EVALUATION OF SMOKE DETECTORS FOR USE IN UNDERGROUND MINES 

C. D. Litton, NIOSH, Pittsburgh, PA 

ABSTRACT 

Laboratory experiments were conducted to determine the 

responses of a prototype smoke detector and a commercially available 

photoelectric smoke detector to smoke particles generated from 

various combustion sources. The prototype smoke detector combines 

optical scattering measurements with ionization chamber 

measurements in order to reduce/eliminate nuisance alarms due to the 

presence of airborne dusts or diesel exhaust particles. The 

commercially available smoke detector is designed for use in harsh 

environments where airborne dust represents a major problem due 

both to nuisance alarms and detector contamination. In the 

experiments, the responses of the two detectors were measured when 

exposed to smoke particles from the exhaust of a diesel engine and 

from a variety of fire sources, including wood, coal, styrene butadiene 

rubber, and No. 2 diesel fuel. For the solid fuels, data were obtained 

for both smoldering and flaming combustion. This report describes the 

experiments, their results, and the use of these results as they apply to 

early-warning fire sensors capable of the rapid and reliable detection of 

fires in atmospheres that may or may not be contaminated by either 

airborne dust or the products produced from diesel engines. 

Subsequent to these laboratory experiments, six smoke detectors were 

installed in an underground limestone mine for further testing and 

evaluation. 

DISCLAIMER: The findings and conclusions in this report have not 

been formally disseminated by the National Institute for Occupational 

Safety and Health and should not be construed to represent any 

agency determination or policy.

INTRODUCTION 

Background 

Fire sensors that detect the smoke and gases produced during 

the early stages of developing fires are often compromised by the 

presence of background levels of aerosols or gases that mimic the 

signatures of the developing fires, often resulting in frequent false, or 

nuisance, sensor alarms. When this frequency is high, the tendency is 

to either ignore sensor alarms, or to de-energize the sensors, with the 

potentially catastrophic consequence that an actual fire is not detected. 

For instance, previous surveys of installed residential smoke detectors 

(1), indicated that nearly 20% of the detectors did not have functioning 

power sources, and of these, about one-third were intentionally 

disconnected because of nuisance alarms. In another study (2), 159 of 

273 smoke detectors (59%) examined by fire departments subsequent 

to the extinguishment of residential fires that went undetected were 

found to be disconnected from the power source. Nuisance alarms 

can occur in industrial settings, as well, with similar actions and 

consequences--real alarms that may be ignored or sensors that are 

disconnected from their power source--resulting in fires that cost lives 

and destroy property. A recent workshop (3) highlighted the problems 

associated with nuisance alarms in aircraft cargo areas and critical 

telecommunications systems, and stressed the need to develop 

improved fire sensing systems and test procedures for installed fire 

detection systems. Fire detection in underground mines and tunnels is 

often compromised by exhaust products from diesel engines or other 

vehicles, or by routine procedures, such as welding or flame cutting. In 

mines, and to a somewhat lesser degree in tunnels, dust is an everpresent problem. 

A significant level of research is being conducted to resolve some 

of these problems. For smoke, efforts continue to more accurately and 

completely define the properties of smoke produced from different 

sources (4-7) and to develop improved techniques for smoke 

measurement (8). Characterizing the signatures of interfering sources 

using multi-sensor arrays coupled with neural networks or other multisignature alarm algorithms (9-11) offer promise in many applications. 

However, the use of these multi-sensor approaches are generally 

application-specific in that different applications may require different 

sensors and the necessary algorithms can vary significantly from one 

application to the next. In some of these approaches, it is not only the 

relative signals from different sensors, but also the manner in which 

these signals vary with time, that allow for the discrimination. 

However, incorporating time into the detection process can delay the 

alarm and thus be detrimental to the early-warning capability of the 

system. In underground mines, multi-sensor approaches and simpler 

gas ratio techniques (12-13) have also been used with varying degrees 

of success. In general, the use of multi-sensor packages and software 

to process the signals and make decisions increases both the 

complexity and the cost of the system, not only in terms of initial 

expense, but also in terms of system maintenance and sensor 

replacement. 

One alternative to these approaches is the development of 

simple, stand-alone fire sensors that capitalize on the differences 

between common, interfering aerosol and/or gas backgrounds and 

those that result from developing fires so that the discrimination occurs 

via the sensor and its associated electronics rather than from a more 

complex processing algorithm. This paper describes the laboratory 

evaluation of two candidate smoke sensors for the detection of fires in 

underground mines, where major background sources are dust and the 

emissions from diesel engines that are used routinely in day-to-day 

mining operations. 

The Sensors 

The prototype smoke detector utilizes the responses of both an 

ionization chamber and an optical scattering chamber to discriminate 

between fires and nuisance sources that are not fire-related. Previous 

reports (14-16) have described this approach and presented the 

relevant data using discrete ionization chambers and optical scattering 

chambers. Briefly, the prototype smoke detector consists of an 

ionization chamber, typical in design to those used in commercial 

smoke detectors, where smoke particles are sensed due to the 

depletion of ions within the air space between two electrodes; and an 

optical scattering chamber where the collimated light beam from a 

laser diode is scattered by smoke particles into silicon photo-detectors 

at forward angles of 15° and 30°. Figure 1 is a schematic of the two 

chambers. In this study, a prototype instrument was fabricated that 

combined both chambers into one package, together with improved 

electronics for storage and processing of the data. A photograph of 

the fabricated prototype, opened to show the locations of the ionization 

and scattering chambers, is shown in Figure 2. 

The commercial smoke detector is a photoelectric type that

measures light scattered at a forward angle of 45°. This detector is 

designed to operate in harsh environments containing dusts and water 

mists that can interfere with and degrade the performance of typical 

smoke detectors. To do this, the detector uses an internal fan that is 

activated every 35 seconds to sample the surrounding air for a period 

of five seconds. Within this five second interval, the air is flowed 
 

 

 

through a 32 μm filter to remove the dust particles and water droplets 

that may be present. The air then flows through the scattering 

chamber where air is sampled for smoke particles before it exhausts to 

the outside air. Internal sensors detect clogged filters that are easily 

replaced or signal that the fan is malfunctioning. While this sensor 

contains no capability to discriminate nuisance particles from smoke 

particles, it uses flow through a filter to eliminate the dust and it uses 

light scattering which is relatively insensitive to the very small particles 

from diesel exhausts, thus reducing the frequency of alarms from these 

nuisance sources. A schematic of this sensor showing the flow of air 

and particles during the five second sampling interval is shown in 

Figure 3. Experiments were conducted to assess the reproducibility of 

results and the reliability of using either the prototype or commercial 

sensor for early-warning fire detection. 

Figure 1. Schematic of the ionization chamber (top) and the optical 

scattering chamber (bottom) used in the prototype detector. 

Figure 2. Photograph of prototype smoke detector evaluated during 

this study. 

Figure 3. Schematic illustrating the flow of air during the five second 

sampling period of the commercial smoke sensor. 

Experimental 

Combustion experiments to produce smoke particles were 

conducted in the configuration shown in Figure 4 and described in 

more detail in reference (17). Smoke particles from either flaming or 

smoldering combustion were generated in a cubical smoke chamber 

measuring 0.32 m along each edge and then flowed into a standard UL 

217 smoke box (18) through a variable-orifice iris that controlled the 

rate of aerosol accumulation within the smoke box. Inside the smoke 

box, three of the commercial smoke detectors were placed on a 

platform and two small internal fans were used to mix the incoming 

smoke particles to produce a uniform distribution throughout the 

chamber. The optical density of the aerosol was measured over a 1.48 

m optical path using an incandescent lamp and a standard photocell 

with a peak response at a wavelength of 546 nm and a spectral 

response matching the spectral response of the human eye. During 

the experiments, smoke particle samples were continuously extracted 

through a metal sample port inserted into the top of the smoke box 

very close to the location of the three commercial sensors and then 

flowed to three of the prototype smoke detectors. In this configuration, 

data were obtained for flaming No. 2 diesel fuel (a small pool flame), 

flaming coal, flaming wood, flaming styrene-butadiene rubber (SBR), 

smoldering coal, smoldering wood, and smoldering SBR. In a 

subsequent series of experiments, a Model 8520 DustTrak Aerosol 

Monitor, using a PM2.5 nozzle, was added to this experimental system 

along with a six-angle optical scattering module operating at a 

wavelength of 632.8 nm (see Figure 5 for schematic of the optical 

scattering device). 

For diesel exhaust particles, the experimental system in which the 

tests were conducted, known generically as a dust box, is shown in 

Figure 6 (see Appendix) and described in greater detail in Reference 

(19). Briefly, dusts or diesel exhaust particles are dispersed near the 

top of the dust box, allowed to mix thoroughly and then fall via gravity 

coupled with a small, imposed flow. Samples of diesel exhaust 
 

 

particles are extracted through 10 mm cyclones near the bottom of the 

dust box at nominal flow-rates of 2 lpm and flowed to three prototype 

smoke detectors. In this configuration, data were acquired for particles 

produced from the exhaust of a diesel generator under different load 

conditions 

Figure 4. Schematic of the smoke box and sample chamber in which 

the combustion experiments were conducted. 

Figure 5. Schematic of the six-angle optical scattering device. 

During the diesel exhaust experiments, a Tapered Element 

Oscillating Microbalance (TEOM) (20) was used to continuously 

measure the mass concentrations of aerosol. In the TEOM, a small 

filter is mounted onto a hollow tuning fork vibrating at a fixed 

frequency. Particles in the flow through this filter are deposited on the 

filter increasing the filter mass. As the filter mass increases, the 

frequency of vibration decreases proportionally so that the change in 

mass due to accumulation of particles on the filter is measured as a 

function of time. The rate of change of the filter mass (due to smoke 

particles) divided by the volumetric flow rate through the filter yields the 

average mass concentration. 

RESULTS AND ANALYSIS 

Experiments Using Only the Prototype Smoke Detector 

Because of their simplicity, the combustion experiments using the 

UL 217 smoke box could be conducted quickly resulting in a large 

number of experiments so that several tests under identical conditions 

could be used to assess the reproducibility of the data and the 

variations that occurred from one test to the next. In general, 

combustion aerosol mass concentrations varied over the range from 

roughly 0.5 mg/m3

 to approximately 30 mg/m3. In the data and analysis 

that follow, particular attention was paid to mass concentrations < 10 

mg/m3

, since it is within this mass concentration range that earlywarning fire detectors generally alarm. The basic data acquired for the 

prototype sensor are summarized as averages in the following Table 1, 

where the averages represent measurements from typically 2 to 4 tests 

for each combustion source and combustion mode. It is also worth 

noting that, although differences for one source or mode, from one test 

to the next, did occur, these differences were generally within ± 15-

20% of the average reported. For each test, the ion chamber and 

angular scattering signals were found to vary linearly with the wellmixed aerosol mass concentrations in the smoke box. The resultant 

sensitivities, in volts per mg/m3

, were defined to be the slopes from 

linear regressions of the signals as functions of the mass 

concentrations. In general, the linear regression analyses yielded r2

-

values greater than 0.90 and typically in the range of 0.95 to 0.98. In 

the table, the response of the ionization chamber is given by the 

quantity CEV, in volts, corresponding to the change in potential of the 

floating, collection electrode. The response of the photo-detectors, 

also in volts, represent the changes in signal at 15° and 30°, V(15) and 

V(30), respectively. The aerosol mass concentration in the smoke box, 

M, is in mg/m3

. 

As discussed in a previous paper (14), it is convenient to look at

the ratios of the ionization chamber responses to the optical scattering 

responses as a means for discriminating between fire smoke particles 

and diesel exhaust particles. These ratios are displayed in Table 2, 

where the ratio, CEV/V(15), for diesel exhaust particles is more than a 

factor of ten greater than the average ratio for flaming combustion 

particles and almost a factor of 35 greater than the average ratio for 

smoldering combustion particles. It is worth noting at this point that 

from previous data (21) the response of the ionization chamber to dust 

particles (typically those in the respirable range from about 0.80 μm to 

10 μm) is approximately zero. 

When all of the data for both CEV/M and V(15)/M are plotted as a 

function of the ratio, CEV/V(15), the curves of Figure 7 result, 

indicating that there are definite correlations. For the ionization 

chamber, this correlation is given by the expression: 

 CEV/M = 0.02145 [CEV/V(15)]2/3 (1) 

and for the optical scattering at 15°, by the expression: 

 V(15)/M = 0.02145/[CEV/V(15)]-1/3 (2) 

A similar correlation (not shown) also exists for the ratio of 

ionization chamber response to the response of the optical scattering 

at 30°. These correlations with ratios are important not only because 

they provide a clear mechanism for determining if the particles are 

produced from a fire or from a diesel engine but also because they can 

be used to calculate mass concentrations, surface area 

concentrations, and average particle diameters as outlined in a 
previous report (14). Also shown in Figure 7 are the data obtained 

from previous experiments, labeled FSJ Data (2002). 

Table 1. Measured sensitivities, volts/(mg/m3

), for diesel exhaust 

particles and various combustion aerosols using the bipolar ion 

chamber with floating collection electrode and the dual angle scattering 

module at 15° and 30° for the prototype smoke detector. Sensitivities 

for each combustion source represent the average of 2 to 4 separate 

experiments. 

Aerosol Source CEV/M V(15)/M V(30)/M 

Diesel Exhaust 0.455 0.0047 Not Measured 

Flaming

No. 2 Diesel Fuel 0.0778 0.01056 0.0020 

Pittsburgh Seam Coal 0.0796 0.0115 0.00267 

SBR 0.0934 0.01095 0.0023

Douglas Fir 0.1270 0.00976 0.00136 

Smoldering

Pittsburgh Seam Coal 0.0466 0.0131 0.0041 

SBR 0.0426 0.0138 0.0041

Douglas Fir 0.0313 0.0200 0.0051 

Table 2. Sensitivity ratios for the three types of aerosols measured 

during these experiments 

Aerosol Source CEV/V(15) CEV/V(30) 

Diesel Exhaust 98.2 Not Measured 

Flaming Combustion 9.17 53.0 

Smolder Combustion 2.81 9.64 

Sensitivities vs CEV/V15

0.001

0.01

0.1

1

0.1 1 10 100 1000

CEV/V15

CEV/M or V15/M

CEV/M Data Regression Fit V15/M Data Regression Fit FSJ Data (2002) FSJ Data (2002)

Figure 7. Plots of the ionization chamber and 15° optical scattering 

sensitivities as a function of their ratio for the prototype smoke 

detector. Also shown are data from previous experiments. 

Experiments Using Both the Prototype and the Commercial 

Smoke Detector 

Because the commercial smoke detector was not available for the 

initial experiments conducted using only the prototype smoke detector, 

a second series of experiments were conducted and simultaneous 

data acquired for both detectors. This series of experiments used 

combustion sources and modes identical to those used in the initial 

series of experiments. 

In general, the data for the commercial smoke detector tested 

indicated that the detector was very responsive to particles from the 

smoldering combustion mode, not responsive to the diesel exhaust 

particles, and either not responsive or marginally responsive to 

particles from the flaming combustion mode. To demonstrate the 

response of the commercial smoke detector to particles from both the 

smoldering and flaming modes, Figure 8 is a plot of the response of 

this sensor to a typical experiment using wood as the combustible 

sample, along with the responses of the ionization chamber and the 

15° optical scattering detector from the prototype smoke detector. The 

response during the later stages of the flaming wood fire occurred after 

flaming had ceased and the combustion had returned to a smoldering 

mode. For data obtained during the flaming combustion mode, the 

superior response of the ionization chamber is clearly evident. From 

the data presented in a subsequent section differences in sensor 

 

response are due to the smaller particle diameters generated during 

the flaming combustion mode compared to the larger particle 

diameters produced in the smoldering combustion mode. 

For all of the data for the smoldering combustion mode, the 

commercial smoke detector alarmed at an average value of 0.162 volts 

for the 15° optical scattering signal and an average smoke particle 

mass concentration of 11.0 mg/m3

. The average value of the ionization 

chamber signal at the commercial detector alarm varied from a low 

value of 0.22 volts to a maximum value of 1.07 volts. The average 

signals from the 15° angular scattering and ionization chamber at the 

commercial smoke detector alarm are shown in Table 3. It is worth 

noting that in the flaming combustion mode experiments the maximum 

observed mass concentration never exceeded 8.0 mg/m3

, and it is 

believed that the combination of these lower mass concentrations 

coupled with the smaller particle diameters are responsible for 

commercial smoke detector’s poor response to the flaming fires. 

-0.5

0

0.5

1

1.5

2

2.5

0 200 400 600 800 1000 1200

Time (seconds)

Sensor Response (volts)

Ion

Optical

Commercial Detector

Smoldering Wood Flaming Wood

Figure 8. Responses of the ion and optical chambers of the prototype 

smoke detector and the alarms of the commercial smoke detector to 

both smoldering and flaming wood smoke. 

Table 3. Average values of the prototype ionization chamber response 

(ΔCEV), the 15° optical scattering response (ΔI(15)), and the average 

smoke particle mass concentrations at the alarm point of the 

commercial detector to smoldering fires. 

Combustible Sample CEV 

(volts) 

V(15) 

(volts) 

Mass 

Concentration 

(mg/m3

) 

Pittsburgh Seam Coal 1.07 0.136 12.6 

Douglas Fir 0.28 0.200 8.9 

Styrene Butadiene Rubber 0.22 0.182 10.3 

Angular Scattering and Particle Size 

Aerosols produced from combustion processes usually appear in 

the form of aggregate particles with smaller, primary particles linked 

together to form irregular shapes that are fractal-like in appearance 

and amenable to relatively simple analyses to determine their physical 

characteristics. To determine if the responses of the commercial 

smoke detector to both flaming and non-flaming fires could be 

attributed to differences in the particle size and shape of the smoke 

produced, a subsequent series of experiments were conducted using 

the six-angle optical scattering device shown in Figure 5, the ionization 

chamber of the prototype smoke detector, and the Model 8520 

DustTrak aerosol monitor operating in the PM2.5 mode. In these 

experiments, data were analyzed to produce an average dimension for 

the smoke particle aggregates, the radius of gyration, denoted by RG; 

the average diameter of the primary particles forming an aggregate, dP; 

and the relative angular scattering sensitivities, in volts per mg/m3

. 

Details of the analysis can be found in References 15 and 21. 

For simplicity, data are presented only for experiments for flaming 

and smoldering Douglas Fir. Figures 9 and 10 show the angular 

sensitivities for flaming and smoldering Douglas Fir, respectively. 

Comparing the two figures, it is found that the sensitivity to smoke 

produced from the smoldering fires is roughly a factor of 2 to 3 greater 

than the sensitivity to smoke from the flaming fires. This would mean 

that a much higher flaming smoke concentration would be required for 
 

an angular scattering smoke detector, such as the commercial smoke 

detector, to alarm at some pre-set voltage—precisely the behavior 

observed in the previous experiments. In addition, for a given source 

of particles the relative differences between the angular scattering 

sensitivities can be used to calculate the values for RG and these 

values coupled with the response of the ionization chamber to yield the 

primary particle diameters, dP. These analyses are shown in Figures 

11 and 12 for both flaming and smoldering combustion. From Figure 

11, it can be seen that the smoldering case generates particles with a 

larger radius of gyration than the flaming case. From Figure 12, the 

primary particle diameters produced from smoldering are also much 

larger than those produced from flaming. Both the larger primary 

particle diameters and the larger radii of gyration appear to be major 

factors that account for the more intense scattering by particles 

produced from smoldering combustion. Additional analysis similar to 

that reported previously (22) indicates that the particles produced from 

smoldering have a much higher volatility and lower carbon content 

resulting in significantly higher scattering with an albedo that is roughly 

1.5 to 2.0 times higher than the albedo from particles produced from 

flaming combustion. 

Angular Sensitivities for Flaming Wood

0

0.05

0.1

0.15

0.2

0.25

0.3

0 200 400 600 800 1000 1200 1400

Time, seconds

Volts/(mg/m3)

V15/M V22.5/M V30/M V45/M

Figure 9. Angular sensitivities to smoke from flaming Douglas Fir. 

Angular Sensitivities for Smoldering Wood

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0 200 400 600 800 1000 1200

Time, seconds

Volts/(mg/m3)

V15/M V22.5/M V30/M V45/M

Figure 10. Angular sensitivities to smoke from smoldering Douglas 

Fir. 

In-Mine Installation 

In October 2007, six of the commercial smoke detectors were 

installed in an underground limestone mine. This particular mine is 

relatively young and the underground workings relatively compact, so 

that the underground areas to be protected are all relatively close to 

each other. The six detectors were located according to the diagram 

of Figure 13 and connected to a central control pane, shown in Figure 

14, which was located in the electrical room. The outputs of the 

detectors were monitored continuously and any alarms or malfunctions 

recorded by the control panel software, which then reset the detectors 

automatically. To-date, the system has recorded one detector alert 

due to clogging of the inlet filter on the detector. Not long after the 

initial installation, the main electrical line connecting four of the smoke 

detectors to the central control panel was severed by mining 

equipment resulting in the loss of 4 of the 6 detectors. However, the 

remaining two sensors continued to function properly without any 

alarms or malfunctions. 

Radii of Gyration

0

50

100

150

200

250

300

350

400

450

500

0 100 200 300 400 500 600 700 800 900 1000

Time, seconds

Radius, nm

Smoldering Wood Flaming Wood

Figure 11. The radii of gyration, RG, for both smoldering and flaming 

Douglas Fir. 

Primary Particle Diameters

0

10

20

30

40

50

60

0 100 200 300 400 500 600 700 800 900 1000

Time, seconds

Diameter, nm

Smoldering Wood Flaming Wood

Figure 12. Primary particle diameters for smoldering and flaming 

Douglas Fir.

Approximately two months following the initial installation, the 

severed line was repaired and the system restored to operation only to 

have the line severed approximately one day later. A subsequent visit 

found that the central control panel had been rendered inoperative due 

to penetration by massive quantities of dust. The control panel was 

returned to the Pittsburgh Laboratory, refurbished with improved seals 

to reduce dust penetration, and then re-deployed in the mine. The 

system has now remained operational for ~3 months without any major 

problems or malfunctions. The numbers of alarms or system warnings 

will be collected and analyzed during the next visit and it is expected 

that the system will remain installed throughout the upcoming year and 

upgraded with the addition of 4 to 6 additional smoke detectors. 

CONCLUSIONS 

The results of this study indicate that the prototype smoke 

detector fabricated to combine both the ionization chamber and the 

optical scattering chamber functions as expected. The responses of 

the two components are similar to the responses previously measured 

as separate components. The utilization of the ratio of ionization 

chamber signal to optical scattering signal shows potential for use in 
 

 

the discrimination of very fine particles, such as those from diesel 

exhausts, and very coarse particles, such as mine dusts. The 

commercial smoke detector showed adequate response to smoldering 

combustion, but did not exhibit good response to flaming fires. 

However, the potential for the detector to be insensitive to very small 

particles, such as those from diesel exhausts and flaming fires, 

because it operates on the principle of light scattering warrants further 

test and evaluation under typical mine conditions. In addition, the 

lifetimes of the filters used in the commercial smoke detectors need 

further evaluation for their adequacy. The in-mine evaluation of the 

smoke detection system is expected to continue for at least another 

year. 

Figure 13. Diagram showing the location of smoke detectors in the 

underground limestone mine. Air flows down the slope and is 

exhausted through the exhaust fan shaft. Intervening flow patterns are 

ill-defined. 

Figure 14. Photograph of the central control panel used for the inmine installation of smoke detectors. The control panel measures 

161⁄8” x 141⁄2” x 51⁄2” and can accommodate up to 99 individual smoke 

detectors. 

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APPENDIX 

“A” “B”

Figure 6. Schematic (A) and photograph (B) of the dust box where the response to diesel exhaust particles was measured.