tier 2 is protected by a password, and tier 1 is not. Pass-
word protection prevents unauthorized users from access-
ing functions that have a direct effect on system perform-
ance. For example, the calibrate and motor specification
functions alter data used in computing motor deterioration.

Tier 1 (unprotected) menu options are as follows:

Data base.—Allows a user to examine the contents of
the historical data base file or any one of the daily files.

Motor specifications. —Allows a user to read the specifi-
cation listing on any motor.

System.—Provides access to protected menu functions.
The user must know the system password to proceed from
this menu option to the tier 2 options listed below.

Tier 2 (protected) menu options are as follows:

Motor specifications —Permits a user to edit motor spec-
ification data. This option is typically chosen after an
existing motor is replaced by one with different specifica-
tions. Since motor specification data are used in calcu-
lating deterioration, it is essential that this information be
kept up to date.

Alarms —Allows a user to activate or disable the MMS
alarm for any motor.

Calibrate.—Allows a user to calculate a new software
calibration factor for a motor. Calibration factors are
typically computed once, either when the MMS program
is installed for the first time or when a motor is replaced.

Exit.—Allows the user to terminate the MMS program.

Version 1.0 of the MMS program accomplished all
stated design objectives and was subsequently installed
on the Joy 16CM continuous miner for demonstration
purposes. However, like most first-version programming
efforts, the program evolved over time and this caused
problems, specifically two key problems. First and most
notable was the fact that the program lacked modularity
(because of the cut-and-paste nature of writing the pro-
gram as time went on). This made it difficult to incorpor-
ate new features. Second, the program was written in
three languages. Although the languages are Intel prod-
ucts, they are implemented differently.

VERSION 2.0

After using Version 1.0, it became evident that a sec-
ond version was needed. Although Version 1.0 met the
original design objectives, several features needed to be
changed to improve program performance and usage.

Version 2.0 is a demonstration program rather than a
prototype of a program that can be used in the field.
Graphics mode is used to display user information more
clearly. Although actual data are taken and displayed,
these data are not used when trend lines are displayed,
because the miner is not run frequently enough to get
enough data from the miner to show meaningful trend
lines. Data developed from Bureau experience in mod-
cling motors were used to display trends.

Version 2.0 of the MMS is written entirely in Borland
Turbo C version 2.0. A library of functions was developed
to replace the Intel BITBUS library, which is not com-
patible with Turbo C.

Version 2.0 is made up of two programs rather than
one as in Version 1,0, The first program (MMSP) is the
actual demonstration program, and the second program
(MMSXP) is used to set various system variables used by
MMSP.

MMSP was programmed using KADAK AMX-86 ver-
sion 3.0 as an operating system. MMSP is, however, a
much simpler program than Version 1.0 because it op-
erates mostly in non-real-time mode. Only the data acqui-
sition and display update are done in real-time.

The program has two major displays. The first display
shows the miner in outline with the motors shown sym-
bolically in color. The color of each motor symbol, green,
yellow, or red, indicates the relative state of each motor
based on its most recent deterioration values. Green rep-
resents a motor with normal deterioration values, yellow
represents higher-than-normal values, and red represents
a motor with deterioration values high enough to indicate
imminent failure. While in this display the user can also
display one or more windows that show the deterioration
values for all motors, the state of the audible alarm, and
trend line graphs. The second display is a simulation of
the display the machine operator would see—a red, yellow,
or green light for each motor.

MMSXP is an auxiliary program used to set system
variables used by MMSP. These variables are alarm lev-
els, timer interval, and calibration constants. This pro-
gram must be run at a time when MMSP is not running.
MMSXP is a normal (non-real-time) program that was
programmed using Turbo C version 2.0 and Vermont
Views version 2.0 windowing software.


MOTOR MONITORING SYSTEM FOR A CONTINUOUS MINER

By John R. Thalimer,’ John J. McClelland,” and Gerald T. Homce®

ABSTRACT

The U.S. Bureau of Mines has investigated the early detection of insulation failure in squirrel cage
induction motors for the past 4 years. Research was done using a sophisticated empirical data-modeling
technique based on values calculated from a motor’s voltage and current phasors. This technique
produces two polynomial equations that calculate the insulation leakage current and power. These
models were implemented in a prototype system that monitors six motors on a continuous miner for
insulation leakage. These insulation leakage values are used to anticipate insulation failure.

The system consists of a motor-data-system for each motor on the machine and a control computer
located away from the miner. Each motor-data-system consists of an analog interface to the motor’s
voltages and currents, a single-board computer that reads digitized data and calculates voltage and
current phasors, and a bus node that interfaces the single-board computer with the rest of the system
by way of a serial bus system. Using this bus system, the control computer requests and receives phasor
data from the motor-data-systems.

From these data the control computer calculates and displays two deterioration values for each motor,
for leakage current and power, using Bureau-developed models. These values are stored in a data base
from which the user can display graphs of each motor’s deterioration values over time.

|Blectronics engineer.

2Computer engineer.

Electrical engineer.

Pittsburgh Research Center, U.S. Bureau of Mines, Pittsburgh, PA.


Control

Cutterhead
computer

Traction
motor

Gathering head—
conveyor motor

controls

Figure 5.—Continuous miner, motors, controls, and Motor Monitoring System.

When this system was designed there were three op- _single-board computers. Figure 6 shows the current and
tions for transferring data between the motor-data-system —_ potential transformer wiring. There are current trans-
and the control computer. The first was to send the raw _ formers for the line current on each phase of each motor
data points from the ADC, the second was to send pha- _and one set of potential transformers for the machine line-
sors, and the third was to calculate each motor’s de-  to-line voltages. The voltage signals are fed to each mo-
terioration levels at the motor-data-system and send.only —_toy’s analog interface since they are needed in calculating

the two deterioration values. However, when this system voltage and current phasor values with the proper phase
was considered as a part of a larger common BITBUS sys- relationship.

tem that includes navigation and machine control systems, Figure 7 shows one of the analog interface boards

only the second method was viable. The first method that were designed and built in-house. Each board has

overloads the bus and the third method does not provide seven channels, six of which are used by this system, Fig.

phasor values for other nodes on the system that may need ue § shows a schematic wiring diagram of one channel,

them. Each channel accepts a differential voltage signal of ap-

proximately 5 V peak-to-peak and outputs a 0- to 5-V

ANALOG INTERFACE signal centered at 2.50 V. This voltage offset is neces-

The analog interface provides an interface between the sary because of the 0- to 5-V ADC’s on the single-board
current and potential transformers and the ADC on the computers.


THEORETICAL BASIS FOR EARLY MOTOR FAILURE DETECTION

Past Bureau contract research examining mine electrical
system safety investigated the possible benefits of using
continuous monitoring techniques to evaluate the condition
of power system components (3). Researchers concluded
that early detection of deterioration in mine electrical
system components could significantly improve system
safety and availability. As part of an independent research
program, the work was continued, with further analysis of
the relationship between the mechanisms of electrical com-
ponent deterioration and their resulting signatures (4).
Recent Bureau-funded efforts in this area produced sev-
eral computer models to simulate power system and induc-
tion motor operation under deteriorated conditions and
identified characteristics associated with deterioration
involving windings in induction motors (2).

The research programs just described produced infor-
mation that can be used to form a theoretical basis for the
detection of low-level insulation deterioration. However,
this information had not yet been successfully implemented
in a well-defined method to detect the presence and level
of electrical deterioration. This situation prompted the
Bureau to initiate an in-house research project to develop
such a method.

APPROACH

Information from past research suggests that a math-
ematical relationship or group of relationships can be
used to identify electrical deterioration, using measurable
power system parameters, but identifying the appropriate
input features and deriving suitable relationships is a com-
plex task. In-house research utilized an empirical data
mathematical modeling approach to this problem, employ-
ing commercially available data-modeling software and
information from laboratory-generated power systems to
create the necessary relationship(s).

PNETTR-4X (Polynomial NETwork TRainer version
4X) is a data-modeling software package marketed by
General Research Corp. that can create a polynomial
network model called an adaptive learning network (ALN)
to represent a physical process (5). PNETTR uses an
unsupervised learning method to build ALN’s, selecting
only the input features that are necessary for accurate
modeling. For this research, input data were electrical
features extracted from laboratory systems undergoing
simulated deterioration. PNETTR selected the features
that were most significant for modeling system operation
and created ALN’s, relating them to dependent variables
indicating deterioration severity.

This research modeled three-phase squirrel cage in-
duction motors, the electric motors most widely used in

mining operations. Electrical failure often originates with
the breakdown of insulation and subsequent leakage of
current through an abnormal path, eventually resulting in
a fault (3). The process of insulation breakdown was used
in this research as the basis for quantifying progressive
deterioration of induction motors, with deterioration
severity indicated by the level of current flowing and power
dissipated in an abnormal path. Such leakage current can
seldom be located, much less measured, in the field, but it
is readily controlled and measured in laboratory simu-
lations. Therefore, laboratory simulations can be used to
establish an empirical relationship between deterioration
current and power levels and readily measured electrical
values, and this relationship can be employed to detect
deterioration in the field.

Motor-alternator sets powered by a motor test station
and loaded by a bank of resistors were used to generate
the required power system terminal information. To simu-
late varying levels of current leakage (insulation deteriora-
tion) across various points on the motor system, a bank of
resistors was connected to the motor leads through a vari-
able transformer. The leakage current levels simulated for
laboratory tests were recorded during data acquisition for
each sample taken and, along with the calculated deterio-
ration power, became the dependent variables in PNETTR
data files. Electrical parameters derived from three-phase
voltage and current terminal values served as independent
variables.

Laboratory-generated data represent a wide range of
motor system operating conditions, including different
deterioration (insulation leakage) positions and levels and
different motor load levels. Several individual samples
were taken for each distinct laboratory system condition
and were subsequently processed to yield system observa-
tions for input to PNETTR. Most of these observations
were used in the development of the ALN’s, while the re-
mainder were reserved to form independent evaluation
data sets. The root-mean-square (RMS) of residuals be-
tween the actual and model-calculated deterioration levels
for these evaluation data sets provides an indication of
ALN accuracy.

FAILURE DETECTION ADAPTIVE
LEARNING NETWORKS

Results of PNETTR modeling indicate that ALN’s can
detect and quantify low-level deterioration on a motor
system, independent of deterioration type and level and
motor load level. The most accurate ALN’s developed
thus far, covering a wide range of simulated system con-
ditions for 50-, 100-, and 150-hp motors, are shown below.


INTRODUCTION

More than 50% of all industrial motor failures are due
to winding insulation failure (1).4 This, along with bear-
ing failure, accounts for 80% of all failures. Therefore,
combining conventional bearing failure detection methods
with winding insulation failure detection methods will
create a system that can detect up to 80% of all electric
motor failures.

Prediction of motor failure is important from both a
safety and a production standpoint (2); it is much safer
and less expensive to change a motor before failure than
during an operating shift.

Presently, insulation resistance (megger) testing of
motor windings is done at some mine sites. For this test
the motor must be taken out of service and disconnected
from the power system.

The U.S. Bureau of Mines is conducting research to
develop techniques to determine the leakage current and
power due to deterioration of motor winding insulation.

Research has shown that this leakage current and power
can be determined by measuring the motor’s voltage and
current phasors while the motor is in normal operation.
The leakage current and power are modeled as polynomial
functions of common engineering values that can be cal-
culated from these phasors. The Motor Monitoring Sys-
tem (MMS) is the first attempt at using this research in a
prototype application.

The MMS is a computer-based distributed processor
system for anticipating catastrophic insulation failure in
the induction motors on a continuous miner. The system
is being demonstrated on a Joy 16CM® continuous miner
(fig. 1), which is used by Bureau researchers as a test-bed
for advanced mining applications. This research addresses
two Bureau goals: to provide a safe and healthful work
environment for miners and to reduce the cost of coal
production.

‘Italic numbers in parentheses refer to items in the list of references
at the end of this report.

Reference to specific products does not imply endorsement by the
US. Bureau of Mines.

Figure 1.—Continuous miner.


HARDWARE DESCRIPTION

The MMS installed on the Joy 16CM continuous miner
is a distributed processor system interconnected with
BITBUS, a commercially available control bus system
(fig. 2). Connections are made to BITBUS through nodes
that are connection points on the bus. The control com-
puter is the master node, which controls all operation on
BITBUS, and the bus node portions of the motor-data-
systems are slave nodes. The miner has a separate
BITBUS network that is used for control and navigation.
The MMS is designed to eventually link into the control
and navigation network.

Except for the control computer, the system is mounted
on the miner. Figure 3 shows a box containing most of
the hardware mounted on top of the miner’s left-side

Cy} computer
=

nn i acckaiec dad Torte 1
‘Bus Single - board
erreus| rode computers,
| [
1 I C4

current analog signals,

1
i}

i}

i}

I

1

=

H

Coo ‘ooco

I

I

oe oS Tr

3 phase moter vltoge ond '
Analog interface {

I

I

'

Figure 3Motor Monitoring System on continuous miner.

contactor case. Figure 4 shows the analog boards, single-
board computers, and bus nodes mounted inside this box.
Each motor’s current and potential transformers are
mounted inside the miner’s contactor cases. The six mo-
tors range from 15 to 175 hp. Figure 5 shows the location
of the MMS, motor controls, and motors.

The control computer is located away from the miner
and is the control point for the monitoring system. It also
calculates and stores motor deterioration data.

Each motor-data-system is interfaced to its motor
through an analog interface and analog-to-digital converter
(ADC). This ADC is integral to the single-board com-
puter’s microprocessor. On command from the control
computer, the motor-data-system digitizes phase-to-phase
voltage and line current analog signals, and from these
values calculates phasor values using a fast Fourier trans-
form. After the motor-data-system finishes the phasor
calculations, they are sent to the control computer using
BITBUS, for use in calculating deterioration values.

The motor-data-systems’ bus nodes provide an inter-
face between the motor-data-systems and BITBUS. These
nodes are slave nodes that can only respond to commands
sent from the master node. The master node is a board
contained in the control computer.

CONTROL COMPUTER

The control computer is an IBM Advanced Technology
(AT) clone personal computer (PC) with a 40-MB hard
disk. It is connected to the BITBUS through an Intel
PCX344 Intelligent BITBUS interface board plugged into
an expansion slot.

Figure 4.—Motor Monitoring System.


IC| 9306

BUREAU OF MINES
INFORMATION CIRCULAR/1992

Motor Monitoring System for
a Continuous Miner

By John R. Thalimer, John J. McClelland,
and Gerald T. Homce

UNITED STATES DEPARTMENT OF THE INTERIOR


2v2 FI
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Differential input
(channel 1)
4

TP2
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(channel 1)
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Figure 8.—Analog interface schematic for one channel.

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BUS NODES

The bus nodes are Intel iRCB 44/10A digital input-
output (I/O) controller boards. They are used to interface
the motor-data-system with BITBUS. Figure 9 shows the
parallel interface between a single-board computer and its
bus node. The Start Data Acquisition bit is set on the bus
node to start data acquisition and calculation of the pha-
sors. When phasor calculation is done, the first byte of
phasor data is stored in the data port and the Data Ready
bit is set. This byte of data is read from the bus node data
port, and the Data Request bit is set. All of the phasor
data are sent to the control computer a byte at a time
using the same process as for the first byte. .

Some thought was given to combining the functions of
a bus node and single-board computer by using an Intel
iRCB 44/20 analog I/O remote control board. This idea
was rejected because the board’s operating system and
ADC could not operate at the speeds and timing accuracy
necessary to sample the voltage and current at 32 samples
per cycle (11,520 samples per second). Also, the bus node
8051 microcontroller is not intended to be used for float-
ing point calculations.

Ad
Data - 8 bits
a

(P10 -P1.7)

Data ready

P20
Data request
s pat bPort2
Start data acquisition
P22
Single-board

L* |

computer

Figure 9.—Data and control signals between bus node and
motor monitor.

SINGLE-BOARD COMPUTERS

The single-board computers are Intel 80C196KB micro-
controller single-board computers (Intel EV80C196KB
evaluation board). The 80C196KB microcontroller was
chosen because it has an 8-channel 10-bit ADC, par-
allel ports and support for floating point operation, and
because it is inexpensive.


Line current instrumentation
(3 for each motor)

CT shunt resistor

(1% wirewound with heat sink) aa
<<]
2 cutting motors- 10% CT, 0.732, 50W shunt
2 traction motors - 6% CT, 1.470, 25W shunt Single motor
| head-conveyor motor-% CT, 1.580, 25W shunt power conductor

| pump motor - 6% CT, 1.002, 25W shunt

Voltage instrumentation
(common to entire system)

200:1 isolation 3p Bus
transformers. ABC

Ye GSsssssssS al
we Sse
we SSS)

Figure 6.—Potential transformer and current transformer (CT) wiring.

Figure 7.—Analog interface board.


Deterioration current ALN:
X= Ay + AQXy + AgXs + AGX Xs + ASX?
+ AGKS? + ADK)? + AQXS3,
and
Y1 = Ag + AyoX7 + AyrX2 + ArX3
+ AggXaX3 + AggX7? + AysXp”
+ AygX3? + AygX7? + AygXp?.
Deterioration power ALN:
Xg = Ayg + AzoXy + AniX2 + AnoXy
+ AggXX + AggXpXq + AgsXy?

+ AggX? + AarXy> + AagX2°,

and

Y2 = Ag + AzoXg + AgiXs + AgnXeXoy

where X, = negative sequence current polar magni-

tude,
X_ = negative sequence current polar angle,
X3 = negative sequence current x-coordinate,
X4 = negative sequence current y-coordinate,
Xs = zero sequence current polar magnitude,
X_ = three-phase average of real power,
X, = first-layer output for deterioration cur-

rent ALN,

Xq_ = first-layer output for deterioration power
ALN,

Y1

deterioration current level,
Y, = deterioration power level,
and A,-Aj) = coefficients.

The RMS errors for calculation of deterioration
power and current, using the above ALN’s to evaluate

independent data sets for each motor used in training, are
listed in table 1.

Table 1.—Root-mean-squar
of deterioration current

rors for calculation
power, percent

‘Adaptive learning S0-hp 100-hp _180-hp
network data__data__data

Current . 18 2.0 19

Power .. 1315 14

Whether errors of several percent (of motor line cur-
rent or power) are acceptable for actual deterioration-
detection systems depends on the as-yet unconfirmed char-
acteristics of induction motors prior to complete failure.
Considering, however, that 25% leakage current levels can
exist in motors without immediate obvious effects, the
resolution possible with the ALN accuracies listed in ta-
ble 1 may well be acceptable for practical deterioration
monitoring (4).

In the subject research, failure detection techniques
were developed using simulated deterioration conditions,
based on the assumption that in actual motor failure, in-
sulation degradation would be gradual and of sufficient
magnitude to allow early detection. Field measurements
from previous research suggest that this is the case, but no
quantitative study has been done to verify the foregoing
assumption,

To address this situation, ongoing work includes accel-
erated life testing of motors. These tests attempt to in-
duce gradual insulation failure in laboratory motors to
confirm the presence of detectable insulation breakdown
prior to motor failure. In these tests, typical mine equip-
ment motors are operated at above-normal temperatures
to accelerate winding insulation degradation. Motor elec-
trical parameters are closely monitored during this deteri-
oration process, and deterioration current and power levels
are calculated using ALN’s. The results are analyzed to
identify unique signatures present prior to complete motor
failure. Carefully controlled acceleration of motor aging
permits the completion of this work in a practical time
frame, while allowing extrapolation of results to motor life
under normal operating conditions.

Another approach for validation of ALN-based tech-
niques to detect early motor failure is long-term testing of
a large number of motors in the field. Currently proposed
work would monitor 25 to 50 motors in a mineral process-
ing plant over a period of several years. This would allow
ALN analysis of motor characteristics prior to actual fail-
ures under normal operating conditions and, as described
above, evaluate the ability of ALN’s to anticipate complete
failure.


hp
MB

a

UNIT OF MEASURE ABBREVIATIONS USED IN THIS REPORT
horsepower v
megabyte Ww

ohm

volt

watt



SINGLE-BOARD COMPUTER SOFTWARE

All programming for the single-board computers was
done using the Intel ASM-96 assembler and the Intel re-
locator and linker, RL96, on an IBM AT clone. An in-
circuit emulator (Intel ICE-196PC) running on the same
IBM AT clone was used for debugging software. When
the software was running properly it was transferred to
PROM’s and these PROM’s were installed on the single-
board computers.

Figure 11 is a flow diagram of the program. The pro-
gram was written in three modules: AZDRUN, A2D, and
FFTVS. A2DRUN is the main module that controls the
flow of the program. A2D is a module that contains the
code for the acquisition of data via the ADC. FFTVS is
a fast Fourier transform module (6) that is used to obtain
the phasor values sent back to the control computer by
way of the BITBUS. The flow of the program is fairly
simple. The program first initializes its stack and the
processor’s parallel I/O ports, Then the program goes in-
to a loop waiting for the Data Request bit (fig. 9) to be
set. When this is done the program acquires the data us-
ing code from the A2D module and calculates phasor data
using the FFTV5 module. After the data are calculated,
they are sent to the control computer a byte at a time by
way of BITBUS.

ANTICIPATED FUTURE DEVELOPMENT

ALN’s have been developed for four motor sizes:
10, 50, 100, and 150 hp. The MMS uses the 50-hp ALN,
which provides acceptable results, even though the motors
range from 15 to 175 hp. Future systems would either cal-
culate deterioration using an ALN for each motor that
closely matches that motor, or a single ALN for a range of
motors that approximate the miner’s motors.

MMS’s used in mines would take a different form from
the system described above. The system would consist of
a motor-data-system for each motor but without a control
computer. The motor-data-system would calculate and

Initialize A2DRUN

Data
request

A2DRUN

Acquire
data a2D
Calculate
phasors | FFTVS
Output
praeat, | A2DRUN

Figure 11.Single-board computer program flow diagram.

temporarily store the deterioration values for its motor. If
a deterioration value were to go out of range the motor-
data-system would send a message to the operator’s panel
indicating that the motor is about to fail. Periodically the
motor-data-systems would send the stored data to a com-
puter in the mine office over a data link or to a portable
computer that could be brought to the machine. When
transferred, the data would be added to a data base of
deterioration values for each motor. These data could
then be studied to better estimate the time to failure for
any motor.

SUMMARY

An MMS was developed for use on a continuous miner.
Two versions of the system were developed; they differ
only in the control computer software. Version 1.0 uses
character-based output, and Version 2.0 uses graphics out-
put. Version 2.0 also uses a separate program to set sys-
tem operating parameters rather than including these func-
tions in the main program.

If a future system is developed it would likely reside
entirely on the miner with only a very basic operator

display. In this case, a method would be needed to trans-
fer deterioration values from the system to a computer in
the mine office. The mine office computer could then be
used to track trends in the deterioration values, In ad-
dition, separate ALN’s would be used for each motor, or
one common ALN would be developed specifically for the
miner’s motors,


CONTENTS

Abstract... 6... e eee cece cece tee eens
Introduction . .
Theoretical basis for early motor failure detection
Approach .
Failure detection adaptive learning networks
Hardware description . eee
Control computer
Analog interface
Bus nodes ....
Single-board computers
Software description
Version 1.0 .
Version 2.0
Single-board computer software
Anticipated future development
Summary
References . .

Continuous miner
Motor Monitoring System for continuous miner .
Motor Monitoring System on continuous miner .
Motor Monitoring System ..
Continuous miner, motors, controls, and Motor
Potential transformer and current transformer
Analog interface board .
‘Analog interface schematic for one channel... .
Data and control signals between bus node and motor monitor sees
Motor Monitoring System version 1.0 software command hierarchy . .
Single-board computer program flow diagram ...........0000005

PS yengavayye

Be

TABLE

1. Root-mean-square errors for calculation of deterioration current and power 2.2.0... cc. ec ee enone 4


Library of Congress Cataloging in Publication Data:

Thalimer, John R.

Motor monitoring system for a continuous miner / by John R. Thalimer, John J.
McClelland, and Gerald T. Homce.

p. cm. — (Information circular / United States Department of the Interior,
Bureau of Mines; 9306)

Includes bibliographical references (p. 12).
1. Mining machinery—Electric ‘driving—Reliability—Data processing. 2. Elec-
tric motors, Induction—Reliability-Data processing. I. McClelland, John J.

Il. Homce, Gerald T. III. Title. IV. Series: Information circular (United States.
Bureau of Mines); 9306.

TN345.T49 1992 622s—dc20 = [622’.8] 91-42043. ss CIP



SOFTWARE DESCRIPTION

There are two versions of the MMS program. The first
uses character-oriented output, and the second uses graph-
ic output. The first version was written using the pro-
gramming languages C, Pascal, and PLM; the second was
written entirely in C. This change took place because
modules written in three languages were cumbersome to
link. The first version was written using a data base writ-
ten in-house. For the second version an off-the-shelf data
base product was used.

Code also was written for the single-board computers.
This code was written, compiled, and linked using a cross-
assembler and then loaded into programmable read-only
memory (PROM) for use in the single-board computers.

VERSION 1.0

Version 1.0 of the MMS program is a real-time,
multitasking program that runs on the control computer.
The program computes and displays motor deterioration
values and services user menu requests while it collects
motor data over the BITBUS network.

The MMS program was written mostly in Intel Pascal
(PAS86 version 2.0) and Intel C (ic86 version 4.1), with a
small piece of code written in Intel PLM86. Intel lan-
guages were chosen because of the need to use Intel’s
Universal BITBUS Interface (UBI) library, which is not
compatible with other vendor languages. . Use of this
library was necessary to communicate and perform remote
access and control functions over the BITBUS network.

Initially, all programming was done in Pascal. Pascal
code is generally considered to be very readable, making
it easier to maintain. In addition, Bureau programmers
had used Pascal extensively in previous programming ef-
forts. These advantages, however, were quickly offset by
some serious programming limitations placed on the lan-
guage by the operating system.

Eventually, Bureau programmers decided to develop
only C-coded program modules to avoid the problems en-
countered with Pascal. Although programs written in C
can be quite cryptic and difficult to read, they are portable
across different computer systems.

The MMS program was targeted to run on an IBM
compatible PC with an operating system with real-time,
multitasking capability. These operating system features
were necessary for the MMS program to collect data over
the network without interruption while servicing user menu
requests and updating display information, The operat-
ing system (Microsoft Disk Operating System; MS-DOS)
found on most PC’s did not satisfy these requirements.

KADAK AMX-86 version 2.0 is a development package
for configuring and implementing real-time, multitasking
operating systems; AMX was found to be ideal for build-
ing the Bureau’s MMS program. The programmer builds
an application program, such as the MMS program, to use
the various AMX facilities that enable real-time, multitask-
ing programming. In addition, the programmer describes
specific characteristics of the program in a configuration
module for use by AMX during program execution. AMX
uses this information to drive the program according to
the programmer’s specifications.

The primary objectives in writing the MMS program
were to quantify motor deterioration and to activate a
system alarm when the deterioration level rises above an
acceptable threshold. To accomplish this objective, the
program periodically collects data and applies formulas
derived from laboratory investigations of motor winding
insulation failure to compute deterioration levels. If the
computed deterioration is out of range, an alarm is
triggered.

A rudimentary data base was written to manage the
motor data. Each time motor deterioration levels are
computed and displayed they are subsequently written to
a file on the hard disk. This output file is given the name
of the current calendar date. All data collected on the
same day are written to the same file. For example, all
motor deterioration data collected on January 1, 1990,
append to the daily file JAN0190.

Up to seven daily files are maintained by the MMS
program. When attempts are made to open and write an
eighth file, the oldest file’s data are summarized and added
to the summary data base, and that daily file is deleted.

Figure 10 shows the various functions available from
the user menu. The user menu is divided into two tiers;

User menu
Tier |,
unprotected [-—————
Data base ‘System Motor
specifications
Password

Tier 2,
protected = 1

Motor Alarms Calibrate Exit

specifications

Figure 10.—Motor Monitoring System version 1.0 software
command hierarchy.


REFERENCES

1. Heising, C.R. Quantitative Relationship Between Scheduled Elec-
trical Preventative Maintenance and Failure Rate of Electrical Equip-
ment, IEEE Trans. Ind. Appl., v. IA-18, No. 3, 1982, pp. 268-272,

2. Kohler, J. L., and F. C. Trutt. Prediction of Incipient Electrical-
Component Failures (contract J0338028, PA State Univ.), BuMines
OFR 35-88, 1987, 307 pp.; NTIS PB 88-213590.

3. Morley, L. A., and J. L. Kobler. Final Report—Evaluation of
Coal-Mine Electrical-System Safety (grant G0155003, PA State Univ.).
BuMines OFR 160-81, 1981, 258 pp.; NTIS PB 82-139338.

4. Kohler, J. L. A Decision-Theoretic Method for the Classification
of Incipient-Failure Patterns Which Are Characteristic of Deteriorating
Mine Power-System Components. Ph. D. Thesis, PA State Univ., Uni-
versity Park, PA, 1983, 141 pp.

5. General Research Corp., McLean, VA. PNETTR-4X User's
Guide and Technical Reference. Aug. 1986, 74 pp.

6. Horden, I. An FFT Algorithm for MCS-96 Products Including
Supporting Routines and Examples. Embedded Control Applications
Handbook. Intel Corp., 1989, pp. 6-103 to 6-177.