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Fire detector systems with ‘distributed intelligence’ the pulse polling system
Fire Safety Journal, 6 (1983) 225 - 231
225
Fire Detector Systems with 'Distributed Intelligence' The Pulse Polling System R. VON TOMKEWITSCH Siemens AG, Munich (F.R.G.)
SUMMARY
Well over a million fire detectors are currently in use in the Federal Republic o f Germany. Provided they are correctly installed and efficiently maintained, they detect fires reliably at a very early stage. A t the present time, the false alarm rate equals about 1% o f the number o f installed detectors per annum. This false alarm rate must be at least proportionately reduced as further detectors are installed. Since it is scarcely possible to improve tried-and-tested detector designs, the employm e n t o f higher-grade detector signal processing methods suggests itself. However, 'more intelligent" detector signal processing using microprocessors calls for an entirely new fire detection system structure: detectors which independently 'decide' whether an alarm criterion is m e t and then initiate an alarm are replaced by sensors which continuously transmit their measured values to the 'intelligence' panel for evaluation. Passive panels which simply receive alarm signals from activated detectors and indicate these or transmit them to the fire brigade are replaced by active processors using permanently improved algorithms for the detection o f real fires. A structural change o f this type is possible provided the positive -- and the customary -characteristics o f the conventional technique are not lost, viz. two-wire lines between detector and panel, simple installation and handling, easy detector replaceability, low cost, etc. The pulse detector technology is described in detail; it combines the simplicity o f conventional fire detection systems with new characteristics, e.g. identification o f individual detectors, p e r m a n e n t functional check o f all connected detectors, automatic notification o f 0379-7112183/$3.00
maintenance requirement prior to a slowly developing fault (e.g. such as that caused by corrosion or contamination), uniform response sensitivity unaffected by drifting from the operating points o f the detectors and, above all, greater protection against false alarms.
INTRODUCTION
In order to distribute intelligence one must take for granted that there is intelligence, or that it is necessary. In the case of fire protection systems there are three functions which can be described as needing a certain 'intelligence' or, to put it in more technical terms, which require data processing: (1) processing of signals from automatic fire detectors; (2) raising of alarm in the event of fire, especially if data such as operation plan data and counter-measures are to be indicated automatically, depending on the location of the fire; (3) automatic initiation of defence measures, such as moving the fire fighting apparatus into action, switching on escape route indicators, closing fire protection doors, and opening smoke outlets. As the meeting at which this paper was presented was concerned with automatic fire detection, the discussion below will refer particularly to the first function, the processing of signals from automatic fire detectors.
WHY MORE INTELLIGENCE? In the Federal Republic of Germany there are more than one million automatic fire detectors in operation. These detectors, if competently installed, have for more than 30 © Elsevier Sequoia/Printed in The Netherlands
226
years reliably detected the outbreak of fire in its initial phases. Why is the question of 'distributed intelligence' being raised at the present time? Well, primarily more intelligence is needed. Early warning fire detectors, especially smoke detectors, are sensitive measuring devices. They can also be put into alarm operation by environmental factors. Of course, all producers of fire detectors make rigorous efforts to exclude false alarms in their basic design. This has been achieved up to now by a deterministic approach: each false alarm has been associated with a probable cause -- such as contamination, insects, influence of temperature, wind, humidity, corrosion, strikes of lightning, electromagnetic influence or smoke-like symptoms, such as vapour from welding operations, etc. When certain causes of false alarms accumulated, the detectors were improved with respect to their construction and circuitry in order to reduce these influences. Thanks to these methods, and to experience gained in the development of automatic fire detectors over a period of four decades, false alarm rates of 1% have been achieved. In other words, 100 installed detectors produce, on average, only one false alarm per year. False alarm rates can be below this level in the case of high-quality, well-serviced detectors installed in clean rooms; however, the rates can be exceeded to a considerable e x t e n t under unfavourable conditions of application. In the view of fire brigades and users, the false alarm rates should be further improved to an extent corresponding to the increased distribution of automatic fire detectors, if false alarms are n o t to become a problem. If a further reduction of these false alarm rates by at least one order of magnitude is aimed at, new methods will have to be applied. Since there is hardly anything about the detectors which might be improved, then it follows t h a t the approach should be through improved evaluation methods of detector signals and through more suitable algorithms for distinguishing false alarms from real ones. This higher quality signal processing means 'more intelligence'. WHY DISTRIBUTED INTELLIGENCE?
In conventional fire detection systems it has been up to the detectors to decide
whether the local concentration of the fire characteristics justify a fire alarm. The 'intelligence' provided for this decision is rather modest: heat detectors evaluate the rise in temperature, and smoke detectors, in general, check only whether the smoke concentration exceeds a certain threshold value. The control panel can contribute to the reduction of false alarms by interrogating twice a detector sending out an alarm (socalled alarm repetition) and by transmitting an alarm to the fire station only if two neighbouring fire detectors respond (so-called dual line or dual detector dependency). These logical combinations of detector signals -already well k n o w n - - have recently been con° sidered by the VdS (German Association for the approval of fire detectors) as requirements to fulfil the specifications for a 'fire detection system with increased reliability'. They can already be considered as the beginning of a 'distributed intelligence', since the detectors evaluate the local concentration of the fire characteristic, whereas the control panel surveys the duration and local expansion of the incident. The probability of an alarm due to electromagnetic influence or to the closely restricted occurrence of an error characteristic is reduced in that way. It should be stated here that the only formal accomplishment of these measures does not guarantee their success. If the period of time from the beginning of the fire outbreak up to its detection is not to increase considerably, the n u m b e r of detectors per surveillance area should be duplicated in the case of a dual detector dependency. On the other hand, if this combination is to contribute to the reduction of false alarms due to errors, the detectors so combined should be installed at the furthest possible distance from each other. The protective value of a fire detection system based on 'distributed intelligence' as described above, therefore, depends to a great extent on its optimal design.
E V O L U T I O N A R Y J U M P BY T H E MICROPROCESSOR
It is well known t h a t the advent of the microprocessor has reduced the price at which 'technical intelligence' can be realized. New means, however, usually require new ways, too. The mere replacement by a microproces-
227
sor of the discrete logic applied up to now will not bring about a decisive break-through. Microprocessors axe systems capable of rapidly processing many different successive logic operations. They are efficient if this capacity for successive accomplishment of tasks is exploited. It is therefore suggested that the intelligence of the conventional detector should be shifted to the control panel completely, changing in that way the design of the fire detection system. Detectors which now decide independently whether there is a cause for alarm will become dependent sensors, permanently transmitting their measured values to the intelligence panel for evaluation. Passive control panels which just receive and indicate alarm signals and transmit them to the fire stations whenever the detectors respond will become active processing systems, permanently applying highquality algorithms to discern real fire from error characteristics. Such a change of system, however, can be realized only if the good qualities that we are accustomed to in the present technology are maintained: the dual-wire line between the detectors and the control panel, simple installation and application, simple replacement of the detectors, and the low cost level.
THE PULSE POLLING SYSTEM
The following is a description of a new fire protection system {see Fig. 4). Its developm e n t has been based on the main idea of the optimal combination of the conventional and the new principles (Fig. 1): dual-wire line is maintained except for the b-wire which, is now interrupted in each detector. The line is interrogated once per second (Fig. 2). Each
detector responds with an impulse il, i2 . . . . . i30. The control panel checks whether each of them is still there. The chief attraction is the fact t h a t the distance of the response impulses M1, M 2. . . . , M30 is variable and changes in accordance with the measured value of the detectors. The time link (Fig. 3) is adjusted to a maximum period of time when there is no smoke in the measuring transformer. If smoke penetrates the measuring chamber of a detector, the time link will reduce its response period depending more or less on the smoke density. This technology which is especially free from interference, is well known as pulselength modulation and our system derives its name therefrom: 'the pulse polling process'. If a warning or a control operation is to be released, the microprocessor in the control panel will first reduce the line voltage. The control unit, the measuring interval of which is affected by the control impulse uc, then transmits an o u t p u t signal (external alarm indicator in Figs. 1 and 2). This o u t p u t signal energizes LEDs in the detectors or in the external alarm indicators. Ifi the control units a potential free contact KST is closed.
ADVANTAGES OF THE ALARM ORGANIZATION
This system includes a lot of advantages for the user. There is no need to adjust an address because the detectors transmit in the order in which they are installed. Mechanics may instal or replace sensors after cleaning, as has been possible so far. Errors due to false addresses or confusion are excluded. The control panel identifies each measured value deriving from different detectors. In the case of an alarm or a failure it is possible to identify the detector concerned.
l 1
2
detector
detector
3
control panel
24V_~__
1 , I11 J q ,
I
external alarm indicator
Fig. 1. D e t e c t o r line o f t h e pulse polling s y s t e m w i t h u p to 30 units.
control unit
detector
228
u(~)
L mm
US
UC
mlllm
I
J
lirai
I
t
t I 1 I I I
] ] n 1
I I I I
M~
M2
(M3)
M~.
Fig. 2. V o l t a g e and c u r r e n t curve o n t h e d e t e c t o r line during a polling cycle, u s = start impulse at the beginning o f t h e polling cycle; u c = c o n t r o l i m p u l s e ; i i = i m p u l s e n u m b e r ; M i = m e a s u r e d values.
I i
1
_
Fig. 3. Basic circuit diagram o f a d e t e c t o r for t h e pulse polling s y s t e m . TQ = t r a n s m i s s i o n for pulse c o u n t s ; T L = line c o n n e c t i n g t r a n s i s t o r s (refer t o Fig. 1 ).
In conventional systems the lines have in most cases been equipped with far fewer detectors than required b y technical specifications because the control panel cannot discern from which detector the alarm is coming. Fire protection requirements determine the location of the lines and the n u m b e r of detectors on them. Because of its ability to identify detectors, the pulse polling system allows the location of the line to be optimised on the basis of a building's construction. However, in order to fulfil fire protection requirements, surveillance zones to which detectors may be aUocated m a y be defined completely independently of their order in the line (Fig. 4).
'Marshalling' of the detectors, as has been done so far by the line installation, is now replaced by modern data feed in the control panel. A D V A N T A G E S O F THE O P E R A T I O N RELIABILITY
Conventional fire detector lines are permanently and automatically supervised for wire breaks and earth faults. Supervision of the transducer function and detector circuitry is exercised exclusively in accordance with the requirements of periodical maintenance. Figure 5 shows what can happen within the maintenance intervals. The operation point of
229
single indication: o¢¢~ address of the I. message alarm tailure surveillance zone 1
surveillance zone 2
surveillance zone 3
Fig. 4. Ionization-type smoke detector and control panel plug-in unit for the pulse polling system.
a detector can drift away due to ageing of the units, or, above all, due to dust or contamination. If the quiescent value UMO withdraws from the response threshold of the detector, the latter becomes more and more insensitive, with the eventual possibility of complete inefficiency. For reasons of safety detectors are generally developed to allow the quiescent value to drift towards the alarm threshold due to contamination and this results in a likely increase of false alarms. In the pulse polling system the microprocessor in the control panel evaluates data from all detectors about every second and processes a sliding average UM0 for each detector (Fig. 6). If there is the danger of one quiescent value drifting from the permissible operation area, a signal 'preventive maintenance' is indicated in the control panel when the upper or lower limits Up are surpassed for any detector concerned. The man responsible for maintenance can check at any time
whether the system is running true to form by interrogating these signals and thus fix dates for maintenance. If one quiescent value is drifting out of the permissible operation area defined by the limits uf, the failure indication of the surveillance zone involved will light up.
ADVANTAGES
OF FALSE A L A R M
SUPPRESSION
False alarms are either fault alarms based on detector failure or error alarms caused by fire-like incidents (Fig. 7). Analyses show that false alarms include fault and error alarms to about the same degree. As shown in Fig. 5, contamination, humidity, wind, and insects can increase both the fault and error alarm rates, whereas t h e y can decrease the distance to the response threshold Uta in conventional threshold detectors. False alarms -- due to fault or error -- are also caused by trifling
230 UM
no
UM '
alarm
t
Uth
uf Up .
..................................... .
.
.
.
.
.
.
.
.
.
.
.
.
.
.
uMe
u~
2
(a)
years
(a)
.
.
lar!mr q
t
, ,: y
UM
Ulh
Y
/
UM
, r
L;f
Lip
fadun: I:)reveqhve t'~d ptellanc9
~;th
UM0
,
IP
I
2
years
(b) (b)
Fig. 5. Results o f a q u i e s c e n t value drift in a conventional t h r e s h o l d d e t e c t o r : (a) d e t e c t o r less sensitive; (b) d e t e c t o r m o r e sensitive, u M = measured value o f the d e t e c t o r ; uMO = q u i e s c e n t value ( w i t h o u t s m o k e ) ; Uth = response threshold.
Fault alarms (~50%~
Fig. 6. Results o f a q u i e s c e n t value drift in the pulse polling s y s t e m : (a) response sensitivity maintained; (b) permissible o p e r a t i o n area surveyed. UM, Ulvi0, Uth are defined in Fig. 5; Up = limits for preventive maintenance; uf = limits for failure indication.
error alarms ( ~ 5 0 % )
!~rc like rrl{~itlerlt, !) a~,llr !nanuta(-lqrei
- electrical influence (lightening, fluorescent hght radto)
~hl,t ,, hre (c~c]arette smoke gor'nousllOfi products)
contamination, humidity, wind, insects
2.
no sweep c*rcuit in the detector mere efficient evaluation
1.
sliding operation point and more efficient evaluation
3,
evaluabon o! fire quantitle~
Fig. 7. Measures t o reduce false alarm rates in the pulse polling s y s t e m .
231
incidents when the distance between the quiescent value and the response value decreases. To avoid this unwanted effect the pulse polling system provides for a follow-up of the response threshold of each detector if its quiescent value UM0 changes (Fig. 6). In this way a constant response sensitivity (measure 1, Fig. 7) is achieved within the whole permissible operation area. In conventional detectors a very short, needle-shaped impulse, e.g. a few ms, triggers the sweep circuit if it exceeds the response threshold, thus storing the alarm condition in the detector concerned. The response of the sweep circuit to electromagnetic influences is a well-known cause of false alarms. The pulse polling system does not include such a sweep circuit, neither in the detectors nor in the control panel. Consequently, false alarms of this kind do not appear (measure 2, Fig. 7). It is difficult to differentiate fire characteristics from error characteristics because the latter involve smoke from useful fires (cigarette and pipe smoke, car exhaust gas, fires in neighbouring fields, etc.) which are not different from the smoke of a damaging fire. One might escape from the dilemma by declaring all fires where people are present to be utility fires. If we start from the suggestion that all rooms in a factory during the regular work time are occupied, it would then be sufficient to switch through the alarms automatically to the fire station only during the period from the end of work time until the beginning of work. This procedure, however, is not approved by the fire brigades and the property insurance companies in the Federal Republic of Germany, and I think this attitude is justified. One should n o t ignore the fact that alarm suppression or delay due to such day/ night switching involves danger because holidays, short-time work and other extraordinary events exist. We consider that it is safer to have an automatic fire detection system respond only at a time when the smoke grows to a certain intensity, rather than integrating people into the alarm procedure as an unreliable link. This consideration is based on the assumption t h a t error characteristics do n o t produce the relevant a m o u n t of smoke. The response behaviour of a fire detection system, of course, must be t u n e d into the fire risk of an object. This is possible in the pulse polling system by the definition of 'fire quantities' to which the system m u s t trigger an
MTBA [yearsl
B5
f
fire quantity B necessary tot alarm triggering are • functions of smoke concentration and time
800
200
£ 1 6 2 and 85 a r e values based oe experience and dependent on the detec~or type and the specific environment
120
5'
mlnlrnal smoke concentration
[loss m]
Fig. 8. Average mean time between two false alarms (MTBA) related to one detector as a function o f the smoke concentration and fire quantity required for alarm triggering in the pulse polling system.
alarm. The fire quantity should be considered as a function of the smoke concentration and time and can be fed as a parameter into the microprocessor evaluating the measured data of detectors (measure 3, Fig. 7). Figure 8 shows that the average mean time between two false alarms (MTBA) of a detector depends to a large extent on the fire quantities necessary for response. It is also essential to register at what minimal smoke concentration the calculation of the actual fire quantity must start in the microprocessor in order to raise an alarm at B1, B2, or B3. The minimum smoke concentration, therefore, is entered on the abscissa of the family of characteristics. It will be possible in the future to develop such families of characteristics for each typical environment (office buildings, metal workshops, wood processing factories, etc.) in order to forecast the false alarm probability to be expected. Each detector in the pulse polling system could be used as a data detector storing measured data for such families of characteristics to be established. It will be possible in t h a t way to transmit the experience of such systems to others -- another kind of 'distributed intelligence'.
225
Fire Detector Systems with 'Distributed Intelligence' The Pulse Polling System R. VON TOMKEWITSCH Siemens AG, Munich (F.R.G.)
SUMMARY
Well over a million fire detectors are currently in use in the Federal Republic o f Germany. Provided they are correctly installed and efficiently maintained, they detect fires reliably at a very early stage. A t the present time, the false alarm rate equals about 1% o f the number o f installed detectors per annum. This false alarm rate must be at least proportionately reduced as further detectors are installed. Since it is scarcely possible to improve tried-and-tested detector designs, the employm e n t o f higher-grade detector signal processing methods suggests itself. However, 'more intelligent" detector signal processing using microprocessors calls for an entirely new fire detection system structure: detectors which independently 'decide' whether an alarm criterion is m e t and then initiate an alarm are replaced by sensors which continuously transmit their measured values to the 'intelligence' panel for evaluation. Passive panels which simply receive alarm signals from activated detectors and indicate these or transmit them to the fire brigade are replaced by active processors using permanently improved algorithms for the detection o f real fires. A structural change o f this type is possible provided the positive -- and the customary -characteristics o f the conventional technique are not lost, viz. two-wire lines between detector and panel, simple installation and handling, easy detector replaceability, low cost, etc. The pulse detector technology is described in detail; it combines the simplicity o f conventional fire detection systems with new characteristics, e.g. identification o f individual detectors, p e r m a n e n t functional check o f all connected detectors, automatic notification o f 0379-7112183/$3.00
maintenance requirement prior to a slowly developing fault (e.g. such as that caused by corrosion or contamination), uniform response sensitivity unaffected by drifting from the operating points o f the detectors and, above all, greater protection against false alarms.
INTRODUCTION
In order to distribute intelligence one must take for granted that there is intelligence, or that it is necessary. In the case of fire protection systems there are three functions which can be described as needing a certain 'intelligence' or, to put it in more technical terms, which require data processing: (1) processing of signals from automatic fire detectors; (2) raising of alarm in the event of fire, especially if data such as operation plan data and counter-measures are to be indicated automatically, depending on the location of the fire; (3) automatic initiation of defence measures, such as moving the fire fighting apparatus into action, switching on escape route indicators, closing fire protection doors, and opening smoke outlets. As the meeting at which this paper was presented was concerned with automatic fire detection, the discussion below will refer particularly to the first function, the processing of signals from automatic fire detectors.
WHY MORE INTELLIGENCE? In the Federal Republic of Germany there are more than one million automatic fire detectors in operation. These detectors, if competently installed, have for more than 30 © Elsevier Sequoia/Printed in The Netherlands
226
years reliably detected the outbreak of fire in its initial phases. Why is the question of 'distributed intelligence' being raised at the present time? Well, primarily more intelligence is needed. Early warning fire detectors, especially smoke detectors, are sensitive measuring devices. They can also be put into alarm operation by environmental factors. Of course, all producers of fire detectors make rigorous efforts to exclude false alarms in their basic design. This has been achieved up to now by a deterministic approach: each false alarm has been associated with a probable cause -- such as contamination, insects, influence of temperature, wind, humidity, corrosion, strikes of lightning, electromagnetic influence or smoke-like symptoms, such as vapour from welding operations, etc. When certain causes of false alarms accumulated, the detectors were improved with respect to their construction and circuitry in order to reduce these influences. Thanks to these methods, and to experience gained in the development of automatic fire detectors over a period of four decades, false alarm rates of 1% have been achieved. In other words, 100 installed detectors produce, on average, only one false alarm per year. False alarm rates can be below this level in the case of high-quality, well-serviced detectors installed in clean rooms; however, the rates can be exceeded to a considerable e x t e n t under unfavourable conditions of application. In the view of fire brigades and users, the false alarm rates should be further improved to an extent corresponding to the increased distribution of automatic fire detectors, if false alarms are n o t to become a problem. If a further reduction of these false alarm rates by at least one order of magnitude is aimed at, new methods will have to be applied. Since there is hardly anything about the detectors which might be improved, then it follows t h a t the approach should be through improved evaluation methods of detector signals and through more suitable algorithms for distinguishing false alarms from real ones. This higher quality signal processing means 'more intelligence'. WHY DISTRIBUTED INTELLIGENCE?
In conventional fire detection systems it has been up to the detectors to decide
whether the local concentration of the fire characteristics justify a fire alarm. The 'intelligence' provided for this decision is rather modest: heat detectors evaluate the rise in temperature, and smoke detectors, in general, check only whether the smoke concentration exceeds a certain threshold value. The control panel can contribute to the reduction of false alarms by interrogating twice a detector sending out an alarm (socalled alarm repetition) and by transmitting an alarm to the fire station only if two neighbouring fire detectors respond (so-called dual line or dual detector dependency). These logical combinations of detector signals -already well k n o w n - - have recently been con° sidered by the VdS (German Association for the approval of fire detectors) as requirements to fulfil the specifications for a 'fire detection system with increased reliability'. They can already be considered as the beginning of a 'distributed intelligence', since the detectors evaluate the local concentration of the fire characteristic, whereas the control panel surveys the duration and local expansion of the incident. The probability of an alarm due to electromagnetic influence or to the closely restricted occurrence of an error characteristic is reduced in that way. It should be stated here that the only formal accomplishment of these measures does not guarantee their success. If the period of time from the beginning of the fire outbreak up to its detection is not to increase considerably, the n u m b e r of detectors per surveillance area should be duplicated in the case of a dual detector dependency. On the other hand, if this combination is to contribute to the reduction of false alarms due to errors, the detectors so combined should be installed at the furthest possible distance from each other. The protective value of a fire detection system based on 'distributed intelligence' as described above, therefore, depends to a great extent on its optimal design.
E V O L U T I O N A R Y J U M P BY T H E MICROPROCESSOR
It is well known t h a t the advent of the microprocessor has reduced the price at which 'technical intelligence' can be realized. New means, however, usually require new ways, too. The mere replacement by a microproces-
227
sor of the discrete logic applied up to now will not bring about a decisive break-through. Microprocessors axe systems capable of rapidly processing many different successive logic operations. They are efficient if this capacity for successive accomplishment of tasks is exploited. It is therefore suggested that the intelligence of the conventional detector should be shifted to the control panel completely, changing in that way the design of the fire detection system. Detectors which now decide independently whether there is a cause for alarm will become dependent sensors, permanently transmitting their measured values to the intelligence panel for evaluation. Passive control panels which just receive and indicate alarm signals and transmit them to the fire stations whenever the detectors respond will become active processing systems, permanently applying highquality algorithms to discern real fire from error characteristics. Such a change of system, however, can be realized only if the good qualities that we are accustomed to in the present technology are maintained: the dual-wire line between the detectors and the control panel, simple installation and application, simple replacement of the detectors, and the low cost level.
THE PULSE POLLING SYSTEM
The following is a description of a new fire protection system {see Fig. 4). Its developm e n t has been based on the main idea of the optimal combination of the conventional and the new principles (Fig. 1): dual-wire line is maintained except for the b-wire which, is now interrupted in each detector. The line is interrogated once per second (Fig. 2). Each
detector responds with an impulse il, i2 . . . . . i30. The control panel checks whether each of them is still there. The chief attraction is the fact t h a t the distance of the response impulses M1, M 2. . . . , M30 is variable and changes in accordance with the measured value of the detectors. The time link (Fig. 3) is adjusted to a maximum period of time when there is no smoke in the measuring transformer. If smoke penetrates the measuring chamber of a detector, the time link will reduce its response period depending more or less on the smoke density. This technology which is especially free from interference, is well known as pulselength modulation and our system derives its name therefrom: 'the pulse polling process'. If a warning or a control operation is to be released, the microprocessor in the control panel will first reduce the line voltage. The control unit, the measuring interval of which is affected by the control impulse uc, then transmits an o u t p u t signal (external alarm indicator in Figs. 1 and 2). This o u t p u t signal energizes LEDs in the detectors or in the external alarm indicators. Ifi the control units a potential free contact KST is closed.
ADVANTAGES OF THE ALARM ORGANIZATION
This system includes a lot of advantages for the user. There is no need to adjust an address because the detectors transmit in the order in which they are installed. Mechanics may instal or replace sensors after cleaning, as has been possible so far. Errors due to false addresses or confusion are excluded. The control panel identifies each measured value deriving from different detectors. In the case of an alarm or a failure it is possible to identify the detector concerned.
l 1
2
detector
detector
3
control panel
24V_~__
1 , I11 J q ,
I
external alarm indicator
Fig. 1. D e t e c t o r line o f t h e pulse polling s y s t e m w i t h u p to 30 units.
control unit
detector
228
u(~)
L mm
US
UC
mlllm
I
J
lirai
I
t
t I 1 I I I
] ] n 1
I I I I
M~
M2
(M3)
M~.
Fig. 2. V o l t a g e and c u r r e n t curve o n t h e d e t e c t o r line during a polling cycle, u s = start impulse at the beginning o f t h e polling cycle; u c = c o n t r o l i m p u l s e ; i i = i m p u l s e n u m b e r ; M i = m e a s u r e d values.
I i
1
_
Fig. 3. Basic circuit diagram o f a d e t e c t o r for t h e pulse polling s y s t e m . TQ = t r a n s m i s s i o n for pulse c o u n t s ; T L = line c o n n e c t i n g t r a n s i s t o r s (refer t o Fig. 1 ).
In conventional systems the lines have in most cases been equipped with far fewer detectors than required b y technical specifications because the control panel cannot discern from which detector the alarm is coming. Fire protection requirements determine the location of the lines and the n u m b e r of detectors on them. Because of its ability to identify detectors, the pulse polling system allows the location of the line to be optimised on the basis of a building's construction. However, in order to fulfil fire protection requirements, surveillance zones to which detectors may be aUocated m a y be defined completely independently of their order in the line (Fig. 4).
'Marshalling' of the detectors, as has been done so far by the line installation, is now replaced by modern data feed in the control panel. A D V A N T A G E S O F THE O P E R A T I O N RELIABILITY
Conventional fire detector lines are permanently and automatically supervised for wire breaks and earth faults. Supervision of the transducer function and detector circuitry is exercised exclusively in accordance with the requirements of periodical maintenance. Figure 5 shows what can happen within the maintenance intervals. The operation point of
229
single indication: o¢¢~ address of the I. message alarm tailure surveillance zone 1
surveillance zone 2
surveillance zone 3
Fig. 4. Ionization-type smoke detector and control panel plug-in unit for the pulse polling system.
a detector can drift away due to ageing of the units, or, above all, due to dust or contamination. If the quiescent value UMO withdraws from the response threshold of the detector, the latter becomes more and more insensitive, with the eventual possibility of complete inefficiency. For reasons of safety detectors are generally developed to allow the quiescent value to drift towards the alarm threshold due to contamination and this results in a likely increase of false alarms. In the pulse polling system the microprocessor in the control panel evaluates data from all detectors about every second and processes a sliding average UM0 for each detector (Fig. 6). If there is the danger of one quiescent value drifting from the permissible operation area, a signal 'preventive maintenance' is indicated in the control panel when the upper or lower limits Up are surpassed for any detector concerned. The man responsible for maintenance can check at any time
whether the system is running true to form by interrogating these signals and thus fix dates for maintenance. If one quiescent value is drifting out of the permissible operation area defined by the limits uf, the failure indication of the surveillance zone involved will light up.
ADVANTAGES
OF FALSE A L A R M
SUPPRESSION
False alarms are either fault alarms based on detector failure or error alarms caused by fire-like incidents (Fig. 7). Analyses show that false alarms include fault and error alarms to about the same degree. As shown in Fig. 5, contamination, humidity, wind, and insects can increase both the fault and error alarm rates, whereas t h e y can decrease the distance to the response threshold Uta in conventional threshold detectors. False alarms -- due to fault or error -- are also caused by trifling
230 UM
no
UM '
alarm
t
Uth
uf Up .
..................................... .
.
.
.
.
.
.
.
.
.
.
.
.
.
.
uMe
u~
2
(a)
years
(a)
.
.
lar!mr q
t
, ,: y
UM
Ulh
Y
/
UM
, r
L;f
Lip
fadun: I:)reveqhve t'~d ptellanc9
~;th
UM0
,
IP
I
2
years
(b) (b)
Fig. 5. Results o f a q u i e s c e n t value drift in a conventional t h r e s h o l d d e t e c t o r : (a) d e t e c t o r less sensitive; (b) d e t e c t o r m o r e sensitive, u M = measured value o f the d e t e c t o r ; uMO = q u i e s c e n t value ( w i t h o u t s m o k e ) ; Uth = response threshold.
Fault alarms (~50%~
Fig. 6. Results o f a q u i e s c e n t value drift in the pulse polling s y s t e m : (a) response sensitivity maintained; (b) permissible o p e r a t i o n area surveyed. UM, Ulvi0, Uth are defined in Fig. 5; Up = limits for preventive maintenance; uf = limits for failure indication.
error alarms ( ~ 5 0 % )
!~rc like rrl{~itlerlt, !) a~,llr !nanuta(-lqrei
- electrical influence (lightening, fluorescent hght radto)
~hl,t ,, hre (c~c]arette smoke gor'nousllOfi products)
contamination, humidity, wind, insects
2.
no sweep c*rcuit in the detector mere efficient evaluation
1.
sliding operation point and more efficient evaluation
3,
evaluabon o! fire quantitle~
Fig. 7. Measures t o reduce false alarm rates in the pulse polling s y s t e m .
231
incidents when the distance between the quiescent value and the response value decreases. To avoid this unwanted effect the pulse polling system provides for a follow-up of the response threshold of each detector if its quiescent value UM0 changes (Fig. 6). In this way a constant response sensitivity (measure 1, Fig. 7) is achieved within the whole permissible operation area. In conventional detectors a very short, needle-shaped impulse, e.g. a few ms, triggers the sweep circuit if it exceeds the response threshold, thus storing the alarm condition in the detector concerned. The response of the sweep circuit to electromagnetic influences is a well-known cause of false alarms. The pulse polling system does not include such a sweep circuit, neither in the detectors nor in the control panel. Consequently, false alarms of this kind do not appear (measure 2, Fig. 7). It is difficult to differentiate fire characteristics from error characteristics because the latter involve smoke from useful fires (cigarette and pipe smoke, car exhaust gas, fires in neighbouring fields, etc.) which are not different from the smoke of a damaging fire. One might escape from the dilemma by declaring all fires where people are present to be utility fires. If we start from the suggestion that all rooms in a factory during the regular work time are occupied, it would then be sufficient to switch through the alarms automatically to the fire station only during the period from the end of work time until the beginning of work. This procedure, however, is not approved by the fire brigades and the property insurance companies in the Federal Republic of Germany, and I think this attitude is justified. One should n o t ignore the fact that alarm suppression or delay due to such day/ night switching involves danger because holidays, short-time work and other extraordinary events exist. We consider that it is safer to have an automatic fire detection system respond only at a time when the smoke grows to a certain intensity, rather than integrating people into the alarm procedure as an unreliable link. This consideration is based on the assumption t h a t error characteristics do n o t produce the relevant a m o u n t of smoke. The response behaviour of a fire detection system, of course, must be t u n e d into the fire risk of an object. This is possible in the pulse polling system by the definition of 'fire quantities' to which the system m u s t trigger an
MTBA [yearsl
B5
f
fire quantity B necessary tot alarm triggering are • functions of smoke concentration and time
800
200
£ 1 6 2 and 85 a r e values based oe experience and dependent on the detec~or type and the specific environment
120
5'
mlnlrnal smoke concentration
[loss m]
Fig. 8. Average mean time between two false alarms (MTBA) related to one detector as a function o f the smoke concentration and fire quantity required for alarm triggering in the pulse polling system.
alarm. The fire quantity should be considered as a function of the smoke concentration and time and can be fed as a parameter into the microprocessor evaluating the measured data of detectors (measure 3, Fig. 7). Figure 8 shows that the average mean time between two false alarms (MTBA) of a detector depends to a large extent on the fire quantities necessary for response. It is also essential to register at what minimal smoke concentration the calculation of the actual fire quantity must start in the microprocessor in order to raise an alarm at B1, B2, or B3. The minimum smoke concentration, therefore, is entered on the abscissa of the family of characteristics. It will be possible in the future to develop such families of characteristics for each typical environment (office buildings, metal workshops, wood processing factories, etc.) in order to forecast the false alarm probability to be expected. Each detector in the pulse polling system could be used as a data detector storing measured data for such families of characteristics to be established. It will be possible in t h a t way to transmit the experience of such systems to others -- another kind of 'distributed intelligence'.