EP0660282B1 - Brandmeldesystem zur Früherkennung von Bränden - Google Patents

Brandmeldesystem zur Früherkennung von Bränden Download PDF

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Publication number
EP0660282B1
EP0660282B1 EP94119614A EP94119614A EP0660282B1 EP 0660282 B1 EP0660282 B1 EP 0660282B1 EP 94119614 A EP94119614 A EP 94119614A EP 94119614 A EP94119614 A EP 94119614A EP 0660282 B1 EP0660282 B1 EP 0660282B1
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EP
European Patent Office
Prior art keywords
signal
fire
alarm
alarm system
detector
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Expired - Lifetime
Application number
EP94119614A
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German (de)
English (en)
French (fr)
Other versions
EP0660282A1 (de
Inventor
Marc Pierre Dr. Thuillard
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Siemens AG
Original Assignee
Siemens Building Technologies AG
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Filing date
Publication date
Application filed by Siemens Building Technologies AG filed Critical Siemens Building Technologies AG
Publication of EP0660282A1 publication Critical patent/EP0660282A1/de
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Classifications

    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B17/00—Fire alarms; Alarms responsive to explosion

Definitions

  • the present invention relates to a fire detection system for the early detection of Fires, with at least one linear smoke or a scattered light or a Flame detector and with an evaluation circuit and fuzzy logic Signal processing stage for those generated in the at least one detector Signals, the signal processing stage means for time analysis of the Contains signals.
  • Linear smoke detectors such as the type detector offered by Cerberus AG A2400, contain a transmitter that emits a modulated infrared beam, and a receiver that collects and evaluates the incoming infrared radiation.
  • the detector has a long monitoring distance of at least 3, for example Meters; Smoke entering the beam weakens the infrared radiation.
  • Flame detectors such as the infrared detector offered by Cerberus AG of Type S2406, contain two pyroelectric sensitive to specific wavelengths Sensors and can fire a relatively long distance, for example Detect over 20 meters.
  • Linear smoke detectors are sensitive to various disturbances, which are rough two classes can be divided.
  • One category is environmental disturbance such as fluctuations in the refractive index of the air at elevated temperature or condensation or water droplets on the optics of the detector with increased Humidity, or electromagnetic interference from radio telephones and the like.
  • the other category of interference is interference, for example Interruptions of the light beam by a person, an object or a Machine, or movements of the walls supporting the detectors.
  • this object is achieved in that the at least one Detector each has only one type of sensor, and that from the signal of this sensor, at least two signal parameters are derived, which are linguistic Form variable of fuzzy logic.
  • a first preferred embodiment of the system according to the invention is characterized in that the signal parameters by the signal gradient and the signal noise is formed.
  • a second preferred embodiment of the arrangement according to the invention is characterized in that the signal parameters by the signal asymmetry and the signal jumps are formed.
  • linear Smoke detector from a transmitter emitting a modulated infrared beam and from one that collects the incoming infrared radiation and in an electronic one Circuit evaluating receiver. It can senders and receivers be arranged opposite each other or next to each other, wherein in the latter case reflectors on the opposite side of the transmitter and receiver are provided.
  • the main components of the receiver include an optical system 1, a photodiode 2 and a signal processing stage 3 with an estimation stage 4 and a fuzzy controller 5.
  • signal processing stage 3 contains an evaluation circuit, in which essentially the amplified signal of the photodiode 2 with a adjustable alarm threshold is compared, and a tracking circuit for compensation of slow changes in the reception signal due to dust deposits or aging of the components.
  • the evaluation circuit and the tracking circuit are known from the A2400 linear smoke detector from Cerberus AG and are not described here. Smoke entering the infrared beam weakens the infrared radiation and causes a corresponding weakening of the received signal. As soon as it drops below a certain value, the receiver triggers an alarm signal.
  • the alarm is triggered only depending on the result of the comparison of the received signal with the alarm threshold is, in the system according to the invention the alarm signal with suitable Fuzzy algorithms are examined and the alarm either confirmed or as a false alarm recognized.
  • a time analysis of the received signal is carried out with a Calculation of several signal parameters and a link between the signal parameters and their division into different event categories using fuzzy logic.
  • the output signal of the photodiode 2 reaches the estimation stage 4, where on the one hand a smoothing of the received signal and on the other hand an estimate of various signal parameters derived from the received signal or signal properties.
  • the raw value of the received signal normalized by the respective signal change ⁇ l through a reference value lo is divided. The ratio is used to smooth the received signal Raw value to signal is examined and a constant is added to the signal or subtracted from this.
  • the signal parameters or signal properties are as shown about noise, gradient, jumps and asymmetry. These parameters are as part of a time analysis of the smoothed signal using signal filters and Intercorrelation functions calculated.
  • the noise is compared successive raw values determined, the gradient as a flowing mean of several measuring points, the asymmetry based on a comparison between Raw value on the one hand and smoothed signal and noise on the other hand, and one for the signal jumps representative jump indicator by comparing the over different long intervals of smoothed signal.
  • the gradient is estimated so that the gradient is very small Steepness or small with a jump and with an increase over a longer time is big. Functionally, this corresponds to a band pass.
  • the fuzzy controller 5 contains three stages ST1 to ST3.
  • the first stage ST1 is fuzzy, which is the conversion of the different numbers of sharp parameters obtained in unsharp amounts, the so-called fuzzy sets.
  • the second stage ST2 are on the fuzzy sets apply the rules established when designing the fuzzy controller, and in the third stage ST3 the defuzzification takes place, that is the calculation the sharp output sizes.
  • the basics of fuzzy logic referred to the now extensive literature on this topic, for example to the book "Fuzzy Set Theory and its Applications" by H.J. Carpenter, Kluwer Academic Publishers, 1991.
  • Fuzzyfication in the first stage ST1 of the fuzzy controller 5 takes place by means of of the fuzzy sets shown in FIGS. 2a to 2d.
  • 2a shows the fuzzy sets For the signal parameter noise, Fig. 2b those for the gradient, Fig. 2c for the jumps and Fig. 2d the fuzzy sets for the asymmetry.
  • the upper limit for the respectively plotted on the ordinate Membership function or for the degree of membership is one, it is in any case normal fuzzy sets.
  • the individual signal parameters are the linguistic variables of fuzzy logic and these linguistic variables can different values assume which names for those in the figures 2a to 2d are fuzzy sets shown.
  • the linguistic variable noise can be one of take three values (small, medium, large); the linguistic variable gradient (Fig. 2b) also one of three values (small, medium, large); the linguistic variable Jumps (Fig. 2c) one of four values (very small, small, medium, large); and the linguistic variable asymmetry (Fig. 2d) one of only two values (small, large).
  • FIG. 3 shows a knowledge base built up from data obtained in practice with the values or linguistic variables of the individual signal parameters and with typical links between these values for certain common fire events and disorders.
  • the fuzzy controller 5 In the case of typical faults, the majority of which also occur in the second Stage ST2 of the fuzzy controller 5 (FIG. 1) are entered, it is for splash water on the optics, for complete or partial coverage of the infrared beam by a person crossing it or an object to condense it the optics with high humidity and strong cooling to an electromagnetic Disturbance (EMI) to shears, such as those in places with high local heat generation, such as in or around factories or in thermal power plants, occur and around test filters. As is well known, the latter are used to to target an alarm as part of maintenance or revision work trigger.
  • the information test filter then means that either a test filter is used, or the beam was partially covered within a very short time.
  • stage ST2 (Fig. 1) is now by the smoothed received signal examined using the knowledge base shown in Fig. 3, whether it is actually a fire or just a malfunction.
  • the fuzzy rules used are formulated in such a way that: If (one of the four conditions mentioned and signal ⁇ alarm threshold) then Fire.
  • the system described is suitable not only for false alarm suppression, but also also for fault diagnosis.
  • Today's linear smoke detectors are already designed that certain disturbances, especially an interruption of the infrared beam or a transmitter failure, an open circuit to the Cable termination terminals of the receiver cause a line break is simulated. If it is determined during troubleshooting that There is no voltage at the terminals mentioned, then the possible causes (receiver cover not installed, light beam interrupted, Transmitter failure, receiver fault) checked in sequence.
  • the fault diagnosis can be essentially more disturbances are expanded and it can also be done much easier, by establishing fuzzy rules for the faults, which is a direct one Display of the probable cause of the fault (s) allowed. This will make the Troubleshooting is much easier and cheaper and you also get the possibility of eliminating the cause of frequently occurring faults.
  • Another way of using the fuzzy logic Information is to automatically adjust the detector sensitivity, by, for example, a higher alarm threshold when streaks occur is chosen, or initiate other measures, for example at If condensation occurs, switch on the heating of the relevant front cover.
  • fuzzy controller changes only a little. Only certain other fuzzy sets have to be defined and others Establish fuzzy rules. However, since the possible causes of faults for all three detector types are very similar, the necessary adjustments are within the framework of the Can the expert.

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  • Business, Economics & Management (AREA)
  • Emergency Management (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Fire Alarms (AREA)
  • Fire-Detection Mechanisms (AREA)
  • Photometry And Measurement Of Optical Pulse Characteristics (AREA)
  • Alarm Systems (AREA)
EP94119614A 1993-12-20 1994-12-12 Brandmeldesystem zur Früherkennung von Bränden Expired - Lifetime EP0660282B1 (de)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
CH03793/93A CH686914A5 (de) 1993-12-20 1993-12-20 Brandmeldesystem zur Frueherkennung von Braenden.
CH3793/93 1993-12-20
CH379393 1993-12-20

Publications (2)

Publication Number Publication Date
EP0660282A1 EP0660282A1 (de) 1995-06-28
EP0660282B1 true EP0660282B1 (de) 2000-08-09

Family

ID=4263585

Family Applications (1)

Application Number Title Priority Date Filing Date
EP94119614A Expired - Lifetime EP0660282B1 (de) 1993-12-20 1994-12-12 Brandmeldesystem zur Früherkennung von Bränden

Country Status (8)

Country Link
EP (1) EP0660282B1 (fi)
JP (1) JPH07200961A (fi)
CN (1) CN1038622C (fi)
AT (1) ATE195386T1 (fi)
CH (1) CH686914A5 (fi)
DE (1) DE59409474D1 (fi)
FI (1) FI111666B (fi)
NO (1) NO324427B1 (fi)

Families Citing this family (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP3184429B2 (ja) * 1995-06-30 2001-07-09 ホーチキ株式会社 防災監視システムの端末感知装置
DE10011411C2 (de) 2000-03-09 2003-08-14 Bosch Gmbh Robert Bildgebender Brandmelder
US6879253B1 (en) * 2000-03-15 2005-04-12 Siemens Building Technologies Ag Method for the processing of a signal from an alarm and alarms with means for carrying out said method
DE10020380A1 (de) * 2000-04-26 2001-10-31 Bodenseewerk Geraetetech Verfahren und Vorrichtung zur Früherkennung einer möglichen Überhitzung eines Gegenstandes
DE10066246A1 (de) * 2000-09-22 2005-10-06 Robert Bosch Gmbh Streulichtrauchmelder
US8659415B2 (en) * 2011-07-15 2014-02-25 General Electric Company Alarm management
CN103956018B (zh) * 2014-05-15 2016-05-11 杜玉龙 一种改进的建筑消防设施报警信号分析处理方法
CN107067683B (zh) * 2017-04-14 2018-01-09 湖南省湘电试研技术有限公司 一种输电线路山火聚类定量预报方法及系统
CN110111548A (zh) * 2019-04-14 2019-08-09 杭州拓深科技有限公司 一种消防报警设备的补偿优化方法

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1990009012A1 (en) * 1989-01-25 1990-08-09 Nohmi Bosai Kabushiki Kaisha Fire alarm
EP1284580A1 (en) * 2001-08-16 2003-02-19 Swisscom Mobile AG System and method for location update in GSM mobile radio network
JP4597989B2 (ja) * 2003-08-27 2010-12-15 コーニンクレッカ フィリップス エレクトロニクス エヌ ヴィ 短毛切断装置及び長毛切断装置を備えたシェービング装置

Also Published As

Publication number Publication date
CN1127394A (zh) 1996-07-24
DE59409474D1 (de) 2000-09-14
EP0660282A1 (de) 1995-06-28
FI945934A0 (fi) 1994-12-16
JPH07200961A (ja) 1995-08-04
NO324427B1 (no) 2007-10-15
NO944821L (no) 1995-06-21
CH686914A5 (de) 1996-07-31
FI111666B (fi) 2003-08-29
ATE195386T1 (de) 2000-08-15
FI945934A (fi) 1995-06-21
NO944821D0 (no) 1994-12-13
CN1038622C (zh) 1998-06-03

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