CN101162545A - Tall building fire light-temperature composite intelligent monitoring prediction device - Google Patents

Abstract

The invention discloses a fire light-temperature composite intelligent monitoring warning device for highrise building, comprising a fire signal detector, a signal transmission device, a central processing unit, a data manager, a fire alarming controller and a warning device, wherein, one end of the data manager is connected with the fire alarming controller through a first analog-to-digital converter (ADC), while the other end is connected with the central processing unit through the signal transmission device; the central processing unit is also connected with the fire alarming controller which is connected with the warning device through a second digital-to-analog converter (DAC); the fire signal detector comprises a fire temperature detector and a fire luminosity detector which are respectively connected with the first ADC. The invention which adopts light-temperature composite fire detecting technology combines the characters of accurate measurement of heat detector and quick response of photodetector; moreover, the invention can solve the problems such as failure alarm and false alarm of a fire to a large extent and also can improve the response sensitivity of the detector.

Description

Tall building fire light-temperature composite intelligent monitoring prediction device

Technical field

The present invention relates to a kind of fire monitoring early-warning and predicting device, specifically be meant a kind of intelligence inspection prewarning forecasting apparatus for fire of high-rise building with light temperature compound detection and self-learning function.

Background technology

The generation of fire brings harm not only for human life, and will bring loss to social property.In recent years, the raising, wealth of society density that is accompanied by the socio-economic development level increases, fire type is enriched constantly, the loss sustainable growth that is caused by fire.Under the environment of current national economy high development, to sensitivity and the reliability that how to improve fire detector, the promptness and the accuracy that improve fire forecast propose more and more higher requirement.The fire of skyscraper has: therefore the characteristics that fire spreading is fast, evacuating personnel is difficult, the difficulty of putting out a fire to save life and property big, fire hidden danger is many have harmfulness.For guaranteeing the safety of people's lives and properties, the automatic fire alarm system design just becomes one of important contents in the high-rise building design.Use high-quality advanced person's fire monitoring early-warning and predicting device, accurately judge fire location, and predict accurately whether burning things which may cause a fire disaster can develop into fire, and fire rank and development degree are predicted, be convenient to put out a fire to save life and property timely, be even more important guaranteeing the skyscraper operation security.

Fire is to comprise mobile, heat and mass and chemical reaction and interactional combustion process thereof, burning can produce gas, gasoloid, smog, flame and a large amount of heat, be referred to as the fire parameter, by mensuration to these parameters, and based on the algorithm of these physical features design identification fire, fire detector just has been born.The heat detector of Chu Xianing the earliest, its principle of work is when fire takes place, and physical change will take place in the thermal sensing element in the detector, and the electric signal that physical change is converted to is transferred to fire alarm control unit subsequently.Owing to reasons such as spatial altitude or air flow, make high temperature of fire gas can't arrive ceiling, heat fire detector can't operate as normal; When the environment temperature of work was too high, heat fire detector was easy to produce wrong report.Along with the development of fire detection technology, sensitive detector had appearred afterwards, come work by surveying electromagnetic radiation that flame causes.Because the velocity of propagation of electromagnetic radiation is exceedingly fast, sensitive detector can in time respond quick breaking out of fire (as inflammable, combustible liquid fire), it is ideal detector to this class early fire alarming, in practice, the general ccd video camera that adopts, but ccd video camera can't be distinguished the difference of mobile high temp objects and fire, fails to report the police thereby may produce.

In present fire of high-rise building inspection prewarning forecasting apparatus, usually adopt single sense cigarette type sensor, temperature-sensitive optical cable or CCD (computer control demonstration video camera), its shortcoming is: not strong to high building structure and fire characteristics specific aim, monitoring means is single, poor reliability, as feel cigarette type sensor and can't survey the flame that the alcohol burning produces, the temperature-sensitive sensor then is difficult for finding smoldering fire, ccd video camera can't be distinguished the difference of mobile high temp objects and fire, fails to report the police thereby may produce; Simultaneously, existing sensitization, sense cigarette, temperature sensitive type Detection Techniques can only be surveyed flame or fire and occur in some search coverage, and can't determine the definite position that fire takes place, and in addition owing to the interference of environment, the situation of omission, wrong report also usually occurs.Compound fire detection technology has the performance of two or more detector simultaneously concurrently, can solve to fail to report, report by mistake, can also improve the response sensitivity of detector.

Summary of the invention

The objective of the invention is to overcome the shortcomings and deficiencies that existing fire of high-rise building inspection prewarning forecasting apparatus exists, provide a kind of based on light temperature compound detection technology, artificial intelligence and fuzzy control technology, have self-learning function, intelligence inspection prewarning forecasting apparatus for fire of high-rise building accurately and efficiently.

Purpose of the present invention is achieved through the following technical solutions:

A kind of tall building fire light-temperature composite intelligent monitoring prediction device comprises fire signal detector, apparatus for transmitting signal, central processing unit, data management system, fire alarm control unit and panalarm; Described data management system comprises data memory and the database that mutual signal connects, data memory one end is connected with fire signal detector by one of analog to digital converter, the other end is connected with central processing unit by apparatus for transmitting signal, central processing unit also is connected with fire alarm control unit, and described fire alarm control unit is connected with panalarm by two of digital to analog converter; Described fire signal detector comprises fire temperature detector and fire photometric detector, and the fire temperature detector is connected with one of analog to digital converter respectively with the fire photometric detector.

For realizing that further the object of the invention, described hygrosensor adopt fusible metal type constant temperature fire detector.Described photometric detector adopts infrared optical flame fire detector, is made up of infrarede emitting diode matrix plane emissive source of forming and the CCD camera receiving end that is provided with infrared filter.Described data memory also is connected with the anti-smoke control system of skyscraper, monitors each equipment running status.Described fire alarm control unit also is connected with manual pull station.Described panalarm comprises warning horn, Fire telephone, fire accident broadcast, fire failure illumination, linkage control device, fire extinguishing system control device and graphics device and standby power supply.

Described central processing unit is a computer management system, this system is connected with skyscraper system ventilation heat exchange measurement mechanism, based on the nonlinear kinetics mechanism exploitation of fire of high-rise building, the complicacy and the uncertainty of fire are carried out quantitative Analysis according to signals such as on-the-spot detecting temperature, luminosity.

The present invention compares with the early warning technology of existing building fire, has following advantage and effect:

(1) adopts the compound fire detection technology of light temperature, have heat detector simultaneously concurrently and measure accurate and sensitive detector reacts characteristics fast, can solve failing to report, reporting by mistake of the condition of a disaster largely, can also improve the response sensitivity of detector;

(2) the fire alarm rank that takes place of utilization fuzzy neural network technology prediction fire of high-rise building, the retrieval system that will predict the outcome is utilized the self-learning capability of neural network, constantly revises sample set and decision rule, realizes the high fault tolerance and the intellectuality of system;

(3) introduce nonlinear kinetics fire of high-rise building mechanism is carried out basic theory, set up the fire of high-rise building model in the different structure characteristics, according to signals such as on-the-spot detecting temperature, gas flow rate, flue gas concentration, pressure the complicacy and the uncertainty of fire are carried out quantitative Analysis, analyze the current condition of a fire and fire development trend, for the rescue and fire-fighting work strong theoretical foundation is provided, strengthen the reliability and the science of early warning system greatly.

Description of drawings

Fig. 1 is a structural representation of the present invention;

Fig. 2 is the theory diagram that data-carrier store shown in Figure 1 is judged the fire the condition of a disaster;

Fig. 3 the present invention judges whether fire takes place and the Positioning Principle block diagram;

Fig. 4 the present invention predicts the Nonlinear Processing process schematic block diagram of the condition of a disaster development.

Embodiment

The invention will be further described below in conjunction with example and accompanying drawing.

As shown in Figure 1, tall building fire light-temperature composite intelligent monitoring prediction device of the present invention, comprise one of fire temperature detector 1, fire photometric detector 2, analog to digital converter 3, data management system 4, monitor 5, apparatus for transmitting signal 6, central processing unit 7, fire alarm control unit 8, digital to analog converter 29, panalarm 10.Fire signal detector comprises that fire temperature detector 1 and fire photometric detector 2, two detectors are connected with one of analog to digital converter 3 respectively.Data management system 4 comprises data memory and the database that mutual signal connects, data memory one end is connected with fire signal detector by one of analog to digital converter 3, the other end is connected with central processing unit 7 by apparatus for transmitting signal 6, central processing unit 7 also is connected with fire alarm control unit 8, and described fire alarm control unit 8 is connected with panalarm 10 by 29 of digital to analog converter.

Fire temperature detector 1 is a heat detector, can adopt the temp.-determined type fire detector (as H8050 and JTW-DZ-262/062 type fixed temperature detector, and JTW-SD-130 bimetallic strip fixed temperature detector) or rate-of-rise detector (as JTW-MC-1302 metal bellows rate-of-rise detector), fire photometric detector 2 is sensitive detectors, can adopt ultraviolet optical flame fire detector (as JTG-ZM-GST9614 point type ultraviolet flame detector) or infrared optical flame fire detector (as the infrared optical flame fire detector of HWH-2 type).

One of analog to digital converter 3 (can adopt AD9200ARS10 position 20MSPS analog to digital converter or ADS52778 path 10 position 65MSPS analog to digital converter) is a digital signal with the fire disaster simulation conversion of signals of fire temperature detector 1 and 2 measurements of fire photometric detector, one of analog to digital converter 3 also links to each other with data management system 4, data management system comprises data-carrier store 4-1 and database 4-2, the information of fire detection signal is saved on the data-carrier store, data-carrier store can adopt built-in nonvolatile memory (as FM18L08 type high-speed data storer), the all types of skyscrapers of storage space fire reference pattern collection carries out pattern relatively among the database 4-2 when judging for fire.

Data management system 4 also is connected with the anti-smoke control system 12 of monitor 5 and skyscraper respectively, fire and evacuating personnel situation that monitor can adopt colour picture monitor (as JVC TM series and SONY SSC series colour picture monitor) or black-and-white monitor (as UJ23-LEE-136BM, SP712 or HS-BM093 type black-and-white monitor) to observe elevator and important Vomitory; The control procedure of the anti-smoke control system of skyscraper is: after central fire control point is received fire alarm signal, directly produce the unlatching of signal controlling exhaust valve, smoke exhaust fan startup, air-conditioning, pressure fan, fire-proof door etc. are closed, and receive the return signal and the fire resisting damper actuating signal of each equipment, monitor each equipment running status.

Data-carrier store 4-1 also is connected with central processing unit 7 by apparatus for transmitting signal 6, apparatus for transmitting signal adopts general in-situ (as Lon Bus etc.), signals such as the on-the-spot detecting temperature that central processing unit 7 comes according to the data-carrier store transmission, luminosity are set up the non-linear dynamic model of fire of high-rise building, and adopt fuzzy log on algorithm that the complicacy and the uncertainty of fire are carried out quantitative Analysis.

Central processing unit 7 also (can adopt JBC-QB-HD99 with fire alarm control unit 8, JB-QGZ-2002 or JB-TB-9800 type fire alarm control unit) connect, the fire characteristic physical quantity that central processing unit is obtained is delivered to fire alarm control unit 8, fire alarm control unit 8 (can adopt AD5601 by digital to analog converter 29, AD5621 or AD654 pattern number converter) be connected with panalarm 10, fire alarm control unit 8 is provided with manual pull station 11 (as YX8804, XHD-02 or FA-105 type manual pull station), panalarm 10 comprises the warning horn 10-1 that has equipped in the skyscraper building, Fire telephone 10-2, fire accident broadcast 10-3, fire failure illumination 10-4, linkage control device 10-5 (comprises hydrant, the automatic spray fire extinguishing, fire-proof door, fire resisting shutter, smoke exhaust fan, air conditioner facility, fire resisting damper, exhaust smoke valve, elevator, induced light, alarm bell etc.), carry out a series of continuous actions by the instruction that central processing unit sends, the employing measure starts fire-fighting equipment automatically; Fire extinguishing system control device 10-6, the work and the malfunction of demonstration fire pump are controlled opening, stopping of fire pump; Graphics device 10-7 comprises the monitor of elevator and main thoroughfare; Standby power supply 10-7 (can adopt EPSONEPS series emergency power system or MJ series fire emergency lighting power supply) is the emergency power supply unit of evacuating, illumination and other important one-level supply loads provide centrally connected power supply under fire.

The present invention adopts fuzzy neural network, the fire signal that utilizes detector, investigation, experiment, Theoretical Calculation to obtain is formed training sample set, train with fuzzy neural network technology, form the fire disaster intelligently prior-warning device that has high fault tolerance, complicated mode classification and debate knowledge.As shown in Figure 2, the detection neural network of the present invention's design, its formation comprises three input neurons, five hidden neurons and three output neurons.Three IN1, the IN2 on the left side, IN3 are input layer, and three signals of ventilation volume of sending of luminosity, temperature and the ventilating system sent of fire detector are transformed normalizing to [0,1] in actual applications, pass to input layer again; Three OT1 in the right, OT2, OT3 are output layer, represent fire probability respectively, fire probability, smoldering fire probability, the output valve scope also is [0,1]; IM1～IM5 between the input and output layer is for hiding layer, and input signal is delivered to output layer again after hiding layer.Respectively have 15 to be connected arc between IN (I) and IM (J) and OT (K), its weights are respectively Wij, Vjk.Summation from the input layer to the middle layer is defined as NET1 (j):

$\mathrm{NET}1\left(j\right)=\underset{i=1}{\overset{M}{\mathrm{\Σ}}}(\mathrm{INi}\·W_{\mathrm{ij}})$

The value of NETI (J) is that the output of hidden layer is transformed into [0,1] with the Sigmoid function;

$\mathrm{IMj}=\frac{1}{1+\exp [-\mathrm{NET}1\left(j\right)\·r1]}$ Similar have the middle layer to be defined as NET2 (k) to the summation of output layer:

$\mathrm{NET}2\left(k\right)=\underset{j=1}{\overset{N}{\mathrm{\Σ}}}(\mathrm{IMj}\·V_{\mathrm{jk}})$

Equally, NET2 (k) also is switched to [0,1]:

$\mathrm{OTk}=\frac{1}{1+\exp [-\mathrm{NET}2\left(k\right)\·r2]}$

The effect of r1 and r2 is a coefficient of revising Sigmoid function curve degree of tilt, is taken as 1.0 and 1.2 usually respectively.In this fire detecting system, use the study definition list of 12 kinds of patterns, as shown in the table.

Table 1

Numbering	Input			Output
										Smoke detector	Heat detector	Gas detector	Fire probability		The fire probability		The smoldering fire probability
	D	R	D	R	D	R
							1	0.1	0				1	0.7	0.661	0.6	0.702	0.9	0.802
2	0.3	0.5	1	0.9	0.885	0.9				0.889	0.1	0.037
							3	0.1	0				0.2	0.3	0.254	0.2	0.187	0.4	0.289
4	0.5	0.1	0.8	0.8	0.829	0.8				0.786	0.7	0.722
							5	0	0.3				0.1	0.1	0.094	0.1	0.098	0.1	0
6	0	0	1	0.4	0.453	0.7				0.588	0.3	0.376
							7	0	1				0	0.2	0.190	0.3	0.307	0.05	0
8	0.3	0.2	0.5	0.7	0.781	0.6				0.701	0.3	0.247
							9	0.6	0.8				0.8	0.95	0.902	0.95	0.904	0.05	0.073
10	0.2	0	0.3	0.6	0.542	0.4				0.431	0.75	0.756
							11	0.1	0				0.1	0.1	0.189	0.05	0.119	0.1	0.205
12	0.4	0.2	0	0.7	0.714	0.65				0.529	0.2	0.260

Like this, the square error E of m input pattern _mCan be expressed as with the square error summation E of 12 kinds of patterns:

$E_m=\underset{k=1}{\overset{3}{\mathrm{\Σ}}}\frac{1}{2}{(O{T}_k-T_k)}^2$

With $E=\underset{m=1}{\overset{12}{\mathrm{\Σ}}}\left(E_m\right)$

Regulate weights Wij, Vjk makes E reach minimum, has promptly finished the neural network learning process.After determining weights, the neural network input layer begins the potential value of pick-up probe, according to the method described above output valve being calculated, is that the smoldering fire probability compares with fire probability, fire probability respectively with the numerical value that calculates, and makes the judgement of whether breaking out of fire at last.As shown in Figure 3, fire signal (as cigarette, temperature etc.) is surveyed numerical value through digital to analog converter 3 conversions, enter the fuzzy neural network computing module 4-1-1 of data-carrier store 4-1, carry out the fuzzy diagnosis of condition of a fire size, the judgement signal B (0 or 1) whether recognition result output can breaking out of fire.

The differentiation result of the variation meeting interference monitoring instrument of environmental factors such as skyscraper mesoclimate, heat flux, natural light, wherein because difference between the differentiation output signal A that causes of the neural network error of calculation and the B, the study that the present invention adopts neural network that the result is differentiated in artificial supervision is improved, and realizes self study and adaptation function.

Fire of high-rise building is one on the one hand and is subjected to multiple factor affecting, complicated nonlinear characteristic, pyrolysis in the fire, on the other hand, although be subjected to the influence of numerous hot disaster factors, embody complicacy, but under similar environment and condition, but the generation of fire can embody similar rule with evolution.The skyscraper building can be divided into Zhongting, room, staircase, these several space-likes of elevator usually, building materials, structure, space characteristics, heat exchange air exchange system all design according to its standard-required in each space-like, thereby have similar burning situation with the space-like.Based on the understanding to skyscraper architectural feature and combustion process, the method that the present invention adopts nonlinear model and pattern-recognition to combine is predicted the development of fire in the skyscraper.According to the dissimilar spaces of skyscraper architectural feature, set up volatile matter pyrolysis and combustion model, combustible Hong combustion model, flame propagation model, fire spread model, the chaotic model of flue gas plume and the coupling map grid pattern that flue gas spreads, thereby construct the fire prediction model of considering various correlative factors.At dissimilar spaces,, accumulated relevant feature respectively, constituted the fire development set of patterns, be stored in the basic data of fire, sorted out, be stored among the fire data base 4-2 fundamental research, laboratory experiment, Field Research and numerical simulation.

As shown in Figure 4, the simulating signal that fire signal detector obtains is transferred to data-carrier store 4-1 by analog to digital converter 3 and concentrates, be transferred to central processing unit 7 by apparatus for transmitting signal 6 again, the ventilation heat exchange parameter that the measurement mechanism of skyscraper system ventilation heat exchange simultaneously 11 records also is transferred to central processing unit 6 by data-interface.When central processing unit 6 takes place to fire according to algorithm predicts, by addressing to monitor signal, obtain the particular location that fire takes place, and positioning signal is transferred to the fire development prediction module, by this positioning signal, characterize the detectable signal of current fire development degree: temperature, pressure, flue gas concentration, gas ingredients and ventilation condition, inquiry the type skyscraper space fire reference pattern collection in database 4-2, carry out pattern relatively, analyze current fire and be belong to glow, fire initial stage or belong to the big fire category.Then these detectable signals are imported into corresponding nonlinear prediction computation model, by volatile matter pyrolysis and combustion model, combustible Hong combustion model, flame propagation model, fire spread model, the chaotic model of flue gas plume and the coupling map grid pattern that flue gas spreads, real-time estimate is carried out in the development of fire.Predicting the outcome of pattern comparison and fire development, and the database 4-2 respective handling decision-making of storage in advance all is presented on the monitor 5.Simultaneously, the development degree of current fire characteristic signal and fire feeds back to database 4-2, replenishes the reference pattern collection.

Because fire phenomena has polytrope, some physical quantity is subjected to the influence of other factors of environment, instantaneous value shows certain randomness, thereby make actual detection to signal be difficult to and the pattern that provides fits like a glove, therefore, pattern has relatively adopted the method for fuzzy diagnosis among the present invention, judges by the approach degree size of object to be monitored and known mode.

In sum, the present invention designs and uses advanced detection algorithm and fire mode identification method to judge fire information, is the intelligent fire detection alarm system with " higher intelligence ".

During work, signal sensor is surveyed the scene and investigate the temperature that obtains, luminosity, data such as ventilation through analog to digital converter 3 signal data memory input 4-1, again the physical quantity signal change procedure is delivered to fire of high-rise building central processing unit 7 through apparatus for transmitting signal 6, analyze the fire characteristic amount that obtains through central processing unit 7 and send fire alarm control unit 8 to, the fire of high-rise building reference pattern that physical quantity signal change procedure and native system are set up compares, obtain prediction case after the contrast to the fire of high-rise building the condition of a disaster, make the judgement whether fire takes place, whether provide fire alarm signal according to this judgement decision again, judging has after the fire alarm, fire alarm is passed to panalarm 10 through digital to analog converter 9, and fire department is carried out the work of putting out a fire to save life and property after receiving fire alarm.Artificially fire alarm control unit 7 is made a response by manual fire alarm call point 11 alarm is implemented effectively, judgement of fire the condition of a disaster and fire alarm accuracy rate that device is made each time feed back to fire of high-rise building data-carrier store 4 through analog to digital converter, artificial neural network technology carries out self study with feedback data, constantly revise sample set and decision rule, and then improve the forest fire reference pattern; The deposit data that feeds back at last is in fire data base 4-2, as the basic data of later fire of high-rise building differentiation.The fire of high-rise building database that the design uses the non-linear mechanism of fire, fuzzy theory and artificial neural network technology to combine and set up, have the ability of self study and the process of Knowledge Discovery, obtain high training sample set of reliable fault-tolerance and decision rule, constantly the oneself replenishes and is perfect, help the mechanism research of fire of high-rise building and improve the intelligentized degree of fire alarm, improve accuracy, promptness and the reliability of fire of high-rise building fire alarm greatly.

Claims (6)

1. a tall building fire light-temperature composite intelligent monitoring prediction device is characterized in that this predictor comprises fire signal detector, apparatus for transmitting signal, central processing unit, data management system, fire alarm control unit and panalarm; Described data management system comprises data memory and the database that mutual signal connects, data memory one end is connected with fire signal detector by one of analog to digital converter, the other end is connected with central processing unit by apparatus for transmitting signal, central processing unit also is connected with fire alarm control unit, and described fire alarm control unit is connected with panalarm by two of digital to analog converter; Described fire signal detector comprises fire temperature detector and fire photometric detector, and the fire temperature detector is connected with one of analog to digital converter respectively with the fire photometric detector.

2. tall building fire light-temperature composite intelligent monitoring prediction device according to claim 1 is characterized in that: described hygrosensor adopts fusible metal type constant temperature fire detector.

3. tall building fire light-temperature composite intelligent monitoring prediction device according to claim 1, it is characterized in that: described photometric detector adopts infrared optical flame fire detector, is made up of infrarede emitting diode matrix plane emissive source of forming and the CCD camera receiving end that is provided with infrared filter.

4. according to each described tall building fire light-temperature composite intelligent monitoring prediction device of claim 1～3, it is characterized in that: described data memory also is connected with the anti-smoke control system of skyscraper.

5. tall building fire light-temperature composite intelligent monitoring prediction device according to claim 1 is characterized in that: described fire alarm control unit also is connected with manual pull station.

6. tall building fire light-temperature composite intelligent monitoring prediction device according to claim 1, it is characterized in that: described panalarm comprises warning horn, Fire telephone, fire accident broadcast, fire failure illumination, linkage control device, fire extinguishing system control device and graphics device and standby power supply.

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