1 Sergej Jegorov, Piotr Wasiewicz 5-th DAMADICS Workshop Łagów, Poland, April 5th-7th, 2004 ACTUATOR BENCHMARK RESULTS: STEP I AND II

2 Łagów, Poland, April 5th-7th, th DAMADICS Workshop Presentation Plan Control Valve Introduction Step I Step II Conclusions

3 Łagów, Poland, April 5th-7th, th DAMADICS Workshop Actuator structure Process Variable CV – Control Value Z – Valve Position P1 – Valve Input Pressure P2 – Valve Output Pressure F – Medium Flow Rate CV – Control Value Z – Valve Position P1 – Valve Input Pressure P2 – Valve Output Pressure F – Medium Flow Rate Control Valve Introduction

4 Łagów, Poland, April 5th-7th, th DAMADICS Workshop Considered models of control valve servomotor rod movement model (1) control valve model (2) actuator model (3) simplified model of the control valve (4) simplified model of actuator (5)

5 Łagów, Poland, April 5th-7th, th DAMADICS Workshop Diagnostic Matrix (theoretical) f1f2f3f4f5f6f7f8f9f10f11f12f13f14f15f16f17f18f19 S1±1 ±1 ±1X S21 1±1 X1 S3±11±11±1 11 X 11 S41 1±1 X 1 S5±11±11±1 11 X 1 1 Control valve vaults Pneumatic servo-motor faults Positioner faultsExternal faults S1 = f(r1),(11) S2 = f(r2),(12) S3 = f(r3),(13) S4 = f(r4),(14) S5 = f(r5).(15) Valve clogging Valve plug or valve seat sedimentation Valve plug or valve seat erosion Increased of valve or bushing friction External leakage Internal leakage Valve clogging Medium evaporation or critical flow Twisted servo-motor's piston rod Servo-motor's housing or terminals tightness Servo-motor's diaphragm perforation Servo-motor's spring fault Electro-pneumatic transducer fault Rod displacement sensor fault Pressure sensor fault Positioner feedback fault Positioner supply pressure drop Unexpected pressure change across the valve Fully or partly opened bypass valves Flow rate sensor fault r1 = Z – Z*(CV), (6) r2 = F – F*(Z, P1, P2), (7) r3 = F – F*(CV, P1, P2), (8) r4 = F – F*(Z), (9) r5 = F – F*(CV), (10)

6 Łagów, Poland, April 5th-7th, th DAMADICS Workshop FDI Structure FD using NN, FI using Fuzzy Logic

7 Łagów, Poland, April 5th-7th, th DAMADICS Workshop Search of Optimal NN Architecture NameDelays 1 Layer 2 Layer 3 Layer Net21051 Net Net32631 Net42610 Transfer functions of all layers are logsig

8 Łagów, Poland, April 5th-7th, th DAMADICS Workshop Examples: NN validation net1 Red line – model output Blue line – real data net3 net4 res

9 Łagów, Poland, April 5th-7th, th DAMADICS Workshop Data Filtering filter1 filter2 filter3

10 Łagów, Poland, April 5th-7th, th DAMADICS Workshop NN Architecture Search. Training data without filtering net1net2 net3 net4

11 Łagów, Poland, April 5th-7th, th DAMADICS Workshop Results achieved by applying filtering of measurements Fault f4 Trained on filter1 but works on filter2 Fault f4 Trained on filter1 and filter2, but works on filter3 Blue – NN trained on filtr1 Red – NN trained on filtr2

12 Łagów, Poland, April 5th-7th, th DAMADICS Workshop Time Diagrams of real and modeled signals. NN trained applying filter2, but examined using filter3 NNr2 r2 res NNr3 r3 res

13 Łagów, Poland, April 5th-7th, th DAMADICS Workshop Time Diagrams of real and modeled signals. NN trained applying filter2, but examined using filter3 NNr4 r4 residual NNr5 r5 residual

14 Łagów, Poland, April 5th-7th, th DAMADICS Workshop Measures of a Neural Networks "health"

15 Łagów, Poland, April 5th-7th, th DAMADICS Workshop Diagnostic Matrix (Practical) f1f2f3f4f5f6f7f8f9f10f11f12f13f14f15f16f17f18f19 S1+1 x xx xxX+1 S2+1x xxxx X S3+1+1 x xx xx X+1 S4+1x xxxx X+1 S5+1+1 x xx xx X+1+1 Control valve vaults Pneumatic servo- motor faults Positioner faultsExternal faults Valve clogging Valve plug or valve seat sedimentation Valve plug or valve seat erosion Increased of valve or bushing friction External leakage Internal leakage Valve clogging Medium evaporation or critical flow Twisted servo-motor's piston rod Servo-motor's housing or terminals tightness Servo-motor's diaphragm perforation Servo-motor's spring fault Electro-pneumatic transducer fault Rod displacement sensor fault Pressure sensor fault Positioner feedback fault Positioner supply pressure drop Unexpected pressure change across the valve Fully or partly opened bypass valves Flow rate sensor fault. DGN0DGN1DGN2DGN3DGN4DGN5DGN Fault free f1, f4, f7, f10, f16 f2 f3, f6, f13, f18, f19 f5, f8, f9, f11, f12, f14 f15f17

16 Łagów, Poland, April 5th-7th, th DAMADICS Workshop Sugeno Type Defuzzificatiom method is whatever (wtaver) Fuzzification (Membership Functions) Input Membership Functions r3, r5 Input Membership Functions r1, r2, r4

17 Łagów, Poland, April 5th-7th, th DAMADICS Workshop Examples of results of isolation of fault 1

18 Łagów, Poland, April 5th-7th, th DAMADICS Workshop Examples of results of isolation of fault 3

19 Łagów, Poland, April 5th-7th, th DAMADICS Workshop Step I results (from forms S1-FF-fx) f1f1mf2f2incf3incf4incf5incf6incf7f7mf8f9f10f11 tdtd 5s15s2s8.278e+004s5.378e+004s4130s-1.672e+004s5s -- - r fd 0% r td 0.98%0.95%0.99%0.94%0.72%0.13%-0.89%0.98% -- - fs d t it 5s15s2s8.278e+004s5.378e+004s4130s-1.672e+004s5s -- - r fi 0% r ti 0.98%0.95%0.99%0.92%0.72%0.02%-0.89%0.98% -- - r mi 0% 0.02%0.38%0.021%0.12%-0.01%0.02%0.01%-- - fs i dacc 0.2 1inf

20 Łagów, Poland, April 5th-7th, th DAMADICS Workshop Step I results (from forms S1-FF-fx) continued f12f13f13mf13incf14f15f16f17f17 incf18f18mf18incf19f19m tdtd -5s6s45s-231s7s6s640s5s6s9409s7s r fd -0% - r td -0.98%0.97% -0.92%0.97% 0.91%0.98%0.97%0.93%0.97% fs d t it -5s6s45s-240s7s35s640s5s6s9409s7s r fi -0% - r ti -0.98%0.97% -0.66%0.97%0.90%0.91%0.98%0.97%0.93%0.97% r mi -0.01%0% -0.28%0%0.07%0.03%0% fs i dacc

21 Łagów, Poland, April 5th-7th, th DAMADICS Workshop Step II results scenario Fault or group DGN1-DGN3DGN5- DGN2DGN5 DGN5 or 1 DGN1 DGN3 Start time Stop timeinf scenario Fault or group DGN6DGN3DGN5DGN3 DGN1 -DGN2DGN3 DGN6 Start time Stop time Inf Infinf Inf

22 Łagów, Poland, April 5th-7th, th DAMADICS Workshop Conclusions fault detection subsystem based on neural network technology was developed fault isolation subsystem based on fuzzy logic technology was developed Neuro-fuzzy FDI system is applicable for actuator fault diagnosis. Fault groups are distinguishable. Close to 1, true fault detection rates factors achieved in Step I confirms acceptable NN models quality High values of true fault isolation rates (Step I) confirms proper isolability features of fuzzy isolation scheme applied Results achieved in Actuator Benchmark Step I are highly acceptable The fault distinguishability problem exists because of limited availability of measurements when considering industrial benchmark Step II). In this case 6 fault groups are distinguishable.