`
`
`
`
`IIIIll |||||||| III III" "III |l||l |||l| |l||| |||I| ||||| "III "III III III" |||I
`USOOSS61610A
`
`
`
`
`
`
`
`
`[19]
`[11] Patent Number:
`Umted States Patent
`
`
`
`
`
`
`
`Schricker et al.
`[45] Date of Patent:
`
`5,561,610
`
`Oct. 1, 1996
`
`[54] METHOD AND APPARATUS FOR
`
`
`
`
`
`INDICATING A FAULT CONDITION
`
`
`
`
`
`
`
`[75]
`
`
`Inventors: David R. Schricker, Dunlap; Satish M.
`
`
`
`
`
`
`-
`Sheny’ EaSt Peona’ bah 0f 111'
`
`
`
`
`
`
`
`[73] ASS‘gnee‘ caterp‘nar Inc" Pe‘ma’ 111.
`
`
`
`
`[21] Appl. No.2 268,693
`_
`
`[22]
`Filed:
`Jun. 30, 1994
`
`
`
`
`
`
`[51]
`Int. Cl.6 ..................................................... G08B 23/00
`
`
`
`
`
`
`[52] US. Cl.
`....................................... 364/551.01; 340/679
`
`
`
`
`
`[58] Field of Search ..................................... 340/679, 680;
`
`
`
`
`
`
`
`
`
`364/550, 551.01, 551.02
`
`[56]
`
`
`
`References Cited
`
`
`
`Re. 31,750
`
`
`3,257,652
`
`3,298,010
`
`3,882,305
`
`
`3,946,364
`4,093,939
`
`4,184,205
`
`4,542,461
`
`
`
`
`U'S' PATENT DOCUMENTS
`
`
`364/550 X
`11/1984 Morrow
`
`
`
`
`340/680X
`6/1966 Foster ............
`
`
`
`
`.. 340/679 X
`1/1967 Dubosq et a1.
`
`
`
`
`
`.. 235/151.11
`5/1975 Johnstone ..........
`
`
`
`
`
`
`
`
`
`
`340/172.5
`3/1976 COdOHlO Ct 81.
`..
`6/1978 Mitchell .......... 340/52
`
`
`
`
`1/1980 Morrow ............
`364/550 X
`
`
`
`
`9/1985 Eldridge et a1.
`........................ 364/424
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`4,583,176
`.................... 364/43l.1l
`4/1986 Yamato et al.
`
`
`
`
`4,749,987
`6/1988 Ishii ................. 340/537
`
`4,787,053
`11/1988 Moore .......
`364551.01
`
`
`
`
`
`133%: gig; gamushita
`318g]
`
`
`
`
`
`erruyer ......
`,
`,
`
`10/1990 Lane etal.
`.. 364/55101
`4,967,381
`
`
`
`
`
`
`5,155,468 10/1992 Stanley et a1.
`....... 340/501
`
`
`
`11/1993 Imam et a1.
`......
`5,253,923
`364/508
`
`.. 364/550
`4/1994 Ebaugh et a1.
`5,303,163
`
`
`
`
`
`
`
`
`
`
`
`Primary Examiner—Edward R. Cosimano
`
`
`
`
`
`
`
`
`Attorney, Agent, or Finn—Steven R. Janda; Mario J. Donato
`
`
`
`57
`
`
`
`ABSTRACT
`
`
`
`[
`]
`An apparatus is provided for indicating a fault condition in
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`a machine having a plurality of parameters each having
`
`
`
`
`
`
`
`levels being dependent upon machine performance. The
`apparatus includes a sensor adapted to produce an electrical
`
`
`
`
`
`
`signal in response to the level of one of the of parameters;
`
`
`
`
`
`
`
`
`and a processor for identifying a trend in the parameter level
`
`
`
`
`
`
`
`
`in response to the electrical signal, calculating the duration
`
`
`
`
`
`
`
`
`and slope of the trend; and determining whether a first
`
`
`
`
`
`
`
`
`
`warning threshold is exceeded in response to the duration
`
`
`
`
`
`
`and slope of the trend, the first warning threshold being 3
`
`
`
`
`
`
`
`
`
`
`
`
`
`function of duration and slope.
`
`16 Claims, 10 Drawing Sheets
`
`
`
`
`
`
`10411.1
`
`
`
`104.112
`
`
`104.11.?)
`
`10441-4
`
`104.11.5
`
`
`
`
`
`
`
`
`
`
`104.11.13
`
`
`DETERMINE SLOPE AND
`DURATION OF TREND
`
`
`
`
` OBTAIN WEIGHTING
`
`
`
`
`
`FACTOR BASED ON
`DISTANCE
`
`
`
`OBTAIN SIGNIFICANCE
`
`
`
`FACTOR BASED ON
`
`
`
`
`
`SLOPE AND DURATION
`
`
`
`
`
`COMBINE WEIGHTING FACTOR
`
`
`AND SIGNIFICANCE FACTOR
`104.11.14
`
`
`
`
`E WARNING PARAMETER
`
`
`
`
`
`CALCULAT
`
`104.11.6
`
`WARNING
`
`LEVEL GREATER
`THAN CAUTION
`
`THRES’HOLD
`
`
` INDICATE CAUTION
`
`
`
`[5
`104.1 1.9
`WARNING
`
`
`
`LEVEL GREATER
`RESET
`N
`
`
`
`
`
`THAN WARNING
`WARNING
`
`
`
`THRES’HOLD
`
`
`INDICATE WARNING
`
`
`STORE FAULT CONDITION
`
`
`
`
`104.11.11
`
`RETURN
`
`
`
`
`104.113
`
`
`
`Page 1 of 16
`
`Hyundai Exhibit 1005
`
`Page 1 of 16
`
`Hyundai Exhibit 1005
`
`

`

`
`US. Patent
`
`
`
`
`Oct. 1, 1996
`
`
`
`
`Sheet 1 of 10
`
`5,561,610
`
`
`
`zo_._.<o_znzzoo
`
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`
`
`Ti.HI
`
`O..0
`
`
`
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`
`
`Z5
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`”3300:
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`BzoFfiEd
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`Page 2 of 16
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`Page 2 of 16
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`

`

`US. Patent
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`
`
`
`Oct. 1, 1996
`
`
`
`
`Sheet 2 of 10
`
`5,561,610
`
`
`
`
`
`“3:002
`
`0.20mhom._m
`
`¢N
`
`NN
`
`FN
`
`
`
`
`W1
`
`
`
`a.22=
`
`
`9%o3<z<#2952
`
`
`
`82m:53:wa£va
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`am0332._<zoE8<;oS<z<420:5?
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`
`10:26Ex.Emté|\+
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`
`
`IMIWIHWH
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`
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`xz_._<._.<n_<.—<
`
`Page 3 0f 16
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`Page 3 of 16
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`

`

`
`US. Patent
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`
`
`
`Oct. 1, 1996
`
`
`
`
`Sheet 3 of 10
`
`5,561,610
`
`
`
`::EFEILEEJ._:E];.
`
`210
`
`212
`
`
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`
`
`READ. MACHINE
`
`
`PARAMETERS
`
`DEPENDENCIES
`
`SATIEFIED
`
`
`
`
`
`
`
`
`STORE
`PARAMETER
`
`
`
`220
`
`
`
`
`
`
`‘REAgHED
`
`TIME OR
`
`
`COUNTS BEEN
`
`Y
`
`222
`
`
`
`
`
`
`
`DETERMINE AND
`
`
`STORE TREND
`
`DATA
`
`224
`
`
`
`Page 4 of 16
`
`Page 4 of 16
`
`

`

`US. Patent
`
`Oct. 1, 1996
`
`Sheet 4 of 10
`
`5,561,610
`
`
`
`
`
`mDZMmH>4mDOInommmzzzmozm30mm
`
`owoo00000$030000O
`
`omo%o
`
`0oo
`
`HOTVA GNHHL
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`Page 5 0f 16
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`Page 5 of 16
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`

`

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`Page 6 of 16
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`

`

`US. Patent
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`
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`Oct. 1, 1996
`
`
`
`Sheet 6 of 10
`
`
`5,561,610
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`
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`Page 7 0f 16
`
`Page 7 of 16
`
`

`

`
`US. Patent
`
`
`
`
`Oct. 1, 1996
`
`
`
`
`Sheet 7 of 10
`
`5,561,610
`
`
`
`3.15-7-
`
`
`
`‘00
`
`
`
`
`
`
`INITIALIZE DEFAULT FIT
`
`
`
`PARAMETERS AND ZERO
`
`ACCUMULATORS
`
`
`OBTAIN OPTIONAL
`
`
`OVERRIDES FROM
`
`DEFAULTS
`
`101
`
`102
`
`
`
`
`
`
`
`
`
`LOAD X,Y DATA
`PAIRS
`
`
`
`
`03
`
`1
`
`
`
`
`SEGMENT XY DATA
`
`
`
`/ WRITE OUT RESULTS
`
`104
`
`
`
`
`
`
`
`CLOSE OUTPUT FILES
`
`
`
`
`105
`
`STOP
`
`105
`
`
`
`Page 8 0f 16
`
`Page 8 of 16
`
`

`

`
`
`US. Patent
`
`Oct. 1, 1996
`
`
`
`Sheet 8 of 10
`
`
`5,561,610
`
`
`
`
`
`ZERO LINEMINUS
`
`STATISTICS
`
`
`1041
`
`
`
`ELLE—E-
`
`
`
`
`
`
`
`
`
`
`SET X—MINUS
`
`START TO
`
`
`BEGINNING OF
`
`
`
`
`X,Y DATA
`
`104.2
`
`
`
`
`
`
`
`
`
`104.3
`
`
`
`
`
`THERE MORE
`
`
`
`UNPROCESSED X,Y
`
`
`
`
`PAIRS THAN THE
`
`X-PLUS WINDOW
`
`
`
`
`
`
`
`
`
`
`
`
`
`STORE LAST
`X—MINUS LINE
`
`
`
`
`
`
`DETERMINE
`ADD NEw X,Y
`WAIT UNTIL A
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`NEW X,Y PAIR
`PAIR To X—MINUS
`
`
`
`
`
`
`
`IS RECIEVED
`AND X—PLUS
`
`
`
`
`
`
`AND LOAD THE
`WINDOWS
`
`
`
`
`
`
`X,Y PAIR
`
`
`
`
`
`
`INCREMENTALLY ADD
`
`
`
`NEW POINT TO
`
`
`
`STATISTICS AND
`
`
`CALCULATE NEW
`
`
`
`BEST FIT LINE
`
`
`
`
`
`
`
`CALCULATE FIT OF
`
`
`
`X-PLUS ON X—MINUS
`
`PROJECTION
`
`
`
`xD‘BESs
`
`
`
`PASS FIT
`CRITERIA
`
`?
`
`
`
`
`
`DEFINE X—MINUS
`
`
`
`AS NEW LINE
`
`
`$5?ng
`
`
`10‘”
`
`104.8
`
`Page 9 0f 16
`
`Page 9 of 16
`
`

`

`US. Patent
`
`
`
`
`Oct. 1, 1996
`
`
`
`
`Sheet 9 of 10
`
`
`5,561,610
`
`
`
`3.1.3-5- '
`
`
`
`
`
`104.7.1
`
`
`
`
`
`FITSTATDENOM =
`
`
`XMINUSMSE +
`
`SLACKCONST *
`XMINUS.VARIANCE
`
`
`
`+ BIAS SLACK
`
`
`
`104.7.2
`
`
`
`
`
`
`
`IS
`
`
`XPLUS.MSE
`4 ITSTATDgNOM > O
`
`FHSTATDENOM
`FHSTAT =
`
`
`
`
`
`
`
`104.7.3
`
`
`104.7.7
` IS
`
`
`FITSTAT >
`
`
`
`
`FIT TOEERANCE
`
`104.7.5
`
`
`
`104.7.4
`
`
`
`FAms a)
`
`
`
`
`
` RETURN.FH
`
`
`
`RETURN Fn
`
`
`PASSES (o)
`
`104.7.8
`
`
`
`Page 10 0f 16
`
`Page 10 of 16
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`

`

`US. Patent
`
`
`
`Oct. 1, 1996
`
`
`
`Sheet 10 of 10
`
`
`5,561,610
`
`
`
`
`
`Ff ___'L|:|_
`
`
`
`104.11.1
`
`
`
`START
`
`
`
`
`
`
`CALCULATE DISTANCE OF LAST POINT
`
`
`
`DETERMINE SLOPE AND
`DURATION OF TREND
`
`
`OBTAIN WEIGHTING
`
`
`
`
`
`FACTOR BASED ON
`
`OBTAIN SIGNIFICANCE
`DISTANCE
`
`FACTOR BASED ON
`
`
`
`SLOPE AND DURATION
`
`
`
`
`104.11.13
`
`
`
`
`
`
`
`104.112
`
`
`
`
`
`
`
`104,11];
`
`
`
`10441.4
`
`
`
`
`
`
`
`
`104.11.14
`
`
`
`
`COMBINE WEIGHTING FACTOR
`
`
`
`AND SIGNIFICANCE FACTOR
`
`
`
`
`104.115
`
`
`
`CALCULATE WARNING PARAMETER
`
`
`
`
`
`
`
`
`104.11.6
`
`
`104.11.8
`
`104.113
`
`
`RESET
`WARNING
`
`
`
`
`WARNING
`
`
`
`LEVEL GREATER
`
`
`
`THAN CAUTION
`
`THRESPHOLD
`
`
`
`INDICATE CAUTION
`
`
`WAITING
`
`
`
`LEVEL GREATER
`N
`
`
`
`
`
`
`THAN WARNING
`
`
`THRESPHOLD
`
`
`
` INDICATE WARNING
`
`
`
`
`
`
`
`
`
`STORE FAULT CONDITION
`
`RETURN
`
`
`
`Page 11 0f16
`
`104.11.11
`
`
`
`Page 11 of 16
`
`

`

`5,561,610
`
`
`
`1
`
`NIETHOD AND APPARATUS FOR
`
`
`
`
`INDICATING A FAULT CONDITION
`
`
`
`
`TECHNICAL FIELD
`
`
`
`
`
`
`
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`
`
`The invention relates generally to devices for diagnosing
`
`
`
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`
`
`
`
`and indicating fault conditions, and more particularly, to a
`
`
`
`
`
`
`
`
`method and apparatus for diagnosing and indicating a fault
`condition in response to the trend in the level of a machine
`
`
`
`
`
`
`
`parameter.
`
`
`BACKGROUND ART
`
`
`
`
`For service and diagnostic purposes, machines are some-
`
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`
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`times equipped with sensors for measuring operating con-
`
`
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`
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`ditions such as engine RPM, oil pressure, water temperature,
`boost pressure, oil contamination, electric motor current,
`
`
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`
`
`
`hydraulic pressure, system voltage, and the like. In some
`
`
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`
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`cases, storage devices are provided to compile a data base
`
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`
`
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`
`
`
`for later evaluation of machine performance and to aid in
`
`
`
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`
`
`
`diagnosis. Service personnel examine the accrued data to get
`a better picture of the causes of the failure or to aid in
`
`
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`
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`
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`diagnosis. Similarly, service personnel evaluate the stored
`
`
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`
`
`
`data to predict future failures and to correct any problems
`before total component failure.
`
`
`
`
`
`
`
`
`
`
`
`In addition, these stored parameters may be examined by
`service or supervisory personnel to evaluate machine and/or
`
`
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`
`
`
`
`
`
`operator performance to ensure maximum productivity of
`the machine. These issues are particularly pertinent to over-
`
`
`
`
`
`
`
`
`the-highway trucks and large work machines such as off-
`
`
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`
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`
`
`highway mining trucks, hydraulic excavators,
`track-type
`
`
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`
`
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`
`
`tractors, wheel loaders, and the like. These machines rep-
`
`
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`
`resent large capital investments and are capable of substan-
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`
`
`
`
`
`tial productivity when operating. It is therefore important to
`
`
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`
`
`predict failures so servicing can be scheduled during periods
`in which productivity will be less affected and so minor
`
`
`
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`
`
`
`
`
`problems can be repaired before they lead to catastrophic
`failures.
`
`Similarly, it is sometimes advantageous to accumulate
`
`
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`
`
`
`
`
`
`
`parameters only when the machine is in a particular oper-
`
`
`
`
`
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`ating .condition. This type of information is predominantly
`used during performance evaluation but may also be used in
`
`
`
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`
`
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`
`
`
`
`
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`failure diagnosis and prognosis. For example, the length of
`time spent in a particular gear while the machine is loaded
`
`
`
`
`
`
`
`
`may be needed to evaluate machine performance.
`
`
`
`
`
`The present invention is directed to overcoming one or
`
`
`
`
`
`
`more of the problems set forth above.
`
`
`
`
`
`
`
`DISCLOSURE OF THE INVENTION
`
`
`
`
`In one aspect of the invention, an apparatus is provided
`
`
`
`
`
`
`
`for indicating a fault condition in a machine having a
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`plurality of parameters each having levels being dependent
`upon machine performance. The apparatus includes a sensor
`
`
`
`
`
`
`
`adapted to produce an electrical signal in response to the
`
`
`
`
`
`
`
`level of one of the parameters; and a processor for identi—
`
`
`
`
`
`
`
`
`
`fying a trend in the parameter level
`in response to the
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`electrical signal, calculating the duration and slope of the
`trend; and determining whether a first warning threshold is
`
`
`
`
`
`
`
`exceeded in response to the duration and slope of the trend,
`
`
`
`
`
`
`
`
`the first warning threshold being a function of duration and
`
`
`
`
`
`
`
`
`
`slope.
`In a second aspect of the invention, a method of indicating
`
`
`
`
`
`
`
`
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`a fault condition is provided. The method includes the steps
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`of sensing a parameter having a level being dependent upon
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`machine performance and responsively producing an elec-
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`trical signal,
`identifying a trend in the parameter level,
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`calculating the duration and slope of the trend, and deter-
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`response to the duration and slope of the trend, the first
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`warning threshold being a function of duration and slope.
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`The invention also includes other features and advantages
`which will become apparent from a more detailed study of
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`the drawings and specification.
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`BRIEF DESCRIPTION OF THE DRAWINGS
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`For a better understanding of the present invention, ref-
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`erence may be made to the accompanying drawings, in
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`which:
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`FIG. 1 is a high level diagrammatic illustration of an
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`embodiment of the invention;
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`FIG. 2 illustrates a plurality of connections to an elec-
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`tronic module in one embodiment of the invention;
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`FIG. 3 illustrates an algorithm performed by the elec-
`tronic module in one embodiment of the invention;
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`FIG. 4 illustrates a plurality of sensor values and best-fit
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`line segments;
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`FIG. 5 illustrates warning levels as a function of slope and
`duration of trended data;
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`FIG. 6 illustrates one instance of a group of data points
`being used to obtain a line segment;
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`FIG. 7 illustrates a high level algorithm performed in one
`embodiment of the invention;
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`FIG. 8 illustrates a portion of the algorithm of FIG. 7 in
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`more detail;
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`FIG. 9 illustrates a portion of the algorithm of FIG. 8 in
`more detail; and
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`FIG. 10 illustrates a portion of the algorithm of FIG. 8 in
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`more detail.
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`BEST MODE FOR CARRYING OUT THE
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`INVENTION
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`Referring to FIG. 1, a machine prognostic system is
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`shown generally by the number 10 and is a data acquisition,
`analysis, storage, and display system for a work machine 12.
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`Employing a complement of on-board and off-board hard-
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`ware and software, the machine prognostic system 10 moni-
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`tors and derives machine component information and ana-
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`lyzes the resulting data to indicate impending component or
`system failures.
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`FIG. 1 illustrates a variety of potential communication
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`systems 14 that may be used to transfer data from the work
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`machine 12 to a central computer system 16 for analysis. In
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`the preferred embodiment, the data is transferred by the
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`Qualcomm satellite system back to the central computer
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`system 16. Alternatively, the data is transferred by a cellular
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`telephone system or by storing data on a computer disk
`which is then mailed to the central computer site for analy-
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`s15.
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`It should be understood that all aspects of the present
`invention could be located on-board the work machine 12
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`thereby eliminating the need for a communication system
`14; however,
`the central computer system 16 allows an
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`entire fleet to be monitored at a central location.
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`Subsets of the data are also transmitted to a display
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`module (not shown) in the operator compartment of the
`work machine 12 for presentation to the operator in the form
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`of gauges and warning messages. During normal operation,
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`gauge values are displayed in the operator compartment.
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`Page 12 of 16
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`During out-of—spec conditions, alarms and warning/instruc-
`tional messages are also displayed.
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`In the preferred embodiment, sensed data is directly
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`sampled by sensors 18 of a type well-known in the art for
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`producing electrical signals in response to the level of
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`operational parameters and includes pulse-width modulated
`sensor data, frequency-based data, five volt analog sensor
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`data, and switch data that has been effectively debounced.
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`The sensors are connected to an electronic module 20 for
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`delivery of the sensor signals.
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`In the embodiment of FIGS. 1 and 2, the sensor signals are
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`delivered to the electronic module 20 by either direct
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`connection of analog sensors, connection by way of an
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`RS485 link, or over a datalink govemed by SAE specifica-
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`tions J1587 and 11708. A pushbutton is also included to
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`trigger the acquisition of a snapshot of data. Connection is
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`also provided from the machine battery and key switch to the
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`electronic module 20.
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`In the preferred embodiment, the electronic module 20
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`includes a Motorola 68000 microprocessor, a lower level
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`communications board (not shown) of a type well-known in
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`the art, and a memory section 24 including high level flash
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`memory and battery backed RAM. The electronic module
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`also includes a pair of R8232 connections, one being avail—
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`able for connection to the satellite communications system
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`21 and the other being available for connection to an
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`off-board computer 22 used in download of data and ini-
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`tialization of the system. In the preferred embodiment, the
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`off-board computer 22 is a laptop personal computer.
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`To document the performance of the machine and/or its
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`major components, performance baselines are stored in an
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`array within the memory device located in the electronic
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`module 20. These baselines are used during key, repeatable
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`performance checks of the machine to help verify machine/
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`component health and, as discussed below, are used as
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`reference points to determine whether the machine is in an
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`operating condition in which machine parameters are to be
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`processed and stored.
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`A subset of parameters for which trend data is to be
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`produced is either predefined or defined via the off—board
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`computer 22 or the central computer 16. Each parameter
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`includes a dependency definition that identifies the condi-
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`tions under which data will be stored for trending purposes.
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`Typically, the dependency definition is selected to indicate
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`the normal operating conditions of the machine;
`for
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`example, when engine RPM are above a certain level and
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`boost pressure is above a predetermined level. The trending
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`definition for each parameter may vary and may be a
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`function of several other machine parameters that shall be
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`referred to as dependencies. Trend data is gathered and
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`stored in memory as the specified dependency definition is
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`met over a specified trend period, which is measured either
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`in time, such as over a period of ten hours, or in counts, such
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`as over a period of ten transmission shifts. Trend data is only
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`obtained while the engine is running. Based on the specified
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`trend type, the maximum, minimum, or cumulative value of
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`data gathered during this period is then stored as a single
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`trend point with counts to determine the average value
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`and/or the points available. The determination of whether to
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`use the average, maximum, or minimum value to obtain the
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`trend point
`is based on the system designer’s decision
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`regarding which type of calculation would provide the best
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`indication of changes in engine performance or impending
`failures. It should also be understood that multiple values
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`could be calculated for the same sensed parameter, i.e. trend
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`points could be calculated to indicate both an average value
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`and a minimum value for a designated machine parameter.
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`The overall trend is formed by storing a specified number
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`of points in the memory device depending on the size of the
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`available memory area and the length of the desired histori-
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`cal data base.
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`Trend data may be reset and the definitions may be
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`redefined by the off—board system 22 via one of the com—
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`munication ports. For example, if a particular application of
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`the machine requires a different dependency definition for
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`one or more of the sensed parameters, the off—board system
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`22 is used to modify the dependency definition by providing
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`commands to erase a given array including a given depen~
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`dency definition and replace that definition with a new
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`dependency definition. Similarly, this function may be per—
`formed by the central computer system 16 via the commu-
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`nication system 14.
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`In addition to the trend data produced for sensed param—
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`eters, it should be understood that calculated values, such as
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`net horsepower or driveline torque, may also be trended in
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`a similar manner. Typically,
`these calculated values are
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`determined by the electronic module 20 according to pre-
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`determined definitions in response to a plurality of sensed
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`parameter signals.
`Referring now to FIG. 3, an algorithm incorporated in an
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`embodiment of the invention and executed by the processor
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`within the electronic module 20 to perform the above
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`functions is now described. In block 212. The electronic
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`module 20 determines whether the engine is running.
`Advantageously, the engine is determined to be running if
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`engine speed exceeds cranking engine speed. If the engine
`is not running, then the algorithm will not proceed. If the
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`engine is running, control proceeds to block 214 where the
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`electronic module 20 reads the sensed machine parameters
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`from the datalink or other inputs.
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`For each of the sensed parameters, the electronic module
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`20 determines at block 216 whether that parameter is to be
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`processed to provide trend data. If trend data is to be
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`provided, the trending definition is retrieved and the depen-
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`dency parameters are checked at block 218 to determine
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`whether the dependency definition is satisfied. If the depen-
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`dency definition is not satisfied, control returns to block 212.
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`The dependency definition for each operating parameter of
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`interest is defined in terms of other sensed machine param-
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`eters. For example,
`the dependency definition for boost
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`pressure may be satisfied only when engine rpm is greater
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`than a low operating speed and less than a high operating
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`speed, when the engine rack setting is greater than a prede-
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`termined level, and when the jacket water temperature is
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`greater than a predefined operating temperature. That is,
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`values for boost pressure are only saved and processed for
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`producing trend information when the above conditions are
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`satisfied. In this way, all boost pressure values used to
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`produce the trend data will have been acquired when the
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`engine is in the same general operating condition. It should
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`be understood that the actual ranges, minimums, and maxi-
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`mums used in the dependency definitions are determined
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`empirically to define the operating conditions of interest and
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`will vary from machine to machine and application to
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`application.
`If the dependency definition is satisfied, control proceeds
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`to block 220 where the value of the sensed parameter is
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`stored. This process is continued until, at block 222, either
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`the time period over which each trend point
`is to be
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`determined or the number of events for which each trend
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`point is to be determined is reached at which point control
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`proceeds to block 224 where the electronic module 20
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`calculates and stores the trend point. The time period or
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`Page 13 of 16
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`number of events is selected in response to the designer’s
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`desire for precision, the availability of memory space in the
`memory device, and the length of time or number of counts
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`required to obtain meaningful trend points. The calculation
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`of the trend point may include accumulating the stored
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`values, selecting the maximum stored value, or selecting the
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`minimum stored value. The calculated trend point is saved
`and the data array for that parameter is then cleared to allow
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`for the storage of data for calculation of the next trend point
`for that parameter.
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`Trend data obtained by way of the algorithm of FIG. 3 is
`illustrated in FIG. 4. While the illustrated data has a sub-
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`stantial variance, straight lines can be fit to the data to
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`illustrate the general trend of the data by known curve fitting
`techniques, such as the least-squares method. The method of
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`determining when a particular straight line trend should be
`terminated and a new line segment defined is described
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`below in connection with the algorithm of FIG. 7.
`Based on the slope and duration of the trends illustrated
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`in FIG. 4, certain judgements can be made regarding the
`likelihood of impending component or system failure. As
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`shown in FIG. 5, functions may be defined in terms of slope
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`and duration of particular trends whereby warning condi—
`tions are indicated in response to either the parameter of
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`interest changing at a very high rate for even a small period,
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`or at a relatively low rate for an extended period. The area
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`indicated by the letter “A” indicates the various combina~
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`tions of slope and duration of trends associated with normal
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`operating conditions. The areas indicated by the letters “B”
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`and “C” indicate the caution region and warning region,
`respectively. That is, normal conditions are indicated if the
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`magnitude of either the slope or duration of a particular trend
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`is relatively small, but as the magnitude of the slope and
`duration increase,
`the likelihood of a fault condition
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`increases.
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`Turning now to FIG. 6, the method of defining a particular
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`line segment associated with a trend in the sensed data is
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`described. A first region of data points in a series of data are
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`selected and indicated by X—. A second region of data points
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`immediately following X— are selected and indicated by X+.
`The sizes of X— and X+ are arbitrary but, in the illustrated
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`embodiment, X— consists of 6 data points and X+ consists
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`of the following 3 data points. In some embodiments, X+
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`may include only a single data point; however, multiple
`points are desirable for X+ to reduce the likelihood that a
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`single aberrant point will cause a line segment to be tenni-
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`nated.
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`The data points in X— are used to calculate a best fit line
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`using a known technique such as least squared errors. Using
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`the derived equation of the line, the data in X+ is tested to
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`determine whether the line segment should continue such
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`that the data points of X+ are added to the line segment data
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`or whether a new line segment should be started and the
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`previous segment terminated. This test is performed by
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`using the following inequality:
`Fit-Statistic =
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`MSE(X+, x+ Based mix-Regression)
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`MSE(X—, x—) +
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`deviation slack + bias slack)
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`< Fit tolerance
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`where: MSE is the mean squared error;
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`deviation slack is a bias to the denominator of the fit
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`statistic to discount MSE changes when there is a high
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`slope to the trend and in the preferred embodiment is
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`equal to a slack constant multiplied by the variance of
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`X—;
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`65
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`Page 14 of 16
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`fit tolerance is a constant controlling the tightness of fit of
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`the data allowed for a given line segment,
`in the
`preferred embodiment is equal to 4.8; and
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`bias slack is a constant used to prevent a new line segment
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`from being formed in the event that the MSE of X— is
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`zero. In the preferred embodiment, bias slack is set
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`equal to zero and decision blocks are included in the
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`algorithm shown in FIG. 9 to handle situations where
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`the fit statistic denominator is equal to zero.
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`If the inequality is true, the left most data point in X+ is
`moved to X— and a new data point is moved to the right most
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`side of X+. If the inequality is false, the line segment is
`terminated and a new X— is defined beginning with the next
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`data point following the defined line segment.
`In one embodiment, if the inequality is false, a fit statistic
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`base is set equal to the present fit statistic. Data points are
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`then continuously added to X— and a new fit statistic is
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`calculated when each new data point is added. Data points
`are no longer added to X— when the fit statistic reaches a
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`preselected fit poomess percentage indicative of the mini—
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`mum ratio of the fit statistic base to the fit tolerance. This
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`allows a subset of the data points in X+ to be added to the
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`line segment if the trend actually changes in the middle of
`X+ rather than at the beginning of the X+ group of data
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`points.
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`The algorithms performed by the present invention are
`now described in connection with FIGS. 7 through 10. At
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`block 100, the algorithm is started. At block 101, the default
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`fit parameters are initialized and any accumulated values are
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`set equal to zero. At block 102, the system determines
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`whether there have been overrides of the defaults. At block
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`103, data points are loaded into the computer system by way
`of one of the communication systems. For each of the data
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`points, the time at which it was stored and its magnitude are
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`arbitrarily chosen as X and Y. This data is next processed at
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`block 104 which is described in more detail in connection
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`with FIG. 8. Following processing of the data, the output
`files are closed at block 105 and the algorithm is terminated
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`at block 106.
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`The fiinctions described in connection with blocks 104
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`and 105 describe a system in which the an