CN116916193B - Coal mining data transmission method for multi-platform collaborative operation - Google Patents
Coal mining data transmission method for multi-platform collaborative operation Download PDFInfo
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- 239000003245 coal Substances 0.000 title claims abstract description 108
- 230000005540 biological transmission Effects 0.000 title claims abstract description 69
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- 238000005065 mining Methods 0.000 title claims abstract description 57
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- 239000004484 Briquette Substances 0.000 description 6
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Abstract
The invention relates to the technical field of data transmission, in particular to a coal mining data transmission method for multi-platform collaborative operation. The method comprises the steps of sequentially obtaining current data sequences corresponding to a coal cutter platform, a scraper conveyor platform, a reversed loader platform, a crusher platform and a belt conveyor platform; acquiring a first fluctuation value according to the difference between each current data in the current data sequence and other current data; acquiring a second fluctuation value according to the change degree between each current data and the current data at the preset position; according to the first fluctuation value and the second fluctuation value, obtaining the fluctuation degree, further obtaining a regular fluctuation degree sequence, constructing a fluctuation tuple sequence, and obtaining a transmission value; and determining current data transmitted to the fully-mechanized co-operation system according to the transmission value. The invention eliminates the problems of strong isolation and mismatching of current data caused by a lag time period, thereby accurately finding out the abnormality in the platform and ensuring the recovery efficiency of coal blocks.
Description
Technical Field
The invention relates to the technical field of data transmission, in particular to a coal mining data transmission method for multi-platform collaborative operation.
Background
The fully-mechanized coal mining working face is a source for coal block production, wherein fully-mechanized coal mining equipment comprises a coal mining machine, a scraper conveyor, a reversed loader, a crusher, a belt conveyor and the like, and is a main tool for coal block stoping. The working condition of the fully-mechanized coal mining equipment directly influences the stoping condition of the coal blocks, so that the running reliability of the fully-mechanized coal mining equipment is improved, the smooth stoping of the coal blocks is ensured, the platform of each fully-mechanized coal mining equipment is required to be monitored in real time, and the anomalies in the platform of the fully-mechanized coal mining equipment are found in time and processed.
In the coal recovery process, the technical indexes, the demand parameters and the like of each platform are difficult to unify, for example, the reciprocating distance of a cutter head and the temperature of a motor are required to be monitored by a coal mining machine, and the speed of the motor is required to be monitored by a scraper conveyor and a reversed loader, so that information between the platforms is not matched; moreover, different lag time periods exist among different platforms of the coal briquette, so that the abnormality judgment can not be carried out on the different platforms at the same time sequence, the information isolation among the different platforms is serious, and the abnormality in the platforms can not be found in time. Meanwhile, due to different lag time periods between different platforms, excessive data redundancy of part of the platforms can be caused, unified corresponding data in each platform cannot be accurately analyzed, and abnormality in the platforms cannot be accurately identified.
Disclosure of Invention
In order to solve the technical problems of data isolation and redundancy caused by a lag time period between different platforms, which lead to the problem that abnormality in the platforms cannot be found accurately and timely, the invention aims to provide a coal mining data transmission method for multi-platform collaborative operation, and the adopted technical scheme is as follows:
the invention provides a coal mining data transmission method for multi-platform collaborative operation, which comprises the following steps:
acquiring current data sequences corresponding to a coal cutter platform, a scraper conveyor platform, a reversed loader platform, a crusher platform and a belt conveyor platform in sequence;
according to the difference between each current data in each current data sequence and other current data, a first fluctuation value of the corresponding current data is obtained; the method comprises the steps of respectively obtaining the change degree between each piece of current data and the current data at a preset position in the current data sequence; acquiring a second fluctuation value of the corresponding current data according to the change degree corresponding to each current data; acquiring the fluctuation degree of corresponding current data according to the first fluctuation value and the second fluctuation value of each current data;
sequencing the fluctuation degrees in each platform to obtain a fluctuation degree sequence of each platform; unifying the length of each fluctuation degree sequence to obtain a regular fluctuation degree sequence of each platform; the fluctuation degrees with the same arrangement positions in the regular fluctuation degree sequence are formed into a fluctuation tuple sequence; acquiring a transmission value of a corresponding fluctuation tuple sequence according to the fluctuation degree of each fluctuation tuple sequence;
And determining current data to be transmitted to the fully-mechanized co-operation system in each platform according to the transmission values.
Further, the method for acquiring the first fluctuation value comprises the following steps:
optionally selecting one current data sequence as a target current sequence, and selecting any one current data in the target current sequence as target current data;
calculating the average value of other current data in the target current sequence except for the target current data as a first reference average value;
and acquiring the absolute value of the difference between the target current data and the first reference mean value as a first fluctuation value of the target current data, and changing the target current data to obtain the first fluctuation value of each current data.
Further, the method for respectively acquiring the variation degree between each current data and the current data at the preset position in the current data sequence comprises the following steps:
acquiring a moment corresponding to the target current data as a target moment, and acquiring a moment corresponding to the current data at a preset position in the target current sequence as a reference moment;
taking the difference value between the target time and the reference time as a target time difference value;
Taking the difference value of the target current data and the current data at a preset position in the target current sequence as a target current difference value;
and changing the target current data by taking the ratio of the target current difference value to the target time difference value as the change degree between the target current data in the target current sequence and the current data at the preset position, and obtaining the change degree between each current data in the target current sequence and the current data at the preset position.
Further, the method for acquiring the second fluctuation value comprises the following steps:
taking the change degree between each current data and the first current data in the current data sequence as a first change degree;
taking the change degree between each current data and the last current data in the current data sequence as a second change degree;
and taking the absolute value of the difference between the absolute value of the first variation degree and the absolute value of the second variation degree as a second fluctuation value.
Further, the method for acquiring the fluctuation degree comprises the following steps:
taking the product of the first fluctuation value and the second fluctuation value as a first result;
and taking the result of the normalization processing of the first result as the fluctuation degree.
Further, the method for sequencing the fluctuation degrees in each platform to obtain a fluctuation degree sequence of each platform comprises the following steps:
and arranging the fluctuation degree corresponding to each current data in the current data sequence of each platform according to the position arrangement sequence of the corresponding current data in the current data sequence to obtain the fluctuation degree sequence of each platform.
Further, the method for acquiring the regular fluctuation degree sequence comprises the following steps:
and keeping the fluctuation degree sequence of each platform consistent with the quantity of the fluctuation degrees in the fluctuation degree sequence of the coal cutter platform through a DTW algorithm, and obtaining a regular fluctuation degree sequence with the same length of each platform.
Further, the method for acquiring the transmission value includes:
acquiring the average value of the fluctuation degree in each fluctuation tuple sequence as the tuple average value of the corresponding fluctuation tuple sequence;
obtaining a fluctuation abnormal value of the corresponding fluctuation tuple sequence according to the difference between each fluctuation degree and other fluctuation degrees in each fluctuation tuple sequence;
taking the product of the tuple mean and the fluctuation outlier as a second result;
and taking the normalized result of the second result as a transmission value.
Further, the method for acquiring the fluctuation outlier comprises the following steps:
optionally selecting one fluctuation tuple sequence as a target fluctuation tuple sequence, and selecting any fluctuation degree in the target fluctuation tuple sequence as a target fluctuation degree;
calculating the mean value of other fluctuation degrees except the target fluctuation degree in the target fluctuation tuple sequence as a second reference mean value;
acquiring the absolute value of the difference between the target fluctuation degree and the second reference mean value as an overall difference value of the target fluctuation degree;
calculating an addition result of a preset constant and the integral difference value as a third result of the target fluctuation degree;
obtaining a third result of each degree of fluctuation in the target fluctuation tuple sequence;
and obtaining the multiplied result of all the third results in the target fluctuation tuple sequence as a fluctuation abnormal value of the target fluctuation tuple sequence.
Further, the method for determining the current data to be transmitted to the fully-mechanized co-operation system in each platform according to the transmission value comprises the following steps:
when the transmission value is greater than or equal to a preset transmission value threshold value, keeping the current data sequences consistent with the current data in the current data sequences of the coal cutter platform through a DTW algorithm, and obtaining regular current data sequences with the same length of each platform; the current data with the same arrangement position in each regular current data sequence is formed into a current tuple sequence; the arrangement sequence of the current data of each platform in the current tuple sequence is the same as the arrangement sequence of the fluctuation degree of each platform in the corresponding fluctuation tuple sequence; transmitting a current tuple sequence corresponding to the fluctuation tuple sequence corresponding to the transmission value to a fully-mechanized mining cooperative operation platform;
When the transmission value is smaller than a preset transmission value threshold, the current data of each platform in the current tuple sequence corresponding to the fluctuation tuple sequence corresponding to the transmission value is not transmitted and is stored in the respective platform.
The invention has the following beneficial effects:
according to the difference between each current data in each current data sequence and other current data, a first fluctuation value of the corresponding current data is obtained, and current data possibly having abnormality is accurately screened out; in order to accurately acquire the fluctuation degree of each current data and further accurately analyze abnormal current data, acquiring the change degree between each current data and the current data at the preset position in the current data sequence, and determining the integral change of the current data in the corresponding current data sequence; therefore, according to the difference between the corresponding change degrees of each current data, a second fluctuation value of the corresponding current data is obtained, the current data is analyzed more accurately, and meanwhile, the problem that the current data cannot be analyzed directly due to overlarge difference of the current data between different platforms is avoided; according to the first fluctuation value and the second fluctuation value of each current data, the fluctuation degree of the corresponding current data is obtained, so that the fluctuation degree of each current data is more accurate; the fluctuation degree sequence of each platform is obtained, the length of each fluctuation degree sequence is adjusted, the regular fluctuation degree sequence of each platform is obtained, the fluctuation degree in each platform is conveniently and uniformly processed, and the problem that data in each platform does not correspond is solved; the fluctuation degree of the same arrangement position in the regular fluctuation degree sequence is formed into a fluctuation tuple sequence, the data in each platform are connected, the data isolation property between each platform is eliminated, the fluctuation degree of fluctuation abnormality can be accurately determined, the transmission value of the corresponding fluctuation tuple sequence is obtained according to the magnitude of each fluctuation degree in each fluctuation tuple sequence, the current data exceeding the normal fluctuation range is accurately obtained, the current data exceeding the normal fluctuation range in each platform is transmitted to the comprehensive mining collaborative operation system, the abnormal fluctuation degree of the current data in the platform is reduced through analysis of the comprehensive mining collaborative operation system, and the coal block recovery process is more efficient. According to the invention, the fluctuation degree of each current data in each platform is obtained, so that the data in each platform can be uniformly and accurately analyzed, the problem that the current data in each platform is not corresponding due to the data isolation and redundancy caused by the lag time period between each platform is solved, the abnormal current data in each platform can be more accurately obtained, the platforms and the adjustment are carried out, and the coal mining efficiency is improved.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions and advantages of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flow chart of a coal mining data transmission method for multi-platform collaborative operation according to an embodiment of the present invention.
Detailed Description
In order to further describe the technical means and effects adopted by the invention to achieve the preset aim, the following is a detailed description of a coal mining data transmission method for multi-platform collaborative operation according to the invention, which is provided by the invention, with reference to the accompanying drawings and the preferred embodiment. In the following description, different "one embodiment" or "another embodiment" means that the embodiments are not necessarily the same. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.
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 belongs.
The following specifically describes a specific scheme of the coal mining data transmission method for multi-platform collaborative operation provided by the invention with reference to the accompanying drawings.
Referring to fig. 1, a flow chart of a coal mining data transmission method for multi-platform collaborative operation according to an embodiment of the invention is shown, the method includes the following steps:
step S1: and sequentially acquiring current data sequences corresponding to the coal cutter platform, the scraper conveyor platform, the reversed loader platform, the crusher platform and the belt conveyor platform.
Specifically, the platform of the fully-mechanized coal mining equipment comprises a coal mining machine platform, a scraper conveyor platform, a reversed loader platform, a crusher platform and a belt conveyor platform. The fully mechanized mining cooperation system is a system for uniformly processing the unified corresponding current data in all platforms.
The scene of the embodiment of the invention is as follows: the data information between each platform is not matched and the operation time period is different in the existing coal block stoping process, so that hysteresis exists in influence fluctuation of each platform on the same coal block. The hysteresis in the embodiment of the invention is as follows: when the coal briquette is in the coal mining machine platform, the scraper conveyor platform, the transfer conveyor platform, the crusher platform and the belt conveyor platform cannot process the coal briquette, and cannot generate data information corresponding to the coal briquette, namely cannot analyze data of a plurality of platforms at the same time. In order to better uniformly analyze the data in each platform, the embodiment of the invention takes a once complete flow of the coal mining blocks as an example, namely, the coal mining blocks start from the coal mining machine platform, pass through each platform in sequence according to the sequence of the coal mining blocks, and until the coal blocks completely leave the belt conveyor platform, and the coal mining blocks are finished.
A sequence of current data for each platform over a run time period is acquired. The operation time period of each platform is a corresponding lag time period of each platform, and a current data sequence of each platform in the corresponding lag time period is obtained. The acquisition method of the current data sequence comprises the following steps: and taking seconds as a unit, acquiring and sequencing current data every second, and acquiring a current data sequence of each platform according to the time sequence from front to back. The method for acquiring the current data sequence in the hysteresis time period corresponding to each platform comprises the following steps:
the cutting part of the coal cutter platform is used for cutting the coal blocks in a reciprocating manner under the traction of electric power, in the coal mining process, the cutting part of the coal cutter platform is different in cutting strength, or the cutting part of the coal cutter platform is different in cutting strength or different in self state, the current data of the coal cutter platform can be fluctuated, and in order to monitor the current fluctuation of the coal cutter platform, a current data sequence of the coal cutter platform in a corresponding lag time period is obtained.
In the coal extraction process of the scraper conveyor platform, the current data of the scraper conveyor platform can be fluctuated due to different coal loading amounts or different self states transported by the scraper conveyor platform, and in order to monitor the current fluctuation in the scraper conveyor platform, a current data sequence of the scraper conveyor platform in a corresponding lag time period is obtained.
The transfer machine platform is single-motor traction equipment, and the transfer machine platform transfers coal block load amounts or the quality of the state of the transfer machine platform is different, so that current data of the transfer machine platform can be fluctuated, and in order to monitor the current fluctuation in the transfer machine platform, a current data sequence of the transfer machine platform in a corresponding lag time period is obtained.
The crusher platform is single motor traction equipment, hardness and size of coal briquette are different in the process of crushing the coal briquette, crushing force of the crusher platform is different, the crushing force in the crusher platform is different or the state of the crusher platform is different, fluctuation of current data of the crusher platform is caused, and in order to monitor the current fluctuation in the crusher platform, a current data sequence of the crusher platform in a corresponding lag time period is obtained.
The belt conveyor platform is double-roller equipment with electric traction, the load capacity of the running coal of the belt conveyor platform is different or the state of the belt conveyor platform is different, the current data of the belt conveyor platform can be fluctuated, and in order to monitor the current fluctuation in the belt conveyor platform, a current data sequence of the belt conveyor platform in a corresponding lag time period is obtained.
Thus, a current data sequence of each platform in a corresponding lag time period is obtained.
The aim of the embodiment of the invention is as follows: aiming at the problems of isolation and redundancy of the current data of each platform caused by a lag time period between the platforms, the embodiment of the invention acquires the fluctuation degree of the current data generated in different platforms, determines abnormal current data according to the fluctuation degree, and transmits the abnormal current data to a fully-mechanized co-operation system, thereby achieving the purpose of eliminating the isolation and redundancy of the current data of each platform, and accurately and timely finding and adjusting the abnormality in the platform.
Step S2: according to the difference between each current data in each current data sequence and other current data, a first fluctuation value of the corresponding current data is obtained; the method comprises the steps of respectively obtaining the change degree between each piece of current data and the current data at a preset position in a current data sequence; acquiring a second fluctuation value of the corresponding current data according to the corresponding change degree of each current data; and acquiring the fluctuation degree of the corresponding current data according to the first fluctuation value and the second fluctuation value of each current data.
Specifically, hysteresis exists between the platforms, and the hysteresis time period of each platform is different, so that the lengths of the current data sequences of different platforms are different, meanwhile, the types of the platforms are different, the current data in each platform may have great difference, and the abnormality in the platforms cannot be directly analyzed according to the current data in each platform uniformly. Therefore, the embodiment of the invention acquires the fluctuation degree of each piece of current data in the current data sequence of each platform, and further analyzes the current data possibly having abnormality in the platform. The specific method for acquiring the fluctuation degree of each current data is as follows:
(1) A first fluctuation value is acquired.
In order to accurately acquire the fluctuation condition of each current data, the embodiment of the invention compares each current data with other current data in a current data sequence to acquire a first fluctuation value of the corresponding current data;
preferably, the method for obtaining the first fluctuation value is as follows: optionally selecting one current data sequence as a target current sequence, and selecting any one current data in the target current sequence as target current data; calculating the average value of other current data excluding the target current data in the target current sequence as a first reference average value; and acquiring the absolute value of the difference between the target current data and the first reference mean value as a first fluctuation value of the target current data, and changing the target current data to obtain the first fluctuation value of each current data.
As an example, the current data sequence of the a-th platform is taken as a target current sequence, the t-th current data in the target current sequence is taken as target current data, wherein the value range of a is [1,5 ]]Because there are a total of 5 platforms in the present embodiment. Acquiring a first reference average value which is the average value of other current data after the t-th current data is removed in the current data sequence of the a-th platform, and acquiring a first fluctuation value L of the t-th current data in the current data sequence of the a-th platform according to the t-th current data and the first reference average value in the current data sequence of the a-th platform a,t The formula of (2) is:
；
wherein L is a,t A first fluctuation value of the t-th current data in the current data sequence of the a-th platform; i a,t T current data in the current data sequence for the a-th platform; n is the total number of current data in the current data sequence of the a-th platform; i a,i Is the ith current data in the current data sequence of the a-th platform, wherein i is not equal to t.
I is that a,t With a first reference mean valueThe closer the current data sequence of the a-th platform, the smaller the fluctuation of the t-th current data, L a,t The more towards 0; i a,t With a first reference mean valueThe greater the difference between the current data sequences, the greater the fluctuation of the t-th current data in the current data sequences of the a-th platform, L a,t The greater than 0; thus, L a,t The larger the current data sequence of the a-th platform, the larger the fluctuation of the t-th current data in the current data sequence of the a-th platform is, the more likely the t-th current data in the current data sequence of the a-th platform is abnormal current data. Wherein,i is not equal to t, the fluctuation condition of the t current data in the current data sequence of the a-th platform can be reflected more accurately, and the possibility of abnormality of the t current data in the current data sequence of the a-th platform can be highlighted more.
According to the method for acquiring the first fluctuation value of the t-th current data in the current data sequence of the a-th platform, the first fluctuation value of each current data in the current data sequence of each platform is acquired.
(2) A second fluctuation value is acquired.
Because the hysteresis period of each platform is fixed, the coal pieces pass through the hysteresis period of each platform as: from the initial contact of each platform to the final complete departure of each platform, the weight of the coal blocks gradually increases gradually in each platform and gradually becomes stable, and then gradually decreases gradually until the coal blocks completely leave the corresponding platforms, and the operation of the coal blocks in the hysteresis time period of each platform is completed. According to the continuous running and weight change of the coal blocks, the current data at each moment in the hysteresis time period of each platform also changes correspondingly, the current data is similar to the initial moment and the cut-off moment of the hysteresis time period under normal conditions, the current data change in the hysteresis time period of each platform changes according to the weight change of the coal blocks, the current data change process is a trend of increasing and then decreasing, and the magnitude of the increasing change degree and the magnitude of the decreasing change degree of the current data are the same. In order to accurately acquire the fluctuation degree of each current data, the change degree of each current data in the current data sequence is analyzed.
Preferably, the method for obtaining the variation degree is as follows: acquiring a moment corresponding to the target current data as a target moment, and acquiring a moment corresponding to the current data at a preset position in the target current sequence as a reference moment; taking the difference value between the target time and the reference time as a target time difference value; taking the difference value of the target current data and the current data at a preset position in the target current sequence as a target current difference value; and changing the target current data by taking the ratio of the target current difference value to the target time difference value as the change degree between the target current data in the target current sequence and the current data at the preset position, and obtaining the change degree between each current data in the target current sequence and the current data at the preset position.
Taking (1) obtaining the nth current data in the current data sequence of the nth platform in the first fluctuation value as an example, taking the current data sequence of the nth platform as a target current sequence, and taking the nth current data in the current data sequence of the nth platform as target current data, wherein the current data in the current data sequence of the nth platform is ordered according to time sequence, so the nth current data is the current data corresponding to the nth moment, and the nth moment is the target moment. In order to accurately acquire the fluctuation degree of each current data in the current data sequence of the a-th platform, the embodiment of the invention sets the current data at the preset position in the target current sequence to be the first current data and the last current data in the target current sequence respectively. The current data at the preset position in the target current sequence can be set by the practitioner according to the actual situation, and the current data is not limited herein. Therefore, the time corresponding to the first current data in the current data sequence of the a-th platform is obtained as an initial target time, and the time corresponding to the last current data is obtained as a cut-off target time; obtaining a result of subtracting the initial target time from the t-th time as a first target time difference, obtaining a result of subtracting the first current data from the t-th current data as a first target current difference, and obtaining a ratio of the first target current difference to the first target time difference, namely the degree of change between the t-th current data and the first current data in the current data sequence of the a-th platform; and obtaining a result of subtracting the t-th time from the cut-off target time as a second target time difference value, obtaining a result of subtracting the t-th current data from the last current data as a second target current difference value, and obtaining a ratio of the second target current difference value to the second target time difference value, namely the degree of change between the t-th current data and the last current data in the current data sequence of the a-th platform. Wherein the degree of change is the slope. According to the method for acquiring the change degree between the t-th current data in the current data sequence of the a-th platform and the current data at the preset position, acquiring the change degree between each current data in the current data sequence of each platform and the current data at the preset position.
The difference between the current data of the first platform and the current data of the second platform is the difference between the current data of the first platform and the current data of the last platform. When the t-th current data in the current data sequence of the a-th platform is not abnormal, the two change degrees of the t-th current data in the current data sequence of the a-th platform are opposite to each other, so that the possibility of occurrence of the abnormality of the t-th current data can be reflected according to the difference between the two corresponding change degrees of the t-th current data. Therefore, the second fluctuation value of the t-th current data is acquired according to the two corresponding change degrees of the t-th current data.
Preferably, the method for obtaining the second fluctuation value is as follows: taking the change degree between each current data and the first current data in the current data sequence as a first change degree; taking the change degree between each current data and the last current data in the current data sequence as a second change degree; and taking the absolute value of the difference between the absolute value of the first variation degree and the absolute value of the second variation degree as a second fluctuation value.
As an example, taking (1) obtaining the t-th current data in the current data sequence of the a-th platform in the first fluctuation value as an example, obtaining the second fluctuation value Δh (I a,t ) The formula of (2) is:
；
in the formula, Δh (I a,t ) A second fluctuation value of the t-th current data in the current data sequence of the a-th platform; f (f) a , (1-t) For the t current number in the current data sequence of the a-th platformThe degree of change between the data and the first current data is a first degree of change; f (f) a , (t-n) The change degree between the t-th current data and the last current data in the current data sequence of the a-th platform is the second change degree; i is an absolute function.
Note that, |f a , (1-t) I and/f a , (t-n) The more similar the I, the more normal the t-th current data in the current data sequence of the a-th platform, Δh (I a,t ) The more towards 0; i f a , (1-t) I and/f a , (t-n) The greater the difference between I, the greater the likelihood of abnormality of the t-th current data in the current data sequence of the a-th platform, Δh (I a,t ) The larger. Wherein the t-th current data may be the first current data and the last current data in the current data sequence of the a-th platform, and Δh (I a,t ) The method of (2) is unchanged.
According to the method for acquiring the second fluctuation value of the t-th current data in the current data sequence of the a-th platform, the second fluctuation value of each current data in the current data sequence of each platform is acquired.
(3) The degree of fluctuation is obtained.
In order to accurately acquire the fluctuation degree of each current data, the fluctuation degree of each current data is acquired according to the first fluctuation value and the second fluctuation value of each current data.
Preferably, the method for obtaining the fluctuation degree is as follows: taking the product of the first fluctuation value and the second fluctuation value as a first result; and taking the result of the normalization processing of the first result as the fluctuation degree.
As an example, taking (1) obtaining the t-th current data in the current data sequence of the a-th platform in the first fluctuation value as an example, obtaining the fluctuation degree k of the t-th current data in the current data sequence of the a-th platform according to the first fluctuation value and the second fluctuation value of the t-th current data in the current data sequence of the a-th platform a,t The formula of (2) is:
；
wherein k is a,t The fluctuation degree of the t-th current data in the current data sequence of the a-th platform; l (L) a,t A first fluctuation value of the t-th current data in the current data sequence of the a-th platform; Δh (I) a,t ) A second fluctuation value of the t-th current data in the current data sequence of the a-th platform; tanh is a hyperbolic tangent function.
L is the same as a,t The larger the fluctuation of the t-th current data in the current data sequence of the a-th platform is, the larger the k is a,t The larger; Δh (I) a,t ) The greater the degree of variation of the t-th current data in the current data sequence of the a-th platform, the greater the fluctuation of the t-th current data in the current data sequence of the a-th platform, k a,t The larger; thus, k a,t The larger the current data sequence of the a-th platform, the more likely the t-th current data is abnormal. The embodiment of the invention uses the tanh function to obtain the first result L a,t ×Δh(I a,t ) Normalization processing is carried out, L a,t And Δh (I) a,t ) Are all non-negative numbers, and therefore, k a,t The value of (2) is in the range of 0 to 1. In another embodiment of the present invention, the normalization processing may be performed on the first result by using normalization methods such as sigmoid function, function transformation, maximum and minimum normalization, and the like, which is not limited herein.
According to the method for acquiring the fluctuation degree of the t-th current data in the current data sequence of the a-th platform, the fluctuation degree of each current data in the current data sequence of each platform is acquired.
Step S3: sequencing the fluctuation degree in each platform to obtain a fluctuation degree sequence of each platform; unifying the length of each fluctuation degree sequence to obtain a regular fluctuation degree sequence of each platform; forming a fluctuation tuple sequence by the fluctuation degrees with the same arrangement positions in the regular fluctuation degree sequence; and acquiring a transmission value of the corresponding fluctuation tuple sequence according to the magnitude of each fluctuation degree in each fluctuation tuple sequence.
Specifically, the fluctuation degree corresponding to each current data in the current data sequence in each platform is arranged according to the position arrangement sequence of the corresponding current data in the current data sequence, and the fluctuation degree sequence of each platform is obtained. As an example, taking the current data sequence of the a-th platform in the step S2 as an example, according to the arrangement position of the current data positions in the current data sequence of the a-th platform, the fluctuation degree of each current data in the current data sequence of the a-th platform is sequentially arranged, for example, the fluctuation degree of the first current data in the current data sequence of the a-th platform is taken as the first element in the fluctuation degree sequence of the a-th platform, and the arranged fluctuation degree sequence is taken as the fluctuation degree sequence of the a-th platform. And acquiring the fluctuation degree sequence of each platform according to the method for acquiring the fluctuation degree sequence of the a-th platform.
Because the total quantity of the current data in the current data sequence of each platform is different, the quantity of the fluctuation degree in the fluctuation degree sequence of each platform is also different, and in order to solve the problem of information mismatch between each platform, the embodiment of the invention unifies the length of the fluctuation degree sequence of each platform and keeps the fluctuation degree sequence of each platform consistent with the length of the fluctuation degree sequence of the coal mining machine platform. Because the coal cutter platform is the first platform for coal block extraction, the coal mining amount of the coal cutter influences current data in each platform, and in order to better find abnormal current data, unified corresponding current data in each platform is analyzed, and the length of a fluctuation degree sequence of the coal cutter platform is the most suitable. Therefore, the fluctuation degree sequence of each platform is adjusted according to the length of the fluctuation degree sequence of the coal mining machine platform, and the regular fluctuation degree sequence of each platform is obtained.
Preferably, the method for obtaining the regular fluctuation degree sequence is as follows: and keeping the fluctuation degree sequence of each platform consistent with the quantity of the fluctuation degrees in the fluctuation degree sequence of the coal cutter platform through a dynamic time warping (Dynamic Time Warping, DTW) algorithm, and obtaining a regular fluctuation degree sequence with the same length of each platform. The DTW algorithm is a dynamic regular time algorithm, which is a known technique and will not be described herein.
As an example, if there are 10 fluctuation degrees in the fluctuation degree sequence of the shearer tables, i.e., 10 elements, the fluctuation degree sequences of the scraper conveyor tables, the crusher tables, and the belt conveyor tables are respectively aligned in combination with the fluctuation degree sequence of the shearer tables by a dynamic time warping (Dynamic Time Warping, DTW) algorithm, the fluctuation degree sequence of each table is adjusted to a regular fluctuation degree sequence having the same number as the fluctuation degree sequence of the shearer tables, and the fluctuation degree sequence of the shearer tables is also divided into regular fluctuation degree sequences for the purpose of subsequent convenience of unified analysis.
The fluctuation degree of the same position in the regular fluctuation degree sequence of each platform is the fluctuation degree corresponding to each platform uniformly, namely the fluctuation degree of the same position in each platform can be mapped to the fluctuation degree of the same coal block in the same time period corresponding to different hysteresis time periods. The fluctuation degree corresponding to each platform is uniformly analyzed, so that current data of fluctuation abnormality can be more accurately reflected. When there are 10 levels of fluctuation in each of the regular fluctuation level sequences, 10 fluctuation tuple sequences can be constituted. Wherein there are 5 levels of fluctuation in each sequence of fluctuation tuples and one level of fluctuation corresponds to the level of fluctuation in one platform, the levels of fluctuation in the sequence of fluctuation tuples may be randomly arranged, without limitation. Analyzing each fluctuation tuple sequence, obtaining a transmission value of each fluctuation tuple sequence, processing current data corresponding to the fluctuation tuple sequence according to the transmission value, and determining the current data required to be transmitted to the fully-mechanized co-operation system, so that the abnormality in the platform can be found timely and accurately.
Preferably, the method for acquiring the transmission value is as follows: acquiring the average value of the fluctuation degree in each fluctuation tuple sequence as the tuple average value of the corresponding fluctuation tuple sequence; obtaining a fluctuation abnormal value of the corresponding fluctuation tuple sequence according to the difference between each fluctuation degree and other fluctuation degrees in each fluctuation tuple sequence; taking the product of the tuple mean value and the fluctuation outlier as a second result; and taking the normalized result of the second result as a transmission value. The method for acquiring the fluctuation abnormal value comprises the following steps: optionally selecting one fluctuation tuple sequence as a target fluctuation tuple sequence, and selecting any fluctuation degree in the target fluctuation tuple sequence as a target fluctuation degree; calculating the mean value of other fluctuation degrees except the target fluctuation degree in the target fluctuation tuple sequence as a second reference mean value; acquiring the absolute value of the difference between the target fluctuation degree and the second reference mean value as the overall difference value of the target fluctuation degree; calculating an addition result of the preset constant and the overall difference value as a third result of the target fluctuation degree; obtaining a third result of each fluctuation degree in the target fluctuation tuple sequence; and obtaining the multiplied result of all third results in the target fluctuation tuple sequence as a fluctuation outlier of the target fluctuation tuple sequence.
Taking the mth fluctuation tuple sequence as a target fluctuation tuple sequence as an example, the fluctuation degree in the mth fluctuation tuple sequence is a sequence formed by the mth fluctuation degree in the regular fluctuation degree sequence of each platform, and the mth fluctuation degree in the regular fluctuation degree sequence of each platform is arranged according to the working sequence of each platform to obtain the mth fluctuation tuple sequence. The arrangement of the degree of fluctuation in the mth fluctuation tuple sequence can be randomly set by the practitioner, and is not limited herein. Because there are 5 platforms in the present embodiment, there are 5 fluctuation degrees in the mth fluctuation tuple sequence. And obtaining a mean value of fluctuation degrees in the m-th fluctuation tuple sequence, namely a tuple mean value. And selecting the r-th fluctuation degree in the m-th fluctuation tuple sequence as a target fluctuation degree, acquiring a second reference mean value which is the mean value of other fluctuation degrees except the r-th fluctuation degree in the m-th fluctuation tuple sequence, and acquiring an absolute value of a difference value between the r-th fluctuation degree and the second reference mean value which is the integral difference value of the r-th fluctuation degree. The embodiment of the present invention sets the preset constant to 1, The operator may set the setting according to the actual situation, and the setting is not limited here. And obtaining a third result which is an addition result of the preset constant and the integral difference value, and obtaining a third result of each fluctuation degree in the mth fluctuation tuple sequence according to a method for obtaining the third result of the mth fluctuation degree. And obtaining the result of multiplying all third results in the mth fluctuation tuple sequence, namely the fluctuation outlier of the mth fluctuation tuple sequence. Thus, the fluctuation outlier Y of the mth fluctuation tuple sequence is obtained m The formula of (2) is:
；
wherein Y is m A fluctuation outlier for the mth fluctuation tuple sequence; k (k) m,r The mth degree of fluctuation in the mth fluctuation tuple sequence;a second reference mean value for the r-th degree of fluctuation in the m-th fluctuation tuple sequence; i is an absolute function.
Note that, the overall difference valueThe more toward 0, the more normal the degree of fluctuation of the nth in the mth fluctuation tuple sequence, Y m The smaller; thus Y m The smaller the current data corresponding to the degree of fluctuation in the mth fluctuation tuple sequence is, the more normal the current data is. The embodiment of the invention sets the preset constant to 1, and avoids Y when the integral difference value corresponding to certain current data is 0 m If the value is directly 0, larger errors are caused, and the abnormal fluctuation degree cannot be identified.
The average value and the abnormal value of the m-th fluctuation tuple sequence are analyzed together to determine the transmission value of the m-th fluctuation tuple sequence, when the possibility of abnormality in the m-th fluctuation tuple sequence is higher, the current data corresponding to the fluctuation degree in the m-th fluctuation tuple sequence is required to be transmitted to a comprehensive mining cooperative operation system, the dispatching maintenance of the platforms is determined, and the current data in each platform is reducedThe possibility of abnormality ensures that coal extraction is performed efficiently. Obtaining the transmission value G of the mth fluctuation tuple sequence according to the tuple average value and the fluctuation abnormal value of the mth fluctuation tuple sequence m The formula of (2) is:
；
wherein G is m A transmission value for the mth fluctuation tuple sequence; k (k) m,r The mth degree of fluctuation in the mth fluctuation tuple sequence; y is Y m A fluctuation outlier for the mth fluctuation tuple sequence; sigmoid is a normalization function.
It should be noted that the tuple averageThe larger the current coal block passes through each platform, the larger the influence of the current coal block on the current data is, namely the larger the fluctuation of the load of each platform caused by the weight of the coal block is, or the possibility of abnormality of each platform is, the larger the corresponding current data needs to be transmitted to the fully-mechanized coal mining collaborative operation system, the larger the requirement for dispatching the platform is, and G m The larger; y is Y m The larger the m-th fluctuation tuple sequence, the more abnormal the partial fluctuation degree in the m-th fluctuation tuple sequence is, or the greater the possibility that each platform has abnormality, the greater the corresponding current data needs to be transmitted to the fully-mechanized co-operation system, and the greater the requirement for dispatching and overhauling the platforms is, G m The larger; thus G m The greater the likelihood of anomalies in the current data corresponding to the degree of fluctuation in the mth fluctuation tuple sequence, the greater the need for transmission to the fully-mechanized co-operating system. The embodiment of the invention uses a sigmoid function to carry out second result +.>Normalization is performed, therefore G m The value of (2) is in the range of 0 to 1. In another embodiment of the invention the second result may be normalized by means of a functional transformation, maximum and minimum normalization, etc.)>The normalization process is performed, and is not limited thereto.
According to the method for acquiring the transmission value of the mth fluctuation tuple sequence, the transmission value of each fluctuation tuple sequence is acquired.
Step S4: and determining current data to be transmitted to the fully-mechanized co-operation system in each platform according to the transmission value.
Specifically, the transmission value indicates the overall fluctuation condition of the current data corresponding to the fluctuation degree, and because the weight of the coal block in each platform is changed, the current data in each platform has fluctuation to a certain degree, therefore, the embodiment of the invention presets a transmission value threshold, transmits the current data corresponding to the fluctuation degree in the fluctuation tuple sequence corresponding to the transmission value greater than or equal to the preset transmission value threshold to the comprehensive mining cooperative operation system, and schedules or trims the platforms through the current data transmitted to the comprehensive mining cooperative operation system. Specifically, the method for determining the current data to be transmitted to the fully-mechanized co-operation system in each platform according to the transmission value comprises the following steps: when the transmission value is greater than or equal to a preset transmission value threshold value, keeping the current data sequences consistent with the current data in the current data sequences of the coal cutter platform through a dynamic time warping (Dynamic Time Warping, DTW) algorithm, and obtaining a warping current data sequence with the same length as each platform; the current data with the same arrangement position in each regular current data sequence is formed into a current tuple sequence; the arrangement sequence of the current data of each platform in the current tuple sequence is the same as the arrangement sequence of the fluctuation degree of each platform in the corresponding fluctuation tuple sequence; transmitting a current tuple sequence corresponding to the fluctuation tuple sequence corresponding to the transmission value to a fully-mechanized mining cooperative operation platform; when the transmission value is smaller than a preset transmission value threshold, the current data of each platform in the current tuple sequence corresponding to the fluctuation tuple sequence corresponding to the transmission value is not transmitted and is stored in the respective platform.
As an example, taking the mth fluctuation tuple sequence in step S3 as an example, the transmission value of the mth fluctuation tuple sequence is obtained, and the preset transmission value threshold is set to 0.5 according to the embodiment of the present invention, and the embodiment can be set according to the actual situation, which is not limited herein. When the transmission value of the mth fluctuation tuple sequence is greater than or equal to a preset transmission value threshold, the fluctuation condition of the fluctuation degree in the mth fluctuation tuple sequence is beyond the normal fluctuation range, and the current data corresponding to the fluctuation degree in the mth fluctuation tuple sequence is required to be transmitted to the fully-mechanized mining collaborative operation system. In order to obtain current data corresponding to each fluctuation degree in each fluctuation tuple sequence, the embodiment of the invention keeps the current data sequence of each platform consistent with the quantity of current data in the current data sequence of the coal mining machine platform through a dynamic time warping (Dynamic Time Warping, DTW) algorithm, and obtains a regular current data sequence with the same length of each platform. The current data sequence of the coal mining machine platform is also divided into regular current data sequences. The regular fluctuation degree sequence of each platform is the same as the number of elements in the regular current data sequence, and meanwhile, the regular fluctuation degree sequence of each platform corresponds to the elements in the same arrangement position in the regular current data sequence one by one. And (3) arranging the current data with the same arrangement position in each regular current data sequence according to the working sequence of each platform, and acquiring a corresponding current tuple sequence in order to keep the same with the platform corresponding to each fluctuation degree in the fluctuation tuple sequence in the step (S3). Thus, each fluctuating tuple sequence has a corresponding current tuple sequence. And transmitting the current tuple sequence corresponding to the mth fluctuation tuple sequence to a fully-mechanized coal mining cooperative operation system, analyzing the current tuple sequence by the fully-mechanized coal mining cooperative operation system, and determining to adjust the coal cutter platform to reduce the coal block yield or increase the coal block yield. Because the coal cutter platform determines the weight of the coal blocks in each platform, the mining amount of the coal blocks in the coal cutter platform can be directly adjusted, so that the current data in each platform is adjusted, and the occurrence of abnormal current data is reduced; and when the mining amount of the coal blocks is irrelevant, stopping the whole flow of coal block stoping, and overhauling each platform. When the transmission value of the mth fluctuation tuple sequence is smaller than a preset transmission value threshold, the fluctuation degree in the mth fluctuation tuple sequence is in a normal fluctuation range, current data in the current tuple sequence corresponding to the mth fluctuation tuple sequence is not transmitted, and the current data are stored in respective platforms.
The present invention has been completed.
In summary, the embodiment of the invention sequentially acquires the current data sequences corresponding to the coal mining machine platform, the scraper conveyor platform, the reversed loader platform, the crusher platform and the belt conveyor platform; acquiring a first fluctuation value according to the difference between each current data in the current data sequence and other current data; acquiring a second fluctuation value according to the change degree between each current data and the current data at the preset position; according to the first fluctuation value and the second fluctuation value, obtaining the fluctuation degree, further obtaining a regular fluctuation degree sequence, constructing a fluctuation tuple sequence, and obtaining a transmission value; and determining current data transmitted to the fully-mechanized co-operation system according to the transmission value. The invention eliminates the problems of strong isolation and mismatching of current data caused by a lag time period, thereby accurately finding out the abnormality in the platform and ensuring the recovery efficiency of coal blocks.
It should be noted that: the sequence of the embodiments of the present invention is only for description, and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments.
Claims (8)
1. The coal mining data transmission method for the multi-platform collaborative operation is characterized by comprising the following steps of:
acquiring current data sequences corresponding to a coal cutter platform, a scraper conveyor platform, a reversed loader platform, a crusher platform and a belt conveyor platform in sequence;
according to the difference between each current data in each current data sequence and other current data, a first fluctuation value of the corresponding current data is obtained; the method comprises the steps of respectively obtaining the change degree between each piece of current data and the current data at a preset position in the current data sequence; acquiring a second fluctuation value of the corresponding current data according to the change degree corresponding to each current data; acquiring the fluctuation degree of corresponding current data according to the first fluctuation value and the second fluctuation value of each current data;
sequencing the fluctuation degrees in each platform to obtain a fluctuation degree sequence of each platform; unifying the length of each fluctuation degree sequence to obtain a regular fluctuation degree sequence of each platform; the fluctuation degrees with the same arrangement positions in the regular fluctuation degree sequence are formed into a fluctuation tuple sequence; acquiring a transmission value of a corresponding fluctuation tuple sequence according to the fluctuation degree of each fluctuation tuple sequence;
Determining current data to be transmitted to a fully-mechanized co-operation system in each platform according to the transmission values;
the second fluctuation value obtaining method comprises the following steps:
taking the change degree between each current data and the first current data in the current data sequence as a first change degree;
taking the change degree between each current data and the last current data in the current data sequence as a second change degree;
taking the absolute value of the difference between the absolute value of the first variation degree and the absolute value of the second variation degree as a second fluctuation value;
the method for determining the current data to be transmitted to the fully-mechanized co-operation system in each platform according to the transmission value comprises the following steps:
when the transmission value is greater than or equal to a preset transmission value threshold value, keeping the current data sequences consistent with the current data in the current data sequences of the coal cutter platform through a DTW algorithm, and obtaining regular current data sequences with the same length of each platform; the current data with the same arrangement position in each regular current data sequence is formed into a current tuple sequence; the arrangement sequence of the current data of each platform in the current tuple sequence is the same as the arrangement sequence of the fluctuation degree of each platform in the corresponding fluctuation tuple sequence; transmitting a current tuple sequence corresponding to the fluctuation tuple sequence corresponding to the transmission value to a fully-mechanized mining cooperative operation platform;
When the transmission value is smaller than a preset transmission value threshold, the current data of each platform in the current tuple sequence corresponding to the fluctuation tuple sequence corresponding to the transmission value is not transmitted and is stored in the respective platform.
2. The method for transmitting coal mining data for multi-platform collaborative operation according to claim 1, wherein the method for acquiring the first fluctuation value comprises:
optionally selecting one current data sequence as a target current sequence, and selecting any one current data in the target current sequence as target current data;
calculating the average value of other current data in the target current sequence except for the target current data as a first reference average value;
and acquiring the absolute value of the difference between the target current data and the first reference mean value as a first fluctuation value of the target current data, and changing the target current data to obtain the first fluctuation value of each current data.
3. The method for transmitting coal mining data for multi-platform collaborative operation according to claim 2, wherein the method for acquiring the degree of variation between each current data and the current data at a predetermined position in the current data sequence comprises:
Acquiring a moment corresponding to the target current data as a target moment, and acquiring a moment corresponding to the current data at a preset position in the target current sequence as a reference moment;
taking the difference value between the target time and the reference time as a target time difference value;
taking the difference value of the target current data and the current data at a preset position in the target current sequence as a target current difference value;
and changing the target current data by taking the ratio of the target current difference value to the target time difference value as the change degree between the target current data in the target current sequence and the current data at the preset position, and obtaining the change degree between each current data in the target current sequence and the current data at the preset position.
4. The method for transmitting coal mining data for multi-platform collaborative operation according to claim 1, wherein the method for acquiring fluctuation degree comprises:
taking the product of the first fluctuation value and the second fluctuation value as a first result;
and taking the result of the normalization processing of the first result as the fluctuation degree.
5. The method for transmitting coal mining data for multi-platform collaborative operations according to claim 1, wherein the method for sequencing the fluctuation degree in each platform to obtain a fluctuation degree sequence of each platform comprises:
And arranging the fluctuation degree corresponding to each current data in the current data sequence of each platform according to the position arrangement sequence of the corresponding current data in the current data sequence to obtain the fluctuation degree sequence of each platform.
6. The method for transmitting coal mining data for multi-platform collaborative operation according to claim 1, wherein the method for acquiring the regular fluctuation degree sequence comprises the steps of:
and keeping the fluctuation degree sequence of each platform consistent with the quantity of the fluctuation degrees in the fluctuation degree sequence of the coal cutter platform through a DTW algorithm, and obtaining a regular fluctuation degree sequence with the same length of each platform.
7. The method for transmitting coal mining data for multi-platform collaborative operation according to claim 1, wherein the method for acquiring transmission values comprises:
acquiring the average value of the fluctuation degree in each fluctuation tuple sequence as the tuple average value of the corresponding fluctuation tuple sequence;
obtaining a fluctuation abnormal value of the corresponding fluctuation tuple sequence according to the difference between each fluctuation degree and other fluctuation degrees in each fluctuation tuple sequence;
taking the product of the tuple mean and the fluctuation outlier as a second result;
And taking the normalized result of the second result as a transmission value.
8. The method for transmitting coal mining data for multi-platform collaborative operation according to claim 7, wherein the method for acquiring the fluctuation outlier comprises:
optionally selecting one fluctuation tuple sequence as a target fluctuation tuple sequence, and selecting any fluctuation degree in the target fluctuation tuple sequence as a target fluctuation degree;
calculating the mean value of other fluctuation degrees except the target fluctuation degree in the target fluctuation tuple sequence as a second reference mean value;
acquiring the absolute value of the difference between the target fluctuation degree and the second reference mean value as an overall difference value of the target fluctuation degree;
calculating an addition result of a preset constant and the integral difference value as a third result of the target fluctuation degree;
obtaining a third result of each degree of fluctuation in the target fluctuation tuple sequence;
and obtaining the multiplied result of all the third results in the target fluctuation tuple sequence as a fluctuation abnormal value of the target fluctuation tuple sequence.
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