CN108506041A - A kind of dynamic disaster mode method for early warning based on Real-time Monitoring Data - Google Patents
A kind of dynamic disaster mode method for early warning based on Real-time Monitoring Data Download PDFInfo
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- CN108506041A CN108506041A CN201810101019.3A CN201810101019A CN108506041A CN 108506041 A CN108506041 A CN 108506041A CN 201810101019 A CN201810101019 A CN 201810101019A CN 108506041 A CN108506041 A CN 108506041A
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- early warning
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- time monitoring
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- dynamic disaster
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- E—FIXED CONSTRUCTIONS
- E21—EARTH DRILLING; MINING
- E21F—SAFETY DEVICES, TRANSPORT, FILLING-UP, RESCUE, VENTILATION, OR DRAINING IN OR OF MINES OR TUNNELS
- E21F17/00—Methods or devices for use in mines or tunnels, not covered elsewhere
- E21F17/18—Special adaptations of signalling or alarm devices
Abstract
The invention belongs to safety production technique fields, and in particular to a kind of dynamic disaster mode method for early warning based on Real-time Monitoring Data includes the following steps：(1) each supplemental characteristic of mine power disaster is recorded according to mounted a variety of real-time monitoring sensors；(2) using record data sequence q early period (x) that dynamic disaster occurs as sample data, a continuously differentiable mode function f (x) and thereon envelope S (x) are established；(3) according to the relativeness of S (x) and f (x) and the derivative f'(x of the change rate Δ S (x) and f (x) of Real-time Monitoring Data) relativeness, calculate the possibility of generation dynamic disaster.The application utilizes one mode function of historical data configurations, is shown according to the monitoring of mine power disaster developing state, realizes and carries out on-line early warning reconciliation police to mine power disaster.
Description
Technical field
The invention belongs to safety production technique fields, and in particular to a kind of dynamic disaster mode based on Real-time Monitoring Data
Method for early warning.
Background technology
Mine power disaster, including bump (rock burst), coal and gas prominent, gushing water are permeable etc. that belong to mine great
Disaster, once this kind of disaster occurs will all cause heavy losses to the human life in mine and property.Therefore, to mine power calamity
Harmful advanced prediction, forecast and early warning just seems of crucial importance.
In the prior art, for the mine power disasters such as coal and gas prominent, bump, gushing water be permeable, can pass through
Micro seismic monitoring, crustal stress detection, electromagnetic radiation monitoring, acoustic emission monitor(ing), gas emission monitoring, water yield monitoring, lane are installed
Indirectly on-line monitoring system carries out numerical value for road displacement monitoring, the resistance of bolt monitoring, support resistance monitoring, roof delamination monitoring etc.
Monitoring, but how the accurate prediction of mine power disaster progress and early warning solution to be warned using these monitoring data, at present
There are no a reliable methods.
But by analyzing real case, discovery monitoring data have mine power disaster the presentation attributes of universality, because
This provides a kind of dynamic disaster mode method for early warning based on implementation monitoring data, is very necessary.
Invention content
It is above-mentioned pre- for mine power disaster early warning without effective ways in the prior art it is an object of the invention to solve
The problem of report, provides a kind of dynamic disaster mode method for early warning based on Real-time Monitoring Data, according to mine power disaster correlation
Monitoring data show situation, and the possibility that mine power disaster occurs carries out sentencing knowledge.
The present invention is achieved by the following technical solutions：
A kind of dynamic disaster mode method for early warning based on Real-time Monitoring Data, includes the following steps：
(1) each supplemental characteristic of mine power disaster is recorded according to mounted a variety of real-time monitoring sensors；
(2) it using record data sequence q early period (x) that dynamic disaster occurs as sample data, establishes one and continuously may be used
Micro- mode function f (x) remembers xdIt is the upward peak point of f (x), fd=f (xd), the coenvelope line of q (x) is S (x)；
(3) according to the relativeness of S (x) and f (x) and the derivative of the change rate Δ S (x) and f (x) of Real-time Monitoring Data
F'(x relativeness) calculates the possibility that dynamic disaster occurs.
Further, the step (3) includes the following steps：
(31) according to the sampling period of monitoring sensor or frequency, setup algorithm step delta x；
(32) for monitoring ordered series of numbers S (x) in real time, once there is some x and xmSo that：S(x-Δx)≥f(xmΔ x) is simultaneously
AndThen take x0=x- Δ x, subsequently enter the early warning period；
(33) as time goes by x points (x >=x0), carry out on-line early warning according to rule.
Further, the on-line early warning rule in step (33) includes conciliating alert three kinds of state without alert state, alert status,
Wherein：
(a) when meeting fd＞ S (x) >=f (xm), and
It takesAs p≤0.2, without alert state, otherwise to enter alert status；
(b) when meeting S (x-2 Δs x) >=fd, and S (x) ＜ S (x- Δ x) ＜ S (x-2 Δs x)；
Other dynamic disaster occurrence factors in addition to monitor value are referred at this time, if other factors tend to disaster, are entered
Otherwise alert status enters the alert state of solution, and return to step (32)；
(c) when meeting S (x-2 Δ x) ＜ f (x-2 Δ x) ＜ fd, and ((x-2 Δ x) enter x- Δ x) ＜ S S (x) ＜ S
The alert state of solution, and return to step (32).
Further, in the situation (a), when the greens of p≤0.2 are without alert state, grading forewarning system is otherwise carried out, according to early warning
Rank is divided into level-one early warning to level Four early warning from low to high；
Wherein, when p ∈ (0.2,0.4] carry out level-one early warning, if p ∈ (0.4,0.6] carry out two level early warning, if p ∈
(0.6,0.8] three-level early warning is carried out, if p ＞ 0.8 carry out level Four early warning.
Compared with prior art, the beneficial effects of the invention are as follows：
The present invention is directed to mine power disaster mode early warning problem, gives a kind of power calamity based on Real-time Monitoring Data
Evil mode method for early warning utilizes microseism energy monitoring, microseism frequency monitoring, in-situ stress monitoring, the monitoring of electromagnetic radiation amplitude, electromagnetism
Radiation frequency monitoring, the monitoring of sound emission frequency monitoring, gas emission, water yield monitoring, Observation of rock displacement of roadway, the resistance of bolt prison
Survey, support resistance monitoring, roof delamination monitoring etc. find its monitoring to the presentation attributes of a universality of mine power disaster
Data decline to a great extent suddenly after lasting rising after a period of time, otherwise disaster accident occurs at this time or can temporarily exclude
The possibility that disaster occurs.The invention is exactly the related monitoring number by the different dynamic disaster to different mine different zones
According to, using historical data construct a mode function, show situation according to mine power disaster correlation monitoring data, to mine
The possibility that dynamic disaster occurs carries out sentencing knowledges, includes that the mines such as coal and gas prominent, bump, gushing water be permeable are moved from realizing
The online real-time dynamic early-warning reconciliation police of power disaster, to reach effective early warning of mine power disaster and prevent in advance.
In addition, the method for the present invention principle is reliable, step is simple, has very extensive application prospect.
It can be seen that compared with prior art, the present invention with substantive distinguishing features outstanding and significantly improving, implementation
Advantageous effect be also obvious.
Description of the drawings
Fig. 1 is a kind of dynamic disaster mode method for early warning flow chart based on Real-time Monitoring Data provided by the invention.
Specific implementation mode
Present invention is further described in detail below in conjunction with the accompanying drawings：
Embodiment 1
A kind of dynamic disaster mode method for early warning based on Real-time Monitoring Data provided in this embodiment, as shown in Figure 1, packet
Include following steps：
(1) each supplemental characteristic of mine power disaster is recorded according to mounted a variety of real-time monitoring sensors；
(2) it using record data sequence q early period (x) that dynamic disaster occurs as sample data, establishes one and continuously may be used
Micro- mode function f (x) remembers xdIt is the upward peak point of f (x), fd=f (xd), the coenvelope line of q (x) is S (x)；
(3) according to the relativeness of S (x) and f (x) and the derivative of the change rate Δ S (x) and f (x) of Real-time Monitoring Data
F'(x relativeness) calculates the possibility that dynamic disaster occurs.
Further, the step (3) includes the following steps：
(31) according to the sampling period of monitoring sensor or frequency, setup algorithm step delta x；
(32) for monitoring ordered series of numbers S (x) in real time, once there is some x and xmSo that：S(x-Δx)≥f(xmΔ x) is simultaneously
AndThen take x0=x- Δ x, subsequently enter the early warning period；
(33) as time goes by x points (x >=x0), carry out on-line early warning according to rule.
Further, the on-line early warning rule in step (33) includes conciliating alert three kinds of state without alert state, alert status,
Wherein：
(a) when meeting fd＞ S (x) >=f (xm), and
It takesAs p≤0.2, without alert state, otherwise to enter alert status；
(b) when meeting S (x-2 Δs x) >=fd, and S (x) ＜ S (x- Δ x) ＜ S (x-2 Δs x)；
Other dynamic disaster occurrence factors in addition to monitor value are referred at this time, if other factors tend to disaster, are entered
Otherwise alert status enters the alert state of solution, and return to step (32)；
In this step, the coenvelope line of monitoring data sequence alreadys exceed mode peak, and begins to decline.At this moment it can refer to
With the relevant other factors of dynamic disaster, such as：Geological structure, coffer mechanics property and other monitorings in addition to the monitor value
Parameter is directly entered alarm condition if other factors also tend to the generation of disaster.
(c) when meeting S (x-2 Δ x) ＜ f (x-2 Δ x) ＜ fd, and ((x-2 Δ x) enter x- Δ x) ＜ S S (x) ＜ S
The alert state of solution, and return to step (32).
Further, in the situation (a), when the greens of p≤0.2 are without alert state, grading forewarning system is otherwise carried out, according to early warning
Rank is divided into level-one early warning to level Four early warning from low to high；
Wherein, when p ∈ (0.2,0.4] carry out level-one early warning, if p ∈ (0.4,0.6] carry out two level early warning, if p ∈
(0.6,0.8] three-level early warning is carried out, if p ＞ 0.8 carry out level Four early warning.
In early warning, different monitoring parameters can be directed to, different mode function f is built for different environment and place
(x), according to the coenvelope line sequence row S (x) of real time data, the cycle of above-mentioned steps 3 is constantly executed, carries out early warning-solution police-early warning
Deng.
Embodiment 2
A kind of dynamic disaster mode method for early warning based on Real-time Monitoring Data provided in this embodiment, including following step
Suddenly：
(1) it is directed to the dynamic disaster mode early warning problem of the different zones in different mines, one or more real-time prisons are installed
Survey sensor, monitor and record multiple data in real time, as microseism energy and change rate, microseism frequency and change rate, crustal stress and
Change rate, electromagnetic radiation amplitude and change rate, frequency of electromagnetic radiation and change rate, sound emission frequency and change rate, Gas
Amount and change rate, water yield and change rate, roadway displacement and change rate, the resistance of bolt and change rate, support resistance and change rate,
Roof delamination and change rate etc..
(2) using record monitoring data sequence q early period (x) when dynamic disaster occurs as sample data, one is established
Continuously differentiable mode function f (x), method for building up are to find an early warning period [x0,x1], if S (x) is as sample
The coenvelope line of monitoring data sequence q (x), in early warning period [x0,x1] in start to continue rising, reach peak point xd∈
[x0,x1] decline suddenly afterwards, and remember T=xd-x0, fd=f (xd), f0=f (x0), it is a tolerance to give a positive number δ ＞ 0.
In the present embodiment, involved mode function f (x) is：
Wherein, A, B, a, b are modal parameter.
It is found that the peak position of f (x) is：
The change rate of f (x) is：
According to specific mine, specific region and dynamic disaster type and sensor type, according to historical record, to parameter
A modality-instance is established in the fitting of A, B, a, b, and data provided in this embodiment are as follows：
One driving face of certain coal mine has occurred gas burst accident at the 11 of certain day, before accident from 5 when to 11
When the face gas outburst amount monitor value that is averaged be shown in Table 1.
1 face gas of table is averaged outburst amount monitor value
According to the mode function of formula (1), being fitted to the data in table 1 can obtain：
A=6.6274841936526
B=4.70241227473465
B=9.64962150468427
A=4.03840985253177
Fitting result is calculated according to this data, is shown in Table 2.
2 initial data of table and and fitting result
| Serial number | 1 | 2 | 3 | 4 | 5 |
| Time (h) | 5 | 8 | 9 | 10 | 11 |
| Monitoring data center line value | 0.3 | 10 | 16 | 18 | 13 |
| Fitting result f (x) | 0.264 | 9.925 | 16.125 | 17.897 | 13.043 |
As can be seen from Table 2, the f (x) being fitted to and initial data are coincide fine, and its maximum of points is：
(3) according to Real-time Monitoring Data sequence S (x) and the relativeness of f (x) and the change rate Δ of Real-time Monitoring Data
The derivative f'(x of S (x) and f (x)) relativeness, and dynamic disaster occurs to calculate in conjunction with other correlative factors after decline
Possibility.
In the present embodiment, it is material calculation to take Δ x=0.05h, and δ=0.5 illustrates how to carry out in the present embodiment below
Real-time mode early warning.
At certain x moment, S (x)=13.243, (x- Δs x)=12.924 S are obtained.
By S (x)=13.243, mode function value is found near the 13.243 and point x no more than 13.243m=8.5, this
Shi You：
f(xm)=13.2427
d(xm)=6.44
f(xmΔ x)=12.919
d(xmΔ x)=6.518
At this point, S (x- Δs x) >=f (xmΔ x) is set up；
And exist：
d(xmΔ x)-δ=f'(xmΔ x) -0.5=6.518-0.5=6.018
It sets up, takes x0=xmΔ x is calculated, into the early warning period.
Meet f at this timed＞ S (x) >=f (xm), and
It obtains
It is shown in green without alert state in the present embodiment in without alert state at this point, p≤0.2.
When the time elapse again 1 it is small when after, i.e. xm=9.5, obtain corresponding numerical value：
S (x)=17.901
(x- Δs x)=17.754 S
f(xm)=17.855
d(xm)=1.891
f(xmΔ x)=17.752
d(xmΔ x)=2.2325；
At this point,
And meet
fd＞ S (x) >=f (xm), and
It can be calculated
Due to p >=0.8, so level Four early warning should be carried out, red early warning is shown as in the present embodiment.
The present invention utilizes historical data by the related monitoring data of the different dynamic disaster to different mine different zones
A mode function is constructed, shows situation according to mine power disaster correlation monitoring data, mine power disaster is occurred
Possibility carries out sentencing knowledge, from realize include the mine power disasters such as coal and gas prominent, bump, gushing water be permeable online reality
When dynamic early-warning reconciliation police, to reach effective early warning of mine power disaster and prevent in advance.
Above-mentioned technical proposal is one embodiment of the present invention, for those skilled in the art, at this
On the basis of disclosure of the invention application process and principle, it is easy to make various types of improvement or deformation, be not limited solely to this
Invent method described in above-mentioned specific implementation mode, therefore previously described mode is only preferred, and and without limitation
The meaning of property.
Claims (4)
1. a kind of dynamic disaster mode method for early warning based on Real-time Monitoring Data, which is characterized in that include the following steps：
(1) each supplemental characteristic of mine power disaster is recorded according to mounted a variety of real-time monitoring sensors；
(2) using record data sequence q early period (x) that dynamic disaster occurs as sample data, establish one it is continuously differentiable
Mode function f (x) remembers xdIt is the upward peak point of f (x), fd=f (xd), the coenvelope line of q (x) is S (x)；
(3) according to the relativeness of S (x) and f (x) and the derivative f' of the change rate Δ S (x) and f (x) of Real-time Monitoring Data
(x) relativeness calculates the possibility that dynamic disaster occurs.
2. a kind of dynamic disaster mode method for early warning based on Real-time Monitoring Data as described in claim 1, which is characterized in that
The step (3) includes the following steps：
(31) according to the sampling period of monitoring sensor or frequency, setup algorithm step delta x；
(32) for monitoring ordered series of numbers S (x) in real time, once there is some x and xmSo that：S(x-Δx)≥f(xmΔ x) andThen take x0=x- Δ x, subsequently enter the early warning period；
(33) as time goes by x points (x >=x0), carry out on-line early warning according to rule.
3. a kind of dynamic disaster mode method for early warning based on Real-time Monitoring Data as claimed in claim 2, which is characterized in that
On-line early warning rule in step (33) include without alert state, alert three kinds of the state of alert status reconciliation, wherein：
(a) when meeting fd＞ S (x) >=f (xm), and
It takesAs p≤0.2, without alert state, otherwise to enter alert status；
(b) when meeting S (x-2 Δs x) >=fd, and S (x) ＜ S (x- Δ x) ＜ S (x-2 Δs x)；
Other dynamic disaster occurrence factors in addition to monitor value are referred at this time, if other factors tend to disaster, into early warning
Otherwise state enters the alert state of solution, and return to step (32)；
(c) when meeting S (x-2 Δ x) ＜ f (x-2 Δ x) ＜ fd, and S (x) ＜ S (x- Δ x) ＜ S (x-2 Δ x), into the alert shape of solution
State, and return to step (32).
4. a kind of dynamic disaster mode method for early warning based on Real-time Monitoring Data as claimed in claim 3, which is characterized in that
In the situation (a), when the greens of p≤0.2 are without alert state, grading forewarning system is otherwise carried out, is divided into from low to high according to warning level
Level-one early warning is to level Four early warning；Wherein, when p ∈ (0.2,0.4] carry out level-one early warning, if p ∈ (0.4,0.6] carry out two level it is pre-
It is alert, if p ∈ (0.6,0.8] three-level early warning is carried out, if p ＞ 0.8 carry out level Four early warning.
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| CN110533887A (en) * | 2019-08-07 | 2019-12-03 | 山东蓝光软件有限公司 | A kind of discrete mode method for early warning of coal and gas prominent disaster based on Real-time Monitoring Data, device and storage medium |
| CN117889791A (en) * | 2024-03-13 | 2024-04-16 | 中国矿业大学(北京) | Underground engineering fault slip monitoring system and control method |
| CN117889791B (en) * | 2024-03-13 | 2024-05-10 | 中国矿业大学(北京) | Underground engineering fault slip monitoring system and control method |
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