HYBRID DECISION-MAKING SYSTEM. Ryszard Michalski, Arkadiusz Rychlik, Sławomir Wierzbicki

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1 TEKA Kom. Mot. Energ. Roln., 2005, 5, HYBRID DECISION-MAKING SYSTEM Ryszard Mchalsk, Arkadusz Rychlk, Sławomr Werzbck Department of Operaton of Vehcles and Machnes, Warma and Mazury Unversty Summary. The paper presents a hybrd decson-makng system orented at the dagnosng of workng machnes on the bass of the knowledge acqured durng laboratory and operatonal tests. Rule-based nference combned wth procedural dagnosng enabled to make a precse dagnoss of the machnes examned n the study. Key words: hybrd system, expert system, dagnostcs, knowledge base, nference strateges INTRODUCTION The fact that modern workng machnes are equpped wth electronc systems enablng automatc control over workng processes makes t necessary to apply complex dagnostc systems supportng these processes. Modern computatonal (nformaton) systems, n contrast to the tradtonal ones, are characterzed by parallel data processng, the use of software capable of learnng: supervsed learnng, whch conssts n adaptaton changes n the values of the weghts of a neural network, unsupervsed learnng, whch conssts n the classfcaton of nput sgnals, and creaton of f-then rule bases of quanttatve knowledge n fuzzy systems. Intellgent nformaton systems are also referred to as expert systems, n whch fuzzy logc s used for the nference process, and knowledge s represented n the symbolc (rule-based) and non-symbolc (numercal) form by means of neural networks and genetc algorthms, or defned wth ndvdualzed nference procedures. It follows that an essental element of the ntellgent expert system s the hybrd nference process [McGarry and MacIntyre 2000], based on both symbolc and non-symbolc knowledge. The above concepts of dagnostc nference were employed to buld a Hybrd Dagnostc Inference System (HDI), composed of the followng knowledge bases: f-then rule base, base of ndvdualzed damage detecton procedures, help base provdng support and hnts to system users.

2 HYBRID DECISION-MAKING SYSTEM 145 The Hybrd Dagnostc Inference System allows to generate a dagnoss usng varous ways of dagnostc knowledge representaton, promotng user-frendly cooperaton, even f the user s not an expert n a gven branch of knowledge. STRUCTURE AND FUNCTIONS OF THE HYBRID DIAGNOSTIC INFERENCE SYSTEM The Hybrd Dagnostc Inference System comprses four nterrelated modules: knowledge acquston module, knowledge representaton module (rule-based and procedural knowledge), nference module and dalogue wth the user module (Fg. 1). Ths system combnes, on a cooperatve bass, two methods of knowledge representaton: rules concernng general knowledge, procedures based on the dentfcaton of ndvdualzed values of the attrbutes of the object examned. The modules of knowledge acquston, nference and dalogue wth the user are dscussed n detal n references [Mchalsk and Rychlk 2000, 2001, Mchalsk et al. 2001]. Hybrd dagnostc nference Expert Knowledge acquston module Knowledge engneer Operatonal tests Laboratory tests Functonal analyss of a machne Lterature-based research Inference module Knowledge representaton module Rule-based < object, attrbute, value> Procedure-based Dagnostc algorthm Knowledge base Ternary base < object, attrbute, value> Algorthm SEP Procedure-based expert system Inference tracng module SER Rule-based expert system Dalogue wth the user module Explanatory mechansms User Fg 1. Structure of the Hybrd Dagnostc Inference System

3 146 Ryszard Mchalsk, Arkadusz Rychlk, Sławomr Werzbck RULE-BASED DIAGNOSING The method of rule-based dagnosng was developed usng a structural model n the form of the Dagnostc Knowledge Matrx (DKM), accordng to the relaton: Dagnostc symptom state (X SD), X set of dagnostc symptoms, SD set of unservceablty (unft) states. In ths method, the dagnosng process s carred out accordng to the followng procedure: 1) For tmes t and Θ (workng lfe of the machne), the symptom vector SD n j ( t,θ) wth elements sd j (t, Θ) s created, where: n number of successve nspectons made accordng to the specfed procedure of nformaton set orderng, takng nto account the crtera appled to control the condton of a machne and localze damage, defect or falure,.e. the crtera of the greatest nformaton ncrement, ease and possblty of check, probablty (certanty) of the occurrence of unservceablty states, j SD number, sd j element of the symptom vector, whch assumes the followng values: 0 f the admssble value of the sgnal has not been exceeded, l f the admssble value of the sgnal has been exceeded. 2) The vector ( t,θ) SD n ) s compared wth the set of standard vectors { SD } j by DKM columns. The vector SD (ncluded n the set ( t,θ) SD n j w, created ) s the vector of the -th unservceablty state,.e. X SD. The general form of the Dagnostc Knowledge Matrx s gven n Table 1. Table 1. Form of the Dagnostc Knowledge matrx (DKM) j 1 X 1 SD 2 SD2 X X SD sd 1 a 1,1 a 2,1 a I,1 sd 2 a 1,2 a 2,2 a I,2 sd J a 1,J a 2,J a I,J The vectors are compared accordng to the followng rule: In DKM, a,j denote ts elements, where: = 1, I numbers of unservceablty states n DKM, j = 1, J numbers of symptoms recorded n DKM.

4 HYBRID DECISION-MAKING SYSTEM a =, elements of the matrx assume the value of 0 f there s no correlaton between the -th unservceablty state and the j-th symptom (CF = 0), where as a,j =, j 1 l f there exsts such a correlaton (CF O). 3) If ( t,θ) SD n j ( SD ) + create another vector 1 ( t, Θ) 4) If ( t,θ) w SD n j ( ) =, the n+1 step s taken to verfy sgnals, whch allows to SD n j. SD = w SD, t means that the -th unservceablty state X. has occurred. 5) If all symptoms recorded n DKM have been verfed and the followng relatonshp has taken place SD, = (,Θ) n 1 J j t { } SD = sd = 1, w j= 1, J t means that the unservceablty state cannot be dentfed explctly on the bass of dagnostc nference, and that at least one symptom of ths state has been observed. Thus, at the end of the dagnosng process t s necessary to enumerate all unservceablty states whose vectors contan the maxmum number of elements assumng the value of l correspondng to the vector SD, = (,Θ) n 1 J j t. Rule-based knowledge s represented by a set of facts and rules n the ternary form <O,A,W>, ncludng: <Object, Attrbute, Value>, where facts are governed by rules by means of logcal conjunctons (and, or, etc,), and the nference module s based on backward nference strateges [Mchalk 2003]. j PROCEDURE-BASED DIAGNOSING Procedural knowledge s a result of certan checkng and verfyng steps (procedures), enablng to estmate the techncal condton of a gven object or workng processes takng place wthn ths object. In ths case the dagnosng procedure may be developed on the bass of analytcal, laboratory and operatonal tests, whch provded the bass for determnng nference algorthms. The algorthms obtaned for logcal and rulebased knowledge may be then processed nto computer programs n the form of dagnostc procedures applcable to varous mechancal assembles of workng machnes. The use of procedural knowledge n the aspect of the functonng of HDI enables to: forecast and dagnose changes n the state/condton, determne the reasons for the exstng state/condton, optmze the structure and operatonal parameters of the object. The man functon of the hybrd dagnostc nference system s to dentfy the unservceablty state of machnes on the bass of the symptoms observed. The functonal, process- and nformaton-related complexty of the dagnosng problem may be presented n ts general form, as nformaton flow control (Fg. 2). The HDI system may be consdered as two ndependent, ntersectng planes representng dagnostc nference. The ntersecton edge of the planes represents ther cooperaton, wth ndependent functonng (Fg. 3).

5 148 Ryszard Mchalsk, Arkadusz Rychlk, Sławomr Werzbck x(t) Workng machne S (t) d Generated symptoms and dagnostc sgnals FACT Dagnostc rules SER Rule-based expert system FACT SER f y(t) y 0 T Dagnoss Another read-out of unservceablty (unft) state N N FACT Knowledge base, accordng to specfed proceduresr SEP Procedure-based expert system F F n FACT SEP base cases T Dagnoss Fg. 2. Illustraton of machne dagnosng usng HDI Dagnoss Fg. 3. Module-based structure of Hybrd Dagnostc Inference The module-based structure of the HDI system enables ndependent functonng of all modules, whose cooperaton takes place by way of data exchange, accordng to user s needs and requrements.

6 HYBRID DECISION-MAKING SYSTEM 149 EXAMPLE OF HYBRID DIAGNOSTIC INFERENCE In the example gven below, the hybrd dagnostc nference system was created usng the PC-Shell program [Mchalk 2003], to represent rule-based knowledge, and the envronment Delhp, to develop procedures of dagnostc nference concernng the techncal condton of the hydraulc system of a combne-harvester. The rule-based knowledge was recorded n the form of facts and rules. The knowledge base was dvded nto fve blocks,.e. source of knowledge, attrbutes, rules, facts, control and check. Procedural knowledge s represented n the Oscllogram program. Ths program enables to vsualze and analyze oscllograms of transents n the cycle of pressure measurement as a functon of tme of the lftng mechansm n the hydraulc system. It also dentfes dynamc ndces determned on the bass of transents. In the case of the hydraulc system of a Bzon Z058 combne-harvester, Hybrd Dagnostc Inference was amed at dentfyng ts unservceablty on the bass of symptoms recorded n the dagnostc knowledge matrx and analyss of pressure change oscllograms. The user can defne and dentfy the problem durng the dalogue wth the system. Ths dscusson can be led at two levels rule-based knowledge and procedural knowledge. Fgure 4 presents a vew of model wndows of the HDI system, applcatons of PC-Shell and Oscllogram. a) b) Fg. 4. A wndow of the HDI system for the hydraulc system of a combne-harvester, a) dalogue box of rule-based knowledge, b) vew of the Oscllogram program wth dentfed characterstcs of a dagnostc sgnal Havng ntalzed the rule-based module, the user has to answer the questons asked by the system. If the user cannot answer them, he can search for nformaton n the procedural knowledge resources. He can acqure the necessary knowledge by analyss of the oscllogram recorded n the Oscllogram program, where the values of the sgnal characterstcs are dentfed, so that they can be used by the rule-based module durng the

7 150 Ryszard Mchalsk, Arkadusz Rychlk, Sławomr Werzbck dagnosng process. The user-system communcaton allows to generate a dagnoss. An example of a dagnoss generated by the system s presented n Fg. 5. Fg. 5. Dagnoss generated by rule-based knowledge n the PC-Shell program The PC-Shell program also provdes tools explanng the dagnoss made. The concluson and premses that enabled to arrve at a gven dagnoss are shown n the dalogue box How. A vew of ths dalogue box s presented n Fg. 6. Fg. 6.Dalogue box provdng explanaton to the dagnoss made n the PC-Shell program The Oscllogram program dentfes the man characterstcs of a dagnostc sgnal. In the procedure consdered t s the pressure n the hydraulc system of a Bzon Z058 combne-harvester. In addton, the program dentfes the key dynamc ndces determned on the bass of transents. CONCLUSIONS The Hybrd Dagnostc Inference system descrbed n the paper, orented at dagnosng unservceablty, was developed on the bass of knowledge ganed durng laboratory and operatonal tests on the studed object. The knowledge acqured and ntroduced

8 HYBRID DECISION-MAKING SYSTEM 151 nto the system, n the form of rules and dagnostc procedures, allows to obtan a greater ntellectual potental of the system,.e. to select the most approprate dagnoss. Due to the combnaton of the two methods of knowledge representaton, ths system s referred to as hybrd. Hybrd systems orented at determnng the techncal condton of machnes are characterzed by dynamc development amed at performng the followng functons: control over the state/condton, forecastng the state/condton, damage localzaton. In order to make the so called ntellgent systems fulfll the above functons, t s ndspensable to apply tools for learnng, whch stll s the major obstacle to ther large-scale development and mplementaton. REFERENCES McGarry Kenneth, MacIntyre 2000: Hybryd Dagnostc system based upon smulaton and artfcal ntelgence. Unversty of Sunderland, UK. Mchalk K. 2003: PC-Shell 4.0, Szkeletowy system ekspertowy. Podręcznk uŝytkownka. AITECH, Katowce. Mchalsk R. 2003: Dagnostyka uszkodzeń w hybrydowym systeme utrzymana maszyn. Mat. V Konferencj Dagnostyka technczna urządzeń systemów WAT, Ustroń. Mchalsk R., Mkołajczak P., Rychlk A. 2001: Rozwój systemów ekspertowych w eksploatacj systemów techncznych, III Krajowa Konferencja Metody systemy komputerowe w badanach naukowych projektowanu nŝynerskm Materały konferencyjne, Kraków. Mchalsk R., Rychlk A. 2000: Metoda dagnozowana złoŝonych maszyn rolnczych z wykorzystanem hybrydowego systemu ekspertowego (na przykładze kombajnu zboŝowego). II Forum Młodych 2000, Problemy naukowe w budowe eksploatacj maszyn, Bydgoszcz- Borówno. Mchalsk R., Rychlk A. 2001: Budowa hybrydowego systemu ekspertowego. Problemy Eksploatacj 3, 42. Mchalsk R., Rychlk A. 2003: Dagnozowane maszyny roboczej z wykorzystanem wnoskowana hybrydowego. InŜynera Systemów Boagrotechncznych, 2 3, Płock. Rutkowska D. 1997: Intelgentne systemy oblczenowe. Wydawnctwo PLJ, Waszawa.