TECHNIQUE OF FORMATION HOMOGENEOUS SAMPLE SAME OBJECTS. Muradaliyev A.Z.

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1 TECHNIQUE OF FORMATION HOMOGENEOUS SAMPLE SAME OBJECTS Muradalyev AZ Azerbajan Scentfc-Research and Desgn-Prospectng Insttute of Energetc AZ1012, Ave HZardab-94 Importance of a problem Relablty of electro power systems (EPS) n many respects depends on relablty of the captal equpment and devces (objects EPS) Modern objects EPS concern to a category of complex objects (CO) CO - multvarate, n other words, characterzed greater number of attrbutes and ther versons As frst approxmaton, these attrbutes presented by two groups The frst group of attrbutes characterzes a desgn CO and the second presented n characterstcs sheet, and the second group -condtons of operaton CO If necessary estmatons of a techncal condton CO (for example, at an estmaton of expedency of a concluson CO on major overhaul), data on a techncal condton of t CO, as a rule, t appears nsuffcent Insuffcent there are not only data on emergency and scheduled swtchngoff, but also data on sze of deteroraton and speed of ts change For ths reason normatve materals attracton of retrospectve data about relablty same CO [1] recommended At ths classfcaton nfluence, the second group of attrbutes that ncreases rsk of the erroneous decson s not consdered Classfcaton CO represents not only mportant, but also a dffcult problem Its dffculty caused by necessty of research of homogeneous (unpresentable) sample CO from a fnal data set (FDS) Accordng to GOST «Statstcal methods of product qualty control» representatve sample s sample (test), whch suffcently reflects propertes of the gven set (n our case FDS) as a whole But what such "suffcently"? Let's enter some defntons of terms: - under unpresentable we shall understand sample on a number of versons of attrbutes (VA), statstcal functon of dstrbuton (sfd) whch not casually dffers from sfd FDS [2] - under FDS we shall understand the retrospectve nformaton presented n the form of the emprcal table (ET) - under ET we shall understand the table whch lnes contan the nformaton on condtons (results of test) CO, and columns - versons of each of examned attrbutes [3] In the llustratve purposes as CO examne power transformers and autotransformers (further: transformers (TR)) On table 1 are resulted passport data TR, and n table 2 - condtons of operaton TR n AISTR [3] These data examned as attrbutes TR Tables 1 and 2 testfy that alongsde wth quanttatve estmatons VA, there are also qualty standards For example, a factory manufacturer TR, system of coolng, a consequence of refusal, etc Thus, attrbutes CO have varous scales of measurement 47

2 Table 1 Table 2 Formally, at classfcaton of retrospectve data on set VA, the nformaton on techncal condton TR sharply decreases, and n a greater part of cases does not allow have not only quanttatve, but also qualty standard of parameters of relablty TR At the same tme t s clear, what not all attrbutes TR are equally sgnfcant (from the pont of vew of relablty of work), and a functonal dvergence sfd FDS and samples should be not less guaranteed value of ts statstcal component Recommend method Assume that: - nameplate data and data on condtons of operaton of all TR power supply systems, and on dspatchng magaznes and certfcates of falures data on scheduled and emergency swtchng-off TR are receved On these data two are made ET, frst of whch (ET1) the second ncludes data on desgn features and condtons of operaton TR, and (ET2) - data on swtchng-off TR and mnmally necessary data for an nput n ET1; 48

3 - s known deduced on major overhaul TR for whch t s necessary to fnd homogeneous sample of the same objects Let's desgnate number examned TR through, number of attrbutes- n, number VA -th TR - r wth = 1, n Followng calculatons are spent: 1 For each of М TR the nterval of tme durng whch the characterstc of emergency and scheduled swtchng-off TR known s determned Desgnate ths nterval through wth = 1, М 2 In each of an nterval, t s determned total duraton of scheduled swtchng-off П (swtchng-off on CR, operatng repar, n a reserve, etc) Desgnate ths sze as ; М М М, 3 Determne sze П - - total duraton of work and dle tme n emergency = = 1 = 1, repar 4 Determned total number of emergency swtchng-off TR Consderng, that emergency swtchng-off happen automatc, manually and under the emergency applcaton, and consequences of swtchng-off TR under the emergency applcaton, as a rule, t s essental less consequences of frst two knds of swtchng-off, expedent to spend separate classfcaton of swtchng-off Desgnate number of examned emergency swtchng-off (for example, under the emergency ав applcaton) through n ; 5 Calculate an estmaton of specfc number of emergency swtchng-off TR: = ав n / In a bass of estmaton, there s assumpton of constant probablty occurrence emergency swtchng-off durng an ndvdual nterval of tme (year) Operatng experence shows, that non-falure operaton TR depends both on ther desgn, and from condtons of operaton Therefore, the average value of sze has no practcal sense Concrete TR can have n park TR analogues, n the form of same TR However, ths sample s non-unform, snce TR can dffer wth condtons of operaton (for example, servce lfe) Therefore, recommendaton [1] about expedency of the account of data on a techncal condton of the same objects demands the specfcaton If to agree wth the above-stated, t s possble to make followng next steps: 6 For everyone VA set TR the specfc number of emergency swtchng-off, j wth j =1, n s calculated The purpose of these calculatons s the fndng = max ; ; ; ; ; ( ), ma x,1, 2, 3, j; 7 Estmatons are compared and, max Comparson spent n vew of casual character of these estmatons, and n vew of not only errors of the frst, but also the second sort The methodology of ths comparson s based on the theory of statstcal modelng and the theory of check statstcal hypotheses and stated by us n [5] If t appears, that the hypothess about a casual dvergence and s more preferable (less sum errors of the frst and second sort), than an alternatve, max hypothess, havng n vew of, that a casual dvergence and,, max n smultaneously means a casual dvergence and, j wth j =1, n wthn the lmts of had statstcal data about emergency swtchng-off TR any of VA nsgnfcant and all TR s represented wth a fle of homogeneous same objects, specfc whch number of refusals equally Though at classfcaton of retrospectve data only to one attrbute t s mprobable, the statement at a casual dvergence and reman constant for any number VA Moreover, process of search of homogeneous, max 49

4 sample same TR stops, and management s (f necessary) transferred to a press of ther lst 8 If the hypothess about not casual dstncton and, sample TR for whch the specfc quantty of emergency swtchng-off equally s accepted for FDS and on these statstcal data s more preferable: 9 Estmatons, j, max are calculated wth 1, ( n -1) 10 Determned { }, ma x = max, j ( 1) ; n j ; = 11 Estmatons and, max (see tem 7) are compared; 12 See tem 8 Recurrence of cycles of classfcaton of data and checks of hypotheses s carred out up to an opportunty of the proved acceptance of a hypothess about a casual dvergence of estmatons and, max homogeneous sample same TR s resulted on fg1, max The ntegrated block dagram of algorthm of formaton of Fg1 Integrated block dagram of algorthm of formaton of homogeneous sample of the same objects CONCLUSION 1 Control of a techncal condton concrete TR retrospectve data about relablty same TR not always can far appear useful It concerns, frst, to TR wth the servce lfe exceedng normatve value, workng unlke controllable TR n condtons wth the ntensve storm actvty, through currents of short crcut exposed to frequent dynamc nfluence, etc 2 Method and algorthm of formaton of homogeneous sample same TR s developed 3 Practcal realzaton of algorthm and the program of formaton of homogeneous sample same TR allows to specfy lst TR, the nformaton on whch techncal condton promotes recognton of a techncal condton controllable TR and by that to rase objectvty of recommendatons on ncrease of relablty TR REFERENCES 1 Farhadzadeh EM, Muradalyev AZ, Farzalyev YZ Crteron of the supervson accuracy of ndexes relablty of power-generatng unts a state dstrct power staton Journal: 50

5 "Relablty: Theory&applcatons" R&RATA (Vol2 No) 2009, March, USA, p Lbov GS Method's foreheads of processng polytypc expermental date -Novosbrsk: Scence, 1981,160p 3 Farhadzadeh EM, Muradalyev AZ, Rafyeva TK, Ismaylova SM Feature of the organzaton and protecton of a database of transformers of a power supply system М: Power engneer 1, RD Volume and norms of test the electrc equpment-м:nc ENAS, p 5 Farhadzadeh EM, Muradalyev AZ, Farzalyev YZ, Nazrova UK Check of statstcal hypotheses at dervaton of estmate specfc number of refusals of the equpment n tme Kev, Electronc modelng 4, 2009, p