CN116500295A - Accurate sensing method for mine ventilation environment parameters - Google Patents
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Abstract
The invention relates to the technical field of data processing, in particular to a mine ventilation environment parameter accurate sensing method, which comprises the following steps: acquiring a time difference between forward propagation and backward propagation of ultrasonic signals in a mine ventilation environment, acquiring forward propagation time and backward propagation time of ultrasonic waves in the mine ventilation environment at each moment, acquiring initial mine wind speed at each moment, and carrying out noise reduction treatment on the initial mine wind speed at each moment in the mine ventilation environment to obtain target wind speed at each moment. According to the method, the time difference is firstly obtained through the cross-correlation method, the initial wind speed is obtained through the time difference method, the Kalman filtering algorithm is optimized through the genetic algorithm, and the optimized Kalman filtering algorithm is used for carrying out noise reduction on the initial wind speed to obtain the target wind speed, so that the accuracy of wind speed extraction is improved.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a mine ventilation environment parameter accurate sensing method.
Background
With popularization and popularization of information technologies such as the Internet of things, big data, artificial intelligence, edge computing and 5G communication in the field of coal mine safety, the new generation of information technology is deeply fused with the energy industry and the mining industry, so that an increasingly important supporting and energizing effect is exerted. The coal mine intellectualization is a core technical support for high-quality development of coal industry, accelerates the development of coal mine intellectualization, builds a new system of intelligent and green coal industry, realizes intelligent safe, efficient, green development, clean and efficient utilization of coal resources, and is a strategic task and a requisite path for high-quality development of coal industry in China.
The wind speed data acquired by the intelligent ventilation system for mines is acquired by utilizing an ultrasonic scanning wind measuring method, the traditional 'point-to-surface' monitoring mode is changed, the accuracy, reality and reliability of the wind direction, the wind quantity, the wind speed and other data in the ventilation system for mines are realized, the real-time ventilation state of the mines is objectively reflected, however, the wind speed is acquired by mainly utilizing a sensor in the process of detecting the wind speed.
However, the detection principle of the sensor in the prior art is basically based on the time difference method for detecting the wind speed, namely, an ultrasonic sensor is mainly used, an electric signal is formed into an acoustic signal through a transmitting transducer, the acoustic signal is formed into an electric signal through a receiving transducer, the electric signal is processed by an amplifying circuit through a medium Zhou Bianya device, other clutters are filtered through a band filtering circuit, and finally the electric signal is received and processed by a chip to obtain the wind speed, however, the sensor is inevitably affected by random disturbance in the inside and noise introduced due to interference of a hardware circuit in the process of generating, transmitting, receiving and converting the ultrasonic signal in the detection process, so that the measured data is inaccurate.
Therefore, it is necessary to provide a method for accurately sensing parameters of the ventilation environment of the mine to solve the above problems.
Disclosure of Invention
The invention provides a precise sensing method for mine ventilation environment parameters, which aims to solve the problem of inaccurate wind speed detection in mine ventilation environment parameters in the prior art.
The invention relates to a mine ventilation environment parameter accurate sensing method which adopts the following technical scheme: the method comprises the following steps:
acquiring the time difference between downstream propagation and countercurrent propagation of ultrasonic waves in a mine ventilation environment when the cross correlation between a transmitting signal and a receiving signal of the ultrasonic waves in the mine ventilation environment is maximum by using a cross correlation method;
acquiring the forward flow transmission speed and the backward flow transmission speed of ultrasonic waves in the mine ventilation environment at each moment according to the environmental temperature at each moment for the environmental temperature at each moment in the mine ventilation environment; acquiring the forward flow propagation time and the backward flow propagation time of the ultrasonic wave at each moment in the mine ventilation environment according to the measuring distance of the ultrasonic wave and the forward flow transmission speed and the backward flow transmission speed of the ultrasonic wave at each moment;
according to the measuring distance of the ultrasonic wave, the time difference, the forward flow propagation time and the backward flow propagation time of the ultrasonic wave at each moment, and the included angle value between the ultrasonic wave direction and the wind direction, the initial mine wind speed at each moment is obtained;
and obtaining an error covariance matrix of a Kalman filtering algorithm based on the initial mine wind speeds at different moments, optimizing the error covariance matrix by using a genetic algorithm to obtain a target error covariance matrix, obtaining a target Kalman filtering algorithm, and carrying out noise reduction treatment on the initial mine wind speed at each moment in a mine ventilation environment according to the target Kalman filtering algorithm to obtain the target wind speed at each moment.
Preferably, acquiring the initial mine wind speed at each moment includes:
wherein V is 0 Representing the initial mine wind speed at a certain moment;
alpha represents the included angle value between the propagation direction of ultrasonic wave at a certain moment and the wind direction;
COS alpha represents the cosine value of the included angle value between the propagation direction of ultrasonic waves at a certain moment and the wind direction;
when the cross correlation between the transmitted signal and the received signal of the ultrasonic wave is maximum, the time difference between downstream propagation and counter-flow propagation of the ultrasonic wave in the mine ventilation environment;
l represents the measurement distance of the ultrasonic wave;
t ab representing the downstream propagation time of an ultrasonic signal at a certain moment in the mine ventilation environment;
t ba the counter-current propagation time of an ultrasonic signal at a certain moment in the mine ventilation environment is shown.
Preferably, acquiring the forward flow transmission speed and the backward flow transmission speed of ultrasonic waves in the mine ventilation environment at each moment comprises the following steps:
V ab ＝(331.45+0.607T)m/s
V ba ＝(331.45-0.607T)m/S
wherein V is ab Representing the downstream transmission speed of ultrasonic waves at each moment in the mine ventilation environment;
V ba representing the speed of countercurrent transmission of ultrasound at each moment in the mine ventilation environment;
t represents the ambient temperature at each moment in the mine ventilation environment.
Preferably, obtaining an error covariance matrix of a kalman filter algorithm includes:
acquiring an error covariance corresponding to each moment according to the initial mine wind speed at each moment;
and obtaining an error covariance matrix of the Kalman filtering algorithm according to the error covariance of all the moments.
Preferably, obtaining the target error covariance matrix includes:
combining the parameter values in the error covariance matrix to form a vector;
binary encoding is carried out on each parameter in the vector;
according to the binary code random combination, a plurality of binary code strings are obtained, each binary code string is used as a dyeing individual, and an initial population is obtained;
acquiring the fitness value of each dyeing individual in the initial population;
updating the initial population to obtain a new population according to the fitness value of each dyeing individual and the condition that the fitness value meets the conditions;
and recalculating the fitness value of each dyeing individual in the new population, and updating the new population until the population converges to obtain a target error covariance matrix.
Preferably, obtaining the fitness value of each dyed individual in the initial population includes:
in the method, in the process of the invention,an fitness value representing the ith dyed individuals in the population inherited to the g generation;
n represents the maximum number of iterations;
y (k (represents the initial mine wind speed at the kth time;
wind speed estimation value obtained by predicting initial mine wind speed at k moment corresponding to ith dyeing individual in population inherited to g generation
Representing the identification value of the ith staining individual inherited into the g generation population.
Preferably, acquiring the fitness value satisfies a condition, including:
where y x k) represents the initial mine wind speed at the kth time;
c (k) represents a state matrix of a kalman filter algorithm at a kth moment;
represents the k-1 th timePredicting the state vector of the state matrix of the Kalman filtering algorithm to obtain the state vector of the state matrix of the Kalman filtering algorithm at the kth moment;
representing the predicted state vector.
The beneficial effects of the invention are as follows: according to the accurate sensing method for the mine ventilation environment parameters, the time difference is firstly obtained through the cross-correlation method, the initial wind speed is obtained through the time difference method, then the Kalman filtering algorithm is optimized through the genetic algorithm, and the optimized Kalman filtering algorithm is used for carrying out noise reduction treatment on the initial wind speed to obtain the target wind speed, so that the accuracy of wind speed extraction is improved.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of the overall steps of an embodiment of a method for accurately sensing parameters of a mine ventilation environment according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
An embodiment of a method for accurately sensing parameters of a mine ventilation environment of the present invention is shown in fig. 1, and the method includes:
s1, acquiring the time difference between forward propagation and backward propagation of ultrasonic signals in a mine ventilation environment;
specifically, in this embodiment, when the cross correlation value of the transmission signal and the reception signal of the ultrasonic wave in the mine ventilation environment is the maximum, the time difference between downstream propagation and upstream propagation of the ultrasonic wave in the mine ventilation environment is obtained by using the cross correlation method, where the time difference between downstream propagation and upstream propagation of the ultrasonic wave in the mine ventilation environment includes:
in the cross-correlation method, the cross-correlation function between signals is calculated to find out the cross-correlation between them, and the cross-correlation function between the ultrasonic wave transmission signal X and the ultrasonic wave reception signal Y is R xy The cross-correlation function is expressed as:
Rxy(t)＝E(X(t)Y(t+D))
wherein E represents an expected value;
x (t) represents an ultrasonic transmission signal at time t;
y (t) represents the received signal of the ultrasonic wave at time t;
R xy (t) cross correlation of the ultrasonic wave transmission signal and the ultrasonic wave reception signal at time t;
d represents the time difference between forward and backward propagation of ultrasonic waves in the mine ventilation environment at the time t;
in the signal processing process, assuming that the average value of the transmitted signal X (t) and the received signal Y (t) of the ultrasonic wave at the time t is 0, the time difference between downstream propagation and upstream propagation of the ultrasonic wave signal in the mine ventilation environment when the interchangeability is maximum is estimated according to the cross correlation methodThe method comprises the following steps:
wherein arg max represents the maximum correlation between the transmitted signal and the received signal of the ultrasonic wave;
R xy (t) ultrasonic wave emission at time tCross correlation of the transmitted signal and the received signal of the ultrasonic wave;
the specific method comprises calculating the cross correlation of the ultrasonic wave transmitting signal and receiving signal at different time, finding the corresponding time difference when the cross correlation is maximum, and obtaining the time difference of downstream propagation and counter-flow propagation of ultrasonic wave signal in mine ventilation environment
So far, when the cross correlation between the transmitting signal and the receiving signal of the ultrasonic wave in the mine ventilation environment is the maximum, the time difference between downstream propagation and countercurrent propagation of the ultrasonic wave in the mine ventilation environment is obtained by using the cross correlation method, wherein the cross correlation method is an algorithm in the prior art, and the embodiment is not repeated.
S2, acquiring forward flow propagation time and backward flow propagation time of ultrasonic waves at each moment in a mine ventilation environment;
it is to be noted that, when the wind speed in the ventilation environment of the mine is detected by utilizing ultrasonic waves, two ultrasonic probes are adopted, wherein one ultrasonic transmitting probe and one ultrasonic receiving probe are adopted, specifically, one probe is arranged at one side of the inlet of the mine, and the other probe is arranged in the tunnel of the mine and is arranged diagonally to the probe at the mine opening.
Specifically, acquiring the forward flow transmission speed and the backward flow transmission speed of ultrasonic waves in a mine ventilation environment at each moment comprises the following steps:
V ab ＝(331.45+0.607T)m/s
V ba ＝(331.45-0.607T)m/s
wherein V is ab Representing the downstream transmission speed of ultrasonic waves at each moment in the mine ventilation environment;
V ba representing the speed of countercurrent transmission of ultrasound at each moment in the mine ventilation environment;
t represents the ambient temperature at each moment in the mine ventilation environment;
331.45m/s represents the propagation velocity of ultrasonic waves at 20 ℃;
0.607 represents the coefficient of variation of the ultrasonic velocity with temperature.
Based on this, the downstream transmission speed V at each moment is obtained ab And the countercurrent transport speed V at each moment ba Then according to the measuring distance of the ultrasonic wave, namely the distance from the ultrasonic probe to the other probe in the embodiment, the distance is recorded as L, the measuring distance is obtained according to the formulas of time, speed and distance, and the downstream propagation time t of the ultrasonic wave at each moment in the mine ventilation environment ab And counter-current propagation time t ba 。
S3, acquiring the initial mine wind speed at each moment;
specifically, according to the measured distance and time difference of the ultrasonic wave, the forward flow propagation time and the backward flow propagation time of the ultrasonic wave at each moment, and the included angle value of the ultrasonic wave direction and the wind direction, the initial mine wind speed at each moment is obtained, and the calculation formula of the initial mine wind speed is as follows:
wherein V is 0 Representing the initial mine wind speed at a certain moment;
alpha represents the included angle value between the propagation direction of ultrasonic wave at a certain moment and the wind direction;
COS alpha represents the cosine value of the included angle value between the propagation direction of ultrasonic waves at a certain moment and the wind direction;when the cross correlation between the transmitted signal and the received signal of the ultrasonic wave is maximum, the time difference between downstream propagation and counter-flow propagation of the ultrasonic wave in the mine ventilation environment;
l represents the measurement distance of the ultrasonic wave;
t ab representing the downstream propagation time of an ultrasonic signal at a certain moment in the mine ventilation environment;
t ba indicating ultrasound at a certain moment in the mine ventilation environmentCounter-current propagation time of the wave signal.
S4, carrying out noise reduction treatment on the initial mine wind speed at each moment in the mine ventilation environment to obtain a target wind speed at each moment;
specifically, the embodiment obtains an error covariance matrix of a kalman filter algorithm based on the initial mine wind speeds at different moments, optimizes the error covariance matrix by using a genetic algorithm to obtain a target error covariance matrix, obtains a target kalman filter algorithm, and performs noise reduction processing on the initial mine wind speed at each moment in a mine ventilation environment according to the target kalman filter algorithm to obtain a target wind speed at each moment.
The method for obtaining the error covariance matrix of the Kalman filtering algorithm comprises the following steps: acquiring an error covariance corresponding to each moment according to the initial mine wind speed at each moment; obtaining an error covariance matrix of a Kalman filtering algorithm according to the error covariance of all the moments, wherein a calculation formula of the error covariance is as follows:
P k ＝(I-K k C)P k|k-1
wherein P is k Indicating the error covariance at time k,
i represents an identity matrix;
K k a Kalman gain value at time k;
c represents a system matrix of a Kalman filtering algorithm;
P k|k-1 the error covariance at time k, which is derived from the error covariance prediction at time k-1, is shown.
It should be noted that, the calculation formula of the error covariance is a formula in the prior art, and this embodiment is not described in detail.
Obtaining a target error covariance matrix, comprising: combining the parameter values in the error covariance matrix to form a vector; binary encoding is carried out on each parameter in the vector; according to the binary code random combination, a plurality of binary code strings are obtained, each binary code string is used as a dyeing individual, and an initial population is obtained; acquiring the fitness value of each dyeing individual in the initial population; updating the initial population to obtain a new population according to the fitness value of each dyeing individual and the condition that the fitness value meets the conditions; and recalculating the fitness value of each dyeing individual in the new population, and updating the new population until the population converges to obtain a target error covariance matrix.
The combination of parameter values in the error covariance matrix forms a vector:
ε＝(q 1 ，q 2 ，q 3 ，q 4 ，q 5 ，......，q r ) T
wherein epsilon represents a vector;
q 1 representing a first parameter value in the vector;
q 2 representing a second parameter value in the vector;
q r representing the value of the r-th parameter in the vector;
t represents a transposed calculation of the parameter values in the vector.
Wherein, obtaining the initial population comprises: when the vector is coded, binary codes with simple operation and quick operation are selected, each element in the vector is binary coded, each binary code is combined to obtain a binary code string, namely a dyeing individual, one dyeing individual is marked as epsilon b, the initial population consists of a plurality of random chromosomes, and the initial population can be marked as follows:
in the method, in the process of the invention,representing an initial population;
represents the first, stained individual in the initial population (generation 0);
n represents the total number of chromosomes in the initial population.
The method for obtaining the fitness value of each dyeing individual in the initial population comprises the following steps:
in the method, in the process of the invention,an fitness value representing the ith dyed individuals in the population inherited to the g generation;
n represents the maximum number of iterations;
y (k) represents the initial mine wind speed at the kth time;
wind speed estimation value obtained by predicting initial mine wind speed at k moment corresponding to ith dyeing individual in population inherited to g generation
Representing the identification value of the ith staining individual inherited into the g generation population.
It should be noted that, the formula is a formula in the prior art, and this embodiment is not described in detail.
Wherein obtaining the fitness value satisfies the condition includes: the expression that the fitness value satisfies the condition is:
wherein y (k) represents an initial mine wind speed at a kth time;
c (k) represents a state matrix of a kalman filter algorithm at a kth moment;
state matrix representing the Kalman filtering algorithm at time k-1State vector of a state matrix of a Kalman filtering algorithm at a kth moment obtained by state vector prediction;
representing the predicted state vector.
It should be noted that, the expression with the fitness value satisfying the condition is an expression in the prior art, and this embodiment is not described in detail.
So far, a target error covariance matrix is obtained when the population converges, a target Kalman filtering algorithm is obtained according to the target error covariance matrix (namely, the Kalman filtering algorithm is reconstructed by using the target error covariance matrix), and then the initial mine speed at each moment is optimized based on the target Kalman filtering algorithm, so that the target wind speed at each moment is obtained.
In summary, the invention provides a method for accurately sensing parameters of a mine ventilation environment, which comprises the steps of firstly obtaining the time difference between forward propagation and reverse propagation of ultrasonic waves in the mine ventilation environment when the cross correlation between a transmitting signal and a receiving signal of the ultrasonic waves in the mine ventilation environment is maximum through a cross correlation method, obtaining an initial wind speed through combining the time difference method, then optimizing a Kalman filtering algorithm by utilizing a genetic algorithm, and carrying out noise reduction treatment on the initial wind speed by utilizing the optimized Kalman filtering algorithm to obtain a target wind speed, thereby improving the accuracy of wind speed extraction.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
Claims (7)
1. The accurate sensing method for the parameters of the ventilation environment of the mine is characterized by comprising the following steps of:
acquiring the time difference between downstream propagation and countercurrent propagation of ultrasonic waves in a mine ventilation environment when the cross correlation between a transmitting signal and a receiving signal of the ultrasonic waves in the mine ventilation environment is maximum by using a cross correlation method;
acquiring the forward flow transmission speed and the backward flow transmission speed of ultrasonic waves in the mine ventilation environment at each moment according to the environmental temperature at each moment for the environmental temperature at each moment in the mine ventilation environment; acquiring the forward flow propagation time and the backward flow propagation time of the ultrasonic wave at each moment in the mine ventilation environment according to the measuring distance of the ultrasonic wave and the forward flow transmission speed and the backward flow transmission speed of the ultrasonic wave at each moment;
according to the measuring distance of the ultrasonic wave, the time difference, the forward flow propagation time and the backward flow propagation time of the ultrasonic wave at each moment, and the included angle value between the ultrasonic wave direction and the wind direction, the initial mine wind speed at each moment is obtained;
and obtaining an error covariance matrix of a Kalman filtering algorithm based on the initial mine wind speeds at different moments, optimizing the error covariance matrix by using a genetic algorithm to obtain a target error covariance matrix, obtaining a target Kalman filtering algorithm, and carrying out noise reduction treatment on the initial mine wind speed at each moment in a mine ventilation environment according to the target Kalman filtering algorithm to obtain the target wind speed at each moment.
2. The method for accurately sensing parameters of a mine ventilation environment according to claim 1, wherein obtaining an initial mine wind speed at each moment comprises:
wherein V is 0 Representing the initial mine wind speed at a certain moment;
alpha represents the included angle value between the propagation direction of ultrasonic wave at a certain moment and the wind direction;
COS alpha represents the cosine value of the included angle value between the propagation direction of ultrasonic waves at a certain moment and the wind direction;
representing ultrasoundWhen the cross correlation between the two signals of the wave transmitting signal and the wave receiving signal is maximum, the time difference between downstream propagation and counter-flow propagation of ultrasonic waves in a mine ventilation environment;
l represents the measurement distance of the ultrasonic wave;
t ab representing the downstream propagation time of an ultrasonic signal at a certain moment in the mine ventilation environment;
t ba the counter-current propagation time of an ultrasonic signal at a certain moment in the mine ventilation environment is shown.
3. The method for accurately sensing parameters of a mine ventilation environment according to claim 1, wherein the step of obtaining a forward flow transmission speed and a backward flow transmission speed of ultrasonic waves in the mine ventilation environment at each moment comprises the steps of:
V ab ＝(331.45+0.607T)m/s
V ba ＝(331.45-0.607T)m/s
wherein V is ab Representing the downstream transmission speed of ultrasonic waves at each moment in the mine ventilation environment;
V ba representing the speed of countercurrent transmission of ultrasound at each moment in the mine ventilation environment;
t represents the ambient temperature at each moment in the mine ventilation environment.
4. The method for accurately sensing parameters of a ventilation environment of a mine according to claim 1, wherein the step of obtaining an error covariance matrix of a kalman filter algorithm comprises the steps of:
acquiring an error covariance corresponding to each moment according to the initial mine wind speed at each moment;
and obtaining an error covariance matrix of the Kalman filtering algorithm according to the error covariance of all the moments.
5. The method for accurately sensing parameters of a mine ventilation environment according to claim 1, wherein obtaining a target error covariance matrix comprises:
combining the parameter values in the error covariance matrix to form a vector;
binary encoding is carried out on each parameter in the vector;
according to the binary code random combination, a plurality of binary code strings are obtained, each binary code string is used as a dyeing individual, and an initial population is obtained;
acquiring the fitness value of each dyeing individual in the initial population;
updating the initial population to obtain a new population according to the fitness value of each dyeing individual and the condition that the fitness value meets the conditions;
and recalculating the fitness value of each dyeing individual in the new population, and updating the new population until the population converges to obtain a target error covariance matrix.
6. The method of claim 5, wherein obtaining fitness values for each dyed individual in the initial population comprises:
in the method, in the process of the invention,an fitness value representing the ith dyed individuals in the population inherited to the g generation;
n represents the maximum number of iterations;
y (k) represents the initial mine wind speed at the kth time;
wind speed estimation value obtained by predicting initial mine wind speed at k moment corresponding to ith dyeing individual in population inherited to g generation
Representing the identification value of the ith staining individual inherited into the g generation population.
7. The method for accurately sensing parameters of a mine ventilation environment according to claim 5, wherein the step of obtaining the fitness value satisfies the condition comprises the steps of:
wherein y (k) represents an initial mine wind speed at a kth time;
c (k) represents a state matrix of a kalman filter algorithm at a kth moment;
a state vector of a state matrix of the Kalman filtering algorithm at the kth moment obtained by predicting the state vector of the state matrix of the Kalman filtering algorithm at the kth-1 moment;
representing the predicted state vector.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310466228.9A CN116500295A (en) | 2023-04-26 | 2023-04-26 | Accurate sensing method for mine ventilation environment parameters |
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| CN116992246A (en) * | 2023-09-27 | 2023-11-03 | 华洋通信科技股份有限公司 | Intelligent sensing method and system for underground airflow parameters |
| CN116992246B (en) * | 2023-09-27 | 2023-12-19 | 华洋通信科技股份有限公司 | Intelligent sensing method and system for underground airflow parameters |
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