 7 25, 8 25, 9 26, 0 26, 1 26, 2 26, 3 26, 4 26, 5 26, 6 26, 7 26, 8 26, 9 27, 0 27, 1 27, 2 27, 3 27, 4 27, 5 27, 6 27, 7 27, 8 27, 9 28, 0 28, 1 28, 2 28, 3 28, 4 28, 5 28, 6 28, 7 28, 8 28, 9 29, 0 29, 1 29, 2 Kkoregz 44 48 52 56 60 64 68 72 76 80 84 88 92 96 100 104 108 112 116 120 124 128 132 136 140 144 148 152 156 160 Pkor e g z TS-11 Nr 1232 TS-11 Nr 1615 TS-11 Nr 1409

Fig. 16. The curve that is used to determine a schedule of corrosion inspections on the basis of the interval coefficient Kcor for execution of corrosion inspections.

6. Recapitulation of the analysis results

The method of characteristic sets made it possible to establish that the inspections of TS-11 ‘Iskra’ aircrafts intended for finding corrosion spots and deterioration of protective coatings with the aim to restore technical operability of the planes should be carried out within 49 months or after each 210 hours of the flying time. However, the method is really troublesome when the issue is to determine schedule and frequency of inspections for individual aircraft units.

The method based on the Fourier spectral analysis made it possible to reveal that inspections for corrosion spots and deterioration of protective coatings aimed at restoration of the aircraft operability should be differentiated for individual aircraft units and carried out within the following time periods:

 Nr 1232 – inspections should take place every two years,  Nr 1409 – inspections should take place every four years,

 Nr 1615 – it proved infeasible to determine schedule of inspections.

Determination of schedules for corrosion inspections on the basis of the Fourier analysis leads to results that do not take into account the processes that are associated with operation of a specific aircraft type and unit.

The analysis carried out on the basis of indices that are characteristic of the process of the aircraft operation has revealed that for the selected aircrafts:

type cor P Pcor unit unit cor K

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 No. 1232 – the inspection with the aim to restore operability of the airframe should be carried out in 153 months,

The analysis of indices that are characteristic of the process of the aircraft operation has demonstrated that the earliest time for the maintenance jobs is 49 months whilst the latest time is 153 months.

7. Conclusions

 When the method of characteristic sets is used, the inspections for corrosion spots and deterioration of protective coatings aimed at restoration of the aircraft operability refer to the entire population of aircrafts in operation.

 The analysis carried out on the basis of the Fourier spectral method shows that it is the method that makes it possible to determine frequency of inspections that should be executed for each aircraft unit; however, conditions of the aircraft operation are neglected.

 When operation of aircrafts is driven by actual technical conditions of the planes it is necessary to carry out inspections intended for restoration of operability of the aircrafts at the level that guarantees their safe operation. The inspections should take place according to individual schedules, with the frequency individually calculated against the results related to a defined aircraft unit.

 The inspections must adhere to the approved schedule of inspections intended for restoration of operability of the aircrafts at the level that guarantees safe operation thereof. Such a schedule must be developed individually for each aircraft unit.

 The schedule of inspections intended for restoration of operability of the aircrafts at the level that guarantees their safe operation should be updated after each 12 months on the basis of data obtained from the operation and maintenance staff.

 When the operation of aircrafts is driven by their actual condition, it is necessary to keep records on faults and defects detected during operation and maintenance of the flying stock in order to carry out the analysis intended for estimation of inspection schedules to maintain integrity of airframes

 The inspections intended for restoration of operability of the aircrafts at the level that guarantees their safe operation should be executed in accordance with the research methodology developed by experts from the Air Force Institute of Technology (ITWL).

(18)

8. References

[1] Анцелиович Л.Л. Надежность, безопасность и живучесть самолета. Машиностроение, Москва, 1985. (ANTSELIOVITCH L.L., Reliability, safety and lifetime of aircrafts. Mashinostrojene, Moscow, 1985.)

[2] Lewitowicz J., Borgoń J., Ząbkowicz W.: Problemy badań i eksploatacji techniki lotniczej. Wyd. ITWL, Warszawa 1993. (Issues of examinations and operations of aircraft equipment. Ed. ITWL, Warsaw, 1993).

[3] Pakiet: Statistica PL dla Windows. Wyd. StatSoft, Kraków 1994. (Software package: Statistica PL for Windows. Ed. StatSoft, Cracow, 1994).

[4] Jaźwiński J., Borgoń J.: Niezawodność eksploatacyjna i bezpieczeństwo lotów. Wyd. KiŁ Warszawa 1989. (Operational reliability and safety of flights. Ed. WKiŁ, Warsaw, 1989).

[5] Смирнов Н.Н., Ицкович А.А.: Обслуживание и ремонт авиационной техники по состоянию. Транспорт, 1980. (SMIRNOV N. N., ICKOVITCH A. A.: Condition-driven maintenance and overhauls of aircraft equipment. Transport, 1980)

Maj. Mariusz Zieja PhD, Eng. graduated from Military University of Technology in 2000 (M.Sc. Eng. in Mechatronics with specialization in Aircraft Avionics). In 2008 he achieved PhD in Mechanical Engineering. He is engaged in development and implementation of IT systems to support aircraft maintenance, safety and reliability management. Since 2002 he has been working for Air Force Institute of Technology.

Piotr Barszcz PhD, Eng. graduated from Military University of Technology in 1984 (M.Sc. Eng. in Mechanics with specialization in Airplanes & Helicopters). In 2000 he achieved PhD in Mechanical Engineering. He is engaged in development and implementation of IT systems to support aircraft maintenance, safety and reliability management. Since 1985 he has been working for Air Force Institute of Technology.