Coal mining face straightness measurement and straightening decision-making method

Abstract

The present invention relates to a method for measuring the straightness of a coal mining working face and making a straightening decision, and belongs to the field of intelligent coal mine technology. The method comprises: determining the current normal pushing distance reference matrix and the cumulative pushing distance reference matrix of the target scraper according to the position data of the coal mining machine, the initial scraper stroke data and the support column pressure data, and after combining to obtain the adjustment pushing distance reference matrix, inputting the adjustment pushing distance reference matrix into a pre-trained scraper straightness intelligent decision model, and the scraper straightness intelligent decision model outputs whether the target scraper currently needs to perform an adjustment pushing operation and the adjustment pushing distance when the adjustment pushing operation is required. Based on this, a method for intelligently deciding whether the target scraper currently needs to perform an adjustment pushing operation and the adjustment pushing distance when the adjustment pushing operation is required is provided, which can not only save labor costs, but also improve the scraper adjustment efficiency, and has a high degree of intelligence.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent coal mines, and in particular to a method for measuring the straightness of a coal mining working face and making a straightening decision. Background Art

[0002] Currently, coal mining faces have developed automation technologies centered around electro-hydraulic control of scrapers and shearer positioning and guidance technologies based on inertial navigation. These technologies, combined with multi-sensor data acquisition systems for coal mining faces, form the core technology cluster for intelligent coal mining faces. Using computer information technology to deeply mine and differentiate massive amounts of coal mine production data enables researchers to identify patterns within the vast amount of data and achieve the goal of scientific data analysis. In actual production, after the scraper performs its initial follow-up action (i.e., the initial push and slide), it is necessary to adjust the straightness between the multiple scrapers until production requirements are met. Therefore, controlling the push and slide distance is crucial to ensuring the straightness between the multiple scrapers on the working face.

[0003] At present, the initial pushing of the scrapers on the coal mining face is mostly performed through an automated machine-following program. The pushing operation is adjusted by manual on-site observation of the linear arrangement conditions between the scrapers, and the scrapers are adjusted again. The adjustment of the pushing distance is manually determined according to the on-site conditions of the coal mining face. This not only requires high labor costs, but also leads to low adjustment efficiency and intelligence. Summary of the Invention

[0004] To solve the above technical problems, the present invention provides a method for measuring the straightness of a coal mining face and making a straightening decision. The technical solution of the present invention is as follows:

[0005] A method for measuring the straightness of a coal mining face and making a straightening decision, comprising:

[0006] S1, obtaining the shearer position data, initial scraper stroke data and support column pressure data during the shearer cutting process at the coal face;

[0007] S2, determining the scraper normal pushing distance matrix and the scraper cumulative pushing distance matrix according to the shearer position data, the initial scraper stroke data and the support column pressure data;

[0008] S3, determining a current normal pushing distance reference matrix of a target scraper according to the normal pushing distance matrix of the scraper, wherein the target scraper is any one of the multiple scrapers in the coal mining face;

[0009] S4, determining the current cumulative push-slide distance reference matrix of the target scraper according to the scraper cumulative push-slide distance matrix;

[0010] S5, combining the normal push-and-slide distance reference matrix and the cumulative push-and-slide distance reference matrix to obtain an adjusted push-and-slide distance reference matrix;

[0011] S6, inputting the adjustment push-slide distance reference matrix into a pre-trained scraper straightness intelligent decision model, and the scraper straightness intelligent decision model outputs whether the target scraper currently needs to be adjusted and the adjustment push-slide distance when the adjustment push-slide operation is required;

[0012] S7, obtaining the adjustment pushing distances of all scrapers on the coal mining face, and determining the number of scraper areas that need to be adjusted and pushed according to the adjustment pushing distances of all scrapers, and measuring the scraper straightness of the coal mining face according to the number of scraper areas that need to be adjusted and pushed.

[0013] Optionally, the S2 includes:

[0014] S21, dividing the initial scraper stroke data into d×m time periods according to the shearer position data, where d is the number of shearer cutting knives and m is the number of scrapers on the coal mining face;

[0015] S22, filtering the initial scraper stroke data of each time period to obtain filtered scraper stroke data of each time period;

[0016] S23, constructing an initial scraper normal push-slide distance matrix and an initial scraper cumulative push-slide distance matrix;

[0017] S24, calculating the values ​​of each element in the initial scraper normal push-slide distance matrix and the initial scraper cumulative push-slide distance matrix based on the support column pressure data and the scraper stroke data after filtering in each time period, and obtaining the scraper normal push-slide distance matrix and the scraper cumulative push-slide distance matrix.

[0018] Optionally, the S22 includes:

[0019] S221, calculate the number of times n that the initial scraper stroke data of each time period changes by more than 10 mm per unit time t, and the amount of change X of the scraper stroke data per unit time t. t ;

[0020] S222, by formula Calculate the data fluctuation frequency V for each time period n and the rate of change V x ;

[0021] S223, filter out the data fluctuation frequency V in each time period n and / or rate of change V x The initial scraper stroke data exceeding the corresponding preset threshold is used to obtain the scraper stroke data after filtering in each time period.

[0022] Optionally, when calculating the values ​​of the elements corresponding to the i-th blade and the j-th scraper in the initial scraper normal push-slide distance matrix and the initial scraper cumulative push-slide distance matrix, the step S24 includes:

[0023] S241, define the scraper push distance X, and calculate the scraper stroke data change X per unit time t. t The accumulated scraper push-slide distance X is calculated. When the push-slide operation occurs again based on the support column pressure data and the scraper stroke data filtered after the corresponding time period of the i-th blade and the j-th scraper, the value of X at this time is determined to be the normal push-slide distance of the i-th blade and the j-th scraper, which is recorded as X. ij-zc ;

[0024] S242, clear X to zero and recalculate the next adjustment push distance X ij-tz2 , and so on, we can finally get the cumulative sliding distance X of the scraper No. j of the i-th knife in the corresponding time period of the scraper No. j of the i-th knife. ij , where X ij Includes normal push distance X ij-zc and multiple adjustments to the push distance X ij-tzM , M∈(2, N), N is the number of times the scraper adjusts the push-slide.

[0025] Optionally, after S242, the step further includes:

[0026] S243, correct normal push distance X ij-zc and adjust the push distance X ij-tzM .

[0027] Optionally, when the scraper No. j is the target scraper, when determining its normal pushing distance reference matrix according to the scraper normal pushing distance matrix, S3 includes:

[0028] In the scraper normal pushing distance matrix, the normal pushing distances of the scrapers on the left and right of the j-th scraper and the normal pushing distance of the j-th scraper are taken, and the average normal pushing distances of all scrapers when the shearer cuts the i-th coal are calculated. The normal pushing distances of the scrapers on the left and right of the j-th scraper, the normal pushing distance of the j-th scraper and the average normal pushing distances of all scrapers on the i-th scraper are used to form a 1×4 normal pushing distance reference matrix, which can be expressed as:

[0029]

[0030] Among them, a is the normal pushing distance, m is the number of scrapers on the coal mining face, a i,j It is the normal pushing distance of scraper No. j when the shearer cuts the i-th piece of coal.

[0031] Optionally, when the scraper No. j is the target scraper, the step S4, when determining its current cumulative push-slide distance reference matrix according to the scraper cumulative push-slide distance matrix, includes:

[0032] In the scraper cumulative push-slide distance matrix, the cumulative push-slide distances of the scraper on the left and right of the scraper No. j over the past two strokes and the cumulative push-slide distances of the scraper on the jth scraper over the past two strokes are taken, and the average value of the cumulative push-slide distances of all scrapers over the past two strokes is calculated. The 2×4 cumulative push-slide distance reference matrix is ​​composed of the cumulative push-slide distances of the scraper on the left and right of the scraper No. j over the past two strokes, the cumulative push-slide distances of the scraper on the jth scraper over the past two strokes and the average value of the cumulative push-slide distances of all scrapers over the past two strokes, which can be expressed as:

[0033]

[0034] Among them, b is the cumulative pushing distance, b i-2,j It is the cumulative pushing distance of scraper No. j when the coal mining machine cuts the i-2th coal.

[0035] Optionally, the S5 includes:

[0036] The normal push-slide distance reference matrix and the cumulative push-slide distance reference matrix are spliced ​​into a 3×4 adjusted push-slide distance reference matrix, which is expressed as:

[0037]

[0038] Optionally, after S2, the step further includes:

[0039] S8, combining the scraper normal push-slip distance matrix and the scraper cumulative push-slip distance matrix to obtain the scraper straightness measurement matrix, and visualizing the scraper straightness measurement matrix.

[0040] Optionally, the scraper straightness intelligent decision model is a random forest model.

[0041] All the above optional technical solutions can be combined arbitrarily, and the present invention does not provide detailed descriptions of the structures after each combination.

[0042] By means of the above solution, the beneficial effects of the present invention are as follows:

[0043] By determining the current normal pushing distance reference matrix and the cumulative pushing distance reference matrix of the target scraper based on the coal mining machine position data, the initial scraper stroke data and the support column pressure data, and after combining to obtain the adjusted pushing distance reference matrix, the adjusted pushing distance reference matrix is ​​input into a pre-trained scraper straightness intelligent decision model. The scraper straightness intelligent decision model outputs whether the target scraper currently needs to perform an adjusted pushing operation and the adjusted pushing distance when the adjusted pushing operation is required. This provides a method for intelligently deciding whether the target scraper currently needs to perform an adjusted pushing operation and the adjusted pushing distance when the adjusted pushing operation is required. It can not only save labor costs, but also improve the scraper adjustment efficiency and has a high degree of intelligence.

[0044] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention and implement it according to the contents of the specification, the following is a detailed description of the preferred embodiments of the present invention with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 This is a flow chart of a method for measuring the straightness of a coal mining face and making straightening decisions provided by an embodiment of the present invention.

[0046] Figure 2 It is a schematic diagram of dividing the initial scraper stroke data according to the coal mining machine position data in an embodiment of the present invention.

[0047] Figure 3 Schematic diagram of the result of visualizing the scraper straightness measurement matrix in an embodiment of the present invention. DETAILED DESCRIPTION

[0048] The following embodiments of the present invention are described in further detail with reference to the accompanying drawings and examples. The following examples are used to illustrate the present invention but are not intended to limit the scope of the present invention.

[0049] The coal mining face straightness measurement and straightening decision-making method provided by the embodiment of the present invention can be implemented by any electronic device with computing function, such as PC, mobile terminal or server. Figure 1 As shown, the method for measuring the straightness of a coal mining face and making a straightening decision according to an embodiment of the present invention includes the following steps S1 to S7:

[0050] S1, obtaining the shearer position data, initial scraper stroke data and support column pressure data during the coal cutting process of the coal mining face.

[0051] Specifically, various types of sensors are installed on the coal mining face. These sensors collect data and send it to electronic devices. The electronic devices can then extract data from the data collected by the corresponding sensors based on the required data type. For example, the position data of the coal mining machine can be obtained from the data collected by the positioning sensor installed on the coal mining machine. Since the hydraulic support stroke data is consistent with the scraper stroke data, the initial scraper stroke data can be obtained from the data collected by the hydraulic support stroke sensor installed on the hydraulic support. The support column pressure data can be obtained from the data collected by the pressure sensor installed on the hydraulic support column.

[0052] Furthermore, after obtaining the coal mining machine position data, initial scraper stroke data and support column pressure data, these data can also be processed for outliers to remove obvious missing values ​​and outliers, thereby reducing the subsequent calculation amount.

[0053] S2, determining the scraper normal pushing distance matrix and the scraper cumulative pushing distance matrix according to the coal mining machine position data, the initial scraper stroke data and the support column pressure data.

[0054] In a specific embodiment, the S2 includes:

[0055] S21, dividing the initial scraper stroke data into d×m time periods according to the shearer position data, where d is the number of shearer cutters and m is the number of scrapers on the coal mining face.

[0056] Specifically, the time can be used as the horizontal axis, and the initial scraper stroke data and the coal mining machine position data can be used as the left and right vertical axes respectively. The coal mining machine position data and the initial scraper stroke data can be plotted in the same coordinate system, such as Figure 2 As shown. At the end of each shearer's bevel cut and during the process of cutting triangular coal, the hydraulic supports and scrapers on the mining face should all complete the pull-and-pull operations. The embodiment of the present invention divides the initial scraper stroke data at this node, obtaining the scraper stroke change data for any scraper in the time period T1 to T2 (T1 and T2 are the end times of two adjacent shearer bevel cuts, respectively). Finally, the initial scraper stroke data of the mining face is divided into d×m time periods based on the number of coal cutters d and the number of scrapers m on the working face.

[0057] Furthermore, since the initial scraper stroke data may experience data fluctuations, data loss, and other problems during the collection, transmission, and storage process, and these anomalies may affect the accuracy of the final calculation results, the embodiment of the present invention further performs the following step S22.

[0058] S22, filtering the initial scraper stroke data of each time period to obtain filtered scraper stroke data of each time period.

[0059] Exemplarily, when S22 is specifically implemented, it includes:

[0060] S221, calculate the number of times n that the initial scraper stroke data of each time period changes by more than 10 mm per unit time t, and the amount of change X of the scraper stroke data per unit time t. t .

[0061] Specifically, the embodiment of the present invention first defines the number of changes n, and the initial value of n is 0, and then compares the two adjacent data in the initial scraper stroke data of each time period. If the difference between the two exceeds 10 mm, the number of times n is increased by 1, until the last two data in the initial scraper stroke data of each time period are compared, and the final value of n is obtained.

[0062] It should be noted that the 10 mm here is an empirical value determined based on the actual operating conditions of the working surface. During specific implementation, this value can be adjusted as needed.

[0063] Furthermore, the scraper stroke data change X per unit time t t It is the difference between the maximum and minimum values ​​of the initial scraper stroke data within unit time t.

[0064] S222, by formula Calculate the data fluctuation frequency V for each time period n and the rate of change V x .

[0065] S223, filter out the data fluctuation frequency V in each time period n and / or rate of change V x The initial scraper stroke data exceeding the corresponding preset threshold is used to obtain the scraper stroke data after filtering in each time period.

[0066] That is to say, when filtering, the embodiment of the present invention filters out the initial scraper stroke data in each time period in which the data fluctuation frequency exceeds the preset threshold of the fluctuation frequency, the change rate exceeds the preset threshold of the change rate, the data fluctuation frequency exceeds the preset threshold of the fluctuation frequency and the change rate exceeds the preset threshold of the change rate.

[0067] S23, constructing the initial scraper normal push-slide distance matrix and the initial scraper cumulative push-slide distance matrix.

[0068] The elements in the initial scraper normal push distance matrix include the normal push distance of each scraper during each cut of coal by the shearer, and the elements in the initial scraper cumulative push distance matrix include the cumulative push distance of each scraper during each cut of coal by the shearer. The cumulative push distance is the sum of the normal push distance and the adjusted push distance. After the shearer completes a cut of coal, the number of push adjustments can be 0 (no further adjustment), 1 (one further adjustment), 2, or multiple times.

[0069] The initial scraper normal push distance matrix is ​​expressed as:

[0070]

[0071] The initial scraper cumulative push-slide distance matrix is ​​expressed as:

[0072]

[0073] when a ij ≠b ij It means that an adjustment push-slide operation occurs after a normal push-slide operation.

[0074] S24, calculating the values ​​of each element in the initial scraper normal push-slide distance matrix and the initial scraper cumulative push-slide distance matrix based on the support column pressure data and the scraper stroke data after filtering in each time period, and obtaining the scraper normal push-slide distance matrix and the scraper cumulative push-slide distance matrix.

[0075] For example, when calculating the values ​​of the elements corresponding to the i-th blade and the j-th scraper in the initial scraper normal push-slip distance matrix and the initial scraper cumulative push-slip distance matrix, the step S24 may include:

[0076] S241, define the scraper push distance X, and calculate the scraper stroke data change X per unit time t. t The accumulated scraper push-slide distance X is calculated. When the push-slide operation occurs again based on the support column pressure data and the scraper stroke data filtered after the corresponding time period of the i-th blade and the j-th scraper, the value of X at this time is determined to be the normal push-slide distance of the i-th blade and the j-th scraper, which is recorded as X. ij-zc .

[0077] Specifically, when the scraper stroke data and the support column pressure data decrease simultaneously within the same period of time, it means that the support has performed a pulling operation and the scraper has performed a pushing operation at the same time.

[0078] Generally, it's assumed that the first scraper stroke change after a shearer completes a cut is caused by normal pushing and sliding, while subsequent zero, one, or multiple stroke changes are caused by adjusting the pushing and sliding operation. Therefore, in this embodiment of the present invention, the scraper pushing and sliding distance X accumulated before the next pushing and sliding operation occurs is determined as the normal pushing and sliding distance for the jth scraper at the i-th cut.

[0079] S242, clear X to zero and recalculate the next adjustment push distance X ij-tz2 (The calculation method here is the same as that of X ij-zc The same way), and so on, we can finally get the cumulative sliding distance X of the scraper No. j of the i-th blade in the corresponding time period of the scraper No. j of the i-th blade. ij ; Among them, X ij Includes normal push distance X ij-zc and multiple adjustments to the push distance X ij-tzM , M∈(2, N), N is the number of times the scraper adjusts the push-slide.

[0080] X ij =X ij-zc +X ij-tz2 +···+X ij-tzN .

[0081] Furthermore, due to the influence of the mechanical clearance of the floating connection mechanism at the connection part of the hydraulic support push cylinder, X ij-zc or X ij-tzM There is an error, therefore, the embodiment of the present invention may further include the following steps after S242: S243, correcting the normal push-slide distance X ij-zc and adjust the push distance X ij-tzM .

[0082] Specifically, when making corrections, let X = g + e m , X is X ij-zc or X ij-tzM , g is the normal pushing distance or the value after adjusting the pushing distance; e m is the error value, which is an empirical value.

[0083] That is, X ij =g ij-zc +g ij-tz2 +···+g ij-tzN +e m × N. Then, the normal sliding distance a of the scraper No. j after correction is ij =g ij-zc , cumulative pushing distance b ij =g ij-zc +g ij-tz2 +···+g ij-tzN Through correction, the normal pushing distance and the adjusted pushing distance are made more consistent with the actual operation of the scraper.

[0084] S3, determining a current normal pushing distance reference matrix of a target scraper according to the normal pushing distance matrix of the scraper, wherein the target scraper is any one of the multiple scrapers in the coal mining working face.

[0085] In a specific embodiment, when the j-th scraper is the target scraper, when determining its normal pushing distance reference matrix based on the scraper normal pushing distance matrix, S3 takes the normal pushing distances of the scrapers to the left and right of the j-th scraper and the normal pushing distances of the j-th scraper in the scraper normal pushing distance matrix, and calculates the average normal pushing distances of all scrapers when the coal mining machine cuts the i-th cut (current cut) coal. The normal pushing distances of the scrapers to the left and right of the j-th scraper, the normal pushing distances of the j-th scraper, and the average normal pushing distances of all scrapers of the i-th cut form a 1×4 normal pushing distance reference matrix, which is expressed as:

[0086]

[0087] Among them, a is the normal pushing distance, m is the number of scrapers on the coal mining face, a i,j It is the normal pushing distance of scraper No. j when the shearer cuts the i-th piece of coal. The same applies to other parameters.

[0088] It should be noted that when the target scraper is at the end position, so that the scraper on one side does not meet the composition requirements of the above-mentioned scraper normal pushing and sliding distance matrix, for example, the target scraper is scraper No. 1, and there is no scraper on its left side, then the data on its left side is filled with the standard value, that is, the standard distance of a normal pushing and sliding operation.

[0089] S4, determining the current cumulative push-slide distance reference matrix of the target scraper according to the scraper cumulative push-slide distance matrix.

[0090] In a specific embodiment, when the j-th scraper is the target scraper, the S4 determines its current cumulative push-slide distance reference matrix based on the scraper cumulative push-slide distance matrix. The cumulative push-slide distances of the scraper on the left and right of the j-th scraper over two historical strokes and the cumulative push-slide distances of the scraper on the j-th scraper over two historical strokes are taken from the scraper cumulative push-slide distance matrix, and the average value of the cumulative push-slide distances of all scrapers over two historical strokes is calculated. The cumulative push-slide distances of the scraper on the left and right of the j-th scraper over two historical strokes, the cumulative push-slide distances of the scraper on the j-th scraper over two historical strokes, and the average value of the cumulative push-slide distances of all scrapers over two historical strokes form a 2×4 cumulative push-slide distance reference matrix, which is expressed as:

[0091]

[0092] Among them, b is the cumulative pushing distance, b i-2,j It is the cumulative pushing distance of scraper No. j when the shearer cuts the i-2th coal. The other parameters are the same; i represents the number of cutters currently cutting coal by the shearer.

[0093] It should be noted that when the target scraper is at the end position, so that the scraper on one side does not meet the composition requirements of the above-mentioned scraper normal pushing and sliding distance matrix, for example, the target scraper is scraper No. 1, and there is no scraper on its left side. At this time, it is assumed that the left side has not been adjusted for pushing and sliding in the past two cuts, and the standard value is filled in on the left side, that is, the standard distance of a normal pushing and sliding operation.

[0094] S5, combining the normal pushing and sliding distance reference matrix and the accumulated pushing and sliding distance reference matrix to obtain an adjusted pushing and sliding distance reference matrix.

[0095] In a specific embodiment, when S5 is implemented, the normal push-and-slide distance reference matrix is ​​spliced ​​after the cumulative push-and-slide distance reference matrix to form a 3×4 adjusted push-and-slide distance reference matrix, which is expressed as:

[0096]

[0097] S6, inputting the adjustment push-slide distance reference matrix into the pre-trained scraper straightness intelligent decision model, and the scraper straightness intelligent decision model outputs whether the current push-slide action of the target scraper needs to be adjusted and the adjustment push-slide distance when the adjustment push-slide operation is required.

[0098] The embodiment of the present invention does not specifically limit the specific type of the scraper straightness intelligent decision model. For example, the scraper straightness intelligent decision model is KNN, SVM, decision tree or random forest.

[0099] It's important to note that before inputting the adjusted push-slide distance reference matrix into the pre-trained scraper straightness intelligent decision-making model, the model must first be trained. Specifically, during training, a model type is selected and initialized. Then, training samples are generated. Finally, the model is trained using a training set from the training samples and tested using a test set from the training samples. Once the model passes the test, the trained scraper straightness intelligent decision-making model is obtained.

[0100] Specifically, when preparing training samples, the historical scraper normal push-slide distance matrix and the historical scraper cumulative push-slide distance training matrix of the historical coal mining machine coal cutting process are obtained, and the normal push-slide distance training matrix and the cumulative push-slide distance training matrix are obtained from them, and combined into an adjusted push-slide distance training matrix. The adjusted push-slide distance training matrix is ​​used as the input of the initialized model, and the model is trained based on this. The specific method for obtaining the historical scraper normal push-slide distance matrix and the historical scraper cumulative push-slide distance matrix is ​​the same as the method for obtaining the scraper normal push-slide distance reference matrix and the scraper cumulative push-slide distance reference matrix mentioned above. The method for obtaining the normal push-slide distance training matrix and the cumulative push-slide distance training matrix is ​​the same as the method for obtaining the normal push-slide distance reference matrix and the cumulative push-slide distance reference matrix mentioned above, and will not be repeated here.

[0101] Further, when making the labels of the training samples, first average the adjusted pushing distances of this scraper and the scrapers of the adjacent supports on the left and right to b i,j -a i,j That is

[0102]

[0103] Then, select the corresponding label according to the result. For example, when C is in the interval 1, the corresponding label is 1; when C is in the interval 2, the corresponding label is 2; when C is in the interval 3, the corresponding label is 3; when C is in the interval 4, the corresponding label is 4. The label is the adjusted pushing distance recommended by the intelligent decision-making model for the scraper straightness, and the interval can be divided according to the actual production requirements. For example: Limited by the manual adjustment in actual production and the decision-making opinion that the accuracy of the working face straightness does not need to be accurate to the mm level, so when C = 0, the label is 0; when 0 < C < 150, the label is 100; when 150 <= C < 300, the label is 200; when C >= 300, the label is 300.

[0104] Preferably, the intelligent decision-making model for the scraper straightness is a random forest model. Specifically, the test results of the test sets of different types of intelligent decision-making models for the scraper straightness are statistically analyzed, and the statistical results shown in Table 1 are obtained. From Table 1, it can be seen that the random forest model has a higher accuracy rate and more advantages compared with other types of models.

[0105] Table 1

[0106]

[0107] Further, the intelligent decision-making model for the scraper straightness outputs whether the target scraper needs to perform the operation of adjusting the pushing distance at present. If the output result of the intelligent decision-making model for the scraper straightness is 0, it means that the target scraper does not need to perform the operation of adjusting the pushing distance at present; if the output result of the intelligent decision-making model for the scraper straightness is a positive value, it means that the target scraper needs to perform the operation of adjusting the pushing distance at present.

[0108] In addition, the number of positive values output by the intelligent decision-making model for the scraper straightness is limited, and one positive value corresponds to an interval of the adjusted pushing distance. For example, when the intelligent decision-making model for the scraper straightness outputs 1, the corresponding adjusted pushing distance is 100nn; when the intelligent decision-making model for the scraper straightness outputs 2, the corresponding adjusted pushing distance is 200nn, and so on.

[0109] Furthermore, after obtaining the adjusted pushing distance when the target scraper needs to perform the operation of adjusting the pushing distance, perform the operation of adjusting the pushing distance on the target scraper according to the adjusted pushing distance. Specifically, when executing, the scraper can be automatically adjusted according to the program control, or the operation of adjusting the pushing distance can be performed manually.

[0110] S7, obtaining the adjustment pushing distances of all scrapers on the coal mining face, and determining the number of scraper areas that need to be adjusted and pushed according to the adjustment pushing distances of all scrapers, and measuring the scraper straightness of the coal mining face according to the number of scraper areas that need to be adjusted and pushed.

[0111] Among them, when obtaining the adjustment pushing distance of other scrapers on the coal mining working face, it is also achieved through the above steps S3 to S6.

[0112] Specifically, a scraper area includes at least three consecutive scrapers. When determining the number of scraper areas that need to be adjusted and pushed, areas where more than three consecutive scrapers need to be adjusted and pushed are marked, and the number of marked areas is counted to determine the number of scraper areas that need to be adjusted and pushed.

[0113] Furthermore, when measuring the scraper straightness of a coal mining face based on the number of scraper areas requiring adjustment and pushing operations, if the number of scrapers included in the number of scraper areas requiring adjustment and pushing operations accounts for a value greater than a preset threshold value, the scraper straightness of the coal mining face is determined to be poor. For example, if there are 100 scrapers in a coal mining face, and after model analysis, it is determined that scrapers 36 to 40 require adjustment and pushing operations, this area is marked. If the number of scrapers included in the area requiring adjustment and pushing operations accounts for 5% of the total number of scrapers in the coal mining face, the scraper straightness of the coal mining face is determined to be good; if the number of scrapers included in the area requiring adjustment and pushing operations accounts for more than 30% of the total number of scrapers in the coal mining face, the scraper straightness of the coal mining face is determined to be poor.

[0114] In a specific embodiment, after S2, the method further includes:

[0115] S8, combining the scraper normal push-slip distance matrix and the scraper cumulative push-slip distance matrix to obtain the scraper straightness measurement matrix, and visualizing the scraper straightness measurement matrix.

[0116] Specifically, when combining, the scraper normal push-slip distance matrix and the scraper cumulative push-slip distance matrix can be arranged in order from top to bottom. At this time, the scraper straightness measurement matrix can be expressed as:

[0117]

[0118] Furthermore, when visualizing the scraper straightness measurement matrix, the horizontal axis represents the scraper number and the vertical axis represents the scraper push distance, as shown in the figure. Figure 3 As shown, the push and slide distance of each knife is distinguished by different colors, and the adjusted push and slide distance is displayed in white. Figure 3Medium orange represents the normal push-slide distance of the first scraper cut, plotted according to the first row of the straightness metric matrix. Simultaneously, the cumulative push-slide distance of the coal mining face is plotted according to the second row of the straightness metric matrix. Overlapping areas are represented in orange, while non-overlapping areas (i.e., areas where push-slide adjustments have occurred) are represented in white. When plotting the second cut, the cumulative push-slide distance of the previous cut (i.e., the curve plotted in the second row) is plotted according to the third row of the straightness metric matrix. Simultaneously, the cumulative push-slide distance of the previous cut is plotted according to the fourth row of the straightness metric matrix. Overlapping areas are represented in green, while non-overlapping areas (i.e., areas where push-slide adjustments have occurred) are represented in white. This process is repeated to visualize the entire straightness metric matrix.

[0119] In summary, the method provided by the embodiment of the present invention relies on the electro-hydraulic control system of the hydraulic support of the existing coal mining working face, collects and analyzes the coal mining machine position data, support column pressure data, and scraper stroke data during the working face advancement process, comprehensively considers influencing factors such as mechanical clearance, studies the calculation method of the scraper advancement distance of the coal mining working face, obtains the calculation method of the adjustment pushing distance after the scraper automatically follows the machine, and evaluates the scraper straightness of the coal mining working face according to the adjusted pushing distance, thereby providing an intelligent coal mining working face straightness measurement and straightening decision-making method, which can save labor costs, improve scraper adjustment efficiency, and has a high degree of intelligence.

[0120] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for measuring the straightness of a coal mining face and making a straightening decision, characterized in that: include: S1, obtaining the shearer position data, initial scraper stroke data and support column pressure data during the shearer cutting process at the coal face; S2, determining the scraper normal pushing distance matrix and the scraper cumulative pushing distance matrix according to the shearer position data, the initial scraper stroke data and the support column pressure data; The S2 includes: S21, dividing the initial scraper stroke data into d×m time periods according to the shearer position data, where d is the number of shearer cutting knives and m is the number of scrapers on the coal mining face; S22, filtering the initial scraper stroke data of each time period to obtain filtered scraper stroke data of each time period; S23, constructing an initial scraper normal push-slide distance matrix and an initial scraper cumulative push-slide distance matrix; S24, calculating the values ​​of each element in the initial scraper normal push-slide distance matrix and the initial scraper cumulative push-slide distance matrix based on the support column pressure data and the scraper stroke data after filtering in each time period, to obtain the scraper normal push-slide distance matrix and the scraper cumulative push-slide distance matrix; S3, determining a current normal pushing distance reference matrix of a target scraper according to the normal pushing distance matrix of the scraper, wherein the target scraper is any one of the multiple scrapers in the coal mining face; When j When the scraper No. 1 is the target scraper, the S3, when determining its normal pushing distance reference matrix according to the scraper normal pushing distance matrix, includes: Take the first j The normal pushing distance of the scraper on the left and right of the scraper No. j The normal pushing distance of the scraper No. i The average value of the normal pushing distance of all scrapers when cutting coal is obtained from the j Normal pushing distance of scraper No. j Normal pushing distance of scraper No. i The average value of the normal push-slide distance of all scrapers forms a 1×4 normal push-slide distance reference matrix, which is expressed as: ; Among them, a is the normal pushing distance, m is the number of scrapers on the coal mining face, Cutting the first i Knife Coal Time j Normal pushing distance of scraper No. S4, determining the current cumulative push-slide distance reference matrix of the target scraper according to the scraper cumulative push-slide distance matrix; When j When the scraper No. is the target scraper, the S4, when determining its current cumulative push-slide distance reference matrix according to the scraper cumulative push-slide distance matrix, includes: Take the first j The cumulative pushing distance of the scraper No. 1 on each side is two scrapers in history. j The cumulative pushing distance of scraper No. in the past two cuts is calculated, and the average value of the cumulative pushing distance of all scrapers in the past two cuts is calculated. j The cumulative pushing distance of the scraper No. 1 on each side is two scrapers in history. j The cumulative pushing distance of scraper No. 2 during the past two cuts and the average cumulative pushing distance of all scrapers during the past two cuts constitute a 2×4 cumulative pushing distance reference matrix, which is expressed as: ； Among them, b is the cumulative pushing distance, Cutting the first i -2 coal hours j The cumulative pushing distance of scraper No. S5, combining the normal push-and-slide distance reference matrix and the cumulative push-and-slide distance reference matrix to obtain an adjusted push-and-slide distance reference matrix; S6, inputting the adjustment push-slide distance reference matrix into a pre-trained scraper straightness intelligent decision model, and the scraper straightness intelligent decision model outputs whether the target scraper currently needs to be adjusted and the adjustment push-slide distance when the adjustment push-slide operation is required; S7, obtaining the adjustment pushing distances of all scrapers on the coal mining face, and determining the number of scraper areas that need to be adjusted and pushed according to the adjustment pushing distances of all scrapers, and measuring the scraper straightness of the coal mining face according to the number of scraper areas that need to be adjusted and pushed.

2. The method for measuring the straightness of a coal mining face and making a straightening decision according to claim 1, characterized in that: The S22 includes: S221, calculate the initial scraper travel data unit time for each time period t Number of changes in the inner stroke exceeding 10 mm n , and unit time t Scraper stroke data change within X t ; S222, by formula Calculate the frequency of data fluctuations in each time period V n and rate of change V x ; S223, filter out the data fluctuation frequency in each time period V n and / or rate of change V x The initial scraper stroke data exceeding the corresponding preset threshold is used to obtain the scraper stroke data after filtering in each time period.

3. The method for measuring the straightness of a coal mining face and making a straightening decision according to claim 2, characterized in that: The S24 calculates the initial scraper normal push-slide distance matrix and the initial scraper cumulative push-slide distance matrix. i Knife j The value of the element corresponding to the scraper number includes: S241, define the scraper push distance X, and convert the unit time t Scraper stroke data change within X t Accumulated into the scraper push distance X, and when according to the support column pressure data and the i Knife j The scraper stroke data after filtering the corresponding time period of the scraper No. determines that when the push-slide operation occurs again, the value of X at this time is determined to be i Knife j The value of the normal pushing distance of the scraper is recorded as ; S242, clear X to zero and recalculate the next adjustment push distance X ij-tz2 , and so on, we finally get i Knife j Scraper No. i Knife j The cumulative pushing distance of scraper No. in the corresponding time period is X ij , where X ij Includes normal pushing distance and multiple adjustments to the push distance X ij-tzM , M∈(2,N), N is the number of times the scraper adjusts the push-slide.

4. The method for measuring the straightness of a coal mining face and making a straightening decision according to claim 3, characterized in that: The S242 further includes: S243, corrected normal push-slide distance X ij-zc and adjust the push distance X ij-tzM .

5. The method for measuring the straightness of a coal mining face and making a straightening decision according to claim 1, characterized in that: The S5 includes: The normal push-slide distance reference matrix and the cumulative push-slide distance reference matrix are spliced ​​into a 3×4 adjusted push-slide distance reference matrix, which is expressed as: 。 6. The method for measuring the straightness of a coal mining face and making a straightening decision according to claim 1, characterized in that: The S2 also includes: S8, combining the scraper normal push-slip distance matrix and the scraper cumulative push-slip distance matrix to obtain the scraper straightness measurement matrix, and visualizing the scraper straightness measurement matrix.

7. The method for measuring the straightness of a coal mining face and making a straightening decision according to claim 1, characterized in that: The scraper straightness intelligent decision-making model is a random forest model.

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