CN114104654A - Monitoring method for automatic coal blending - Google Patents

Monitoring method for automatic coal blending Download PDF

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CN114104654A
CN114104654A CN202111303090.8A CN202111303090A CN114104654A CN 114104654 A CN114104654 A CN 114104654A CN 202111303090 A CN202111303090 A CN 202111303090A CN 114104654 A CN114104654 A CN 114104654A
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coal blending
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张莹
陈小艺
周思阳
张弓
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Wuhan University of Technology WUT
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Abstract

The invention relates to a monitoring method for automatic coal blending, which comprises the following steps: acquiring instantaneous flow data of a plurality of coal types; determining a proportional control chart according to the instantaneous flow data; and adjusting the coal blending ratio formed by the plurality of coal types according to the proportion control chart. The invention applies the proportion control chart to the port silo coal blending system, realizes the on-line monitoring of the coal blending proportion, improves the accuracy of port coal blending and achieves the aim of accurately monitoring the coal blending process.

Description

Monitoring method for automatic coal blending
Technical Field
The invention relates to the technical field of monitoring, in particular to a monitoring method for automatic coal blending.
Background
The coal blending is to mix the coals with different coal qualities according to a certain proportion so as to meet the requirements of various customers, achieve the purposes of reducing cost, stabilizing coal quality and reducing pollution discharge, and have better economic benefit, social benefit and environmental benefit. At present, the coal blending system mainly has 3 modes of ground type, underground tunnel type and silo mixing type, and each mode has respective characteristics and application range. Silo blending coal is the most advanced coal blending mode at present. Compared with the traditional open-air storage yard, the silo storage yard has the advantages of small occupied area, high automation level, low equipment maintenance cost, high coal blending precision, small field pollution and the like, has outstanding advantages in the problems of environmental protection, rain and snow prevention, coal quality guarantee and the like due to the sealing property of the silo storage yard, and is suitable for areas with various coal types, large flow and diversified coal quality.
The coal blending is realized in a dynamic process, which is a process of mixing several different coal types into a new coal type, and the size of the coal flow is determined by the mixing proportion of each coal type. The guarantee of the accuracy of the dynamic coal blending process is the key point for obtaining high-quality mixed coal. At present, a plurality of mature port coal blending modes such as loading coal blending, unloading coal blending and the like exist at home and abroad. But the accurate control of the coal blending ratio and the automatic online quality monitoring cannot be simultaneously met all the time. How to adopt an effective high-precision control method is one of the contents which have been discussed for a long time in the coal industry, most of the methods for improving the precision start from hardware, start from a coal blending process, and have high improvement cost and complex operation. And the related research for monitoring the coal blending data is little. Therefore, how to realize accurate control of the coal blending ratio is an urgent problem to be solved.
Disclosure of Invention
In view of the above, there is a need to provide a monitoring method for automatic coal blending, so as to overcome the problems of inaccurate control and difficult monitoring of the coal blending ratio in the prior art.
The invention provides a monitoring method for automatic coal blending, which comprises the following steps:
acquiring instantaneous flow data of a plurality of coal types;
determining a proportional control chart according to the instantaneous flow data;
and adjusting the coal blending ratio formed among the plurality of coal types according to the proportion control chart.
Further, the determining a proportional control map according to the instantaneous flow data includes:
filtering according to the instantaneous flow data to determine corresponding filtering flow data;
determining a controlled parameter of the coal blending ratio under a controlled condition and an out-of-control parameter under an out-of-control condition according to the filtering flow data;
and determining the proportional control chart according to the controlled parameter and the runaway parameter.
Further, the filtering according to the instantaneous flow data to determine corresponding filtered flow data includes: and denoising and cleaning the instantaneous flow data through a Kalman filtering algorithm to obtain the corresponding filtering flow data.
Further, the determining a controlled parameter of the coal blending ratio under a controlled condition and an out-of-control parameter under an out-of-control condition according to the filtering flow data includes:
counting according to the filtering flow data, and determining upper single-side statistic and lower single-side statistic of the proportional control chart;
and determining the controlled parameter and the out-of-control parameter according to the upper single-edge statistic and the lower single-edge statistic by using a Markov chain method.
Further, the determining the upper single-side statistic and the lower single-side statistic of the ratio control graph according to the statistics performed on the filtered flow data includes:
determining coal flow proportions of different coal types according to the filtering flow data, and determining initial statistics according to the coal flow proportions;
carrying out normalized distribution transformation on the initial statistic to obtain a distribution statistic;
and determining the upper single-side statistic and the lower single-side statistic of the proportion control chart according to the distribution statistic.
Further, the determining the controlled parameter and the runaway parameter according to the upper single-sided statistic and the lower single-sided statistic by using a markov chain method includes:
determining a one-step transfer matrix of the Markov chain by using a Markov chain method;
and determining the controlled parameters according to the one-step transition matrix, wherein the controlled parameters comprise at least one of a minimum value acceptable for the average run length under the controlled state, a maximum value accepted for the average sample capacity under the controlled state, a process deviation size, proportions under the controlled state, corresponding variation coefficients of coal flow rates of different coal types and correlation coefficients.
Further, the determining the controlled parameter and the runaway parameter according to the upper single-sided statistic and the lower single-sided statistic by using a markov chain method further includes:
solving a mixed integer nonlinear programming model with equality constraints under the relevant parameters under the controlled time;
and optimizing the proportional control chart, and determining a group of decision variables which minimize the average running length under the out-of-control state.
Further, the determining the proportional control chart according to the relevant parameters and performing real-time point tracing updating includes: sampling the instantaneous flow data, calculating the related parameters of each sample, drawing the proportional control chart, and updating the real-time point tracing, wherein the first sampling adopts a small sample capacity n(1)＝nsFor the ith sampling, when the upper single-side statistic is smaller than the alarm limit, the next sampling with the small sample capacity n(i+1)＝nsOtherwise, the large sample capacity n is adopted(i+1)＝nLN (1) is the sample capacity of the first sampling, n (i +1) is the sample capacity of the (i +1) th sampling, ns is the preset small sample capacity, and nL is the preset large sample capacity.
Further, the adjusting the coal blending ratio formed among the plurality of coal types according to the proportion control map comprises:
and correlating a plurality of proportion control charts generated by different coal types, and sending out an early warning signal to adjust the coal blending ratio of different coal types when at least one proportion control chart judges that the proportion is out of control.
Further, judging that the proportion is out of control comprises the following steps: sampling statistics is carried out according to the instantaneous flow data, and corresponding real-time statistics is determined; if the real-time statistic is within the control limit of the proportional control chart, judging that the coal blending ratio is controlled and stable; if the real-time statistic is between the control limit and the warning limit of the proportional control chart, judging that the coal blending ratio is in a warning state, and enlarging the sample capacity of the sample; and if the real-time statistic exceeds the warning limit, judging that the coal blending ratio is in an out-of-control state.
Compared with the prior art, the invention has the beneficial effects that: firstly, effectively acquiring instantaneous flow data of different coal types; secondly, drawing a corresponding proportion control chart by using instantaneous flow data, wherein the belt conveyor coal blending ratio monitoring method based on the proportion control chart algorithm has better sensitivity and actual operability and can quickly and effectively react to the conditions of out-of-control and mean shift of the coal blending process; and finally, the ratio control chart is utilized to effectively monitor and adjust the coal blending ratio, thereby avoiding the coal quality fluctuation condition caused by the out-of-control coal blending ratio and ensuring the stability of the coal quality.
Drawings
FIG. 1 is a schematic view of an embodiment of an application system of a monitoring method for automatic coal blending according to the present invention;
FIG. 2 is a schematic flow chart of an embodiment of a monitoring method for automatic coal blending according to the present invention;
FIG. 3 is a flowchart illustrating an embodiment of step S2 in FIG. 2 according to the present invention;
FIG. 4 is a flowchart illustrating an embodiment of step S22 in FIG. 3 according to the present invention;
FIG. 5 is a flowchart illustrating an embodiment of step S221 in FIG. 4 according to the present invention;
FIG. 6 is a flowchart illustrating an embodiment of step S222 in FIG. 4 according to the present invention;
FIG. 7 is a flowchart illustrating another embodiment of step S222 in FIG. 4 according to the present invention;
FIG. 8 is a schematic structural diagram of an embodiment of an automatic coal blending weighing system provided by the present invention;
FIG. 9 is a schematic diagram of one embodiment of a proportional control diagram provided by the present invention;
fig. 10 is a schematic structural diagram of an embodiment of a monitoring device for automatic coal blending provided by the invention.
Detailed Description
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate preferred embodiments of the invention and together with the description, serve to explain the principles of the invention and not to limit the scope of the invention.
In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implying any number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. Further, "plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Reference throughout this specification to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the present invention. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the described embodiments can be combined with other embodiments.
The invention provides a monitoring method, a monitoring device and a storage medium for automatic coal blending, which fully consider the characteristics of a mode-hopping excitation environment, combine various wavelength characteristics, capture the mode-modulation phenomenon and provide a new idea for further improving the accuracy of mode-hopping detection. The following are detailed below:
an embodiment of the present invention provides an application system of a monitoring method for automatic coal blending, and fig. 1 is a schematic view of a scenario of an embodiment of an application system of a monitoring method for automatic coal blending provided by the present invention, where the system may include a server 100, and a monitoring device for automatic coal blending, such as the server in fig. 1, is integrated in the server 100.
The server 100 in the embodiment of the present invention is mainly used for:
acquiring instantaneous flow data of a plurality of coal types;
determining a proportional control chart according to the instantaneous flow data;
and adjusting the coal blending ratio formed among the plurality of coal types according to the proportion control chart.
In this embodiment of the present invention, the server 100 may be an independent server, or may be a server network or a server cluster composed of servers, for example, the server 100 described in this embodiment of the present invention includes, but is not limited to, a computer, a network host, a single network server, a plurality of network server sets, or a cloud server composed of a plurality of servers. Among them, the Cloud server is constituted by a large number of computers or web servers based on Cloud Computing (Cloud Computing).
It is to be understood that the terminal 200 used in the embodiments of the present invention may be a device that includes both receiving and transmitting hardware, i.e., a device having receiving and transmitting hardware capable of performing two-way communication over a two-way communication link. Such a device may include: a cellular or other communication device having a single line display or a multi-line display or a cellular or other communication device without a multi-line display. The specific terminal 200 may be a desktop, a laptop, a web server, a Personal Digital Assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, an embedded device, and the like, and the type of the terminal 200 is not limited in this embodiment.
Those skilled in the art will understand that the application environment shown in fig. 1 is only one application scenario of the present invention, and does not constitute a limitation on the application scenario of the present invention, and that other application environments may further include more or fewer terminals than those shown in fig. 1, for example, only 2 terminals are shown in fig. 1, and it is understood that the application system of the monitoring method for automatic coal blending may further include one or more other terminals, which is not limited herein.
In addition, as shown in fig. 1, the application system of the monitoring method for automatic coal blending may further include a memory 200 for storing data, such as instantaneous flow data, a ratio control map, a coal blending ratio, and the like.
It should be noted that the scenario diagram of the application system of the monitoring method for automatic coal blending shown in fig. 1 is only an example, and the application system and the scenario of the monitoring method for automatic coal blending described in the embodiment of the present invention are for more clearly illustrating the technical solution of the embodiment of the present invention, and do not form a limitation on the technical solution provided in the embodiment of the present invention.
An embodiment of the present invention provides a monitoring method for automatic coal blending, and referring to fig. 2, fig. 2 is a schematic flow chart of an embodiment of the monitoring method for automatic coal blending provided by the present invention, including steps S1 to S3, where:
in step S1, instantaneous flow data of several coal types is acquired;
in step S2, determining a proportional control map based on the instantaneous flow data;
in step S3, the blending ratio of the plurality of coal types is adjusted according to the ratio control map.
In the embodiment of the invention, firstly, instantaneous flow data of different coal types are effectively acquired; secondly, drawing a corresponding proportion control chart by using instantaneous flow data, wherein the belt conveyor coal blending ratio monitoring method based on the proportion control chart algorithm has better sensitivity and actual operability and can quickly and effectively react to the conditions of out-of-control and mean shift of the coal blending process; and finally, the ratio control chart is utilized to effectively monitor and adjust the coal blending ratio, thereby avoiding the coal quality fluctuation condition caused by the out-of-control coal blending ratio and ensuring the stability of the coal quality.
It should be noted that the ratio control map is preferably a ratio control map of variable sample capacity index weighted moving average ratio control, which is referred to as VSS EWMA-RZ control algorithm for short, and the coal blending ratio is monitored in real time to improve the coal blending accuracy. And a VSS EWMA-RZ control chart is introduced into a control system to monitor the coal blending ratio in real time. The filtered coal flow data obtains relevant parameters such as average running length, standard deviation of running length and the like when the coal flow is controlled or out of control according to the algorithm flow of the proportional control chart, then the proportional control chart is drawn according to a built-in algorithm, point drawing is carried out in real time for updating, and the proportional on-line monitoring of the coal is completed; according to the judgment criterion of the control chart, when the coal blending ratio is out of control, the output of the coal feeder is immediately guided to be adjusted through a feedback signal.
As a preferred embodiment, the VSS EWMA-RZ control chart combines the variable sample capacity strategy with the EWMA-RZ control chart to make up for the lack of lower sensitivity of the EWMA-RZ control chart to large offsets and improve the performance of the EWMA proportional control chart.
As a preferred embodiment, referring to fig. 3, fig. 3 is a schematic flowchart of an embodiment of step S2 in fig. 2 provided by the present invention, where the step S2 specifically includes steps S21 to S23, where:
in step S21, performing filtering according to the instantaneous flow data to determine corresponding filtered flow data;
in step S22, determining a controlled parameter of the coal blending ratio under a controlled condition and an out-of-control parameter under an out-of-control condition according to the filtering flow data;
in step S23, the proportional control map is determined according to the controlled parameter and the runaway parameter.
In the embodiment of the invention, firstly, instantaneous flow data is effectively filtered, so that the accuracy of the data is ensured; then, corresponding feature extraction is carried out on the filtering flow data, and relevant parameters in the filtering flow data are determined; and finally, drawing a proportional control chart based on the relevant parameters.
As a preferred embodiment, step S21 specifically includes: and denoising and cleaning the instantaneous flow data through a Kalman filtering algorithm to obtain the corresponding filtering flow data.
In the embodiment of the invention, a Kalman filtering algorithm is added into the weighing system. And taking the instantaneous flow measured by the belt weigher as an observed value, and denoising and cleaning impact data generated by coal breakage and instrument error data of the measuring equipment by using a Kalman filtering algorithm to obtain more real coal flow. Aiming at the influence of a weighing system on the accuracy of coal blending, a Kalman filtering algorithm is introduced to carry out data cleaning on the process data so as to provide more accurate coal flow data for a proportional control chart and improve the final quality of blended coal.
As a preferred embodiment, referring to fig. 4, fig. 4 is a schematic flowchart of an embodiment of step S22 in fig. 3 provided by the present invention, where the step S22 specifically includes steps S221 to S222, where:
in step S221, performing statistics according to the filtered flow data, and determining an upper single-side statistic and a lower single-side statistic of the proportional control graph;
in step S222, the controlled parameter and the runaway parameter are determined according to the upper single-sided statistic and the lower single-sided statistic by using a markov chain method.
In the embodiment of the invention, the filtering flow data after filtering processing is used for solving the average running length, the standard deviation of the running length and other related parameters when the control and the runaway are carried out according to the algorithm flow of the proportional control chart.
As a preferred embodiment, referring to fig. 5, fig. 5 is a schematic flowchart of an embodiment of step S221 in fig. 4 provided by the present invention, where the step S221 specifically includes step S2211 to step S2213, where:
in step S2211, determining coal flow proportions of different coal types according to the filtered flow data, and determining an initial statistic according to the coal flow proportions;
in step S2212, performing normalized distribution transformation on the initial statistics to obtain distribution statistics;
in step S2213, the upper single-side statistic and the lower single-side statistic of the proportion control map are determined according to the distribution statistic.
In the embodiment of the invention, the upper single-side statistic and the lower single-side statistic of the proportion control chart are effectively determined by utilizing the statistical characteristics.
In a specific embodiment of the present invention, the procedure for determining the upper single-sided statistic and the lower single-sided statistic is as follows:
first, determine initial statistics
Figure BDA0003338632860000091
Figure BDA0003338632860000092
Wherein, Xi、YiThe coal flow of the two kinds of filtered coal is reflected in a proportion control chart for monitoring the coal blending ratio as a random variable;
secondly, obtaining Z i statistic by adopting normalized distribution transformation;
Figure BDA0003338632860000093
wherein the content of the first and second substances,
Figure BDA0003338632860000094
which is the inverse of the distribution function of a standard normal distribution,
Figure BDA0003338632860000095
is composed of
Figure BDA0003338632860000096
The cumulative distribution function of (2) is formulated as:
Figure BDA0003338632860000097
Figure BDA0003338632860000098
wherein Z is0Is proportional, gamma, in a controlled stateX,γYIs the coefficient of variation of the variable X Y, ρ is the correlation coefficient of the variable XY;
thirdly, determining statistics of the controlled state VSS EWMA-RZ control chart
Figure BDA0003338632860000099
The statistics of the upper single-side VSS EWMA-RZ control chart are as follows:
Figure BDA00033386328600000910
wherein the upper control limit is UCL+＝KUThe initial value of the statistic is
Figure BDA00033386328600000911
The corresponding lower control limit is LCL +0, the warning limit is UWL+＝0+RU(UCL+-0)＝RUUCL+In which K isU>0 is a control limit coefficient, RUE (0,1) is a warning limit coefficient;
the statistic of the lower single-edge VSS EWMA-RZ control chart is as follows:
Figure BDA00033386328600000912
as a preferred embodiment, referring to fig. 6, fig. 6 is a schematic flowchart of an embodiment of step S222 in fig. 4 provided in the present invention, where the step S222 specifically includes step S2221 to step S2222, where:
in step S2221, a one-step transition matrix of the markov chain is determined using a markov chain method;
in step S2222, the controlled parameters are determined according to the one-step transition matrix, where the controlled parameters include at least one of a minimum acceptable average run length in the controlled state, a maximum acceptable average sample capacity in the controlled state, a process offset size, a proportion in the controlled state, corresponding coefficients of variation of coal flows of different coal types, and correlation coefficients.
In the embodiment of the invention, the relevant parameters in the controlled time are effectively determined by utilizing a Markov chain method.
In a specific embodiment of the present invention, the flow of determining the relevant parameters when controlled is as follows:
the method comprises the steps of firstly, deducing the average running length ARL, the standard deviation SDRL and the average sample capacity ASS of a unilateral VSS EWMA-RZ control chart by using a Markov chain method; wherein, the one-step transfer matrix of the Markov chain is as follows:
Figure BDA0003338632860000101
AKL＝qT(I-Q)-11
Figure BDA0003338632860000102
wherein q is an initial probability vector q ═ (1, 0., 0)T，ASS＝(n0，…，np，np+1) Pi, Q is a (p +1) -dimensional transition probability matrix, r is (I-Q1), and I is a unit column vector;
wherein the content of the first and second substances,
Figure BDA0003338632860000103
wherein the calculation formula of the matrix R is as follows:
Figure BDA0003338632860000111
second, determining the average run length ARL under controlled conditions0Acceptable minimum value L0, average sample volume under controlled state ASS0Acceptable maximum n0, process deviation size tau, ratio under control Z0Variation of variable X YCoefficient of variation gammaX,γYAnd values of parameters such as a correlation coefficient rho; let n bes＝1；nL＝n0+1；λ+0.05 or λ-0.05; based on the computational requirements (convergence of markov chains), λ needs to be greater than 0.05.
As a preferred embodiment, referring to fig. 7, fig. 7 is a schematic flowchart of another embodiment of step S222 in fig. 4 provided in the present invention, where the step S222 specifically includes step S2223 to step S2224, where:
in step S2223, under the relevant parameters in the controlled time, solving a mixed integer nonlinear programming model with equality constraints;
in step S2224, the proportional control map is optimized, and a set of decision variables that minimize the average run length in the runaway state is determined.
In the embodiment of the invention, a mixed integer nonlinear programming model with equality constraint is utilized to effectively determine a group of decision variables with the minimum average running length in an out-of-control state.
In a specific embodiment of the invention, under the current parameters, solving a mixed integer nonlinear programming model with equality constraint, optimizing a unilateral VSS EWMA-RZ control chart, and obtaining a set of decision variables (n) which can minimize the average running length ARL1 under the out-of-control states，nL，λ+，KU，RU) Or (n)s，nL，λ-，KD，RD) The value of (a). The model is as follows:
the objective function is:
minARL1(ns，nL，λ+，KU，RU,γX,γY,ρ,τ,z0)
the equation is constrained to:
ARL0(ns，nL，λ+，KU，RU,γX,γY,ρ,τ＝1,z0)＝200
ASS0(ns，nL，λ+，KU，RU,γX,γY,ρ,τ＝1,z0)＝n0
KU>0
RU∈(0,1)
λ+∈(0,1]
1<ns<n0<nL≤31
ns,nL∈N+
wherein the lower single-sided VSS EWMA-RZ control chart requires constraint KU>0 is replaced by the following formula KD<0, the above constraint equations are respectively combined for the sample volumes (n)s，nL) Control limit coefficient KUAlarm limit coefficient RUAnd a smoothing coefficient lambda+And (6) carrying out constraint.
As a preferred embodiment, the step S23 includes: sampling the instantaneous flow data, calculating the related parameters of each sample, drawing the proportional control chart, and updating the real-time point tracing, wherein the first sampling adopts a small sample capacity n(1)＝nsFor the ith sampling, when the upper single-side statistic is smaller than the alarm limit, the next sampling with the small sample capacity n(i+1)＝nsOtherwise, the large sample capacity n is adopted(i+1)＝nL，n(1)For the first sampled sample volume, n(i+1)Sample capacity of i +1 th sample, nsFor a preset small sample volume, nLFor a preset large sample capacity
In the embodiment of the invention, the sampling accuracy and the sampling completeness are ensured by utilizing the variable sample, and the coal blending precision is improved.
In one embodiment of the present invention, a single-sided VSS EWMA-RZ control chart may be drawn after sampling and calculating the statistics for each sample. In the implementation process, the first sampling adopts a small sample capacity n(1)＝nsFor the ith sample, when Yi +<At UWL, the next time a small sample capacity n is used(i+1)＝nsOtherwise, the large sample capacity n is adopted(i+1)＝nL. Specifically, when Y is<UWL, which indicates that the sample is in a controlled state, and the small sample capacity is continuously adopted next time; when UCL is used<Y<UWL, which means that it is still in a controlled state, but is located in a warning zone. The next time, large sample capacity is needed to be adopted, and the sampling range is enlarged; when Y is>The UCL, indicating an out of control condition, requires further inspection.
As a preferred embodiment, the step S3 includes:
and correlating a plurality of proportion control charts generated by different coal types, and sending out an early warning signal to adjust the coal blending ratio of different coal types when at least one proportion control chart judges that the proportion is out of control.
In the embodiment of the invention, the proportion control chart is used for early warning, the proportion control charts of various coal blending ratios are correlated, and an alarm can be given in time when the ratio is out of control, so that the quality of coal blending is ensured.
As a preferred embodiment, the process of determining the loss of control of the ratio includes: sampling statistics is carried out according to the instantaneous flow data, and corresponding real-time statistics is determined; if the real-time statistic is within the control limit of the proportional control chart, judging that the coal blending ratio is controlled and stable; if the real-time statistic is between the control limit and the warning limit of the proportional control chart, judging that the coal blending ratio is in a warning state, and enlarging the sample capacity of the sample; and if the real-time statistic exceeds the warning limit, judging that the coal blending ratio is in an out-of-control state.
In the embodiment of the invention, the ratio of coal blending is effectively determined by utilizing the proportion control chart, and if the ratio exceeds the early warning line, an early warning signal is sent out, so that the aims of real-time monitoring and real-time early warning are fulfilled.
Referring to fig. 8 and 9, fig. 8 is a schematic structural diagram of an embodiment of an automatic coal blending weighing system provided by the present invention, and fig. 9 is a schematic diagram of an embodiment of a proportional control diagram provided by the present invention, so as to more clearly illustrate the technical solution of the present invention:
the monitoring method for automatic coal blending is applied to the automatic coal blending weighing system shown in figure 8, and the automatic coal blending weighing system is used for enabling every 3 discharging discharge spouts of the same silo to be a group of large-volume silos sharing one set of automatic coal blending weighing system. As shown in fig. 8, the bottom of each silo is designed with 6 discharge spouts, each 3 discharge spouts share one set of automatic coal blending weighing system, and each discharge spout is provided with an air cannon and a loosening machine. The whole automatic coal blending system consists of a coal feeder device, a weighing system and a closed-loop control system. The device specifically comprises an activation coal feeder, a belt conveyor, a weighing and speed measuring sensor, a frequency converter, an integrator instrument and an industrial personal computer.
The two coal blending processes are implemented as follows:
firstly, coal from a storage yard can be transferred to a bypass third belt conveyor 3 and a fourth belt conveyor 4 to a large-volume first silo 5 and a second silo 6 with 1 ten thousand tons of single storage capacity after passing through a first belt conveyor 1 and a second belt conveyor 2 of the storage yard;
and secondly, storing one coal in each large-volume silo, wherein each coal enters the first activation coal feeder 7 or the second activation coal feeder 8 through a silo discharge nozzle. The first activation coal feeder and the second activation coal feeder control discharging according to a set coal blending proportion, coal falls to a first metering short belt conveyor 9 and a second metering short belt conveyor 10, and the belt conveyors are provided with weighing sensors 14 and speed measuring sensors;
thirdly, the coal in the first silo 5 and the second silo 6 continuously falls on a first metering short belt conveyor 9 and a second metering short belt conveyor 10 with belt weighers through a first activating coal feeder 7 or a second activating coal feeder 8, and a weighing sensor 14 converts the weight of the coal into 1-20 mV instantaneous signals, and transmits the instantaneous signals to a Kalman filter 15 for data cleaning treatment to obtain more accurate instantaneous coal flow;
and fourthly, transmitting the processed instantaneous coal flow data to an integrator 16 for PID operation. Respectively defining the processed data as parameters X and Y according to the setting of a PID algorithm, solving related parameters of a control limit and an alarm limit according to a VSS EWMA-RZ proportional control chart algorithm flow, drawing a proportional control chart according to the related parameters, and updating points in real time to finish the online monitoring of the proportion between the two coals. According to the judgment criterion of the control chart, when the coal blending ratio is out of control, a corresponding alarm indicator lamp is turned on a screen, and the integrator 16 immediately outputs a feedback current signal of 4-20 mA to the frequency converter 17 to control the activated reclaimers 7 and 8 to adjust the output force so that the actual coal dropping amount is as equal to the set coal blending ratio as much as possible, thereby stabilizing the coal blending accuracy;
and fifthly, different coal types fall into the distribution belt conveyor 11 after passing through the first metering short belt conveyor 9 and the second metering short belt conveyor 10, are mixed and blended according to needs, are fully and uniformly mixed, and can be converged into the first ship-loading belt conveyor 12 and the second ship-loading belt conveyor 13 according to actual requirements, so that high-precision coal blending is completed in the process of conveying and loading.
When the three kinds of coal are blended, drawing three control charts on the instantaneous flow of the three kinds of coal, wherein the three control charts are mutually associated and restricted, and when the alarm rule is changed to at least one control chart, the judgment is valid, the system alarm is caused, and the activated coal feeder is controlled to make corresponding adjustment; the alarm condition is that the control chart judges that the coal proportioning out of control exceeds the warning limit of the control chart;
wherein, if the target mixing ratio of the two types of coal which need to be monitored at present is 1: 1(Z0 ═ 1), the instantaneous flow rate of the belt conveyor under the controlled process state was subjected to a normal distribution with an average value of 12.5kg/s, and the flow rates of the two types of materials were expressed by variables (X, Y). Taking gammaX＝0.2，γYWhen Z0 is 1 at steady state of 0.2 and ρ 0, assuming the process is always running at rated production rate, the flow rates on both conveyors are 12.5kg/s, i.e., μX＝12.5，μY12.5. 5, for the situation that the ratio Z0-1 of the two coals in the production process can be shifted to Z1-1.1, a proper ratio control chart needs to be selected and optimally designed and discovered. Deviation of coal proportioning;
in the experiment, 30 times of sampling detection are carried out, the maximum sample capacity is 31, the normal operation Z0 of the equipment during the first 10 times of sampling is assumed to be 1, after the 10 th sampling, the flow of one belt conveyor is assumed to be increased to 13.75kg/s due to the abnormality of the unloading equipment so as to simulate the runaway process in the runaway state, and the proportion of two kinds of coal is shifted to Z1 which is 1.1. The detection result of the VSS EWMA-RZ control chart is shown in the following figure 2, and the control chart sends out a process out-of-control alarm at the 2 nd sample point after the coal proportion deviation, so that the control chart is very sensitive in monitoring the coal blending ratio, can timely identify the abnormality in the process and guarantee the quality of blended coal. And when the coal blending process is in a controlled state, the phenomenon of false alarm occurs, which shows the effectiveness of the VSS EWMA-RZ control chart in monitoring the coal blending quality.
An embodiment of the present invention further provides a monitoring device for automatic coal blending, and referring to fig. 10, fig. 10 is a schematic structural diagram of an embodiment of the monitoring device for automatic coal blending provided by the present invention, where the monitoring device 1000 for automatic coal blending includes:
an obtaining unit 1001 configured to obtain instantaneous flow data of a plurality of coal types;
the processing unit 1002 is used for determining a proportional control chart according to the instantaneous flow data;
and the adjusting unit 1003 is used for adjusting the coal blending ratio of the various coal types according to the proportion control chart.
The more specific implementation of each unit of the monitoring device for automatic coal blending can be referred to the description of the monitoring method for automatic coal blending, and has similar beneficial effects, and the detailed description is omitted here.
The embodiment of the invention also provides a computer readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the method for monitoring automatic coal blending is realized.
Generally, computer instructions for carrying out the methods of the present invention may be carried using any combination of one or more computer-readable storage media. Non-transitory computer readable storage media may include any computer readable medium except for the signal itself, which is temporarily propagating.
A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages, and in particular may employ Python languages suitable for neural network computing and TensorFlow, PyTorch-based platform frameworks. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The embodiment of the invention also provides a computing device, which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein when the processor executes the program, the monitoring method for automatic coal blending is realized.
The computer-readable storage medium and the computing device provided by the above embodiments of the present invention can be implemented by referring to the content specifically described in the implementation of the monitoring method for automatic coal blending according to the present invention, and have similar beneficial effects to the monitoring method for automatic coal blending described above, and are not described again here.
The invention discloses a monitoring method for automatic coal blending.
According to the technical scheme, the proportion control chart is applied to the port silo coal blending system, so that the online monitoring of the coal blending proportion is realized, and the accuracy of port coal blending is improved. A VSS EWMA-RZ control chart (variable sample volume index weighted moving average proportional control chart) algorithm is introduced in a coal blending quality control link, so that the real-time online monitoring of the coal blending quality is realized, and the coal blending precision is improved. Experiments and data analysis show that the algorithm has no false alarm phenomenon when the coal blending system is in a stable state, and can give an alarm in time when the blending ratio is out of control, so that the quality of coal blending is guaranteed. The method for using the proportional control chart in the coal blending system has a very obvious detection effect on the ratio of the flow rates of the two types of coal, and the control chart can quickly respond when the mean value is suddenly changed; when the mean value is slowly shifted, corresponding images can be displayed, and the effectiveness and the sensitivity of the method in a port coal blending scene are proved.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention.

Claims (10)

1. A monitoring method for automatic coal blending is characterized by comprising the following steps:
acquiring instantaneous flow data of a plurality of coal types;
determining a proportional control chart according to the instantaneous flow data;
and adjusting the coal blending ratio formed among the plurality of coal types according to the proportion control chart.
2. The method for monitoring automatic coal blending according to claim 1, wherein the determining a proportional control chart according to the instantaneous flow data comprises:
filtering according to the instantaneous flow data to determine corresponding filtering flow data;
determining a controlled parameter of the coal blending ratio under a controlled condition and an out-of-control parameter under an out-of-control condition according to the filtering flow data;
and determining the proportional control chart according to the controlled parameter and the runaway parameter.
3. The method for monitoring automatic coal blending according to claim 2, wherein the filtering according to the instantaneous flow data to determine corresponding filtered flow data comprises: and denoising and cleaning the instantaneous flow data through a Kalman filtering algorithm to obtain the corresponding filtering flow data.
4. The method for monitoring automatic coal blending according to claim 2, wherein the determining the controlled parameter of the coal blending ratio under the controlled condition and the out-of-control parameter under the out-of-control condition according to the filtering flow data comprises:
counting according to the filtering flow data, and determining upper single-side statistic and lower single-side statistic of the proportional control chart;
and determining the controlled parameter and the out-of-control parameter according to the upper single-edge statistic and the lower single-edge statistic by using a Markov chain method.
5. The method for monitoring automatic coal blending according to claim 4, wherein the determining the upper single-sided statistic and the lower single-sided statistic of the proportion control chart by performing statistics according to the filtered flow data comprises:
determining coal flow proportions of different coal types according to the filtering flow data, and determining initial statistics according to the coal flow proportions;
carrying out normalized distribution transformation on the initial statistic to obtain a distribution statistic;
and determining the upper single-side statistic and the lower single-side statistic of the proportion control chart according to the distribution statistic.
6. The method for monitoring automatic coal blending according to claim 4, wherein the determining the controlled parameter and the runaway parameter according to the upper single-sided statistic and the lower single-sided statistic by using a Markov chain method comprises:
determining a one-step transfer matrix of the Markov chain by using a Markov chain method;
and determining the controlled parameters according to the one-step transition matrix, wherein the controlled parameters comprise at least one of a minimum value acceptable for the average run length under the controlled state, a maximum value accepted for the average sample capacity under the controlled state, a process deviation size, proportions under the controlled state, corresponding variation coefficients of coal flow rates of different coal types and correlation coefficients.
7. The method for monitoring automatic coal blending of claim 6, wherein the determining the controlled parameter and the runaway parameter from the upper single-sided statistic and the lower single-sided statistic using a Markov chain method further comprises:
solving a mixed integer nonlinear programming model with equality constraints under the relevant parameters under the controlled time;
and optimizing the proportional control chart, and determining a group of decision variables which minimize the average running length under the out-of-control state.
8. The method for monitoring automatic coal blending according to claim 2, wherein the determining the proportion control chart according to the relevant parameters and performing real-time point-tracing updating comprises: sampling the instantaneous flow data, calculating the related parameters of each sample, drawing the proportional control chart, and updating the real-time point tracing, wherein the first sampling adopts a small sample capacity n(1)＝nsFor the ith sampling, when the upper single-side statistic is smaller than the alarm limit, the next sampling with the small sample capacity n(i+1)＝nsOtherwise, the large sample capacity n is adopted(i+1)＝nL，n(1)For the first sampled sample volume, n(i+1)Sample capacity of i +1 th sample, nsFor a preset small sample volume, nLIs a preset large sample capacity.
9. The method for monitoring automatic coal blending according to claim 1, wherein the adjusting the coal blending ratio formed among the plurality of coal types according to the proportion control map comprises:
and correlating a plurality of proportion control charts generated by different coal types, and sending out an early warning signal to adjust the coal blending ratio of different coal types when at least one proportion control chart judges that the proportion is out of control.
10. The method for monitoring automatic coal blending according to claim 1, wherein the step of judging the proportion out of control comprises: sampling statistics is carried out according to the instantaneous flow data, and corresponding real-time statistics is determined; if the real-time statistic is within the control limit of the proportional control chart, judging that the coal blending ratio is controlled and stable; if the real-time statistic is between the control limit and the warning limit of the proportional control chart, judging that the coal blending ratio is in a warning state, and enlarging the sample capacity of the sample; and if the real-time statistic exceeds the warning limit, judging that the coal blending ratio is in an out-of-control state.
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