CN102080569A - Distributed optical fiber temperature measurement-based fire early warning method for belt conveyor - Google Patents

Abstract

The invention relates to the field of coal mine safety, in particular to a distributed optical fiber temperature measurement-based fire early warning method for a belt conveyor. The method comprises the following steps of: dividing a temperature measuring optical fiber into a temperature measuring point, a channel and an area, and processing temperature data measured by the temperature measuring optical fiber by an absolute temperature early warning method, an area relative temperature difference early warning method, an area normal distribution early warning method, a measuring point temperature rise slope early warning method and a measuring point temperature rise variation trend early warning method to acquire a channel threshold early warning characteristic value, an area threshold early warning characteristic value, an area relative temperature early warning characteristic value, an area temperature normal distribution statistical characteristic value, a measuring point threshold early warning characteristic value, a measuring point temperature rise slope early warning characteristic value and a measuring point temperature rise accumulated trend early warning characteristic value; inputting the characteristic values and the measuring point temperature rise accumulated trend early warning characteristic value into a back propagation (BP) neural network model; and outputting a warning coefficient, an early warning coefficient and a safety coefficient by using the BP neural network model.

Description

Ribbon conveyer fire alarm method based on distributed optical fiber temperature measurement

Technical field

The present invention relates to the safety of coal mines field, particularly a kind of fire alarm method that is used for mine belt conveyor.

Background technology

Mine belt conveyor is owing to use for a long time, bring out fire easily, its fire inducement mainly contains following several respects: 1. cylinder skids: under the normal operation, the slip of the relative cylinder surface of adhesive tape generally is no more than 2%, if adhesive tape skids, then exist bigger relative slip between adhesive tape and the cylinder, and cause friction Temperature Rise, as can not in time finding,, temperature will cause fire in case rising to the adhesive tape ignition temperature. and the reason that common drive roll skids has: the back head coal piling of buying securities with all one's capital, anti-skidding glue serious wear on the cylinder, full load starting after stopping in emergency etc.; The main cause that driven cylinder skids then is that roller bearings is badly damaged or stuck.2. carrying roller fault: in the rubber conveyer firing accident, one of main cause that to cause the too high adhesive tape that ignites of carrying roller temperature rise be mining in recent years sealing-tape machine fire owing to carrying roller is stuck.Because the ambient conditions of down-hole is relatively poor, is easy to enter dust in the Idler bearing, the life-span is shorter, and after damage of bearings is stuck, adhesive tape will continue friction on the carrying roller surface, make a large amount of heat of carrying roller accumulation.The carrying roller temperature rises to very high, thus roasting combustion adhesive tape, and the coal-fired powder of the beans-and bullets shooter of going forward side by side enlarges the intensity of a fire rapidly.Also find in the investigation. mainly be that snub pulley does not change and causes that easily adhesive tape catches fire, because snub pulley, particularly near the snub pulley at tail place, carriage is overhead very near, very easily by clear and bright with on the coal dust that scatters surround, coal piling appears, cause the radiating condition variation of carrying roller, make stuck carrying roller temperature rise too high.3. spontaneous combustion of pulverized coal: exist a large amount of dumps on rubber conveyer ground along the line, owing to contact and oxidative heat generation with air, under the not smooth situation of radiating condition, the heat that oxidation generates greater than to around the heat that distributes, cause the temperature of coal to raise gradually and cause " glowing ", in case will spontaneous combustion form the intensity of a fire when reaching the burning-point of coal.4. outside burning things which may cause a fire disaster: except the above-mentioned fire that causes by sealing-tape machine itself, the Another reason that causes the sealing-tape machine fire is extraneous unexpected burning things which may cause a fire disaster, as artificial naked light, wire short-circuiting, down-hole electric substation catch fire, unreasonable field Welding, big spoil fall and produce fire by friction below the adhesive tape etc.

Domestic present rubber conveyer Integrated Protection System kind is many, and the manufacturer that scale is bigger mainly contains Tianjin Huaning electronics, Bake, Tianjin, institute of Chongqing coal section, Changzhou connection power automation, science and technology Changzhou, world automation academy etc.The domestic commonplace technology of rubber conveyer fire monitoring that is applied to has: temperature (containing the memorial alloy temperature pick up), smog, carbonomonoxide concentration, flame detector and heat-sensitive cable technology.Wherein main still based on smog, Carbon Monoxide Detection and temperature, realize that key positions such as rubber conveyer head, tail are carried out the condition of a fire to be surveyed.But present smog and Carbon Monoxide Detection technology exist very big limitation, and false alarm rate is very high during actual at the scene the use, and result of use is bad; The temperature detection technology has multiple, to technology such as memorial alloy and noncontact infrared measurement of temperature, all can not realize distributed, the continuous monitoring in whole transportation lane from traditional Pt resistance.

Summary of the invention

In view of this,, the invention discloses a kind of ribbon conveyer fire alarm method based on distributed optical fiber temperature measurement in order to address the above problem, can be to distributed, the continuous monitoring of carrying out in whole transportation lane.

The object of the present invention is achieved like this: based on the ribbon conveyer fire alarm method of distributed optical fiber temperature measurement, the thermometric optical fiber distributed type is arranged on the ribbon conveyer, wherein, at the crucial thermometric of ribbon conveyer position, thermometric optical fiber is installed by thermometric optical fiber heat conduction anchor clamps, and described ribbon conveyer fire alarm method based on distributed optical fiber temperature measurement comprises the steps:

1) thermometric optical fiber is divided into point for measuring temperature, passage, the zone, utilize absolute temperature early warning method, zone relative temperature difference early warning method, zone normal distribution early warning method, survey mark temperature rise slope early warning method and survey mark temperature rise variation tendency early warning method are handled the temperature data that thermometric optical fiber records, and obtain passage thresholding early warning characteristic value, zone thresholding early warning characteristic value, zone relative temperature early warning characteristic value, regional temperature normal distribution statistical characteristics, survey mark thresholding early warning characteristic value, survey mark temperature rise slope early warning characteristic value and survey mark temperature rise accumulative total trend early warning characteristic value;

2) with passage thresholding early warning characteristic value, regional thresholding early warning characteristic value, regional relative temperature early warning characteristic value, regional temperature normal distribution statistical characteristics, survey mark thresholding early warning characteristic value, survey mark temperature rise slope early warning characteristic value and survey mark temperature rise accumulative total trend early warning characteristic value input BP neural network model;

3) BP neural network model output alarm coefficient, early warning coefficient and safety factor.

Further, described BP neutral net;

Further, described BP neutral net hidden layer number is 5, is limited to 10000 on the training step number, the weights coefficient is got the random number between [1,1], learning rate η=0.5, inertia correction coefficient alpha=0.2, weight convergence factor ξ=0.001 and error convergence factor-beta=0.05;

Further, described absolute temperature early warning method comprises the steps: that specifically temperature that temperature-measuring system of distributed fibers is measured and predefined threshold signal compare, when in case signal amplitude surpasses thresholding, output early warning characteristic value is 1, otherwise output early warning characteristic value is the ratio of measured temperature and thresholding;

Further, described regional relative temperature difference early warning method specifically comprises the steps: the local maximum point retrieval is carried out with the temperature distribution history in this zone in the zone of dividing; The adjacent extreme point that retrieval is come out compares, if adjacent pole temperature difference surpasses thresholding, then exporting the early warning characteristic value is 1, otherwise output early warning characteristic value is the ratio of pole temperature difference value and thresholding;

Further, it is N that described regional normal distribution early warning method comprises the steps: to establish the interior sensor fibre effective length in zone, then this region memory is at N temperature spot, temperature sequence x (n) in this zone is carried out descending sort, and the heavy w=5% of weighting, the temperature spikes/low-points of this sequence is respectively leached N.w, sample average and the sample variance of utilizing filtered temperature sequence to carry out normal distribution are calculated, obtain this regional temperature Density Function of Normal Distribution, utilize Density Function of Normal Distribution, determine that each temperature spot is at this regional normal distribution probability, according to predetermined probabilities border limit normal distribution probability is judged, if greater than predetermined probabilities border limit, then export the early warning characteristic value is 1 to certain temperature spot at this regional normal distribution probability, otherwise output early warning characteristic value is the ratio on distribution probability and probability border;

Further, in the described survey mark temperature rise slope early warning method, the computational methods of slope adopt differential method:

$k\left(t\right)=\frac{\mathrm{dx}\left(t\right)}{\mathrm{dt}};$

The slope threshold s of survey mark is divided into two-stage s1, s2, and the value of two-stage thresholding is respectively:

s ₁＝0.11℃/min

s ₂＝0.1755℃/min

Shu Chu survey mark temperature rise slope early warning characteristic value K[y (t) then] as follows:

$K\left[y\left(t\right)\right]=\left\{\begin{array}{ccc}1.0& k\left(t\right)\&GreaterEqual;{\mathrm{<figure-callout\; id="2"\; label="s"\; filenames="HDA0000037530890000014.png"\; state="\{\{state\}\}">s</figure-callout>}}_2& \\ 0.5& (1+\frac{k\left(t\right)-s_1}{s_2-s_1})& {\mathrm{<figure-callout\; id="2"\; label="s"\; filenames="HDA0000037530890000014.png"\; state="\{\{state\}\}">s</figure-callout>}}_2>k\left(t\right)>s_1\\ 0.0& k\left(t\right)<{\mathrm{<figure-callout\; id="1"\; label="s"\; filenames="HDA0000037530890000013.png"\; state="\{\{state\}\}">s</figure-callout>}}_1& \end{array}\right.;$

Further, described survey mark temperature rise variation tendency early warning method specifically comprises the steps: to define the relative difference function d (n) between temperature and its stationary value:

d(n)＝x(n)-RW；

X (n) is the temperature of survey mark, and Rw is the stationary value before the survey mark;

Definition sum function a (n):

α(n)＝[α(n-1)+1]u(k(n-1)-s _k)；

Wherein u is a unit-step function, and Sk is a predefined thresholding, and its assurance only when the survey mark temperature data changes greatly, is just carried out the computing of temperature rise accumulative total;

Definition temperature rise accumulative total function:

$g\left(n\right)=d\left(n\right)u(\mathrm{\&alpha;}\left(n\right)-N)u(\frac{23.5}{\mathrm{\&Delta;T}}-\mathrm{\&alpha;}\left(n\right));$

The value of N is:

$N=0.638\&times;\frac{23.5}{\mathrm{\&Delta;T}};$

Temperature rise accumulative total early warning feature is output as:

$A\left[g\left(n\right)\right]=\left\{\begin{array}{cc}1& g\left(n\right)>s\\ \frac{g\left(n\right)}{s}& g\left(n\right)<s\end{array}\right.;$

S is a threshold value in the setting formula.

Beneficial effect of the present invention is as follows:

1, can be to distributed, the continuous monitoring of carrying out temperature and the early warning in whole transportation lane.

2, combination is carried out in seven kinds of temperature early warning, can greatly be improved the accuracy of early warning.

Description of drawings

In order to make the purpose, technical solutions and advantages of the present invention clearer, the present invention is described in further detail below in conjunction with accompanying drawing:

Fig. 1 is electrically connected schematic diagram for the thermometric main frame;

The temperature survey principle schematic of Fig. 2 optical fiber temperature-measurement main frame;

Fig. 3 is a kind of internal construction schematic diagram of thermometric optical fiber heat conduction anchor clamps;

Fig. 4 is the external structure schematic diagram of anchor clamps shown in Figure 3;

Fig. 5 is the structural representation of another kind of thermometric optical fiber heat conduction anchor clamps;

Fig. 6 is the installment state schematic diagram of heat conduction anchor clamps;

Fig. 7 is installed in the enlarged diagram at V-arrangement snub pulley place for the heat conduction anchor clamps;

Fig. 8 shows the ribbon conveyer fire alarm method flow schematic diagram based on distributed optical fiber temperature measurement.

The specific embodiment

Fig. 1 is in the ribbon conveyer fire alarm method based on distributed optical fiber temperature measurement, distribution type fiber-optic be electrically connected schematic diagram, as shown in Figure 1, thermometric optical fiber main frame has mouthful output of an amp-light mouth of basis/electricity, a power input interface.The light mouth is linked into main frame through ethernet optical fiber transceiver; The electricity mouth is exported the intrinsic safety signal after safety barrier is isolated.Main frame has two-way optical fiber input measurement passage, is respectively 1, the 2 tunnel.The grade that power input interface can insert the 50Hz alternating voltage is: 127V/220V/380V/660V AC; Power supply divides two-way output, and one tunnel output 24VDC is for inner DTS main frame, and one tunnel output 24VDC is for ethernet optical fiber transceiver.

Optical fiber temperature-measurement main frame in the present embodiment adopts the Raman time-domain reflection technology of light, its temperature survey principle as shown in Figure 2, when laser pulse during along Optical Fiber Transmission, its rear orientation light will be passed transmitting terminal back along optical fiber, by gathering, resolve rear orientation light, extract Raman-stoke occulting light and Raman-anti-Stockton light intensity, thereby obtained optical fiber along the road temperature; Measure the time that arrives transmitting terminal to scattered light simultaneously, just can calculate survey mark in the position of light along the road.

Fire early-warning system of the present invention is to utilize heat conduction anchor clamps conduction key point temperature detection and the direct surveyed area environment temperature of optical fiber, both detections combine and realize rubber conveyer non-blind area temperature monitoring, realize belt conveyor fire earlier detection, early warning under the coal mine.Fig. 3 is a kind of internal construction schematic diagram of thermometric optical fiber heat conduction anchor clamps, Fig. 4 is the external structure schematic diagram of these thermometric optical fiber heat conduction anchor clamps, as shown in the figure, the main body of these thermometric optical fiber heat conduction anchor clamps is that optical fiber is taken in dish 1, this optical fiber is taken in dish 1 and is adopted the good metal material of thermal conductivity to make, as red copper etc., taking in dish 1 medium position at optical fiber is provided with and is used to coil the fine chamber 1a that gives out light, through evidence, have only and sensor fibre is coiled in optical fiber takes in dish and go up and to obtain sufficient heat, therefore under the situation that adopts the coil modes of emplacement, must guarantee that also the placement length of optical fiber in optical fiber is taken in dish will reach 1m, fine chamber design must meet the requirement of optical fiber minimum disc loop diameter D 〉=6.5cm so dish is given out light, to satisfy the optical fiber consume;

As further improvement, these thermometric optical fiber heat conduction anchor clamps also comprise a protection box body, this protection box body comprises upper cartridge body 2 and lower box body 3, one end of upper cartridge body 2 and lower box body 3 is hinged, the other end can closedly relatively tighten, and optical fiber is taken in dish and 1 is arranged on lower box body 2 inside, the horizontal direction of lower box body 2 is provided with optical fiber inlet and optical fiber outlet and is provided with in the bottom of lower box body 2 to take in optical fiber coils the heat-conducting piece 4 that is connected, this heat-conducting piece 4 can adopt takes in optical fiber that dish 1 identical material is made and both can be made into one, and the effect of this heat-conducting piece is temperature conduction to the optical fiber at thermometric position is taken in dish 1; The base plane of lower box body 2 is provided with fastening devices for convenience detach 5, from practicality and operability, fastening devices 5 in the present embodiment has adopted magnetic suction disc, needs the thermometric of key monitoring position thereby can very like a cork the heat conduction chuck body be adsorbed on.

Fig. 5 is the structural representation of another kind of thermometric optical fiber heat conduction anchor clamps, as shown in the figure, these thermometric optical fiber heat conduction anchor clamps have adopted the heat pipe-type structure, promptly utilize heat pipe that the heat of heat-conducting piece is transmitted to the sensor fibre that is attached on the heat pipe, it has mainly comprised conducting strip 6, heat pipe 7 and fixed support device 8, in the present embodiment, thermometric optical fiber is located in inside heat pipe, conducting strip 6 selects for use direct applying of copper sheet and thermometric position to carry out conduction of heat, and heat pipe is connected with conducting strip 6 and heat pipe 7 is fixed on the top of fixed support device 8 by heat pipe pressing plate 7a, and fixed support device 8 is fixed near the thermometric position by retainer nut 9.

By accurate positioning optical waveguides, effective heat conduction optical fiber of 0.5m is installed on the heat pipe, thereby guarantees that this 0.5m optical fiber in the scope of spatial resolution 1m, can realize converting by 0.5m optical fiber the temperature rise of 1m optical fiber.Because the heat dissipation characteristics of heat pipe self is become reconciled, therefore must with heat pipe and thermometric optical fiber near heat pipe to the small part naked section, be arranged with windproof sheath, can guarantee that just sensor fibre absorbs maximum heats.

Fig. 6 is a heat conduction anchor clamps installment state schematic diagram, Fig. 7 is installed in the enlarged diagram at V-arrangement snub pulley place for the heat conduction anchor clamps, as shown in the figure, thermometric optical fiber heat conduction anchor clamps 10 can be set at cylinder such as rubber conveyer head, tail and ribbon conveyer each carrying roller (only having marked the local circumstance that is arranged on the upper supporting roller place among Fig. 6) along the line, and particular location comprises: the represented inboard axle head of V-type snub pulley that goes out among head drum bearing (ball) cover, aircraft tail cylinder end cap, tension drum end cap and Fig. 7.And the temperature-sensitive optical fiber that is arranged on thermometric heat conduction anchor clamps outside is monitored rubber conveyer space environment temperature along the line, emphasis monitoring return belt below float coal temperature, tail coal piling regional temperature.

The ribbon conveyer fire alarm method based on distributed optical fiber temperature measurement of present embodiment, all thermometric optical fiber is installed at each thermometric position by thermometric optical fiber heat conduction anchor clamps, the thermal conductive surface of thermometric optical fiber heat conduction anchor clamps directly contacts with the thermometric position and the temperature at this position is directly conducted to thermometric optical fiber, wherein, at the crucial thermometric of ribbon conveyer position, thermometric optical fiber is installed by thermometric optical fiber heat conduction anchor clamps, in practice, concrete crucial thermometric position comprises head drum bearing (ball) cover, aircraft tail cylinder end cap, tension drum end cap; The inboard axle head of V-type snub pulley; Described ribbon conveyer fire alarm method based on distributed optical fiber temperature measurement comprises the steps:

1) thermometric optical fiber is divided into point for measuring temperature, passage, the zone, utilize absolute temperature early warning method, zone relative temperature difference early warning method, zone normal distribution early warning method, survey mark temperature rise slope early warning method and survey mark temperature rise variation tendency early warning method are handled the temperature data that thermometric optical fiber records, and obtain passage thresholding early warning characteristic value, zone thresholding early warning characteristic value, zone relative temperature early warning characteristic value, regional temperature normal distribution statistical characteristics, survey mark thresholding early warning characteristic value, survey mark temperature rise slope early warning characteristic value and survey mark temperature rise accumulative total trend early warning characteristic value;

2) with passage thresholding early warning characteristic value, regional thresholding early warning characteristic value, regional relative temperature early warning characteristic value, regional temperature normal distribution statistical characteristics, survey mark thresholding early warning characteristic value, survey mark temperature rise slope early warning characteristic value and survey mark temperature rise accumulative total trend early warning characteristic value input BP neural network model;

3) BP neural network model output alarm coefficient, early warning coefficient and safety factor.Described BP neutral net hidden layer number is 5, is limited to 10000 on the training step number, and the weights coefficient gets [1,1] random number between, learning rate η=0.5, inertia correction coefficient alpha=0.2, weight convergence factor ξ=0.001 and error convergence factor-beta=0.05.

Step 2) in, specifying of each warning algorithm is as follows:

Absolute temperature early warning method

Temperature and predefined threshold signal that this algorithm is measured with temperature-measuring system of distributed fibers compare, in case when signal amplitude surpasses thresholding, just export the early warning characteristic signal.

The Threshold detection method algorithm of fibre optic temperature sensor: the temperature of establishing fibre optic temperature sensor is x (t), and near the environment temperature this temperature pick up is h (t), and comparison signal is y (t), and T is transforming function transformation function (heat conduction model), and then it can be expressed as:

y(t)＝T[x(t)-h(t)]+x(t) (1-1)

$D\left[y\left(t\right)\right]=\left\{\begin{array}{cc}1& y\left(t\right)>s\\ y\left(t\right)/s& y\left(t\right)\&le;s\end{array}\right.---(1-2)$

D[y (t) wherein]=1 expression temperature rise transfinites.S in the formula is divided into Three Estate, and it is first order early warning line that s1=50 is set respectively; S2=70 is a second level early warning line, and s3=90 is a third level early warning line.And for the non-fibre optic temperature sensor survey mark in the temperature-measuring system of distributed fibers, promptly environment temperature point h (t) algorithm is as follows:

$D\left[h\left(t\right)\right]=\left\{\begin{array}{cc}1& h\left(t\right)>e\\ h\left(t\right)/e& h\left(t\right)\&le;e\end{array}\right.---(1-3)$

Parameter e in the formula has represented the threshold value of environment temperature, and the setting of parameter e is divided into passage and regional two-stage.The passage thresholding is set to e _t=80, D[h (t)]=1 expression channel environment temperature over-range, D[h (t)]=h (t)/er represents the ratio between channel environment temperature and the thresholding; Regional temperature thresholding e _rAccording to environmental differences, its parameter setting is generally less than e _tSpecifically being provided with needs to decide according to the regional temperature characteristic.

Zone relative temperature algorithm

Zone relative temperature algorithm is applicable to a certain specific region that rubber conveyer has been divided, and the temperature distribution history in this zone is carried out the local maximum point retrieval; The adjacent extreme point that retrieval is come out compares.If certain on the temperature distribution history is x (n) a bit, then its condition that satisfies extreme value is as follows:

$\left\{\begin{array}{c}x\left(n\right)>x(n-1)\\ x\left(n\right)>x(n+1)\end{array}\right.---(1-4)$

The extreme point x (n) that satisfies this condition is designated as f (n).Because the continuity of Temperature Distribution if adjacent pole temperature difference surpasses thresholding s, promptly satisfies formula (1-4), then exports the early warning characteristic value.

$D\left[f\left(n\right)\right]=\left\{\begin{array}{cc}1& [f\left(n\right)-f(n-1)>s]\left|\right[f\left(n\right)-f(n-1)>s]\\ \max /s& \max (f\left(n\right)-f(n-1),f\left(n\right)-f(n-1))\&le;s\end{array}\right.---(1-5)$

Zone relative threshold s is traditionally arranged to be 4, D[f (n)]=1, represent that regional relative temperature transfinites; D[f (n)]=max/s, represent the ratio of regional relative temperature and thresholding.When if regional relative temperature transfinites, then need to calculate this temperature x (n) at the shared weighted value A of this regional temperature thresholding et _w[x (n)], that is:

$A_w\left[x\left(n\right)\right]=\left\{\begin{array}{cc}\frac{x\left(n\right)}{e_r}& 0<x\left(n\right)<e_r\\ 1& x\left(n\right)\&GreaterEqual;e_r>0\end{array}\right.---(1-6)$

A in the formula _wThe span of [x (n)] be (0,1].Simultaneously with D[f (n)] and A _w[x (n)] is as the feature early warning output of regional relative temperature algorithm.

Regional temperature normal distribution warning algorithm

Suppose that the sensor fibre effective length is N in this zone, then this region memory is at N temperature spot, and wherein N is at least greater than 100.In order to filter The noise, the temperature sequence x (n) in this zone is carried out descending sort, and the heavy w=5% of weighting, the temperature spikes/low-points of this sequence is respectively leached N.w.Sample average and the sample variance of utilizing filtered temperature sequence to carry out normal distribution are calculated.

$\stackrel{\&OverBar;}{E}=\underset{n=i}{\overset{N(1-2w)}{\mathrm{\&Sigma;}}}x\left(n\right)---(1-7)$

$S_{\mathrm{\&sigma;}2}=\frac{1}{N(1-2w)-1}\underset{n=i}{\overset{N(1-2w)}{\mathrm{\&Sigma;}}}{[x\left(n\right)-\stackrel{\&OverBar;}{E}]}^2---(1-8)$

Thereby it is as follows to obtain this regional temperature Density Function of Normal Distribution:

$f\left[x\left(n\right)\right]=\frac{1}{\sqrt{2\mathrm{\&pi;}{S}_{\mathrm{\&sigma;}2}}}\exp [-\frac{{[x\left(n\right)-\stackrel{\&OverBar;}{E}]}^2}{2S_{\mathrm{\&sigma;}2}}]---(1-9)$

Utilize Density Function of Normal Distribution, determine that each temperature spot is at this regional normal distribution probability f[x (n)], whether the empirical probability border limit p=0.01 according to experiment is obtained judges and reports to the police, that is:

As f[x (n)] during greater than p, S[f[x (n)]]=1 feature early warning output as regional temperature normal distribution warning algorithm.

Survey mark temperature rise slope warning algorithm

The computational methods of slope adopt differential method:

$k\left(t\right)=\frac{\mathrm{dx}\left(t\right)}{\mathrm{dt}}---(1-11)$

In practice, slope is generally used Δ X (t)=X (t ₂)-X (t ₁), Δ T=t ₂-t ₁Time in temperature-measuring system of distributed fibers sampling interval, t ₂Be current time, t ₁Be previous moment.In order to improve temperature slope computation's reliability and antijamming capability, the survey mark temperature data average and delay process have been carried out.

Slope threshold s for survey mark is divided into two-stage s1, s2, and the value of two-stage thresholding is respectively:

s ₁＝0.11(℃/min)

s ₂＝0.1755(℃/min)

Then survey mark temperature rise slope early warning feature is exported K[y (t)] as follows:

$K\left[y\left(t\right)\right]=\left\{\begin{array}{ccc}1.0& k\left(t\right)\&GreaterEqual;s_2& \\ 0.5& (1+\frac{k\left(t\right)-s_1}{s_2-s_1})& {\mathrm{<figure-callout\; id="2"\; label="s"\; filenames="HDA0000037530890000014.png"\; state="\{\{state\}\}">s</figure-callout>}}_2>k\left(t\right)>{\mathrm{<figure-callout\; id="1"\; label="s"\; filenames="HDA0000037530890000013.png"\; state="\{\{state\}\}">s</figure-callout>}}_1\\ 0.0& k\left(t\right)<s_1& \end{array}\right.---(1-12)$

Survey mark temperature rise variation tendency algorithm

The temperature of survey mark is x (n), and the stationary value before the survey mark is Rw, the relative difference function d (n) between definition temperature and its stationary value.

d(n)＝x(n)-RW (1-13)

In order to overcome interference such as noise, calculate meaningfully Cai consider that the survey mark temperature data has only when changing significantly, introduced a sum function a (n):

α(n)＝[α(n-1)+1]u(k(n-1)-s _k) (1-14)

Wherein u is a unit-step function, Sk=0.11 (℃/min) be a predefined thresholding, its only guarantees just to carry out totally computing of temperature rise when the survey mark temperature data changes greatly.Then can define temperature rise accumulative total function:

$g\left(n\right)=d\left(n\right)u(\mathrm{\&alpha;}\left(n\right)-N)u(\frac{23.5}{\mathrm{\&Delta;T}}-\mathrm{\&alpha;}\left(n\right))---(1-15)$

N be one with calculate the relevant value of temperature rise accumulative total siding-to-siding block length.Only calculate temperature rise accumulative total when α (n) 〉=N, as α (n) 〉=23.5/ Δ T, g (n)=0 reenters the next accumulative total cycle.Choosing the temperature rise cumulative time is 23.5min, and Δ T is the time in temperature data sampling interval, adds certain redundancy, and the value of N is at present:

$N=0.638\&times;\frac{23.5}{\mathrm{\&Delta;T}}---(1-16)$

Temperature rise accumulative total early warning feature is output as:

$A\left[g\left(n\right)\right]=\left\{\begin{array}{cc}1& g\left(n\right)>s\\ \frac{g\left(n\right)}{s}& g\left(n\right)<s\end{array}\right.---(1-17)$

S=25 in the setting formula, A[g (n)] for the output of temperature rise accumulative total early warning feature, for characterizing the weighted value of temperature rise accumulative total degree.

The above only preferably is not limited to the present invention for of the present invention, and obviously, those skilled in the art can carry out various changes and modification and not break away from the spirit and scope of the present invention the present invention.Like this, if of the present invention these are revised and modification belongs within the scope of claim of the present invention and equivalent technologies thereof, then the present invention also is intended to comprise these changes and modification interior.

Claims (8)

1. based on the ribbon conveyer fire alarm method of distributed optical fiber temperature measurement, it is characterized in that: the thermometric optical fiber distributed type is arranged on the ribbon conveyer, wherein, at the crucial thermometric of ribbon conveyer position, thermometric optical fiber is installed by thermometric optical fiber heat conduction anchor clamps, and described ribbon conveyer fire alarm method based on distributed optical fiber temperature measurement comprises the steps:

1) thermometric optical fiber is divided into point for measuring temperature, passage, the zone, utilize absolute temperature early warning method, zone relative temperature difference early warning method, zone normal distribution early warning method, survey mark temperature rise slope early warning method and survey mark temperature rise variation tendency early warning method are handled the temperature data that thermometric optical fiber records, and obtain passage thresholding early warning characteristic value, zone thresholding early warning characteristic value, zone relative temperature early warning characteristic value, regional temperature normal distribution statistical characteristics, survey mark thresholding early warning characteristic value, survey mark temperature rise slope early warning characteristic value and survey mark temperature rise accumulative total trend early warning characteristic value;

2) with passage thresholding early warning characteristic value, regional thresholding early warning characteristic value, regional relative temperature early warning characteristic value, regional temperature normal distribution statistical characteristics, survey mark thresholding early warning characteristic value, survey mark temperature rise slope early warning characteristic value and survey mark temperature rise accumulative total trend early warning characteristic value input BP neural network model;

3) BP neural network model output alarm coefficient, early warning coefficient and safety factor.

2. a kind of ribbon conveyer fire alarm method based on distributed optical fiber temperature measurement as claimed in claim 1 is characterized in that: described BP neutral net.

3. a kind of ribbon conveyer fire alarm method as claimed in claim 2 based on distributed optical fiber temperature measurement, it is characterized in that: described BP neutral net hidden layer number is 5, be limited to 10000 on the training step number, the weights coefficient gets [1,1] random number between, learning rate η=0.5, inertia correction coefficient alpha=0.2, weight convergence factor ξ=0.001 and error convergence factor-beta=0.05.

4. as each described a kind of ribbon conveyer fire alarm method in the claim 1 to 3 based on distributed optical fiber temperature measurement, it is characterized in that: described absolute temperature early warning method comprises the steps: that specifically temperature that temperature-measuring system of distributed fibers is measured and predefined threshold signal compare, when in case signal amplitude surpasses thresholding, output early warning characteristic value is 1, otherwise output early warning characteristic value is the ratio of measured temperature and thresholding.

5. as each described a kind of ribbon conveyer fire alarm method in the claim 1 to 3 based on distributed optical fiber temperature measurement, it is characterized in that: described regional relative temperature difference early warning method specifically comprises the steps: the local maximum point retrieval is carried out with the temperature distribution history in this zone in the zone of dividing; The adjacent extreme point that retrieval is come out compares, if adjacent pole temperature difference surpasses thresholding, then exporting the early warning characteristic value is 1, otherwise output early warning characteristic value is the ratio of pole temperature difference value and thresholding.

6. as each described a kind of ribbon conveyer fire alarm method in the claim 1 to 3 based on distributed optical fiber temperature measurement, it is characterized in that: it is N that described regional normal distribution early warning method comprises the steps: to establish the interior sensor fibre effective length in zone, then this region memory is at N temperature spot, temperature sequence x (n) in this zone is carried out descending sort, and the heavy w=5% of weighting, the temperature spikes/low-points of this sequence is respectively leached N.w, sample average and the sample variance of utilizing filtered temperature sequence to carry out normal distribution are calculated, obtain this regional temperature Density Function of Normal Distribution, utilize Density Function of Normal Distribution, determine that each temperature spot is at this regional normal distribution probability, according to predetermined probabilities border limit normal distribution probability is judged, if certain temperature spot is limit greater than the predetermined probabilities border at this regional normal distribution probability, then exporting the early warning characteristic value is 1, otherwise output early warning characteristic value is the ratio on distribution probability and probability border.

7. as each described a kind of ribbon conveyer fire alarm method based on distributed optical fiber temperature measurement in the claim 1 to 3, it is characterized in that: in the described survey mark temperature rise slope early warning method, the computational methods of slope adopt differential method:

$k\left(t\right)=\frac{\mathrm{dx}\left(t\right)}{\mathrm{dt}};$

The slope threshold s of survey mark is divided into two-stage s1, s2, and the value of two-stage thresholding is respectively:

s ₁＝0.11℃/min

s ₂＝0.1755℃/min

Shu Chu survey mark temperature rise slope early warning characteristic value K[y (t) then] as follows:

$K\left[y\left(t\right)\right]=\left\{\begin{array}{ccc}1.0& k\left(t\right)\&GreaterEqual;s_2& \\ 0.5& (1+\frac{k\left(t\right)-s_1}{s_2-s_1})& s_2>k\left(t\right)>s_1\\ 0.0& k\left(t\right)<s_1& \end{array}\right..$

One kind as in the claim to 3 as described in each based on the paving method of the ribbon conveyer fire alarm method of distributed optical fiber temperature measurement, it is characterized in that: described survey mark temperature rise variation tendency early warning method specifically comprises the steps: to define the relative difference function d (n) between temperature and its stationary value:

d(n)＝x(n)-RW；

X (n) is the temperature of survey mark, and Rw is the stationary value before the survey mark;

Definition sum function a (n):

α(n)＝[α(n-1)+1]u(k(n-1)-s _k)；

Wherein u is a unit-step function, and Sk is a predefined thresholding, and its assurance only when the survey mark temperature data changes greatly, is just carried out the computing of temperature rise accumulative total;

Definition temperature rise accumulative total function:

$g\left(n\right)=d\left(n\right)u(\mathrm{\&alpha;}\left(n\right)-N)u(\frac{23.5}{\mathrm{\&Delta;T}}-\mathrm{\&alpha;}\left(n\right));$

The value of N is:

$N=0.638\&times;\frac{23.5}{\mathrm{\&Delta;T}};$

Temperature rise accumulative total early warning feature is output as:

$A\left[g\left(n\right)\right]=\left\{\begin{array}{cc}1& g\left(n\right)>s\\ \frac{g\left(n\right)}{s}& g\left(n\right)<s\end{array}\right.;$

S is a threshold value in the setting formula.

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