In mine evaluation of discriminating mine fire sensors 

J.C. Edwards, R.A. Franks, G.F. Friel, C.P. Lazzara, & J.J. Opferman 

National Institute for Occupational Safety and Health, Pittsburgh Research Laboratory, Pittsburgh, PA, USA 

1 INTRODUCTION 

NIOSH’s mission to protect the health and safety of 

workers has a unique role in underground mines 

where the miner’s escape from toxic POC in the 

event of a fire is severely restricted. One aspect of 

the miner’s protection is reliable early in-mine fire

detection. Another equally important issue is discrimination of true fire alarm signals from nuisance

emissions produced alarm signals associated with 

normal mining activities. The in-mine use of an atmospheric mine monitoring system to monitor hazardous conditions has increased significantly over 

the past decade (Panigrahi & Ghose, 1999). 

Previous research (Edwards et al., 2001) investigated the response of multiple sensors to coal, electrical cable insulation, conveyor belt, and diesel fuel

combustion. It was demonstrated for the solid fuel

combustion experiments that in the absence of background diesel emissions, smoke and MOS (metal oxide semiconductor) fire sensors with an alarm value 

set to be a ten standard deviation (S.D.) change in 

the signal from its ambient value, alarmed before the 

carbon monoxide (CO) sensor measured a 5 ppm 

CO concentration increase. If the fire state and nuisance emissions state are considered to be two 

modes of combustion characterized by bimodal gas

signatures, then a sensor with a clear bimodal discrimination would be a practical method to discriminate the fire and false nuisance emissions

alarm. It was also determined that a MOS sensor 

sensitive to oxides of nitrogen (NOx) had a bimodal

response to NOx producing nuisance events, such as 

diesel emissions and acetylene cutting, and products-of-combustion (POC) from open fires. The extension of that research is to evaluate the capability 

for fire detection in the presence of diesel emissions. 

CO and POC particulates from diesel emissions and 

a CO sensor’s chemical cell’s cross-sensitivity to 

hydrogen gas (H2) can cause false fire sensor alarms

in a mining operation. An additional undesirable 

consequence of false alarms is the unintended learning by miners to ignore false alarms, which can result in ignoring true fire alarms. For the purpose of 

determining the mine fire-nuisance alarm discriminating capability of fire sensors, a series of experiments were conducted in the NIOSH/PRL Safety 

Research Coal Mine to evaluate the capability of 

multiple sensors to differentiate an incipient coal or 

conveyor belt smoldering fire from diesel emissions. 

ABSTRACT: A National Institute for Occupational Safety and Health’s (NIOSH) mine fire detection research project was undertaken to evaluate multiple mine fire sensor types for nuisance alarm discrimination.

The response of multiple fire sensor types to three small coal fire and three small conveyor belt fires in the 

presence of diesel emissions was evaluated in NIOSH’s Pittsburgh Research Laboratory (PRL) Safety Research Coal Mine (SRCM). An array of fire sensors which included an optical and ionization smoke sensor, a

chemical cell CO sensor, and Metal Oxide Semiconductor (MOS) sensors, was used to sample the diesel engine and fire source emissions. The mine fire detection experiments demonstrated the ability of a MOS sensor

with a bimodal response to NOx and products-of-combustion (POC) to respond to the onset of smoldering 

combustion in the presence of CO and POC particulates from a diesel locomotive. As part of an in-mine 

evaluation in an operating coal mine, the MOS NOx responsive sensor and an ionization smoke sensor was

demonstrated as a method to discriminate diesel emissions and cross-interference of H2 on a CO chemical cell 

fire sensor at a battery charging station. The reinforcement of mine fire sensor information with the use of 

multiple sensor types, such as an MOS sensor and ionization and optical smoke sensors, is shown to be important for nuisance alarm discrimination and early mine fire detection. 
An additional phase was the implementation of a select combination of fire sensors in an operating mine

to evaluate their capability to identify nuisance 

events such as battery charging and diesel emissions. 

To accomplish this, an operational mine was selected in which battery charging occurred daily and 

diesel equipment was moved occasionally. The interpretation of the data strictly in terms of alarm values set relative to clear air would lead to nuisance

alarms from non-open combustion in-mine events 

with isolated unimodal POC gas response sensors. A 

sensor with bimodal response to diesel emissions 

and open combustion would provide a measure of 

discrimination, but would not be advantageous for

discriminating other non-combustion signatures, 

such as H2 from a battery charging operation. In this 

latter situation a smoke particulate sensor would 

provide the discrimination. These inherent fire detection limitations associated with isolated fire sensors suggests the solution to mine fire discrimination 

from nuisance alarms could reside in the deployment

of multiple sensor types.

2 EXPERIMENTAL PROCEDURE 

Figure 1 shows a schematic of the section of the 

SRCM in which the mine fire experiments were

conducted. A diesel locomotive was positioned in BFigure 1. Plan view of a portion of the SRCM. 

Butt upwind of its intersection with Room 10 to 

supply diesel emissions to the ventilation current 

which was split at Room 10 for the coal combustion 

experiments, and was positioned at its intersection 

with Room 10 for the belt combustion experiments. 

For the belt combustion experiments the diesel exhaust was fed into Room 10 through a hose attached 

to the diesel. The exhaust end of the hose was directed at a vertical plate in Room 10 within 5 m of 

B-Butt to provide a well mixed diesel contaminant 

distribution at the first downwind sensor station in 

Room 10 located 36 m downwind of B-Butt. Room

10, in which the fire is located, has an average 

height and width of 2.0 m and 3.9 m, respectively. 

F-Butt has an average height and width of 1.9 m and 

4.5 m, respectively. For the experiments conducted, 

the average air quantity at the fire zone was 2.66 

m3

/s, and at the end of F-Butt was 4.73 m3/s. The 

increase in air quantity downwind of the fire zone 

was caused by leakage into F-Butt around brattices

shown along the ribs in figure 1 which block crosscuts connecting F-Butt and parallel airways. 

The three coal combustion experiments, numbered 74-76, utilized the heating of approximately 

14 kg of lumped coal with a diameter less than 5 cm 

in a 0.61 m square pan with embedded electrical 

strip heaters. The electrical resistive heating rate was 

increased slowly to a maximum rate of 2.4 kW to

produce conditions which would challenge the fire

sensors with an initially weak signature in the diesel

emissions background. The three conveyor belt section heating experiments, numbered 77-79, were 

conducted with the heating of a 0.53 m square belt 

section about 1.1 cm thick. The belt was mechanically attached to a 0.48 cm thick steel plate which 

was heated on the non-belt side with electrical strip 

heaters. The plate produced a uniform conductive 

heating of the belt. The maximum heating rate was

3.3 kW. 

The fire sensor types used for the experiments are 

listed in table 1. Sensor SA is an optical path smoke 

Table 1. Fire sensor types used. 

Sensor Type

SA Optical Smoke

SB Ionization Smoke

CO Electrochemical Carbon Monoxide 

MA, MB, MC MOS (MA, MB volatile organic compound (VOC); MC bimodal NOx , POC) 

sensor which operates at an infrared wavelength 

with a transmitter-receive separation of 9.25 m in 

Room 10, and 9.65 m in F-Butt. The ionization sensor SB, MOS sensors MA, MB, and MC, and the

chemical cell CO sensor are all diffusion mode point

sensors. Sensor MA is more sensitive to CO than 

volatile organic compounds (VOC), whereas MB is

more sensitive to VOC than CO. Duplicate sensors 

are positioned at S1, 18 m downwind from the fire, 

and at S2, 148 m downwind from the fire. At each 

sensor station a light obscuration monitor was positioned to determine the smoke obscuration. The light 

obscuration monitor consisted of an ordinary visible 

light source and a photovoltaic cell separated by one

meter to measure the optical attenuation by the air

transported smoke particulates. From the optical attenuation, the smoke optical density can be calcu-
lated. The sensor analog output data were collected 

with a data acquisition system at 2 s time intervals. 

3 RESULTS AND DISCUSSION 

For the data analysis, the CO alarm value was set to

a concentration rise of 5 ppm above ambient. The

alarm value for each smoke and MOS sensor was 

defined to be a ten standard deviation change in the 

signal from its measured clear air ambient value 

which occurred prior to the diesel emissions. For

sensors SA, SB, and MC the average ratio of the 

mean to standard deviation for the twelve data sets 

was 247, 388, and 86, respectively. These two orders 

of magnitude ratios indicate a relatively noise free 

signal prior to the detectable event. The response of 

the unimodal sensors CO, SA, and SB, and the bimodal sensor MC to diesel emissions and fire POC 

for the six combustion experiments in the presence 

of diesel emissions are evaluated relative to the first 

visual observation of smoke. The sensor-smoke lag 

time, defined to be the time of the fire sensor alarm, 

as defined for sensors CO, SA, SB, and MC at sensor stations S1 and S2, less the time of the first observation of smoke, is shown in tables 2 and 3 respectively. 

Tables 2 and 3 show that there are no false alarms 

associated with the use of sensor MC for fire detection in the diesel emissions background. However, 

sensor MC would not be able to distinguish fire 

POC from the H2 emitted at a battery charging station. The isolated use of sensor SB would result in 

false fire sensor alarms for each experiment at both 

sensor stations. Sensors CO and SA have mixed results as fire sensors in a diesel emissions background 

with no consistent pattern. The significant time difference in CO alarm time relative to first smoke observation time for the coal and belt experiments is 

due to the increased CO concentration in the diesel

emissions regime for the belt experiments as a result 

of the direct feed of diesel emissions into Room 10. 

This shows that alarms from isolated sensor types 

may not provide reliable fire detection alarms. For

this reason multiple fire sensor types should be 

evaluated simultaneously. 

To provide an interpretation of the sensor response to the mine emissions events for characterizing fire growth and the combustion stage, the degree 

and rate of response of the sensors to a given event 

needs to be considered in addition to the sensor

fixed alarm point. It is the sensor characteristic response that provides a utility for fire sensors that 

would not necessarily be considered for fire protection if only an individual sensor alarm point was

Table 2. Sensor-smoke lag time, seconds, at station S1*.

Experiment no.

(type)

CO SA SB MC OD 

74 (coal) -320 -365 -2664 71 213 

75 (coal) -873 335 -1821 311 1468

76 (coal) 285 57 -2359 235 747 

77 (belt) -3715 224 -2221 533 591 

78 (belt) -3100 -3109 -3045 664 632 

79 (belt) -2929 106 -3039 298 711 

Table 3. Sensor-smoke lag time, seconds, at station S2.*

Experiment 

no. (type) 

CO SA SB MC

74 (coal) 1394 71 -2138 394 

75 (coal) 2319 796 -1507 732 

76 (coal) 1864 819 -2011 378 

77 (belt) -2923 903 -2165 862 

78 (belt) -2216 -410 -2484 1040

79 (belt) -2295 1078 -2650 830 

*

A negative time elapse indicates a sensor false alarm produced

by the diesel emissions. 

considered. Figures 2 and 3 show the response of the 

fire sensors SA, SB, and MC at S1 and S2 for coal 

combustion experiment no. 75. The sensor values 

were normalized by the ambient value prior to the 

diesel emissions generation. A comparison of the response of the optical (SA) and ionization (SB)

smoke sensors at S1 and S2 in figures 2 and 3 for the 

diesel emissions only and the smoldering combustion region shows the ionization smoke sensor SB is

more responsive than the optical smoke sensor SA in 

the diesel emissions only region, whereas the optical 

smoke sensor is more responsive than the ionization 

smoke sensor in the smoldering combustion region. 

0

1

2

3

4

5

8:39 8:53 9:06 9:20 9:33 9:46 10:00 10:13 10:27 10:40

TIME

MC

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

1.1

SA, SB

DIESEL

SMOKE

FLAME

MC

SA

SB

Figure 2. Response at S1 of optical and ionization smoke 

sensors and MOS sensor to diesel emissions and coal combustion for experiment no. 75. 
0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

8:39 8:53 9:06 9:20 9:33 9:46 10:0010:1310:2710:40

TIME

MC

0.7

0.75

0.8

0.85

0.9

0.95

1

1.05

1.1

SA, SB

DIESEL

SMOKE

FLAME

MC

SA

SB

Figure 3. Response at S2 of optical and ionization smoke sensors and MOS sensor to diesel emissions and coal combustion 

for experiment no. 75. 

In the flaming coal combustion stage, the ionization 

smoke sensor is more responsive than the optical 

smoke sensor. The estimated travel time from S1 to 

S2 based upon the measured airflow of 2.05 m3

/s 

and 3.91 m3

/s for experiment no. 75 at the locations

shown in figure 1 is 373 s, which is 89 pct of the 

421s time difference in alarm times for MC. Sensor 

MC shows an expected characteristic signal decrease 

associated with the NOx component of the diesel

emissions, and a signal increase to the fire POC. 

The signal decrease is associated with oxygen adsorption on the semiconductor surface from the decomposed NOx. The disadvantage of sensor MC is 

its lack of quantitative precision when compared 

with CO sensors. Although MOS sensors are very 

sensitive to a wide spectrum of gases, they are not 

very species selective. 

Figure 4 shows for experiment no.75 at S1 the response of the CO sensor, and the volatile organic 

compound (VOC) sensitive MOS sensors MA and

MB to diesel emissions and coal combustion. There 

is a 5 ppm CO alarm at 9:29, which occurs in the

diesel emissions zone prior to energizing the strip 

heater elements. Sensors MA and MB show a measurable response coincident with the CO sensor response. Comparison with figure 2 shows this is in 

contrast with the lack of response of smoke sensors 

SA and SB at the time of increased CO from the diesel locomotive. Figure 4 shows that sensors MA and 

MB are no more discriminatory of combustion than 

is the CO sensor in the diesel emissions environment. An evaluation of the response of sensors MA

and MB at S1 for the three coal and three belt combustion experiments showed that sensor MA’s response is no earlier than the CO sensor response to 

smoldering combustion, whereas sensor MB, which 

is more sensitive to VOCs, responds as rapidly as

the CO sensor. For smoldering belt combustion with 

delayed CO emissions, sensor MB can respond earlier than the CO sensor. These different characteristic responses of MOS, smoke, and CO sensors demonstrate the utility of multiple sensor types for mine

fire nuisance event discrimination. 

The particulate emissions’ optical density, which 

is determined by particulate size and concentration, 

can be used as a benchmark for smoke sensor alarm 

points. A smoke optical density equal to 0.022 m-1 is 

the alarm value (Code of Federal Regulations, 2001) 

for a mine smoke sensor. Column OD in table 2 

show reports the time at which the smoke optical 

density equals 0.022 m-1

 as measured by the light 

obscuration monitor at sensor station S1 less the first 

smoke observation time. In each experiment the 

smoke optical density alarm value did not occur in 

the diesel emissions period prior to smoldering 

combustion. However, the negative values in table 2 

shows that the ionization smoke sensor SB alarmed 

prior to visible smoke particulates from the heated 

coal. This implies that smoke sensor SB alarm value 

in terms of a 10 S.D. change from ambient conditions is a more stringent smoke alarm value than an 

optical density of 0.022 m-1. At an alarm value of 

0.022 m-1, sensor SB was determined at S1 for the 

six experiments to be between 30 and 71 S.D. from 

its ambient value in clear air. To increase the alarm 

value definition of SB in terms of the number of 

standard deviations from clear air value to delay 

sensor SB alarm would not be an adequate solution 

to the problem, since an increased alarm level required to discriminate open combustion from nuisance events would never be known with any definitive certainty due to the diesel emissions variable 

optical density. This would apply to the other sensors exclusive of MC, which has a definite bimodal

response to differentiate diesel emissions from a fire 

signature. 

0

5

10

15

20

25

8:398:539:069:209:339:46

10:0010:1310:2710:40

TIME

CO, PPM

0

1

2

3

4

5

6

7

MA, MB

DIESEL

SMOKE

FLA

M

E

MA

MB

CO

MA, CO

MB

Figure 4. Response of CO sensor and sensors MA and MB

at S1 for experiment no. 75. 
At sensor station S2 the smoke optical density 

only exceeded 0.022 m-1 for experiment nos. 74, 77, 

and 78. The lower optical density for experiment

nos. 75, 76, and 79 was due to smoke dispersion 

over the entry cross-section and dilution from leakage around brattices. However, at S2, as was the 

case at S1, a definite alarm could be associated with 

MC’s bimodal response to the combustion generated 

smoke superimposed upon the diesel emissions. 

Figure 5 shows for experiment no. 75 the average

response of two CO sensors mounted near the roof 

and across the entry at S1, and the measured optical 

density at S1 for the coal combustion in the presence 

of diesel emissions experiment. A false CO alarm at 

9:29 in the diesel emissions only regime produced 

by the diesel locomotive occurs at a smoke optical 

density equal to 0.0031 m-1. The smoke optical density did not reach 0.022 m-1 until 10:08. As previously noted, the event at 9:29 was detected by VOC 

sensors MA and MB, but not detected by smoke

sensors SA and SB. Reliance upon a CO sensor in 

the presence of diesel emissions or other nuisance 

sources of combustion without interpreting either the 

shape of the signal response or the data supplied by 

complementary fire sensors would lead to the erroneous conclusion of the occurrence of a fire. This

particular CO signal increase is attributed to the diesel locomotive. 

The different response characteristics between 

smoke sensors SA and SB in the diesel and smoke

emissions as shown in figures 2 and 3 suggests a

combined signal as a possible metric for mine fire 

nuisance signal discrimination. Sensor SA, as an optical sensor, is more responsive to larger diameter

particles associated with smoldering combustion, 

than is the ionization smoke sensor SB, which is 

more sensitive to the particulate number concentration. One possible metric is the ratio of signal SB response to signal SA response. An analysis was made

of the characteristic response of the MOS sensor MC 

and the ratio SB/SA to diesel emissions and to open 

fire combustion POC. For this analysis each sensor 

signal was normalized by its clear air value. Figure 6 

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1

8:398:539:069:209:339:46

10:0010:1310:2710:40

TIME

OD, m-1

0

5

10

15

20

25

CO, PPM

DIESEL

SMOKE

FLA

M

E

CO OD

0

1

2

3

4

5

8:398:539:069:209:339:46

10:0010:1310:2710:40

TIME

MC

0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

SB / SA

DIESEL

SM

O

K

E

FLA

M

E

SB / SA

MC

Figure 6. Response of MOS sensor MC and ratio of

normalized ionization to optical smoke sensors at S1 for

coal combustion experiment no. 75. 

shows the response of the normalized signals MC 

and the ratio SB/SA to the clear air, diesel emissions, and coal smoldering and flaming stages for

coal combustion experiment no. 75. The observed 

pattern of a decrease in sensor MC due to the NOx is 

coincident with the decrease in the ratio SB/SA during the diesel emissions only regime. The observed 

occurrence of smoke from the coal combustion is associated with the increase in both the MOS sensor

MC and the ratio SB/SA above the clear air value of 

unity. Figure 7 shows a similar pattern for conveyor

belt combustion in the presence of diesel emissions. 

This sensor response pattern was found to occur for

all six experiments at sensor stations S1 and S2. The 

effect at S2 was less pronounced due to the dilution 

and dispersion of the POC. For experiment nos. 74-

0

0.5

1

1.5

2

2.5

3

8:308:438:579:109:249:379:51

10:0410:1810:3210:4510:5911:13

TIME

MC

0

1

2

3

4

5

6

7

SB / SA

DIESEL

SMOKE

FLAME

MC

SB / SA

79. 

Figure 5. Optical density (OD) and CO at S1 for experiment no. 75. 

Figure 7. Response of MOS sensor MC and ratio of

normalized ionization to optical smoke sensors at S1 for

belt combustion experiment no. 
79 the average lag time of a 20 pct increase in the 

signal ratio SB/SA at S1 relative to the first visual 

observation of smoke was 11 min. This is greater 

than the 6 min average lag time for sensor MC based 

upon the values in table 2. The selection of the

20 pct signal increase as a criterion is motivated by 

the noise in the sensors’ signal ratio. The noise is 

apparent from a comparison of the response of sensor MC with the ratio SB/SA in figures 6 and 7. A 

comparison of the individual sensor responses, SA 

and SB, in figure 2 shows that it is the extreme sensitivity of SA to fire POC which produces the strong 

variations in the ratio. Although sensor MC will respond to H2 from a battery charging operation in a

manner similar to its response to fire POC, the combination of sensors MC, SA, and SB could also be 

used to discriminate a battery charging operation 

from fire POC since the ratio SB/SA would not be

affected by the H2. This could indicate that the combined use of MC, SA, and SB would be suitable for 

discriminating diesel POC emissions and battery 

charging H2 emissions from open combustion. The

reinforcement of sensor information with the use of 

multiple sensor types is important for nuisance 

alarm discrimination and early mine fire detection. 

An evaluation of multiple sensors was conducted 

in an operating underground coal mine immediately 

downwind of a battery charging station. The sensors 

used for the evaluation, which included a CO sensor, 

ionization smoke sensor SB, and MOS sensors MA, 

MB, and MC, were located upwind of a regulator in 

intake air. A portable data acquisition system was

used to collect data at one-minute intervals. Interpretation of the data was based upon previously conducted sensor evaluation in the SRCM and the occasional presence of an observer during data retrieval 

and sensor maintenance. Figure 8 shows sensor response for one 24 hr period. The time period from 

1:00 PM to 5:00 PM in figure 8 can be identified as 

one complete battery charging time period. This is 

based upon the increase in the CO signal with no decrease in smoke sensor SB’s signal. The CO sensor 

response is the result of cross-interference from H2. 

Sensors MA and MB are also responsive to H2. Sensor MB is more responsive than MA to the nuisance

emissions from the battery charging. The absence of 

a coincident increase in sensor MC’s signal and a 

decrease in SB’s signal over the 24 hr period eliminates any possibility of open combustion. Prior to 

this event at 11:37 AM diesel emissions were detected by sensor MC as indicated by its rapid signal

decrease. Smoke sensor SB was not affected by the 

diesel emissions. 

Figure 9 shows the response of the CO sensor to a 

battery charging operation. At 9:45 and 9:46 AM

two gas samples were drawn by an observer at the 

CO sensor location. Analysis of the gas samples determined ambient CO less than 3 ppm, and H2 concentrations of 155 and 192 ppm. The in-mine indicated CO sensor value was 18 ppm. This

demonstrates the cross-interference effect of the CO 

on the chemical cell. 

0

2

4

6

8

1 0

1 2

1 4

1 6

1 8

2 0

2 :4 8

A M

3 :3 8

A M

4 :2 8

A M

5 :1 8

A M

6 :0 8

A M

6 :5 8

A M

7 :4 8

A M

8 :3 8

A M

9 :2 8

A M

T IM E

CO, PPM

B A TTER Y C H A R GIN G

Figure 9. CO sensor response to battery charging operation.

0

5

10

15

20

25

30

12:00

AM

3:21

AM

6:41

AM

10:03

AM

1:24

PM

4:44

PM

8:07

PM

11:28

PM

TIME

CO, PPM

0

0.5

1

1.5

2

2.5

3

3.5

VOLT

CO

MA

MB

MC

SB

4 CONCLUSIONS 

1. No false alarms occurred when MOS sensor 

MC was used to determine smoldering coal 

or mine belt section fires in diesel emissions

background. 

2. Use of the ionization smoke sensor would result in false alarms at both sensor stations for

the six experiments conducted. 

3. The ionization smoke sensor was more

responsive than optical smoke sensor in

diesel emissions regime than in smoldering

combustion regime. Figure 8. Sensor response to battery charging and diesel

emissions in an underground coal mine. 4. It is not practical to increase the smoke sensor alarm to accommodate diesel emissions, 
since the diesel emissions concentration is 

variable. 

5. Neither an individual CO alarm nor an individual smoke sensor alarm can distinguish 

open combustion from diesel emissions. 

6. Ratio of normalized ionization smoke sensor 

signal to optical smoke sensor signal was 

less than unity for diesel emissions, and 

greater than unity for smoldering combustion. 

Combination of an MOS NOx sensitive sensor 

and the ratio of normalized ionization smoke sensor 

signal to optical smoke sensor signal seems to be a 

possible method to not only discriminate open combustion from diesel emissions, but also to discriminate diesel emissions from H2 produced by battery 

charging which cannot be determined by a chemical 

CO sensor due to cross-interference. 

This research shows the significance of multiple 

fire sensors for mine fire nuisance event discrimination. The mission of NIOSH to protect the health 

and safety of mine workers is furthered by the exclusion of false fire alarms associated with in-mine 

nuisance emissions events, and the recognition of a 

fire signature in the presence of diesel emissions.

Although some sensor combinations may be redundant for one type of open fire nuisance emissions 

discrimination, they will be significant for another 

scenario of open fire nuisance emissions discrimination. The analysis of the sensor response characteristics demonstrates the need to develop a systematic 

approach based upon a set of algorithms to process 

the sensor data. One such methodology would be the 

use of neural analysis. 

REFERENCES 

Code of Federal Regulations, 30CFR, Parts 75.340 and 75.344. 

2001. Office of the Federal Register, National Archives 

and Standards Administration, U.S. Government Printing 

Office, Washington, D.C., July 1, 2001. 

Edwards, J.C., Franks, R.A., Friel, G.F., Lazzara, C.P., & 

Opferman J.J. 2001. Discriminatory mine fire source detection. In S. Wasilewski (ed.), Seventh International Mine 

Ventilation Congress; Proc., Cracow, Poland, Ch.91, pp. 

649-655 June 17-22, 2001. Research and Development 

Center EMAG. 

Panigrahi, D.C., & Ghose, A.K. 1999. Atmospheric 

monitoring systems in underground coal mines. J. of 

Mines, Metals & Fuels, 301-304.