Diagnosis (06) Diagnosis by Chronicles Alban Grastien - - PowerPoint PPT Presentation

diagnosis 06
SMART_READER_LITE
LIVE PREVIEW

Diagnosis (06) Diagnosis by Chronicles Alban Grastien - - PowerPoint PPT Presentation

Diagnosis (06) Diagnosis by Chronicles Alban Grastien alban.grastien@rsise.anu.edu.au Systems to Diagnose 1 Chronicle 2 Chronicle Recognition 3 Generation of Chronicles 4 Systems to Diagnose 1 Chronicle 2 Chronicle Recognition 3


slide-1
SLIDE 1

Diagnosis (06)

Diagnosis by Chronicles Alban Grastien alban.grastien@rsise.anu.edu.au

slide-2
SLIDE 2

1

Systems to Diagnose

2

Chronicle

3

Chronicle Recognition

4

Generation of Chronicles

slide-3
SLIDE 3

1

Systems to Diagnose

2

Chronicle

3

Chronicle Recognition

4

Generation of Chronicles

slide-4
SLIDE 4

Notion of Event

Definition (erk.)

An event is something that happens at some time.

Example

“The button is switched on.” “A mail is received.” “An alarm is emitted.” “The temperature increases.” (but not “The temperature is increasing”) “The temperature starts increasing.”, “The temperature ends increasing.” “The temperature reaches a high value.”

slide-5
SLIDE 5

Formal Definition of an Event

Beware !

event occurrence = event type An event (occurrence) is defined by: Event type (what happened) Parameters (more precisely what happened) Time of occurrence (when it happened) Unique identifier (to distinguish from other similar events)

slide-6
SLIDE 6

Diagnosis

Dynamic system

Observations

The observations generated by the system are events. Alarm emitted by a component Log entry from a software Observation of a sensor at a given time Sound at a given time Etc.

Diagnosis

Determine what happened. . .

slide-7
SLIDE 7

Examples

Power Supply Networks Telecommunication Networks Factory Web Services Mail Servers Airplanes etc.

slide-8
SLIDE 8

1

Systems to Diagnose

2

Chronicle

3

Chronicle Recognition

4

Generation of Chronicles

slide-9
SLIDE 9

Unformal Definition

Principle

A chronicle is a pattern of events with time constraints A chronicle is a signature of a behaviour (normal or faulty) → diagnosis

Examples

The pattern that corresponds to the fact that a light was switched on by mistake is:

Light li is switched on at time t Light li is switched off at time t′ where t′ < t + 1s

slide-10
SLIDE 10

Formally

Chronicle [Dousson 1996]

A set of events occurrence – an event is

An event type A set of parameters A time occurrence

A set of time constraints between the events

Example

Switch([?li,on],t1) Switch([?li,off],t2) t2 − t1 ∈ [0, 1]

slide-11
SLIDE 11

1

Systems to Diagnose

2

Chronicle

3

Chronicle Recognition

4

Generation of Chronicles

slide-12
SLIDE 12

Chronicle Recognition

Switch([l1,on],0.2) Switch([l2,on],0.3) Switch([l1,off],0.5) Switch([l3,on],0.6) Switch([l4,on],1.1) Switch([l2,off],1.4) Switch([l4,off],1.5) Switch([l4,on],1.7) Switch([l5,on],1.8) Switch([l3,off],1.9) Switch([l4,off],2.0) etc.

slide-13
SLIDE 13

Chronicle Recognition

Switch([l1,on],0.2) Chronicle 1 Switch([l2,on],0.3) Switch([l1,off],0.5) Chronicle 1 Switch([l3,on],0.6) Switch([l4,on],1.1) Switch([l2,off],1.4) Switch([l4,off],1.5) Switch([l4,on],1.7) Switch([l5,on],1.8) Switch([l3,off],1.9) Switch([l4,off],2.0) etc.

slide-14
SLIDE 14

Chronicle Recognition

Switch([l1,on],0.2) Chronicle 1 Switch([l2,on],0.3) Switch([l1,off],0.5) Chronicle 1 Switch([l3,on],0.6) Switch([l4,on],1.1) Chronicle 2 Switch([l2,off],1.4) Switch([l4,off],1.5) Chronicle 2 Switch([l4,on],1.7) Switch([l5,on],1.8) Switch([l3,off],1.9) Switch([l4,off],2.0) etc.

slide-15
SLIDE 15

Chronicle Recognition

Switch([l1,on],0.2) Chronicle 1 Switch([l2,on],0.3) Switch([l1,off],0.5) Chronicle 1 Switch([l3,on],0.6) Switch([l4,on],1.1) Chronicle 2 Switch([l2,off],1.4) Switch([l4,off],1.5) Chronicle 2 Switch([l4,on],1.7) Chronicle 3 Switch([l5,on],1.8) Switch([l3,off],1.9) Switch([l4,off],2.0) Chronicle 3 etc.

slide-16
SLIDE 16

Chronicle Recognition

Switch([l1,on],0.2) Chronicle 1 Switch([l2,on],0.3) Switch([l1,off],0.5) Chronicle 1 Switch([l3,on],0.6) Switch([l4,on],1.1) Chronicle 2 Chronicle 4 Switch([l2,off],1.4) Switch([l4,off],1.5) Chronicle 2 Switch([l4,on],1.7) Chronicle 3 Switch([l5,on],1.8) Switch([l3,off],1.9) Switch([l4,off],2.0) Chronicle 3 Chronicle 4 etc.

slide-17
SLIDE 17

On-line recognition

Hypothesis

The observations are processed in the order they are received

Principle

Maintain a list of partial recognised chronicles When a new observation is received

Add new chronicles corresponding to the extension of existing chronicles with this event Remove the chronicles that can no longer be recognised (because of time constraints)

Chronicle Recognition System (CRS)

http://crs.elibel.tm.fr/index.html

slide-18
SLIDE 18

Example

[?l,on] Switch [0, ∞] [?l,off] Switch [0, ∞]

[0, 1]

slide-19
SLIDE 19

Example

⊲ Observation 1: Switch([l1,on],0.2)

[?l,on] Switch [0, ∞] [?l,off] Switch [0, ∞]

[0, 1]

slide-20
SLIDE 20

Example

Observation 1: Switch([l1,on],0.2)

[?l,on] Switch [0, ∞] [?l,off] Switch [0, ∞]

[0, 1]

[l1,on] Switch 0.2 [l1,off] Switch [0.2,1.2]

[0, 1]

slide-21
SLIDE 21

Example

⊲ Observation 2: Switch([l2,on],0.3)

[?l,on] Switch [0, ∞] [?l,off] Switch [0, ∞]

[0, 1]

[l1,on] Switch 0.2 [l1,off] Switch [0.2,1.2]

[0, 1]

slide-22
SLIDE 22

Example

Observation 2: Switch([l2,on],0.3)

[?l,on] Switch [0, ∞] [?l,off] Switch [0, ∞]

[0, 1]

[l1,on] Switch 0.2 [l1,off] Switch [0.2,1.2]

[0, 1]

[l2,on] Switch 0.3 [l2,off] Switch [0.3,1.3]

[0, 1]

slide-23
SLIDE 23

Example

⊲ Observation 3: Switch([l1,off],0.5)

[?l,on] Switch [0, ∞] [?l,off] Switch [0, ∞]

[0, 1]

[l1,on] Switch 0.2 [l1,off] Switch [0.2,1.2]

[0, 1]

[l2,on] Switch 0.3 [l2,off] Switch [0.3,1.3]

[0, 1]

slide-24
SLIDE 24

Example

Observation 3: Switch([l1,off],0.5)

[?l,on] Switch [0, ∞] [?l,off] Switch [0, ∞]

[0, 1]

[l1,on] Switch 0.2 [l1,off] Switch [0.2,1.2]

[0, 1]

[l2,on] Switch 0.3 [l2,off] Switch [0.3,1.3]

[0, 1]

[l1,on] Switch 0.2 [l1,off] Switch 0.5

[0, 1]

slide-25
SLIDE 25

Example

⊲ Observation 4: Switch([l3,on],0.6)

[?l,on] Switch [0, ∞] [?l,off] Switch [0, ∞]

[0, 1]

[l1,on] Switch 0.2 [l1,off] Switch [0.2,1.2]

[0, 1]

[l2,on] Switch 0.3 [l2,off] Switch [0.3,1.3]

[0, 1]

slide-26
SLIDE 26

Example

Observation 4: Switch([l3,on],0.6)

[?l,on] Switch [0, ∞] [?l,off] Switch [0, ∞]

[0, 1]

[l1,on] Switch 0.2 [l1,off] Switch [0.2,1.2]

[0, 1]

[l2,on] Switch 0.3 [l2,off] Switch [0.3,1.3]

[0, 1]

[l3,on] Switch 0.6 [l3,off] Switch [0.6,1.6]

[0, 1]

slide-27
SLIDE 27

Example

⊲ Observation 5: Switch([l4,on],1.1)

[?l,on] Switch [0, ∞] [?l,off] Switch [0, ∞]

[0, 1]

[l1,on] Switch 0.2 [l1,off] Switch [0.2,1.2]

[0, 1]

[l2,on] Switch 0.3 [l2,off] Switch [0.3,1.3]

[0, 1]

[l3,on] Switch 0.6 [l3,off] Switch [0.6,1.6]

[0, 1]

slide-28
SLIDE 28

Example

Observation 5: Switch([l4,on],1.1)

[?l,on] Switch [0, ∞] [?l,off] Switch [0, ∞]

[0, 1]

[l1,on] Switch 0.2 [l1,off] Switch [0.2,1.2]

[0, 1]

[l2,on] Switch 0.3 [l2,off] Switch [0.3,1.3]

[0, 1]

[l3,on] Switch 0.6 [l3,off] Switch [0.6,1.6]

[0, 1]

[l4,on] Switch 1.1 [l4,off] Switch [1.1,2.1]

[0, 1]

slide-29
SLIDE 29

Example

⊲ Observation 6: Switch([l2,off],1.4)

[?l,on] Switch [0, ∞] [?l,off] Switch [0, ∞]

[0, 1]

[l1,on] Switch 0.2 [l1,off] Switch [0.2,1.2]

[0, 1]

[l2,on] Switch 0.3 [l2,off] Switch [0.3,1.3]

[0, 1]

[l3,on] Switch 0.6 [l3,off] Switch [0.6,1.6]

[0, 1]

[l4,on] Switch 1.1 [l4,off] Switch [1.1,2.1]

[0, 1]

slide-30
SLIDE 30

Example

Observation 6: Switch([l2,off],1.4)

[?l,on] Switch [0, ∞] [?l,off] Switch [0, ∞]

[0, 1]

[l3,on] Switch 0.6 [l3,off] Switch [0.6,1.6]

[0, 1]

[l4,on] Switch 1.1 [l4,off] Switch [1.1,2.1]

[0, 1]

slide-31
SLIDE 31

Example

⊲ Observation 7: Switch([l4,off],1.5)

[?l,on] Switch [0, ∞] [?l,off] Switch [0, ∞]

[0, 1]

[l3,on] Switch 0.6 [l3,off] Switch [0.6,1.6]

[0, 1]

[l4,on] Switch 1.1 [l4,off] Switch [1.1,2.1]

[0, 1]

slide-32
SLIDE 32

Example

Observation 7: Switch([l4,off],1.5)

[?l,on] Switch [0, ∞] [?l,off] Switch [0, ∞]

[0, 1]

[l3,on] Switch 0.6 [l3,off] Switch [0.6,1.6]

[0, 1]

[l4,on] Switch 1.1 [l4,off] Switch [1.1,2.1]

[0, 1]

[l4,on] Switch 1.1 [l4,off] Switch 1.5

[0, 1]

slide-33
SLIDE 33

Example

⊲ Observation 8: Switch([l4,on],1.7)

[?l,on] Switch [0, ∞] [?l,off] Switch [0, ∞]

[0, 1]

[l3,on] Switch 0.6 [l3,off] Switch [0.6,1.6]

[0, 1]

[l4,on] Switch 1.1 [l4,off] Switch [1.1,2.1]

[0, 1]

slide-34
SLIDE 34

Example

Observation 8: Switch([l4,on],1.7)

[?l,on] Switch [0, ∞] [?l,off] Switch [0, ∞]

[0, 1]

[l4,on] Switch 1.1 [l4,off] Switch [1.1,2.1]

[0, 1]

[l4,on] Switch 1.7 [l4,off] Switch [1.7,2.7]

[0, 1]

slide-35
SLIDE 35

Example

⊲ Observation 9: Switch([l5,on],1.8)

[?l,on] Switch [0, ∞] [?l,off] Switch [0, ∞]

[0, 1]

[l4,on] Switch 1.1 [l4,off] Switch [1.1,2.1]

[0, 1]

[l4,on] Switch 1.7 [l4,off] Switch [1.7,2.7]

[0, 1]

slide-36
SLIDE 36

Example

Observation 9: Switch([l5,on],1.8)

[?l,on] Switch [0, ∞] [?l,off] Switch [0, ∞]

[0, 1]

[l4,on] Switch 1.1 [l4,off] Switch [1.1,2.1]

[0, 1]

[l4,on] Switch 1.7 [l4,off] Switch [1.7,2.7]

[0, 1]

[l5,on] Switch 1.8 [l4,off] Switch [1.8,2.8]

[0, 1]

slide-37
SLIDE 37

Example

⊲ Observation 10: Switch([l3,off],1.9)

[?l,on] Switch [0, ∞] [?l,off] Switch [0, ∞]

[0, 1]

[l4,on] Switch 1.1 [l4,off] Switch [1.1,2.1]

[0, 1]

[l4,on] Switch 1.7 [l4,off] Switch [1.7,2.7]

[0, 1]

[l5,on] Switch 1.8 [l4,off] Switch [1.8,2.8]

[0, 1]

slide-38
SLIDE 38

Example

Observation 10: Switch([l3,off],1.9)

[?l,on] Switch [0, ∞] [?l,off] Switch [0, ∞]

[0, 1]

[l4,on] Switch 1.1 [l4,off] Switch [1.1,2.1]

[0, 1]

[l4,on] Switch 1.7 [l4,off] Switch [1.7,2.7]

[0, 1]

[l5,on] Switch 1.8 [l4,off] Switch [1.8,2.8]

[0, 1]

slide-39
SLIDE 39

Example

⊲ Observation 11: Switch([l4,off],2.0)

[?l,on] Switch [0, ∞] [?l,off] Switch [0, ∞]

[0, 1]

[l4,on] Switch 1.1 [l4,off] Switch [1.1,2.1]

[0, 1]

[l4,on] Switch 1.7 [l4,off] Switch [1.7,2.7]

[0, 1]

[l5,on] Switch 1.8 [l4,off] Switch [1.8,2.8]

[0, 1]

slide-40
SLIDE 40

Example

Observation 11: Switch([l4,off],2.0)

[?l,on] Switch [0, ∞] [?l,off] Switch [0, ∞]

[0, 1]

[l4,on] Switch 1.1 [l4,off] Switch [1.1,2.1]

[0, 1]

[l4,on] Switch 1.7 [l4,off] Switch [1.7,2.7]

[0, 1]

[l5,on] Switch 1.8 [l4,off] Switch [1.8,2.8]

[0, 1]

[l4,on] Switch 1.1 [l4,off] Switch 2.0

[0, 1]

[l4,on] Switch 1.7 [l4,off] Switch 2.0

[0, 1]

slide-41
SLIDE 41

Example

[?l,on] Switch [0, ∞] [?l,off] Switch [0, ∞]

[0, 1]

[l4,on] Switch 1.1 [l4,off] Switch [1.1,2.1]

[0, 1]

[l4,on] Switch 1.7 [l4,off] Switch [1.7,2.7]

[0, 1]

[l5,on] Switch 1.8 [l4,off] Switch [1.8,2.8]

[0, 1]

slide-42
SLIDE 42

1

Systems to Diagnose

2

Chronicle

3

Chronicle Recognition

4

Generation of Chronicles

slide-43
SLIDE 43

Generating chronicles

By hand (expert knowledge) Machine learning

From simulation or real data (cf. [Fromont et al., AIME 2005]) From model (cf. [Guerraz–Dousson, DX 2005])