Laboratory evaluation of smoke detectors for use in underground mines

Charles D. Litton * 

* Tel.: 4123866752; fax: 4123866595.

E-mail address: chl3@cdc.gov

National Institute for Occupational Safety and Health, Pittsburgh Research Laboratory/Disaster Prevention and Response Branch, Box 626, Cochrans Mill Road,

Pittsburgh, PA 15236, USA

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 to both 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 combustions. 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.

1. Introduction

1.1. 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 was intentionally disconnected because of

nuisance alarms. In another study [2], 273 smoke detectors were

examined by fire departments subsequent to the extinguishment

of residential fires that went undetected. Of these, 159 (59%) 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

destroy both life and 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 cutting. In mines, and to a

somewhat lesser degree in tunnels, dust is an ever-present

problem.

A significant level of research is being done 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 multi-signature alarm algorithms [9–11] offers

promise in many applications. But the use of these multi-sensor

approaches is 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

base, 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 potentially 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.

1.2. The sensors

The prototype smoke detector, the first sensor that was

evaluated during this study, utilized the responses of both an

ionization chamber and an optical scattering chamber to

discriminate between nuisance sources that are not fire-related.

Previous research [14–16] has described this approach and

presented the relevant data using discrete ionization chambers

and optical scattering chambers. Briefly, the prototype 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 151 and

301. Fig. 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.

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

chamber (bottom) used in the prototype detector.

A photograph of the fabricated

prototype, opened to show the locations of the ionization and

scattering chambers, is shown in Fig. 2.

Fig. 2. Photograph of prototype smoke detector evaluated during this study.

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The commercial smoke detector, the second sensor that was

evaluated in these experiments, was a photoelectric type that

measures light scattered at a forward angle of 451. 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 s to sample the surrounding

air for a period of 5 s. Within this 5 s interval, the air is flowed

through a 32 mm 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 5 s sampling interval is shown in

Fig. 3. The experiments were conducted to assess the reproducibility of previous experiments and thus the reliability of using

either the prototype or commercial sensor for early-warning fire

detection.

2. Experimental

Combustion experiments to produce smoke particles were

conducted in the configuration shown in Fig. 4 and described

in more detail in Ref. [17], where smoke particles from either

flaming or smoldering combustion are generated in a cubical

enclosure measuring 0.30 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 1.483 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 tube 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.

For diesel exhaust particles, the experimental system in which

the tests were conducted, known generically as a dust box, is

shown in Fig. 5 and described in greater detail in Ref. [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.

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 what amounts to 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.

Fig. 3. Schematic illustrating the flow of air during the 5 sec sampling period of the commercial smoke sensor.

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3. Results and analysis

3.1. 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

,

although in the data and analysis that follow, particular attention

was paid to mass concentrations o10 mg/m3

, since it is within

this mass concentration range that early-warning fire detectors

generally alarm. The basic data acquired for the prototype sensor

are summarized as averages in 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

715–20% of the average reported. For each test, the ion chamber

and angular scattering signals were found to vary linearly with the

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well-mixed aerosol mass concentrations in the smoke box. The

resultant sensitivities, in V/(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

r

2

-values greater than 0.90 and typically in the range 0.95–0.98. 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 photodetectors, also in volts, represents the changes in signal at 151 and

301, V(15) and V(30), respectively. The aerosol mass concentration

in the smoke box, M, is in mg/m3

.

Fig. 4. Schematic of the smoke box and sample chamber in which the combustion experiments were conducted.

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 10 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 to 10 mm) is

approximately 0.

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 Fig. 6 result,

indicating that there are definite correlations. For the ionization

chamber, this correlation is given by

CEV=M 1⁄4 0:021451⁄2CEV=Vð15Þ 1⁄2

2=3 (1)

and for the optical scattering at 151, by

Vð15Þ=M 1⁄4 0:02145=1⁄2CEV=Vð15Þ 1⁄2 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 301. 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 Fig. 6 are the data

obtained from previous experiments.

Fig. 5. Schematic (A) and photograph (B) of the dust box where the response to diesel exhaust particles was measured.

Table 1

Measured sensitivities, V/(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 151 and 301 for the prototype

smoke detector

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

Sensitivities for each combustion source represent the average of 2–4 separate

experiments.

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

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3.2. 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, Fig. 7 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 151 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 due to the

much smaller particle diameters generated during the flaming

combustion mode.

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

commercial smoke detector alarmed at an average value of 0.162 V

for the 151 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 V to a maximum value of 1.07 V.
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)

Fig. 6. Plots of the ionization chamber and 151 optical scattering sensitivities as a function of their ratio for the prototype smoke detector. Also shown are data from

previous experiments.

-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

Fig. 7. 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 (DCEV), the 151

optical scattering response (DI(15)), and the average smoke particle mass

concentrations at the alarm point of the commercial detector to smoldering fires

Combustible sample CEV (V) V(15)

(V)

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

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The average signals from the 151 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 is responsible for commercial smoke detector’s

poor response to the flaming fires.

4. 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 both very

small particles, such as those from diesel exhausts, because it

operates on the principle of light scattering and to the larger

particles as a result of the flow and filter incorporated into the

detector warrant further test and evaluation under typical mine

conditions.
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