Intelligent control method for wireless Feng Shui automatic spraying and dust reduction system

Abstract

The present invention relates to the field of intelligent control technology, and specifically to an intelligent control method for a wireless Feng Shui automatic spraying and dust reduction system. The method includes: obtaining the target dust concentration corresponding to each sensor at the current control time according to the fitting straight line corresponding to each sensor in the mining area and the fitting straight line corresponding to each neighboring sensor in the neighboring sensor set corresponding to each sensor, obtaining the clustering cluster corresponding to each sensor according to the difference between the target dust concentration corresponding to each sensor at the current control time and the cluster center point of each clustering cluster, and regulating the operating parameters of the wireless Feng Shui automatic spraying system through the clustering cluster corresponding to each sensor. When the present invention sprays and reduces dust in the mining area, it can avoid the phenomenon of wasting spraying resources as much as possible, and can also relatively effectively reduce the dust concentration or relatively effectively control the dust concentration.

Description

Technical Field

[0001] The present invention relates to the field of intelligent control technology, and in particular to an intelligent control method for a wireless Feng Shui automatic spraying and dust reduction system. Background Art

[0002] Since the dust in the mining area can endanger the health of coal miners, in order to protect the health of coal miners, a wireless Feng Shui automatic spraying and dust reduction system is generally used to control the dust concentration in the mining area. Usually, the dust concentration in the mining area is controlled by intelligently adjusting the operating parameters of the wireless Feng Shui automatic spraying and dust reduction system. In other words, intelligent adjustment of the operating parameters of the wireless Feng Shui automatic spraying and dust reduction system is crucial to protecting the health of coal miners.

[0003] The wireless Feng Shui automatic spraying and dust reduction system includes a sensor network, a data processing center, an automatic spraying machine and a wireless control module. In the prior art, the operating parameters of the wireless Feng Shui automatic spraying and dust reduction system are generally directly adjusted based on the dust concentration collected by the sensors in the mining area, so as to achieve the control of the dust concentration in the mining area. However, since there is air flow in the mining area, and the air flow will cause the dust in the mining area to transfer, that is, it may cause the dust in certain areas of the mining area to transfer to other areas of the mining area. When this happens, the operating parameters of the wireless Feng Shui automatic spraying and dust reduction system determined directly based on the dust concentration collected by the sensors in the mining area may cause a waste of spraying resources when spraying and dust reduction in the mining area, and may also cause the dust concentration to be unable to be effectively reduced or the dust concentration to be unable to be effectively controlled. That is, when there is a transfer of dust in the mining area caused by air flow, the dust concentration directly collected by the sensor cannot be more reliably or accurately used to adjust the operating parameters of the wireless Feng Shui automatic spraying and dust reduction system. Therefore, reliable regulation of the operating parameters of the wireless Feng Shui automatic spraying and dust reduction system is an urgent problem to be solved. Summary of the invention

[0004] In order to solve the above problems, the present invention provides an intelligent control method for a wireless Feng Shui automatic spraying and dust reduction system, and the technical solution adopted is as follows:

[0005] An embodiment of the present invention provides an intelligent control method for a wireless Feng Shui automatic spraying and dust reduction system, comprising the following steps:

[0006] Obtain the historical dust concentration sequence corresponding to each sensor in the mining area and the current dust concentration corresponding to each sensor in the mining area at the current control time;

[0007] According to the position distances between the sensors in the mining area, a set of neighboring sensors corresponding to each sensor is obtained;

[0008] According to the current dust concentration corresponding to each sensor at the current control moment and the historical dust concentration sequence corresponding to each sensor, a fitting straight line corresponding to each sensor is obtained;

[0009] According to the fitting straight lines corresponding to the respective sensors and the fitting straight lines corresponding to the respective neighboring sensors in the neighboring sensor set corresponding to the respective sensors, the target dust concentration corresponding to the respective sensors in the mining area at the current control time is obtained;

[0010] The historical dust concentrations in the historical dust concentration sequence are clustered to obtain various clusters; the clusters corresponding to the various sensors are obtained according to the differences between the target dust concentrations corresponding to the various sensors at the current control moment and the cluster centers of the various clusters, and the operating parameters of the wireless Feng Shui automatic spraying system are regulated according to the clusters corresponding to the various sensors.

[0011] Beneficial effect: The present invention can reliably determine the target dust concentration corresponding to each sensor in the mining area at the current control time through the fitting straight lines corresponding to each sensor in the mining area and the fitting straight lines corresponding to each neighboring sensor in the neighboring sensor set corresponding to each sensor. That is, the present invention can reliably adjust the current dust concentration corresponding to each sensor in the mining area at the current control time based on the fitting straight lines corresponding to each sensor in the mining area and the fitting straight lines corresponding to each neighboring sensor in the neighboring sensor set corresponding to each sensor. Then, the historical dust concentration in the historical dust concentration sequence is clustered to obtain each cluster cluster, and according to the difference between the target dust concentration corresponding to each sensor at the current control time and the cluster center point of each cluster cluster, the cluster cluster corresponding to each sensor is obtained. The cluster cluster corresponding to each sensor can reliably control the operating parameters of the wireless Feng Shui automatic spraying system through the cluster cluster corresponding to each sensor. That is, the operating parameters of the wireless Feng Shui automatic spraying and dust reduction system determined by the present invention based on the target dust concentration corresponding to each sensor at the current control time can avoid the phenomenon of waste of spraying resources as much as possible when spraying and reducing dust in the mining area, and can also relatively effectively reduce the dust concentration or relatively effectively control the dust concentration. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0013] Figure 1 The present invention is a flow chart of an intelligent control method of a wireless Feng Shui automatic spraying and dust reduction system. DETAILED DESCRIPTION

[0014] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field belong to the scope of protection of the embodiments of the present invention.

[0015] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0016] This embodiment provides an intelligent control method for a wireless Feng Shui automatic spraying and dust reduction system, which is described in detail as follows:

[0017] like Figure 1 As shown, the intelligent control method of the wireless Feng Shui automatic spraying dust reduction system includes the following steps:

[0018] Step S001, obtaining each historical dust concentration corresponding to each sensor in the mining area and the current dust concentration corresponding to each sensor in the mining area at the current control moment.

[0019] The main purpose of this embodiment is to reliably or accurately regulate the operating parameters of the wireless Feng Shui automatic spraying and dust reduction system, and the wireless Feng Shui automatic spraying and dust reduction system in this embodiment includes a sensor network, a data processing center, an automatic spraying machine and a wireless control module. The sensors in the sensor network of the wireless Feng Shui automatic spraying and dust reduction system are mainly used to collect data from different areas in the mining area, and the sensors in the sensor network can be connected to the data processing center of the wireless Feng Shui automatic spraying and dust reduction system in the mining area. The data collected by the sensors are also stored in the data processing center. The data processing center of the wireless Feng Shui automatic spraying and dust reduction system mainly functions to analyze and process the data collected by the sensors. The wireless control module of the wireless Feng Shui automatic spraying and dust reduction system mainly functions to intelligently regulate the spraying intensity and spraying frequency of the automatic spraying machine. The automatic spraying machine of the wireless Feng Shui automatic spraying and dust reduction system mainly sprays water in the mining area.

[0020] This embodiment takes any mining area as an example for analysis, and the mining area in this embodiment is in the mining stage, and then sensors are arranged in the mining area, and the positions of various sensors in the mining area are obtained; and in specific applications, the implementer needs to set the positions of sensors in the mining area and determine the number of sensors arranged in the mining area according to the area of ​​the mining area where dust concentration monitoring is required and the monitoring range of the sensor, and the larger the area of ​​the mining area where dust concentration monitoring is required, the more sensors are arranged, and an automatic spraying machine is set in the mining area monitored by each sensor in the mining area; in addition, since this embodiment mainly collects dust concentration in the mining area, the sensors appearing in this embodiment are all dust particle concentration sensors.

[0021] Then, the dust concentrations collected by each sensor in the mining area in the historical time period and the dust concentrations collected by each sensor at the current control time are obtained, and the dust concentrations collected by each sensor in the historical time period are recorded as the historical dust concentrations corresponding to the corresponding sensors, and the dust concentrations collected by each sensor at the current control time are recorded as the current dust concentrations corresponding to each sensor at the current control time; for any sensor, all historical dust concentrations corresponding to the sensor are sorted in order of collection time to obtain the historical dust concentration sequence corresponding to the sensor; therefore, the historical dust concentration sequence corresponding to each sensor can be obtained through the above process.

[0022] In specific applications, it is necessary to set the sensor collection time interval and the length of the historical time period according to actual conditions. For example, in this embodiment, the sensor collection time interval is set to 1 second, and the historical time period is set to the time period from the initial collection moment to the current control moment; the control moment in this embodiment is the moment when the operating parameters of the wireless Feng Shui automatic spraying system are adjusted, and the current control moment is adjacent to and continuous with the historical time period, that is, if the sensor collection time interval is 1 second, then the time interval between the last dust concentration collected by the sensor in the historical time period and the current control moment is 1 second. In addition, in this embodiment, the time interval for adjusting the operating parameters of the wireless Feng Shui automatic spraying system is set to be greater than the sensor collection time interval, for example, the time interval between the current control moment and the next control moment is set to 1 minute; in addition, the operating parameters of the wireless Feng Shui automatic spraying system in this embodiment include spraying intensity and spraying frequency, and the spraying intensity and spraying frequency are the spraying intensity and spraying frequency of the automatic spraying machinery in the wireless Feng Shui automatic spraying system.

[0023] Therefore, this embodiment can obtain the historical dust concentration sequence corresponding to each sensor in the mining area and the current dust concentration corresponding to each sensor in the mining area at the current control time through the above process.

[0024] Step S002, according to the position distance between the sensors in the mining area, obtain the set of neighboring sensors corresponding to each sensor; according to the current dust concentration corresponding to each sensor at the current control moment and the historical dust concentration sequence corresponding to each sensor, obtain the fitting straight line corresponding to each sensor.

[0025] When the operating parameters of the wireless Feng Shui automatic spraying and dust reduction system are adjusted directly based on the dust concentration collected by the sensors in the mining area, there may be a waste of spraying resources, and it may also lead to the inability to effectively reduce the dust concentration in the mining area or the inability to effectively control the dust concentration in the mining area; for example, if the current dust concentration collected by a sensor at the current control time is large, then the operating parameters of the wireless Feng Shui automatic spraying and dust reduction system determined based on the current dust concentration collected by the sensor at the current control time may also be large, that is, the spraying intensity is strong and the spraying frequency is high, but when the dust in the mining area monitored by the sensor transfers to other mining areas, then in the future time period, the dust concentration in the mining area monitored by the sensor may show a downward trend, and the future time period may refer to the time period from the current control time to the next control time, then at this time the operating parameters determined based on the current dust concentration are in the future. In the process of spraying dust reduction in the mining area monitored by the sensor in the future time period, there may be a phenomenon of waste of spraying resources; if the current dust concentration collected by a certain sensor at the current control time is small, then the operating parameters of the wireless Feng Shui automatic spraying and dust reduction system adjusted or determined based on the current dust concentration collected by the sensor at the current control time may also be small, that is, the spraying intensity is weak and the spraying frequency is low, but when the dust in other mining areas is transferred to the mining area monitored by the sensor, then in the future time period, the dust concentration in the mining area monitored by the sensor may show an upward trend, then at this time, the operating parameters of the wireless Feng Shui automatic spraying and dust reduction system determined or adjusted based on the current dust concentration may not be able to effectively reduce the dust concentration or effectively control the dust concentration in the mining area monitored by the sensor in the future time period during the spraying dust reduction process in the mining area monitored by the sensor in the future time period.

[0026] Therefore, in order to avoid the phenomenon of wasting spraying resources and to avoid being unable to effectively reduce the dust concentration in the mining area or being unable to effectively control the dust concentration in the mining area, this embodiment will subsequently obtain the neighboring sensor set corresponding to each sensor according to the position distance between the sensors in the mining area, and obtain the fitting straight line corresponding to each sensor by fitting the current dust concentration corresponding to each sensor at the current control moment and the historical dust concentration corresponding to each sensor. Subsequently, by analyzing the fitting straight line corresponding to each sensor and the fitting straight line corresponding to each neighboring sensor in its corresponding neighboring sensor set, it is possible to more reliably analyze the possibility and amount of dust transfer between each sensor and each neighboring sensor in its corresponding neighboring sensor set. Based on the possibility and amount of dust transfer, the current dust concentration corresponding to each sensor can also be more reliably adjusted to obtain the target dust concentration corresponding to each sensor. Therefore, the specific process of obtaining the neighboring sensor set corresponding to each sensor and obtaining the fitting straight line corresponding to each sensor in this embodiment is as follows:

[0027] For any sensor in the mining area: all sensors other than the sensor in the mining area are recorded as the to-be-determined sensors corresponding to the sensor; for any to-be-determined sensor corresponding to the sensor, the position distance between the sensor and the to-be-determined sensor is recorded as the first distance corresponding to the to-be-determined sensor; then all the to-be-determined sensors corresponding to the sensor are sorted in order from small to large according to the first distance, to obtain the to-be-determined sensor sequence corresponding to the sensor; then the first F to-be-determined sensors in the to-be-determined sensor sequence are recorded as the neighboring sensors corresponding to the sensor, and the set constructed by all the neighboring sensors corresponding to the sensor is recorded as the neighboring sensor set corresponding to the sensor, and in specific applications, the value of F needs to be set according to actual conditions, and the value of F is less than the number of sensors arranged in the mining area. For example, if there are many sensors arranged in the mining area, then the value of F can be set to 5 or 10 in this embodiment.

[0028] Therefore, this embodiment can obtain the neighboring sensor set corresponding to each sensor in the mining area through the above process; next, the fitting straight line corresponding to each sensor is obtained, specifically:

[0029] For any sensor in the mining area, the current dust concentration corresponding to the sensor at the current control moment and the sequence constructed by the last B historical dust concentrations in the historical dust concentration sequence corresponding to the sensor are recorded as the characteristic dust concentration sequence corresponding to the sensor, all data in the characteristic dust concentration sequence corresponding to the sensor are recorded as dust concentrations, and the mark value of the dth dust concentration in the characteristic dust concentration sequence corresponding to the sensor is recorded as d, and all dust concentrations in the characteristic dust concentration sequence are also arranged in the order of collection time; therefore, through the above process, the characteristic dust concentration sequence corresponding to each sensor in the mining area, each dust concentration in the characteristic dust concentration sequence corresponding to each sensor, and the mark value of each dust concentration can be obtained.

[0030] Then a two-dimensional space is constructed, and the horizontal axis of the two-dimensional space is the mark value and the vertical axis is the dust concentration; for any sensor in the mining area, each dust concentration in the characteristic dust concentration sequence corresponding to the sensor and the mark value of each dust concentration are mapped to the constructed two-dimensional space, and the data points corresponding to each dust concentration in the characteristic dust concentration sequence corresponding to the sensor are obtained, and they are all recorded as the original data points corresponding to the sensor, and the horizontal axis value of the data point corresponding to any dust concentration in the characteristic dust concentration sequence is its corresponding mark value, and the vertical axis value is the dust concentration, and then the least squares method is used to perform linear fitting on the data points corresponding to each dust concentration in the characteristic dust concentration sequence corresponding to the sensor, and the fitting straight line and the slope and intercept of the fitting straight line are obtained, and are recorded as the fitting straight line corresponding to the sensor and the slope and intercept of the fitting straight line, and the intercept of the fitting straight line is the vertical intercept.

[0031] In this embodiment, the implementer needs to set the value of B according to the actual situation. For example, in this embodiment, the value of B is set to 10, and the number of data in the characteristic dust concentration sequence is 11.

[0032] Therefore, through the above process, the fitting straight lines corresponding to the various sensors in the mining area at the current control moment can be obtained in the constructed two-dimensional space.

[0033] Step S003, obtaining the target dust concentration corresponding to each sensor in the mining area at the current control moment according to the fitting straight line corresponding to each sensor and the fitting straight line corresponding to each neighboring sensor in the neighboring sensor set corresponding to each sensor.

[0034] Based on the fitting straight lines corresponding to each sensor and the fitting straight lines corresponding to each neighboring sensor in the neighboring sensor set corresponding to each sensor, this embodiment can more reliably analyze the differences or similarities in dust concentration changes between each sensor and each neighboring sensor in its corresponding neighboring sensor set. Based on the analyzed differences or similarities in dust concentration changes, it can more reliably analyze the possibility and amount of dust transfer between the mining area monitored by each sensor and the mining area monitored by each neighboring sensor in its corresponding neighboring sensor set. Subsequently, based on the analyzed possibility and amount of dust transfer, the current dust concentration corresponding to each sensor can be more reliably adjusted, that is, it can more reliably The target dust concentration corresponding to each sensor at the current control time is obtained, and the operating parameters of the automatic spraying machinery of the wireless Feng Shui automatic spraying system for spraying and reducing dust in the mining area monitored by each sensor are subsequently determined based on the target dust concentration corresponding to each sensor at the current control time. When spraying and reducing dust in the mining area monitored by each sensor in the future time period, the phenomenon of waste of spraying resources can be avoided as much as possible, and the dust concentration in the mining area can be effectively reduced or the dust concentration in the mining area can be effectively controlled. The future time period in this embodiment refers to the time period formed from the current control time to the next control time; therefore, the specific process of obtaining the target dust concentration corresponding to each sensor in the mining area at the current control time in this embodiment is:

[0035] For any sensor in the mining area: the abscissa value of the data point corresponding to the last dust concentration in the characteristic dust concentration sequence corresponding to the sensor is recorded as the characteristic abscissa value; a data point with a ordinate value of 0 and an abscissa value of the characteristic abscissa value is obtained in the two-dimensional space, and is recorded as the first data point corresponding to the sensor; a straight line passing through the first data point corresponding to the sensor and parallel to the ordinate axis in the two-dimensional space is recorded as the characteristic straight line corresponding to the sensor; the intersection point of the fitting straight line corresponding to the sensor and the characteristic straight line corresponding to the sensor is obtained, and is recorded as the second data point corresponding to the sensor; the absolute value of the difference between the intercept of the fitting straight line corresponding to the sensor and the ordinate value of the second data point corresponding to the sensor is calculated, and is recorded as the first characterization value corresponding to the sensor, and the abscissa value of the second data point corresponding to the sensor is recorded as the second characterization value corresponding to the sensor; the product of the first characterization value corresponding to the sensor and the second characterization value corresponding to the sensor is calculated, and is recorded as the change characterization value corresponding to the sensor, that is, the change characterization value corresponding to the sensor can characterize the degree of change in dust concentration in the time period between the collection time corresponding to the first dust concentration in the characteristic dust concentration sequence corresponding to the sensor and the current control time.

[0036] And if the change characterization value corresponding to the sensor is larger, it indicates that the degree of change of the dust concentration in the time period from the historical collection moment to the current control moment corresponding to the first dust concentration in the characteristic dust concentration sequence corresponding to the sensor is larger. For example, if the slope of the fitting line corresponding to the sensor is positive and the change characterization value corresponding to the sensor is larger, it indicates that the dust concentration in the time period from the collection moment to the current control moment corresponding to the first dust concentration in the characteristic dust concentration sequence corresponding to the sensor is increased more. In addition, if the slope of the fitting line corresponding to the sensor is positive and the change characterization value corresponding to the sensor is larger, it also indicates that the dust concentration in the mining area monitored by the sensor in the future time period is more likely to increase. Because the characteristic dust concentration sequence corresponding to the sensor is time series data, and the time series data is constructed by the dust concentration collected at the historical collection moment and the current control moment, then the characteristics corresponding to the future time period can be predicted on the fitting line obtained based on the time series data. That is, if the slope of the fitting line corresponding to the sensor is positive and the change characterization value corresponding to the sensor is larger, it indicates that the dust concentration in the mining area monitored by the sensor in the future time period is more likely to increase.

[0037] On the contrary, if the change representation value corresponding to the sensor is smaller, it indicates that the degree of change in dust concentration from the collection moment corresponding to the first dust concentration in the characteristic dust concentration sequence corresponding to the sensor to the current control moment is smaller, and it also indicates that the increase or decrease in dust concentration in the mining area monitored by the sensor in the future time period is smaller; therefore, the change representation value corresponding to each sensor in the mining area can be obtained through the above process.

[0038] For any sensor in the mining area and any neighboring sensor in the neighboring sensor set corresponding to the sensor, when the slope of the fitting straight line corresponding to the sensor and the slope of the fitting straight line corresponding to the neighboring sensor are one positive and one negative, and the difference between the change characterization values ​​corresponding to the two sensors is relatively small, it indicates that the possibility of dust transfer between the mining areas monitored by the two sensors is greater, that is, it indicates that the dust in the mining area monitored by one of the two sensors may be transferred to the mining area monitored by the other sensor; therefore, this embodiment subsequently analyzes the signs of the slopes of the fitting straight lines corresponding to each sensor, the signs of the slopes of the fitting straight lines corresponding to each neighboring sensor in the neighboring sensor set corresponding to each sensor, the change characterization values ​​corresponding to each sensor, and the change characterization values ​​corresponding to each neighboring sensor in the neighboring sensor set corresponding to each sensor, so as to obtain the target possibility characterization values ​​between the mining area monitored by each sensor and the mining area monitored by each neighboring sensor in the neighboring sensor set corresponding to each sensor, and the target possibility characterization values ​​can reflect the possibility of dust transfer between the mining area monitored by each sensor and the mining area monitored by each neighboring sensor in the neighboring sensor set corresponding to each sensor in the future time period.

[0039] Furthermore, since the change characterization value is determined by fitting the straight line, and there is a fitting confidence when obtaining the fitting straight line, and the fitting confidence of the fitting straight line can be reflected by the residual calculated after the fitting is completed, and when the residual is small, it indicates that the fitting effect is good, that is, the fitting confidence of the fitting straight line is good, on the contrary, when the residual is large, it indicates that the fitting effect is poor, that is, the fitting confidence of the fitting straight line is poor; when the fitting confidence corresponding to the fitting straight line is good, it indicates that the credibility of the obtained fitting straight line is high, then the change characterization value obtained based on the fitting straight line with higher credibility is more credible, then the credibility of the possibility of dust transfer between the mining area monitored by the sensor analyzed by the change characterization value at this time and the mining area monitored by its corresponding neighboring sensor is high; on the contrary, when the fitting confidence corresponding to the fitting straight line is poor, it indicates that the credibility of the obtained fitting straight line is low, then the credibility of the change characterization value obtained based on the fitting straight line with lower credibility is also low, then the credibility of the mining area monitored by the sensor analyzed by the change characterization value at this time and the mining area monitored by its corresponding neighboring sensor is low. The credibility of the possibility of dust transfer between domains is low; and the possibility of dust transfer between the mining area monitored by the sensor and the mining area monitored by its corresponding neighboring sensor is an important basis for subsequently determining the target dust concentration corresponding to each sensor. Therefore, in order to make the credibility of the possibility of dust transfer between the mining area monitored by the sensor and the mining area monitored by its corresponding neighboring sensor obtained by subsequent analysis higher, this embodiment will subsequently obtain the first possibility characterization value between each sensor and each neighboring sensor in its corresponding neighboring sensor set based on the sign of the slope of the fitting line corresponding to each sensor, the sign of the slope of the fitting line corresponding to each neighboring sensor in the neighboring sensor set corresponding to each sensor, the change characterization value corresponding to each sensor, the change characterization value corresponding to each neighboring sensor in the neighboring sensor set corresponding to each sensor, the fitting confidence of the fitting line corresponding to each sensor, and the fitting confidence of the fitting line corresponding to each neighboring sensor in the neighboring sensor set corresponding to each sensor. The specific process is:

[0040] For any sensor in the mining area: if the slope of the fitted straight line corresponding to the sensor is positive, the slope sign value of the fitted straight line corresponding to the sensor is recorded as 1; if the slope of the fitted straight line corresponding to the sensor is negative, the slope sign value of the fitted straight line corresponding to the sensor is recorded as -1; if the slope of the fitted straight line corresponding to the sensor is 0, the slope sign value of the fitted straight line corresponding to the sensor is recorded as 0; therefore, the slope sign value of the fitted straight line corresponding to each sensor can be obtained through the above process.

[0041] For any sensor in the mining area: on the fitting straight line corresponding to the sensor, obtain the fitting data points corresponding to each original data point corresponding to the sensor; and the original data point has the same horizontal coordinate value as the fitting data point corresponding to it; the absolute value of the difference between the vertical coordinate value of each original data point corresponding to the sensor and the vertical coordinate value of the fitting data point corresponding to it is recorded as the residual corresponding to the corresponding original data point; the cumulative sum of the residuals corresponding to all the original data points corresponding to the sensor is normalized, and the value after negative mapping of the cumulative sum of the normalized residuals is recorded as the fitting confidence of the fitting straight line corresponding to the sensor; and when the cumulative sum of the residuals corresponding to all the original data points corresponding to the sensor is larger, it indicates that the fitting confidence of the fitting straight line corresponding to the sensor is worse, and conversely, when the cumulative sum of the residuals corresponding to all the original data points corresponding to the sensor is smaller, it indicates that the fitting confidence of the fitting straight line corresponding to the sensor is better.

[0042] In addition, since only when the product of the slope sign value of the fitting line corresponding to each sensor and the slope sign value of the fitting line corresponding to its corresponding neighboring sensor is -1, there may be dust transfer between the mining area monitored by the corresponding sensor and the mining area monitored by its corresponding neighboring sensor, that is, in this embodiment, when the product of the slope sign value of the fitting line corresponding to each sensor and the slope sign value of the fitting line corresponding to its corresponding neighboring sensor is not -1, it indicates that the possibility of dust transfer between the mining area monitored by the corresponding sensor and the mining area monitored by its corresponding neighboring sensor is 0; that is, if there is dust transfer between the mining areas monitored by two sensors, the change trends of the dust concentration in the mining areas monitored by the two sensors are opposite, for example, one shows an upward trend and the other shows a downward trend; therefore, in this embodiment, the specific process of obtaining the first possibility characterization value between each sensor and each neighboring sensor in the corresponding neighboring sensor set is:

[0043] For the mth sensor in the mining area and the nth neighbor sensor in the neighbor sensor set corresponding to the mth sensor:

[0044] If it is determined that the product of the slope sign value of the fitting straight line corresponding to the mth sensor and the slope sign value of the fitting straight line corresponding to the nth neighboring sensor is not -1, it indicates that the possibility of dust transfer between the mining area monitored by the mth sensor and the mining area monitored by the nth neighboring sensor is 0, then the first possibility representation value between the mth sensor and the nth neighboring sensor in the corresponding neighboring sensor set is recorded as 0.

[0045] If it is determined that the product of the slope sign value of the fitting straight line corresponding to the mth sensor and the slope sign value of the fitting straight line corresponding to the nth neighboring sensor is -1, it indicates that there may be dust transfer between the mining areas monitored by the two sensors, and according to the fitting confidence of the fitting straight line corresponding to the mth sensor, the fitting confidence of the fitting straight line corresponding to the nth neighboring sensor, the change characterization value corresponding to the mth sensor and the change characterization value corresponding to the nth neighboring sensor, the first possibility characterization value between the mth sensor and the nth neighboring sensor in the corresponding neighboring sensor set is obtained, and the first possibility characterization value between the mth sensor and the nth neighboring sensor in the corresponding neighboring sensor set is calculated according to the following formula:

[0046]

[0047] Among them, E1 m,n is the first possible representation value between the mth sensor in the mining area and the nth neighboring sensor in its corresponding neighboring sensor set, is the fitting confidence of the fitting line corresponding to the mth sensor in the mining area, is the fitting confidence of the fitting line corresponding to the nth neighboring sensor in the neighboring sensor set corresponding to the mth sensor in the mining area, S m is the change representation value corresponding to the mth sensor in the mining area, S m,n is the change representation value corresponding to the nth neighbor sensor in the neighbor sensor set corresponding to the mth sensor in the mining area, and exp() is an exponential function with a constant e as the base.

[0048] And when The larger the |S m -S m,n The smaller the time, the higher the E1 m,n The larger the value of E1 m,n The larger the value of , the greater the possibility of dust transfer between the mining area monitored by the mth sensor and the mining area monitored by the nth neighboring sensor in the period from the historical collection time to the current control time. It also indicates that the greater the possibility of dust transfer between the mining area monitored by the mth sensor in the mining area and the mining area monitored by the nth neighboring sensor in the future time period, because when S m and S m,n When is close, then the change representation value corresponding to the mth sensor and the change representation value corresponding to the nth neighboring sensor in the future time period predicted based on the fitting straight line are also close; on the contrary, when The smaller, |S m -S m,n | is larger, indicating that E1 m,nThe smaller the value of E1 m,n The smaller the value of , the smaller the possibility of dust transfer between the mining area monitored by the mth sensor and the mining area monitored by the nth neighboring sensor in the time period from the historical collection time to the current control time. It also indicates that the possibility of dust transfer between the mining area monitored by the mth sensor in the mining area and the mining area monitored by the nth neighboring sensor in the future time period is also smaller.

[0049] In addition, due to |S m -S m,n | can reflect the possibility of dust transfer between the mining area monitored by the mth sensor and the mining area monitored by the nth neighboring sensor, and It can also reflect |S m -S m,n | credibility, and when The larger the value of |S m -S m,n The higher the credibility of | The smaller the value of |S m -S m,n The lower the credibility of |, the better. Therefore, this embodiment uses Yes | m -S m,n |Adjustments are made, i.e. by Yes | m -S m,n |Adjust the E1 obtained m,n More reliable.

[0050] Therefore, in this embodiment, the first possibility characterization value between each sensor in the mining area and each neighboring sensor in the corresponding neighboring sensor set can be obtained through the above process.

[0051] Since there are a large number of neighboring sensors of each sensor in the mining area, the credibility of determining whether there is dust transfer between the mining area monitored by each sensor and the mining area monitored by its corresponding neighboring sensor based only on the first possibility characterization value between each sensor and each neighboring sensor in the neighboring sensor set obtained above is low, that is, only based on the first possibility characterization value may lead to misjudgment. For example, the neighboring sensors of sensor g1 in the mining area include sensor g2 and sensor g3, and sensor g3 is also a neighboring sensor of sensor g2. If it is actually that the dust in the mining area monitored by sensor g1 is transferred to the mining area monitored by sensor g2, and the dust in the mining area monitored by sensor g2 is transferred to the mining area monitored by sensor g3, if at this time the difference between the change characterization value corresponding to sensor g1 and the change characterization value corresponding to sensor g3 is small, then at this time, only based on the first possibility characterization value, it may be determined that the dust in the mining area monitored by sensor g1 is transferred to the mining area monitored by sensor g3, which leads to misjudgment. , therefore, the target dust concentration corresponding to each sensor at the current control moment cannot be reliably obtained based only on the first possibility characterization value; however, when there is dust transfer caused by air flow in the mining area, it is usually rare that there is a single transfer from a mining area monitored by one sensor to a mining area monitored by another sensor, and most of the time, the mining area monitored by some sensors is transferred to the mining area monitored by other sensors. Therefore, in order to more reliably obtain the target dust concentration corresponding to each sensor at the current control moment, this embodiment will subsequently obtain the second possibility characterization value between each sensor and its corresponding neighboring sensor by analyzing the neighboring sensor set corresponding to each sensor in the mining area and the neighboring sensor set corresponding to each neighboring sensor in its corresponding neighboring sensor set. Subsequently, based on the first possibility characterization value and the second possibility characterization value, the current dust concentration corresponding to each sensor at the current control moment can be more reliably adjusted, that is, the target dust concentration corresponding to each sensor at the current control moment can be more reliably obtained. Therefore, the specific process of obtaining the second possibility characterization value is:

[0052] For the mth sensor in the mining area and the nth neighbor sensor in its corresponding neighbor sensor set:

[0053] The set constructed by all neighbor sensors that belong to both the neighbor sensor set corresponding to the mth sensor and the neighbor sensor set corresponding to the nth neighbor sensor is recorded as the shared neighbor sensor set; that is, for any sensor in the mining area, if the sensor belongs to the neighbor sensor set corresponding to the mth sensor and also to the neighbor sensor set corresponding to the nth neighbor sensor, it indicates that the sensor is in the shared neighbor sensor set.

[0054] In the shared neighbor sensor set, a set constructed by all neighbor sensors having the same slope sign value as the fitting straight line corresponding to the m-th sensor is recorded as the first sensor set corresponding to the m-th sensor, and the sensors in the first sensor set are recorded as the first sensors; in the shared neighbor sensor set, a set constructed by all neighbor sensors having the same slope sign value as the fitting straight line corresponding to the n-th neighbor sensor is recorded as the second sensor set corresponding to the n-th neighbor sensor, and the sensors in the second sensor set are all recorded as the second sensors.

[0055] And the slope of the fitting straight line corresponding to the first sensor that is closer to the mth sensor in the first sensor set corresponding to the mth sensor is more important. The second sensor in the second sensor set corresponding to the nth neighbor sensor also has the same property, and the slope can characterize the dust concentration change trend in the mining area monitored by the sensor; therefore, for the i-th first sensor in the first sensor set corresponding to the m-th sensor, the reciprocal of the position distance between the m-th sensor and the i-th first sensor in the mining area is recorded as the weight corresponding to the i-th first sensor, and the product of the slope of the fitting straight line corresponding to the i-th first sensor and the weight corresponding to the i-th first sensor is recorded as the eigenvalue corresponding to the i-th first sensor; for the j-th second sensor in the second sensor set corresponding to the n-th neighbor sensor, the reciprocal of the position distance between the n-th neighbor sensor and the j-th second sensor is recorded as the weight corresponding to the j-th second sensor, and the product of the slope of the fitting straight line corresponding to the j-th second sensor in the second sensor set corresponding to the n-th neighbor sensor and the weight corresponding to the j-th second sensor is recorded as the eigenvalue corresponding to the j-th second sensor.

[0056] Therefore, through the above process, the characteristic values ​​corresponding to each first sensor in the first sensor set corresponding to the mth sensor and the characteristic values ​​corresponding to each second sensor in the second sensor set corresponding to the nth neighboring sensor in the neighboring sensor set corresponding to the mth sensor can be obtained.

[0057] The value obtained by adding the slope of the fitting straight line corresponding to the m-th sensor and the cumulative sum of the eigenvalues ​​corresponding to all first sensors in the first sensor set corresponding to the m-th sensor is recorded as the neighbor comprehensive representation value corresponding to the m-th sensor; the value obtained by adding the slope of the fitting straight line corresponding to the n-th neighbor sensor and the cumulative sum of the eigenvalues ​​corresponding to all second sensors in the second sensor set corresponding to the n-th neighbor sensor is recorded as the neighbor comprehensive representation value corresponding to the n-th neighbor sensor in the neighbor set corresponding to the m-th sensor.

[0058] Since dust transfer may exist between the mining area monitored by the corresponding sensor and the mining area monitored by its corresponding neighboring sensor only when the product of the slope sign value of the fitting straight line corresponding to each sensor and the slope sign value of the fitting straight line corresponding to its corresponding neighboring sensor is -1, if it is judged that the product of the slope sign value of the fitting straight line corresponding to the mth sensor and the slope sign value of the fitting straight line corresponding to the nth neighboring sensor is not -1, it indicates that the possibility of dust transfer between the mining area monitored by the mth sensor and the mining area monitored by the nth neighboring sensor is 0, and the second possibility characterization value between the mth sensor and the nth neighboring sensor in the corresponding neighboring sensor set is recorded as 0.

[0059] If it is determined that the product of the slope sign value of the fitting line corresponding to the m-th sensor and the slope sign value of the fitting line corresponding to the n-th neighboring sensor is -1, then according to the slope of the fitting line corresponding to the m-th sensor, the neighbor comprehensive characterization value corresponding to the m-th sensor, the slope of the fitting line corresponding to the n-th neighboring sensor, the neighbor comprehensive characterization value corresponding to the n-th neighboring sensor, and the first possibility characterization value between the m-th sensor and the n-th neighboring sensor in the corresponding neighboring sensor set, the second possibility characterization value between the m-th sensor and the n-th neighboring sensor in the corresponding neighboring sensor set is obtained, and the second possibility characterization value between the m-th sensor and the n-th neighboring sensor in the corresponding neighboring sensor set is calculated according to the following formula:

[0060]

[0061] Among them, E2 m,n is the second possible representation value between the mth sensor and the nth neighboring sensor in the corresponding neighboring sensor set, Norm() is the normalization function, a m is the slope of the fitting line corresponding to the mth sensor, a1 m is the comprehensive representation value of the nearest neighbor corresponding to the mth sensor, a m,n is the slope of the fitted line corresponding to the nth neighbor sensor in the neighbor sensor set corresponding to the mth sensor, a1 m,n is the comprehensive representation value of the nearest neighbor corresponding to the nth nearest neighbor sensor, E1 m is the cumulative sum of the first possible characterization values ​​between the mth sensor and all neighboring sensors in its corresponding neighboring sensor set, and E1 m It is for E1 m,n Normalize.

[0062] In this embodiment, when |a m +a1 m |-|a m,n+a1 m,n The smaller | is, it can only indicate that there is a greater possibility of dust transfer between the mining areas monitored by all the first sensors in the first sensor set corresponding to the mth sensor and the mining areas monitored by all the second sensors in the second sensor set corresponding to the nth neighboring sensor during the period from the historical collection time to the current control, but it cannot reliably indicate that there is a greater possibility of dust transfer between the mining areas monitored by the mth sensor and the mining areas monitored by the nth neighboring sensor during the period from the historical collection time to the current control, and it cannot reliably indicate that there is a greater possibility of dust transfer between the mining areas monitored by the mth sensor and the mining areas monitored by the nth neighboring sensor in the future time period. Therefore, only when |a m +a1 m |-|a m,n +a1 m,n |The smaller and The larger the value, the greater the possibility of dust transfer between the mining area monitored by the mth sensor and the mining area monitored by the nth neighboring sensor during the period from the historical collection time to the current control, and the greater the possibility of dust transfer between the mining area monitored by the mth sensor and the mining area monitored by the nth neighboring sensor in the future time period; that is, when (|a m +a1 m |-|a m,n +a1 m,n |)The smaller and The larger the E2 m,n The larger the value of E2 m,n The larger the value of is, the greater the possibility of dust transfer between the mining area monitored by the mth sensor and the mining area monitored by the nth neighboring sensor in the future time period; on the contrary, when (|a m +a1 m |-|a m,n +a1 m,n |)The bigger and The smaller the time, the higher the E2 m,n The smaller the value of E2 m,n The smaller the value of , the greater the possibility of dust transfer between the mining area monitored by the mth sensor and the mining area monitored by the nth neighboring sensor in the future time period.

[0063] Therefore, the first possibility characterization value and the second possibility characterization value between the mth sensor and the nth neighboring sensor in the corresponding neighboring sensor set are obtained in the above manner, and then the product of the first possibility characterization value and the second possibility characterization value between the mth sensor and the nth neighboring sensor is recorded as the target possibility characterization value between the mth sensor and the nth neighboring sensor in the corresponding neighboring sensor set; and the larger the first possibility characterization value and the second possibility characterization value, the larger the target possibility characterization value, and the larger the target possibility characterization value, indicates that the mth sensor monitored in the time period from the historical collection moment to the current control moment is The greater the possibility of dust transfer between the mining area monitored by the mth sensor and the mining area monitored by the nth neighboring sensor, the greater the possibility of dust transfer between the mining area monitored by the mth sensor and the mining area monitored by its nth neighboring sensor in the future time period; conversely, the smaller the possibility of dust transfer between the mining area monitored by the mth sensor and the mining area monitored by the nth neighboring sensor in the time period from the historical collection time to the current control time, the smaller the possibility of dust transfer between the mining area monitored by the mth sensor and the mining area monitored by the nth neighboring sensor in the future time period.

[0064] Therefore, the target possibility representation value between each sensor and each neighboring sensor in the corresponding neighboring sensor set can be obtained through the above method.

[0065] Next, this embodiment obtains the adjustment degree corresponding to each sensor in the mining area at the current control moment according to the target possibility characterization value between each sensor in the mining area and each neighboring sensor in the corresponding neighboring sensor set and the change characterization value corresponding to each sensor in the mining area and each neighboring sensor in the corresponding neighboring sensor set; the adjustment degree corresponding to the mth sensor in the mining area at the current control moment is calculated according to the following formula:

[0066]

[0067] Among them, γ m is the adjustment degree of the mth sensor in the mining area at the current control moment, N is the number of neighboring sensors in the neighboring sensor set corresponding to the mth sensor in the mining area, E' m,n It is a characterization value of the target dust transfer possibility between the mth sensor in the mining area and the nth neighboring sensor in its corresponding neighboring sensor set.

[0068] when When γ is 0, it indicates that there is no dust transfer between the mining area monitored by the mth sensor and the mining area monitored by other sensors during the period from the historical collection time to the current control time, and it also indicates that the probability of dust transfer between the mining area monitored by the mth sensor and the mining area monitored by other sensors in the future time period is extremely small. Therefore, there is no need to adjust the current dust concentration corresponding to the sensor at the current control time. That is, γ m is 0; in addition, the historical collection time in this embodiment refers to the historical collection time when the first data in the characteristic dust concentration sequence is collected.

[0069] when When it is a positive number, it indicates that the dust concentration in the mining area monitored by the m-th sensor shows an upward trend, which means that the dust in the mining area monitored by the neighboring sensor corresponding to the m-th sensor has a tendency to transfer to the mining area monitored by the m-th sensor in the future time period; since the change representation value corresponding to the sensor can reflect the magnitude of the increase or decrease in the dust concentration in the mining area monitored by the sensor in the future time period, the target possibility representation value between the m-th sensor and the n-th neighboring sensor can reflect the possibility of dust transfer between the mining area monitored by the m-th sensor and the mining area monitored by the n-th neighboring sensor in the future time period. Therefore, when the change representation value corresponding to the n-th neighboring sensor in the neighboring sensor set corresponding to the m-th sensor is larger and the target possibility representation value is larger, that is, S m,n The bigger and E' m,n The larger the value is, the greater the possibility and amount of dust in the mining area monitored by the nth neighboring sensor will be transferred to the mining area monitored by the mth sensor in the future time period; that is, when When is a positive number, if The larger the value, the m The larger the value is, the greater the subsequent adjustment of the current dust concentration corresponding to the mth sensor at the current control time is, and the greater the degree of increase is; on the contrary, when When is a positive number, if The smaller γ is, the m The smaller it is, the smaller the subsequent adjustment of the current dust concentration of the mth sensor corresponding to the current control moment will be, and the smaller the degree of increase will be.

[0070] when When it is a negative number, it indicates that the dust concentration in the mining area monitored by the mth sensor shows a downward trend, which means that in the future time period, the dust in the mining area monitored by the mth sensor has a tendency to transfer to the mining area monitored by the neighboring sensor corresponding to the mth sensor; and when the change representation value corresponding to the nth neighboring sensor in the neighboring sensor set corresponding to the mth sensor is larger and the target possibility representation value is larger, that is, S m,n The bigger and E' m,n The larger the value, the greater the possibility and amount of dust transfer from the mining area monitored by the mth sensor to the mining area monitored by the nth neighboring sensor in the future time period; that is, when If it is a negative number, The larger the value, the m The smaller it is, the greater the subsequent adjustment of the current dust concentration corresponding to the mth sensor at the current control time is, and the greater the degree of reduction is; on the contrary, when If it is a negative number, The smaller γ is, the m The larger it is, the smaller the subsequent adjustment of the current dust concentration of the mth sensor corresponding to the current control moment will be, and the smaller the degree of reduction will be.

[0071] Therefore, through the above process, this embodiment can obtain the adjustment degree corresponding to each sensor in the mining area at the current control moment; then the sum of the current dust concentration corresponding to each sensor at the current control moment and the adjustment degree corresponding to the corresponding sensor is recorded as the target dust concentration corresponding to the corresponding sensor at the current control moment.

[0072] Step S004, clustering the historical dust concentrations in the historical dust concentration sequence to obtain various clusters; obtaining the clusters corresponding to the various sensors according to the differences between the target dust concentrations corresponding to the various sensors at the current control moment and the cluster center points of the various clusters, and regulating the operating parameters of the wireless Feng Shui automatic spraying system according to the clusters corresponding to the various sensors.

[0073] This embodiment will then cluster the historical dust concentrations, and then adjust the operating parameters of the wireless Feng Shui automatic spraying system based on the clustering results and the target dust concentration corresponding to each sensor at the current control time. Therefore, the process of obtaining each cluster in this embodiment is as follows:

[0074] In order to improve the accuracy of subsequent clustering, this embodiment does not directly perform clustering based on the distance between historical dust concentrations, but performs clustering based on the difference between local data sequences constructed by historical dust concentrations, specifically:

[0075] For the cth historical dust concentration in the historical dust concentration sequence corresponding to any sensor: in the historical dust concentration sequence corresponding to the sensor, the data sequence constructed by the historical dust concentration, A consecutive historical dust concentrations adjacent to and located on the left side of the historical dust concentration, and A consecutive historical dust concentrations adjacent to and located on the right side of the historical dust concentration is recorded as the local data sequence corresponding to the historical dust concentration, that is, the number of historical dust concentrations in the local data sequence corresponding to the historical dust concentration is 2A+1. If the number of historical dust concentrations on one side of the historical dust concentration is less than A, 0 is padded so that the length of the local data sequence is 2A+1. In specific applications, the value of A needs to be set according to actual conditions. For example, in this embodiment, the value of A is set to 5, then the number of historical dust concentrations in the local data sequence corresponding to the historical dust concentration is 11.

[0076] Then, the set constructed by the historical dust concentrations of all dust concentrations collected by all sensors in the mining area in the historical time period is recorded as the historical dust concentration set; then, the Euclidean distance between the local data sequences corresponding to any two historical dust concentrations in the historical dust concentration set is calculated, and the historical dust concentrations in the local data sequence are also arranged in the order of collection time; then, all the historical dust concentrations in the historical dust concentration set are clustered using the K-means clustering algorithm and the Euclidean distance between the local data sequences corresponding to any two historical dust concentrations in the historical dust concentration set to obtain various clustering clusters, and the number of clustering clusters in this embodiment is K, and the value of K is obtained by using the elbow method, that is, when clustering, the distance between the two historical dust concentrations is characterized by the Euclidean distance between the local data sequences corresponding to any two historical dust concentrations obtained by calculation, and the method of obtaining K by the elbow method is a well-known technology, so this embodiment will not be described in detail.

[0077] Therefore, this embodiment can obtain each cluster and the cluster center point of each cluster through the above process; then set the operating parameters of the wireless Feng Shui automatic spraying and dust reduction system corresponding to each cluster according to the dust concentration range corresponding to each cluster, and record them as the operating parameters of the automatic spraying equipment corresponding to each cluster, the operating parameters include spraying intensity and spraying frequency, and the wireless Feng Shui automatic spraying and dust reduction system includes automatic spraying equipment.

[0078] In addition, in this embodiment, the operating parameters of the automatic spraying equipment corresponding to each cluster are set by relevant professional personnel based on the dust concentration range corresponding to each cluster. In order to better control the dust concentration in the mining area, under normal circumstances, when the dust concentration is high, the operating parameters of the set automatic spraying equipment are also relatively large.

[0079] Next, this embodiment will obtain the clusters corresponding to each sensor at the current control time based on the target dust concentration and each cluster corresponding to each sensor at the current control time obtained above. Subsequently, the intelligent control of the operating parameters of the wireless Feng Shui automatic spraying system is realized through the clusters corresponding to each sensor in the mining area at the current control time, specifically:

[0080] For the mth sensor in a mine:

[0081] The absolute value of the difference between the target dust concentration corresponding to the sensor at the current control moment and the ordinate value of the cluster center point of each cluster cluster is calculated and recorded as the difference value, and the cluster cluster corresponding to the minimum difference value among the difference values ​​between the target dust concentration corresponding to the sensor at the current control moment and the ordinate value of the cluster center point of each cluster cluster is recorded as the cluster cluster corresponding to the sensor at the current control moment; and at the current control moment, the operating parameters of the automatic spraying equipment for spraying and dust reduction in the mining area monitored by the sensor are adjusted to the operating parameters of the automatic spraying equipment corresponding to the cluster cluster corresponding to the sensor; since the operating parameters in this embodiment include spraying intensity and spraying frequency, the operating parameters of the automatic spraying equipment for spraying and dust reduction in the mining area monitored by the sensor between the current control moment and the next control moment are the operating parameters of the automatic spraying equipment corresponding to the cluster cluster corresponding to the sensor.

[0082] Therefore, through the above process, the operating parameters of the automatic spraying equipment of the wireless Feng Shui automatic spraying system for spraying and dust reduction in the mining area monitored by each sensor can be reliably adjusted or regulated.

[0083] In summary, this embodiment can reliably determine the target dust concentration corresponding to each sensor in the mining area at the current control time through the fitting straight lines corresponding to each sensor in the mining area and the fitting straight lines corresponding to each neighboring sensor in the neighboring sensor set corresponding to each sensor. That is, this embodiment can reliably adjust the current dust concentration corresponding to each sensor in the mining area at the current control time based on the fitting straight lines corresponding to each sensor in the mining area and the fitting straight lines corresponding to each neighboring sensor in the neighboring sensor set corresponding to each sensor, and then cluster the historical dust concentrations in the historical dust concentration sequence to obtain each Clusters are formed, and according to the difference between the target dust concentration corresponding to each sensor at the current control moment and the cluster center point of each cluster, the cluster corresponding to each sensor is obtained. Finally, according to the cluster corresponding to each sensor, the operation parameters of the wireless Feng Shui automatic spraying system can be reliably regulated. That is, the operation parameters of the wireless Feng Shui automatic spraying and dust reduction system determined by this embodiment based on the target dust concentration corresponding to each sensor at the current control moment can avoid the waste of spraying resources as much as possible when spraying and reducing dust in the mining area, and can also relatively effectively reduce the dust concentration or relatively effectively control the dust concentration.

[0084] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. An intelligent control method for a wireless Feng Shui automatic spraying and dust reduction system, characterized in that: The method comprises the following steps: Obtain the historical dust concentration sequence corresponding to each sensor in the mining area and the current dust concentration corresponding to each sensor in the mining area at the current control time; According to the position distances between the sensors in the mining area, a set of neighboring sensors corresponding to each sensor is obtained; According to the current dust concentration corresponding to each sensor at the current control moment and the historical dust concentration sequence corresponding to each sensor, a fitting straight line corresponding to each sensor is obtained; According to the fitting straight lines corresponding to the respective sensors and the fitting straight lines corresponding to the respective neighboring sensors in the neighboring sensor set corresponding to the respective sensors, the target dust concentration corresponding to the respective sensors in the mining area at the current control time is obtained; Clustering the historical dust concentrations in the historical dust concentration sequence to obtain various clusters; obtaining the clusters corresponding to the various sensors according to the differences between the target dust concentrations corresponding to the various sensors at the current control moment and the cluster centers of the various clusters, and regulating the operating parameters of the wireless Feng Shui automatic spraying system according to the clusters corresponding to the various sensors; The method for obtaining the target dust concentration corresponding to each sensor at the current control moment includes: obtaining the adjustment degree corresponding to each sensor at the current control moment, and recording the sum of the current dust concentration corresponding to each sensor at the current control moment and the adjustment degree corresponding to the corresponding sensor as the target dust concentration corresponding to the corresponding sensor at the current control moment.

2. The intelligent control method of a wireless Feng Shui automatic spraying and dust reduction system according to claim 1, characterized in that: The method for obtaining a set of neighboring sensors corresponding to each sensor includes: For any sensor in the mining area: all sensors in the mining area except the sensor are recorded as the sensors to be determined corresponding to the sensor; for any sensor to be determined corresponding to the sensor, the position distance between the sensor and the sensor to be determined is recorded as the first distance corresponding to the sensor to be determined; all sensors to be determined corresponding to the sensor are sorted in order from small to large according to the first distance to obtain a sequence of sensors to be determined corresponding to the sensor; the first F sensors to be determined in the sequence of sensors to be determined are recorded as the neighboring sensors corresponding to the sensor, and the set constructed by all the neighboring sensors corresponding to the sensor is recorded as the neighboring sensor set corresponding to the sensor.

3. The intelligent control method of a wireless Feng Shui automatic spraying and dust reduction system according to claim 1, characterized in that: The method for obtaining the fitting straight lines corresponding to the sensors includes: For any sensor in a mine: The current dust concentration corresponding to the sensor at the current control moment and the sequence constructed by the last B historical dust concentrations in the historical dust concentration sequence corresponding to the sensor are recorded as the characteristic dust concentration sequence corresponding to the sensor, and the mark value of the d-th dust concentration in the characteristic dust concentration sequence is recorded as d; Constructing a two-dimensional space, wherein the horizontal axis of the two-dimensional space is the mark value and the vertical axis is the dust concentration; Each dust concentration in the characteristic dust concentration sequence and the label value of each dust concentration are mapped to the two-dimensional space to obtain the data points corresponding to each dust concentration in the characteristic dust concentration sequence, and all of them are recorded as the original data points corresponding to the sensor. The least squares method is used to perform linear fitting on all the original data points corresponding to the sensor to obtain the fitting straight line corresponding to the sensor.

4. The intelligent control method of a wireless Feng Shui automatic spraying and dust reduction system as claimed in claim 3, characterized in that: The method for obtaining the adjustment degree of each sensor corresponding to the current control moment includes: For any sensor in a mine: The abscissa value of the data point corresponding to the last dust concentration in the characteristic dust concentration sequence corresponding to the sensor is recorded as the characteristic abscissa value; a data point whose ordinate value is 0 and whose abscissa value is the characteristic abscissa value is obtained in the two-dimensional space, and recorded as the first data point corresponding to the sensor; a straight line passing through the first data point and parallel to the ordinate axis in the two-dimensional space is recorded as the characteristic straight line corresponding to the sensor; an intersection point between the fitting straight line corresponding to the sensor and the characteristic straight line corresponding to the sensor is recorded as the second data point corresponding to the sensor; a change characterization value corresponding to the sensor is obtained according to the intercept of the fitting straight line corresponding to the sensor and the coordinate value of the second data point; a slope sign value of the fitting straight line corresponding to the sensor is obtained according to the slope of the fitting straight line corresponding to the sensor; On the fitting straight line corresponding to the sensor, the fitting data points corresponding to the original data points corresponding to the sensor are obtained; the absolute value of the difference between the ordinate value of each original data point corresponding to the sensor and the ordinate value of the fitting data point corresponding to the sensor is recorded as the residual corresponding to the original data point; the cumulative sum of the residuals corresponding to all the original data points corresponding to the sensor is normalized, and the value after negative mapping the cumulative sum of the normalized residuals is recorded as the fitting confidence of the fitting straight line corresponding to the sensor; For the mth sensor in the mining area and the nth neighboring sensor in the neighboring sensor set corresponding to the mth sensor: Obtaining a first possibility characterization value between the m-th sensor and the n-th neighboring sensor according to the fitting confidence of the fitting straight line corresponding to the m-th sensor, the fitting confidence of the fitting straight line corresponding to the n-th neighboring sensor, the change characterization value corresponding to the m-th sensor, the change characterization value corresponding to the n-th neighboring sensor, the slope sign value of the fitting straight line corresponding to the m-th sensor, and the slope sign value of the fitting straight line corresponding to the n-th neighboring sensor; Recording a set constructed by all neighboring sensors that belong to both the neighboring sensor set corresponding to the m-th sensor and the neighboring sensor set corresponding to the n-th neighboring sensor as a shared neighboring sensor set; In the shared neighbor sensor set, a set constructed by all neighbor sensors having the same slope sign value as the fitted straight line corresponding to the m-th sensor is recorded as a first sensor set corresponding to the m-th sensor, and sensors in the first sensor set are recorded as first sensors; in the shared neighbor sensor set, a set constructed by all neighbor sensors having the same slope sign value as the fitted straight line corresponding to the n-th neighbor sensor is recorded as a second sensor set corresponding to the n-th neighbor sensor, and sensors in the second sensor set are all recorded as second sensors; Obtaining a second possibility characterization value between the m-th sensor and the n-th neighboring sensor according to the slope of the fitting straight line corresponding to the m-th sensor, the position distance between the m-th sensor and each first sensor in the first sensor set, the slope of the fitting straight line corresponding to each first sensor in the first sensor set, the slope of the fitting straight line corresponding to the n-th neighboring sensor, the position distance between the n-th neighboring sensor and each second sensor in the second sensor set, and the slope of the fitting straight line corresponding to each second sensor in the second sensor set; The product of the first possibility representation value and the second possibility representation value between the m-th sensor and the n-th neighboring sensor is recorded as the target possibility representation value between the m-th sensor and the n-th neighboring sensor; According to the slope sign value of the fitting straight line corresponding to each sensor, the target possibility characterization value between each sensor and each neighboring sensor in its corresponding neighboring sensor set, and the change characterization value corresponding to each sensor and each neighboring sensor in its corresponding neighboring sensor set, the adjustment degree corresponding to each sensor at the current control moment is obtained.

5. The intelligent control method of the wireless Feng Shui automatic spraying and dust reduction system according to claim 4, characterized in that: The method for obtaining the change characterization value corresponding to the sensor includes: The absolute value of the difference between the intercept of the fitting straight line corresponding to the sensor and the ordinate value of the second data point corresponding to the sensor is recorded as the first characterization value corresponding to the sensor, and the abscissa value of the second data point corresponding to the sensor is recorded as the second characterization value corresponding to the sensor; the product of the first characterization value corresponding to the sensor and the second characterization value corresponding to the sensor is recorded as the change characterization value corresponding to the sensor.

6. The intelligent control method of a wireless Feng Shui automatic spraying and dust reduction system as claimed in claim 4, characterized in that: The method for obtaining the slope sign value of the fitting straight line corresponding to the sensor includes: If the slope of the fitted straight line corresponding to the sensor is positive, the sign value of the slope of the fitted straight line corresponding to the sensor is recorded as 1. If the slope of the fitted straight line corresponding to the sensor is negative, the sign value of the slope of the fitted straight line corresponding to the sensor is recorded as -1. If the slope of the fitted straight line corresponding to the sensor is 0, the sign value of the slope of the fitted straight line corresponding to the sensor is recorded as 0.

7. The intelligent control method of a wireless Feng Shui automatic spraying and dust reduction system as claimed in claim 4, characterized in that: The method for obtaining a first possible characterization value between the m-th sensor and the n-th neighboring sensor comprises: If it is determined that the product of the slope sign value of the fitting straight line corresponding to the m-th sensor and the slope sign value of the fitting straight line corresponding to the n-th neighboring sensor is not -1, the first possibility representation value between the m-th sensor and the n-th neighboring sensor is recorded as 0; If it is determined that the product of the slope sign value of the fitting straight line corresponding to the mth sensor and the slope sign value of the fitting straight line corresponding to the nth neighboring sensor is -1, the first possible representation value between the mth sensor and the nth neighboring sensor is calculated according to the following formula: ； in, is a first possible representation value between the m-th sensor and the n-th neighboring sensor, is the fitting confidence of the fitting line corresponding to the m-th sensor, is the fitting confidence of the fitting straight line corresponding to the nth neighboring sensor in the neighboring sensor set corresponding to the mth sensor, is the change representation value corresponding to the mth sensor, is the change representation value corresponding to the nth neighboring sensor in the neighboring sensor set corresponding to the mth sensor, and exp() is an exponential function with a constant e as the base.

8. The intelligent control method of a wireless Feng Shui automatic spraying and dust reduction system as claimed in claim 7, characterized in that: The method for obtaining a second possible characterization value between the m-th sensor and the n-th neighboring sensor includes: For the ith first sensor in the first sensor set corresponding to the mth sensor, the reciprocal of the position distance between the mth sensor and the ith first sensor is recorded as the weight corresponding to the ith first sensor, and the product of the slope of the fitting straight line corresponding to the ith first sensor and the corresponding weight is recorded as the eigenvalue corresponding to the ith first sensor; For the j-th second sensor in the second sensor set corresponding to the n-th neighbor sensor, the reciprocal of the position distance between the n-th neighbor sensor and the j-th second sensor is recorded as the weight corresponding to the j-th second sensor, and the product of the slope of the fitting line corresponding to the j-th second sensor and the corresponding weight is recorded as the eigenvalue corresponding to the j-th second sensor; The value obtained by adding the slope of the fitting straight line corresponding to the m-th sensor and the cumulative sum of the eigenvalues ​​corresponding to all the first sensors in the first sensor set is recorded as the neighbor comprehensive characterization value corresponding to the m-th sensor; the value obtained by adding the slope of the fitting straight line corresponding to the n-th neighbor sensor and the cumulative sum of the eigenvalues ​​corresponding to all the second sensors in the second sensor set is recorded as the neighbor comprehensive characterization value corresponding to the n-th neighbor sensor; If it is determined that the product of the slope sign value of the fitting straight line corresponding to the mth sensor and the slope sign value of the fitting straight line corresponding to the nth neighboring sensor is not -1, the second possibility characterization value between the mth sensor and the nth neighboring sensor is recorded as 0; if it is determined that the product of the slope sign value of the fitting straight line corresponding to the mth sensor and the slope sign value of the fitting straight line corresponding to the nth neighboring sensor is -1, the second possibility characterization value between the mth sensor and the nth neighboring sensor is calculated according to the following formula: ； in, is the second possible characterization value between the m-th sensor and the n-th neighboring sensor, Norm() is a normalization function, is the slope of the fitting line corresponding to the mth sensor, is the comprehensive representation value of the nearest neighbor corresponding to the m-th sensor, is the slope of the fitting line corresponding to the nth neighboring sensor, is the neighbor comprehensive representation value corresponding to the nth neighbor sensor, is the cumulative sum of the first possibility representation values ​​between the m-th sensor and all neighboring sensors in its corresponding neighboring sensor set.

9. The intelligent control method of a wireless Feng Shui automatic spraying and dust reduction system as claimed in claim 8, characterized in that: The adjustment degree of the mth sensor at the current control moment is calculated according to the following formula: ； in, is the adjustment degree of the m-th sensor at the current control moment, N is the number of neighboring sensors in the neighboring sensor set corresponding to the m-th sensor, is a target possibility representation value between the m-th sensor and the n-th neighboring sensor.

10. The intelligent control method of a wireless Feng Shui automatic spraying and dust reduction system according to claim 1, characterized in that: The method for regulating the operating parameters of the wireless Feng Shui automatic sprinkler system according to the clusters corresponding to each sensor includes: Obtaining the operating parameters of the automatic spraying equipment corresponding to each of the clusters, wherein the automatic spraying equipment is an automatic spraying equipment in a wireless Feng Shui automatic spraying system; For any sensor in a mine: At the current control moment, the operating parameters of the automatic spraying equipment for spraying dust reduction in the mining area monitored by the sensor are adjusted to the operating parameters of the automatic spraying equipment corresponding to the cluster corresponding to the sensor.

Images