KR20180080010A - Filtration and Dust Collection System and Apparatus for controlling Dust Collection System - Google Patents

Abstract

The present invention relates to a dust collection system and an apparatus for controlling the dust collection system. The dust collection system and the apparatus for controlling the dust collection system according to the present invention are able to precisely predict an air jet escapement point by reflecting a current operation status of a precipitation facility in an impact jet type escapement method so as to reduce operation costs. In addition, the current operation status or the environment of the changing precipitation facility is reflected to reset a target wind amount such that a fan motor can be efficiently driven to improve the efficiency of a filtration precipitator.

Description

 BACKGROUND OF THE INVENTION Field of the Invention [0001] The present invention relates to a dust collection system and a dust collection system,

 BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a dust collector technology field, and more particularly, to a filter dust collector using a pulse-jet cleaning method.

 Generally, a filter and dust collector sucks dust through a dust collector, and filters the dust through a filter cloth in the dust collector to remove the filtered clean air through a stack. At this time, dust accumulates on the surface of the filter cloth over time, causing clogging of the filter fabric, resulting in deterioration of filtration performance.

In order to remove the accumulated dust from the filter cloth, there are a vibrating type for mechanically vibrating and removing the dust and an inverse flow type for removing the dust by passing the airflow in the opposite direction, And a shock jet type in which the dust is sequentially removed by injecting the dust at a predetermined time interval.

Among them, the impact jet type having a high exhaustion efficiency of the exhaustion method and less damage to the filter cloth is widely used. The discharge of the conventional impact jet type allows the accumulated air to be removed from the filter cloth by periodically opening the valve according to a predetermined cycle by injecting compressed air.

 However, such a shock jet type method has a disadvantage in that a large amount of electric power is required for each exhaustion, the cost of the gas to be injected is high, and the life of the bag filter is shortened. However, since the operating conditions such as the temperature and the humidity are variable in addition to the pressure loss, it is not taken into consideration and the exhausting efficiency of the air jet is low.

 Further, since the conventional filter and dust collector drives the fan motor according to the target air volume of the fan motor set according to the design value of the initial dust collection facility, it reflects the current state of the dust collection facility that changes as the use date of the filter and dust collector increases It is inevitable that the efficiency of the filter and dust collector is lowered.

Korea Patent No. 10-0957030

 SUMMARY OF THE INVENTION Accordingly, the present invention has been made keeping in mind the above problems occurring in the prior art, and it is therefore an object of the present invention to provide a dust collecting system, There is.

 Further, the present invention is to improve the dust collecting system efficiency by efficiently driving the fan motor by resetting the target air flow rate in accordance with the current operating state or environment of the changing dust collecting facility.

 The dust collection system according to one embodiment includes a hood, a dust collector, a fan, a stack, and a control unit. The hood is installed near the dust source. The dust collector may include a bag filter, an air jet injector, and dust rejection. The hood is connected to the dust collector inlet through the duct. The air jet injector ejects gas to exhaust the bag filter. Denominator rejection collects dust separated by filtering. The fan is connected to the dust collector outlet through a duct and is driven by a fan motor. And the stack is connected to the outlet of the fan. The control unit determines whether or not the air jet injector is exhausted and the fan motor target airflow according to the operating state of the dust collecting system.

 In addition, the operating state variable of the dust collecting system includes the first operating state variable. The dust collection system further includes a first operation state sensor, and the control unit includes a first storage unit and a target air flow rate determination unit. The first operating state variable includes variables such as the number of open hoods, the pressure of the dust collector outlet, and the purge airflow of the stack, and includes temperature, humidity, differential pressure between the dust collector inlet and the dust collector outlet, Dust concentration, and dust collection facility design parameters. The first operating state sensor senses the operating state of the first operating state variable. The first storage unit stores the first operation state data for the first operation state variable from the first operation state sensor. Further, the target airflow determining section includes a machine learning algorithm that inputs the first operating state variable and outputs the fan motor airflow, and learns to optimize the indoor dust concentration using the first operating state data to determine the fan motor target airflow do.

 Further, the dust collection system may further include a fan motor driving unit, and the control unit may further include a proportional integral ratio (PID) control unit. And the fan motor driving section can drive the fan motor in accordance with the output of the target air flow amount determining section. The PID control unit may be connected between the output of the target wind amount determination unit and the fan motor drive unit to perform PID control.

In addition, the operating state variable of the dust collecting system may include a second operating state variable, and the dust collecting system may include a second operating state sensor, a second storing unit, and a discharge determining unit. The second operating state variable may include the dust collector inlet and the differential pressure of the dust collector, which is the differential pressure of the dust collector outlet, as one variable. And the second operation state sensor can sense the operation state for the second operation state variable. The second storage unit may store the second operation state data for the second operation state variable from the second operation state sensor. The exhaust emission determining unit may determine whether or not the air jet injector is exhausted based on a value obtained by comparing the reference differential pressure threshold value and the current dust collector pressure.

 Further, the dust collection system further includes a first number of exhaustion counts, and the second operating status variable includes a number of open hoods, a temperature, a humidity, a dust collector inlet pressure, a dust collector outlet pressure, And a fan motor driving current, and the exhaust emission determining unit may include a exhaustion timing determining unit. The first discharging count counter may count the number of discharging discharges, which is the number of times that the air jet has exhausted the bag filter during a predetermined period. Wherein the exhaustion-timing determining unit includes a machine learning algorithm for inputting a second operating state variable and outputting whether or not the air jet injector is exhausted, wherein the second learning state data is used to minimize the number of exhaustion times To determine the timing of air jet evacuation.

Further, the dust collection system according to an embodiment may further include a second discharge count counter, and the discharge pattern determination unit may include a discharge pattern correction unit. The second discharging count counter can count the number of discharging discharges, which is the number of times the air jet has exhausted the bag filter during a predetermined period. The exhaustion-timing correcting unit can correct the exhaustion timing by analyzing the trends of the second operation state data of the second storage unit and the number of exhaustion times counted by the second exhaustion-count counter.

 A dust collecting system control apparatus according to an embodiment of the present invention includes a hood installed near a dust source, a hood connected to a dust collector inlet through a duct, a bag filter disposed inside the hood, A dust collector connected to the outlet of the dust collector via a duct and driven by a fan motor and connected to the outlet of the fan, And a driving state sensor unit including at least one sensor for sensing a driving state of each of the above-described components. In addition, the apparatus for controlling dust collection system according to an embodiment may include an operation state data collection unit, a dust removal determination unit, and a target air flow rate determination unit. The operation state data collection unit can collect the operation state data on the operation state variable of the dust collection system from the operation state sensor unit. The exhaust emission determination section can determine whether the air jet injector is exhausted or not based on the operation state data and output the exhaust emission determination result. The target air flow rate determination section can determine the target air flow rate by driving the fan motor based on the operation state data.

 In addition, the operating state variable of the dust collecting system control device includes the first operating state variable. The operation state data collection unit includes a first operation state data collection unit. The target airflow determining unit includes a machine learning algorithm that inputs the first operating state variable and outputs the fan motor airflow. The fan motor target airflow can be determined by learning to optimize the indoor dust concentration using the first operating state data have. The first operating state variable includes the number of open hoods, the difference between the dust collector inlet and the dust collector outlet, and the indoor dust concentration as variables. The first operating state variable may further include at least one of a temperature, a humidity, a pressure of the dust collector outlet, a fan motor driving current, a purge airflow of the stack, and a dust collector design variable. The first operation state data collection unit stores the first operation state data for the first operation state variable.

 Further, the dust collection system control apparatus further includes a fan motor driving section for driving the fan motor in accordance with the output of the target airflow amount determination section, further comprising a PID control section. The PID control unit is connected between the output of the target airflow determining unit and the fan motor driving unit so as to control the PID (proportional integral ratio).

The operation state data of the dust collecting system control unit includes a second operation state variable, the operation state data collecting unit includes a second operation state data collecting unit, and the exhaust emission determining unit compares the reference differential pressure difference with the current difference of the present dust collector It is determined whether or not the air jet injector is exhausted. The second operating state variable includes the dust collector inlet and the differential pressure of the dust collector which is the differential pressure of the dust collector outlet as one variable. The second operation state data collection unit stores the second operation state data for the second operation state variable from the operation state sensor.

 Further, the dust collecting system control device according to the present invention further includes a first discharging count counter, and the discharging determining unit includes a discharging timing determining unit. The second operating state variable may further include at least one of a number of open hoods, a temperature, a humidity, a dust collector inlet pressure, a dust collector outlet pressure, a stack exhaust dust concentration, and a fan motor driving current. 1 The number of exhaustion counter counts the number of times of exhaustion, which is the number of times the air jet has exhausted the bag filter during a predetermined period. And the machine learning algorithm includes a machine learning algorithm in which the second operation state variable is input and the exhaust jetting state of the air jet injector is output, and the second operation state data is used to learn to minimize the number of times of exhaustion, Can be determined.

 Further, the dust collection system control device may further include a second exhaustion count counter, and the exhaustion determination unit includes a jumping-off unit during exhaustion. The second number of discharging counts counts the number of discharging times, which is the number of times that the air jet has exhausted the bag filter during a predetermined period. The exhaustion-timing correcting unit can correct the exhaustion timing by analyzing trends of the second operation state data of the second operation state data collecting unit and the number of times of exhaustion counts counted by the exhaustion number-of-times counter.

Also, the operation state sensor unit of the dust collection system control device may be connected via Ethernet according to an aspect.

 Still further, the dust collection system control apparatus may further include a first rainfall learning data classification section. The first rich learning data classifier may be connected between the output of the first operating state data collecting unit and the target air flow determining unit to extract a variable having a strong influence on the target air flow rate among the first operating state variables.

 The dust collection system control device may further include a second well-known learning data classification unit. The second well learning data classifier may be connected between the output of the second operating state data collecting unit and the exhaustion determining unit to extract a variable having a high influence on the determination of the exhaustion timing among the second operating state variables.

 According to the present invention, the exhaustion timing of the air jet can be efficiently controlled to reduce the exhaustion cost of the dust collection system.

 In addition, the efficiency of the dust collecting system can be improved by driving the fan motor efficiently by resetting the fan motor target air volume reflecting the current operating state or environment of the dust collecting facility.

1 is a perspective view of an embodiment of a dust collection system according to an embodiment.
2 is a block diagram of a dust collection system according to an embodiment.
3 is a block diagram of an embodiment of a dust collection system according to an embodiment of the present invention.
4 is a block diagram of an embodiment of a controller of a dust collection system according to an embodiment.
5 is a block diagram of another embodiment of the controller of the dust collection system according to an embodiment.
FIG. 6 is a block diagram of an exhaustion determination unit and a first exhaustion count counter of a dust collection system according to an embodiment.
FIG. 7 is a block diagram of an embodiment of a dust collection system according to an embodiment of the present invention; FIG.
8 is a block diagram of a dust collection system control apparatus according to an embodiment.
FIG. 9 is a block diagram showing another configuration of an apparatus for controlling a dust collection system according to an embodiment of the present invention, in which the first operating state variable, the first operating state data collecting unit, and the target airflow determining unit are different.
10 is a block diagram of an embodiment of a PID controller of a dust collection system control apparatus according to an embodiment of the present invention.
11 is a block diagram of an apparatus for controlling a dust collection system according to an embodiment of the present invention.
12 is a block diagram of an exhaust emission determining unit of an apparatus for controlling dust collection system according to an embodiment of the present invention.
13 is a block diagram of another embodiment of the dust removal determination unit of the dust collection system control apparatus according to the embodiment.
FIG. 14 is a block diagram of a first well training data classifying unit of a dust collecting system control apparatus according to an embodiment.
And FIG.
FIG. 15 is a block diagram of an embodiment of a second rainfall learning data classifier of a dust collection system control apparatus according to an embodiment.

 DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, a dust collecting system and a dust collecting system according to a preferred embodiment of the present invention will be described in detail with reference to the accompanying drawings. Here, the same reference numerals are used for the same components, and repeated descriptions and known functions and configurations that may obscure the gist of the present invention will not be described in detail. Embodiments of the invention are provided to more fully describe the present invention to those skilled in the art. Accordingly, the shapes and sizes of the elements in the drawings and the like can be exaggerated for clarity.

 FIG. 1 is a perspective view of an embodiment of a dust collection system 001 according to an embodiment of the present invention, and FIG. 2 is a block diagram of a dust collection system 001 according to an embodiment.

 1 and 2, the dust collection system 001 according to an embodiment includes a hood 010, a dust collector 030, a fan, a stack 090, and a control unit 100 . The hood 010 (hood) is installed near the dust circle. The dust collector 030 may include a bag filter 050 (bag filter), an air jet injector, and a dust rejection (060). The hood 010 is connected to the dust collector inlet 020 through a duct. The air jet injectors 040 blow out the bag filter 050 by injecting gas. The denial rejection (060) collects the dust separated by filtering. The fan is connected to the dust collector outlet through a duct and is driven by a fan motor (081). And the stack (090) is connected to the outlet of the fan. The control unit 100 determines whether or not the air jet injector 040 is drained and the fan motor 081 (fan motor) target air flow rate according to the operation state variable 110 of the dust collection system 001.

 The dust collecting system (001) according to one embodiment is a kind of a filtering and dust collecting machine which is a known technique and can use a pulse jet type exhausting method as a dust exhausting method. The impact jet type exhausting method is a method of exhausting the dust attached to the surface of the bag filter (050) by using high pressure compressed air through the injection nozzle. Such a draining method uses expensive gas, requires a high power amount, and has a characteristic that the lifetime of the bag filter (050) is short. The air jet exhaustion of a typical filter dust collector is performed every predetermined interval, for example, every 2 to 3 minutes. The controller 100 of the dust collecting system 001 according to an exemplary embodiment of the present invention minimizes the number of times of dust removal and minimizes the operating cost of the dust collecting system 001, 040) can be determined so as to minimize the number of times of exhaustion.

 In addition, the filter dust collector generally aims to increase the efficiency of the filter dust collector by determining the target airflow of the fan motor (081) considering the design parameters of the initial dust collection facility. The efficiency of the filter dust collector can be determined on the basis of the dust concentration difference between the inlet and outlet of the dust collector or the pressure difference between the dust collector inlet 020 and the outlet with respect to the dust concentration of the inlet of the dust collector. Accordingly, in order to increase the efficiency, the conventional filter and dust collector determines the dust density difference between the inlet and outlet of the dust collector when the fan motor 081 is driven according to the target air flow rate of the fan motor 081, And adjusts the number of revolutions of the fan motor (081) based on information relating to the pressure difference of the outlet.

 However, as the target air flow rate of the initially set fan motor 081 is changed over time, the design and manufacturing specifications may be changed depending on the installation conditions, types of discharge facilities, kinds of pollutants, applications, In addition, since the conventional filter dust collector does not reflect the operation state of the other filter dust collectors, the dust collecting system 001 according to the embodiment reflects various factors as described above to increase the efficiency of the dust collecting system 001, So that the target air flow rate of the fan motor 081 can be determined.

 In order to reduce the operation ratio of the dust collection system 001 and to increase the efficiency as described above, the controller 100 according to an embodiment of the present invention attempts to solve the problem by using the means described later.

3 is a block diagram of an embodiment of the controller 100, the first operating state sensor, and the operating state variable 110 of the dust collection system 001 according to an embodiment of the present invention.

 As shown in FIG. 3, the operating state variable 110 of the dust collecting system 001 according to an embodiment includes a first operating state variable 120. The dust collection system 001 further includes a first operation state sensor and the control unit 100 includes a first storage unit 140 and a target air flow rate determination unit 160. The first operating state variable 120 includes variables such as the number of open hoods 010, the pressure of the dust collector outlet 070 and the purge airflow of the stack 090 (stack), and the temperature, humidity, A differential pressure between the dust collector outlet 020 and the dust collector outlet 070, a fan motor driving current 700, an indoor dust concentration, and a dust collection facility design parameter. The first operating state sensor senses the operating state of the first operating state variable. The first storage unit 140 stores the first operation state data 150 for the first operation state variable 120 from the first operation state sensor. The target air flow rate determination unit 160 includes a machine learning algorithm that receives the first operating state variable 120 and outputs the air flow rate of the fan motor 081. Using the first operating state data 150, So as to be optimized to the dust concentration to determine the target air flow rate of the fan motor (081).

 The first operating state variable 120 is a variable used to determine the target air flow rate. The first operating state variable 120 is a difference between the dust concentration difference of the inlet and outlet of the dust collector, which is a main factor in the efficiency of the dust collection system 001, The number of open hoods 010, which is a variable reflecting the pressure difference, the pressure difference between the dust collector inlet 020 and the dust collector outlet 070, and the indoor dust concentration. Since the dust separator differential pressure 190 is in proportion to the number of the open hoods 010 or the indoor dust concentration, the number of open hoods 010, the differential pressure between the dust collector inlet 020 and the dust collector outlet 070, It can be a main variable for determining the target air flow rate of the fan motor 081. [

 Next, at least one of the first operating state variable temperature, humidity, the pressure of the dust collector outlet (070), the fan motor driving current (700), the purge airflow of the stack, And can be used to determine the target air volume. Conventional filter dust collectors do not reflect such factors over time, so that there is a limitation in improving the efficiency of the filter dust collector. For example, when the temperature of the dust collection system (001) rises, the viscosity and the flow rate of the gas increase, thereby increasing the dust separator differential pressure (190). Also, if the humidity is high, the bag filter 050 may be clogged. Accordingly, the dust collection system 001 according to the present invention is configured to calculate at least one of the variables of the temperature, the humidity, the purge air volume of the stack 090, which is a measure of the actual air volume in the stack 090, It is possible to increase the efficiency of the dust collection system 001 by determining the target air volume of the dust collection system 081.

 The first operating state variable of the dust collecting system 001 according to an embodiment is not limited to the above-described variables but may include other variables reflecting the operating state.

 As shown in FIG. 1, the dust collection system 001 according to an embodiment includes a number of open hoods 010 for the first operating state variable, a differential pressure between the dust collector inlet 020 and the dust collector outlet 070, The fan motor driving current 700, and the stack 090 (purge air volume) of the stacker 070, respectively. The sensor that senses each operating state variable 110 may include an analog to digital converter that includes means for sensing the respective operating state and may convert the sensed operating state to a digital signal.

 Also, the first storage unit 140 stores the first operation state data 150 for the first operation state variable 120. The first storage unit 140 according to an aspect may include a communication unit such as a near field wireless communication to directly receive and store the first operation state data 150 from the first operation state sensor. The first storage unit 140 according to another aspect may be connected in circuit with the first operation state sensor to receive and store the first operation state data 150 from the first operation state sensor on a wire.

 The target air flow rate determination unit 160 may analyze the information of the first operation state data 150 received from the first operation state sensor according to an aspect to determine the target air flow rate capable of maximizing the efficiency of the dust collection system 001 . For example, the efficiency of the dust collection system (001) for each variable of the first operating state variable 120 may be analyzed and output in each graph to automatically or manually set the target airflow at which the target efficiency can be achieved .

The target air flow rate determination unit 160 includes a machine learning algorithm that inputs the first operating state variable 120 and outputs the fan motor 081 air volume using the first operating state data 150 according to another aspect However, it is possible to determine the target air flow rate of the fan motor 081 by learning to be optimized for indoor dust concentration. A machine learning algorithm is a group of actions that solve a problem by applying machine learning. Machine learning is a technique known in the art as learning a set of data on a machine and then extracting useful information from data that is input later using the obtained rules or patterns. Machine learning is divided into supervised learning, unsupervised learning and reinforcement learning. Machine learning algorithms are divided into neural network, data mining, decision tree, ), And pattern recognition.

 The dust collection system 001 according to an embodiment can use an appropriate algorithm in the above-described machine learning algorithm according to the accuracy, the learning time, the linearity, and the number of parameters. The indoor dust concentration, the temperature, the humidity, and the pressure of the dust collector outlet (070) are inputted as the input, and the indoor dust And outputting the target air flow rate of the fan motor 081 so as to be optimized for the concentration. In this case, there are six parameters, which require relatively high accuracy and less learning time, and the linearity between parameters is not high, so that machine learning algorithms such as decision trees, support vector computers, and high-order neural networks can be used. In addition, the target air flow rate can be determined using a suitable machine learning algorithm according to the type and the number of the operating state variables 110 to be used.

 1 includes a number of open hoods 010, a dust collector inlet 020 pressure, a dust collector outlet 070 pressure, a dust collector inlet 020, The dust pressure of the dust collector outlet 070, the indoor dust concentration, the temperature and the humidity, the pressure of the dust collector outlet 070, the fan motor driving current 700, the purge airflow of the stack 090, ) And exhausted dust concentration, respectively. The sensor for detecting the number of the open hoods 010 may be located in the hood 010 and may be a signal for controlling the opening and closing of the opening of the hood 010 by the operation state control unit 100 of the dust collection system 001 And may be a sensor that detects the number of open hoods 010 by sensing. And the dust collector inlet (020) pressure sensor may be located in the dust collector inlet (020). The dust collector outlet (070) may be located in the dust collector outlet (070). The differential pressure sensor between the dust collector inlet 020 and the dust collector outlet 070 receives the output of the dust collector outlet 070 pressure sensor and the dust collector inlet 020 pressure sensor through wired or wireless communication, And outputting the result of the execution. The temperature, humidity sensor may be in a predetermined position of the dust collection system 001. For example, it may be installed in the dust collector outlet 070, or may be installed in a duct portion connecting between the dust collector outlet 070 and the fan. In addition, the sensors may be installed at predetermined positions inside or outside the dust collecting system 001 in which the respective sensors can properly perform their functions. 4 is a block diagram of an embodiment of the controller 100 of the dust collection system 001 according to an embodiment of the present invention.

 As shown in FIG. 4, the dust collecting system 001 according to an embodiment further includes a fan motor driving unit 170, and the controller 100 may further include a proportional integral controller (PID) controller 100. The fan motor driving unit 170 can drive the fan motor in accordance with the output of the target airflow amount determination unit 160. [ The PID controller 161 is connected between the output of the target airflow determining unit 160 and the fan motor driver 170 to perform PID control.

 The fan motor driving unit 170 may PWM (Pulse Width Modulation) the fan motor driving unit 170 according to an output of the target airflow determining unit 160 to drive the fan motor 081. For example, the target airflow determining unit 160 may be a fan motor driving current.

 PID control is a known technique in which an output value of a target to be controlled is measured and an error is calculated by comparing the output value with a reference value or a setpoint to be desired, And calculates a control value necessary for the control. The PID controller 161 of the dust collecting system 001 uses the output value of the object to be controlled as the current fan motor purge air amount or the fan motor drive current 700 and outputs the reference value to the target air flow rate determination unit 160. [ The fan motor driving unit 170 can be controlled to reach the reference value as soon as possible through the PID control. The PID controller 161 of the dust collection system 001 can maximize the efficiency of the dust collection system 001 by allowing the fan motor to reach the target air volume of the fan motor 081 as soon as possible. FIG. 8 is a block diagram of another embodiment of the controller 100 of the dust collection system 001 according to the example.

 5, the operating state variable 110 of the dust collecting system 001 according to an embodiment includes a second operating state variable 180, and the dust collecting system 001 includes a second operating state variable 180, The operation state sensor 200, the second storage unit 210, and the exhaustion determination unit 230. [

 The second operating state variable 180 may include the dust collector inlet 020 and the dust collector differential pressure 190 which is the differential pressure between the dust collector outlet 070 as one variable. The second operation state sensor 200 can sense the operation state of the second operation state variable 180 (130). The second storage unit 210 may store the second operation state data 220 for the second operation state variable 180 (130) from the second operation state sensor 200. The exhaust emission determining unit 230 can determine whether or not the air jet injector 040 is exhausted based on a value obtained by comparing the reference differential pressure threshold value and the current dust collector pressure 190.

 As described above, the conventional filter dust collector exhausts the air jet in spite of the fact that dust is not sufficiently collected in the dust collector of the filter dust collector, resulting in an unnecessary cost of operating the filter dust collector. In order to solve this problem, the exhaust emission determining unit 230 of the dust collecting system 001 according to an embodiment can efficiently exhaust the air jet by selecting a criterion for determining whether to exhaust the exhaust gas.

 5, the dust removal determination unit 230 receives the present dust separator pressure 190 from the second storage unit 210 directly or through the second operating state sensor 200 and compares the present dust pressure difference 190 with the reference differential pressure threshold. The exhaust emission determining unit 230 may generate a signal for determining to exhaust the air jet when the current dust collector pressure 190 is equal to or greater than the reference differential pressure threshold as a result of comparison according to an aspect. For example, the dust removal determination unit 230 may input a current detector differential pressure 190 and a reference differential pressure threshold to the comparator and output a logic value 0 if the output value is 0 or a logical value 1 otherwise.

 According to another aspect, the exhaust emission determination unit 230 may generate a signal for determining to exhaust the air jet when the comparison value of the reference differential pressure threshold and the current dust collector differential pressure 190 is within a predetermined range. This can be achieved by configuring two comparators in series on a circuit or by using a microprocessor.

 The reference differential pressure threshold value may be a value preset by the exhaustion determination unit 230 based on the accumulated experience of the operator of the dust collection system 001 according to an aspect. The reference differential pressure threshold is a graph of the second operating state data 220 received from the second operating state sensor 200 for a predetermined period of time, the number of air jet discharging times, or the efficiency of the dust collecting system 001, And may be a result of analyzing through the microprocessor or through a microprocessor. FIG. 6 illustrates an example of the exhaustion determination unit 230 and the first exhaustion count counter 241 of the dust collection system 001 according to an embodiment. FIG.

 As shown in FIG. 6, the dust collection system 001 according to an embodiment further includes a first exhaustion count counter 241, and a second operation state variable 180 (130) Further comprising at least one or more variables selected from the group consisting of the number of the dust collectors (010), temperature, humidity, dust collector inlet (020) pressure, dust collector outlet (070) pressure, stack (090) (230) may include a depletion timing determination unit (240).

The first discharging count counter 241 may count the number of discharging discharges which is the number of times that the air jet has exhausted the bag filter 050 (bag filter) for a predetermined period. The exhaustion timing determination unit 240 includes a machine learning algorithm that receives the second operation state variables 180 and 130 and outputs the exhaustion state of the air jet injector 040. The second operation state data 220 ) Can be used to minimize the number of times of extinguishing to determine the timing of air jet evacuation.

 The machine learning algorithm to be used in the exhaustion-timing determining unit 240 may be based on the type of the operating state variable 110 selected by the input of the exhaustion-timing determining unit 240 as described in the description of the target airflow- The appropriate machine learning algorithm can be selected according to the characteristics.

For example, operation status data is collected through sensors, and dust collection data is collected as a target function for optimization, and collected according to each dust collection system (001) specification that is proved to have a relatively high efficiency. The machine learning algorithm is learned based on the collected data. In this case, the machine learning algorithm is the domain data as the input of the operation state data, and whether or not the exhaustion is to be performed at the current time is outputted. The optimization target function is defined as the direction in which the number of times of exhaustion in each domain data is minimized do. Through this learning, the coefficients of the neural network node can be defined. Meanwhile, the dust removal determination unit 230 of the dust collection system 001 according to an embodiment determines whether or not the air jet is exhausted based on a result of comparing the dust separator pressure difference 190 with the reference differential pressure threshold according to an aspect . When the signal is determined to match the air jet desorption timing determined by the discharge timing determination unit 240 based on the comparison result between the dust separator differential pressure 190 and the reference differential pressure threshold value, It is possible to determine whether or not the air jet is exhausted based on the result of comparison between the reference differential pressure threshold value and the reference differential pressure threshold value. If the two results do not coincide with each other, the exhaust emission determination unit 230 may be programmed to exhaust the air jet injector 040 at the air jet exhaustion timing determined by the exhaustion timing determination unit 240. Or the two types of air jet exhaustion determination methods may be selectively programmed.

 Or the exhaust emission determining unit 230 determines whether or not the air jet is exhausted based on the comparison result between the particulate filter 190 and the reference differential pressure threshold according to another aspect, The operator may be programmed to determine whether or not the air jet is to be exhausted if the operator confirms that the air jet is to be exhausted. Figure 7 is a graph showing the relationship between the controller 100 of the dust collecting system 001 and the second exhaustion count And a counter 250 according to an aspect of the present invention.

 As shown in FIG. 7, the dust collection system 001 according to an embodiment may further include a second discharge count counter 250, and the discharge pattern determiner 230 may include a discharge pattern correction unit . The second discharging count counter (counter) 250 may count the number of discharging discharges, which is the number of times the air jet has exhausted the bag filter 050 (bag filter) during a predetermined period. The jumping-off part 260 upon exhaustion analyzes a trend of the number of times of exhaustion counts counted by the second operation state data 220 and the second exhaustion number counter 250 of the second storage part 210, Can be corrected.

The jumping-off part 260 upon exhaustion can analyze the above-described trends in the form of a graph or correct the exhaustion timing of the air jet on the basis of the results calculated using a predetermined analysis program. For example, if the temperature is too high or the humidity is too high, the air jet may be predicted to advance the time of exhaustion to correct the air jet ejection time. That is, the result of analyzing the data of the operating state variable 110 of the dust collecting system 001 on the result of the air jet desorption determined based on the value obtained by comparing the reference differential pressure threshold value and the current dust collector pressure 190, Correction of the viewpoint can minimize the number of times of exhaustion as much as possible while considering the operating environment of the dust collection system (001).

 8 is a block diagram of a dust collection system control device 002 according to an embodiment.

The dust collecting system control device 002 according to the embodiment is connected to the dust collector inlet 020 through the duct and the hood 010 installed near the dust source, a dust collector 030 including a bag filter for injecting gas and an air jet injector for exhausting the bag filter 050 and a dust rejection unit 060 for collecting dust separated by filtering, A stack 090 connected to the dust collector outlet through a duct and connected to the outlet of the fan and the fan driven by the fan motor 081 and at least one sensor for sensing the operating state for each of the above- And is a control device applied to a dust collecting system including a driving state sensor unit. The apparatus for controlling dust collection system according to one embodiment of the present invention may include an operation state data collection unit 310, a dust removal determination unit 320, and a target air flow rate determination unit 330. The operation state data collection unit 310 can collect the operation state data for the operation state variable 300 of the dust collection system from the operation state sensor unit. The exhaust emission determination unit 320 can determine whether the air jet injector 040 is exhausted or not based on the operation state data and output the exhausted state. The target air flow rate determination unit 330 can determine the target air flow rate by driving the fan motor 081 based on the operation state data.

The dust collecting system can use the pulse jet type exhausting method as the exhausting method. In order to minimize the operation cost of the dust collecting system by minimizing the number of times of exhausting dust because the impact jet type exhausting method has good efficiency of dust collecting and processing, It is possible to determine whether or not to exhaust the air jet injector 040 by using the first operation state data received from the data collecting unit 350, thereby minimizing the number of times of exhaustion.

 The target air flow rate of the initially set fan motor (081) may be changed over time depending on the installation conditions, the kind of the exhaust facilities, the kind of pollutant, the application, and the like. In addition, since the conventional filter dust collector does not reflect the operation state of the other filter dust collectors, the dust collecting system according to the embodiment of the present invention is designed to increase the efficiency of the dust collecting system in order to reflect various factors as described above, So that the target air volume of the motor 081 can be determined.

 In order to reduce the operating cost of the dust collecting system and increase the efficiency of the dust collecting system, the dust removal determining unit 320 and the target airflow determining unit 330 of the dust collecting system control unit 002 according to an embodiment may include means To solve the problem. 9 is a flowchart illustrating an operation of the dust collecting system control apparatus according to an embodiment of the present invention when the first operation state variable 340, the first operation state data collection unit 350, FIG.

As shown in FIG. 9, in one embodiment, the operating state variable 300 of the dust collecting system control device 002 includes a first operating state variable 340. The operation state data collection unit 310 includes a first operation state data collection unit 350. The target air flow rate determination unit 330 includes a machine learning algorithm that receives the first operating state variable 340 and outputs the air flow rate of the fan motor 081. The target air flow rate determination unit 330 uses the first operating state data to optimize So that the target air flow rate of the fan motor 081 can be determined.

 The first operating state variable 340 includes the number of open hoods 010, the difference between the dust collector inlet 020 and the dust collector outlet 070, and the indoor dust concentration as variables. In addition, the first operating state variable 340 is a function of the temperature, humidity, the pressure of the dust collector outlet 070, the fan motor driving current 700, the purge airflow of the stack 090, And may further include at least one or more variables. The first operation state data collection unit 350 stores the first operation state data for the first operation state variable 340.

 The first operating state variable is a variable used to determine the target air flow rate, and is a variable that reflects the dust concentration difference between the inlet and outlet of the dust collector, or the pressure difference between the dust collector inlet 020 and the outlet, The number of open hoods 010, the pressure difference between the dust collector inlet 020 and the dust collector outlet 070, and the indoor dust concentration as main parameters. Since the differential pressure of the dust collector is proportional to the number of the open hoods 010 or the indoor dust concentration, the number of open hoods 010, the differential pressure between the dust collector inlet 020 and the dust collector outlet 070, 081) can be a main variable for determining the target air flow rate.

 At least one of the first operating state variable temperature, humidity, the pressure of the dust collector outlet 070, the fan motor driving current 700, the purge airflow of the stack 090 (stack) The above parameters can be further used to determine the target air flow rate.

 The first operating state variable of the dust collecting system control device 002 according to an embodiment is not limited to the above-described variables but may include other variables reflecting the operating state.

As shown in FIG. 1, the dust collecting system according to an embodiment of the present invention includes a number of open hoods 010 for the first operating state variable, a differential pressure between the dust collector inlet 020 and the dust collector outlet 070, A sensor for sensing the state, temperature, humidity, the pressure of the dust collector outlet 070, the fan motor driving current 700, and the purge air volume of the stack 090 (stack), respectively. The sensor that senses each operating state variable 300 may include an analog to digital converter that includes means for sensing the respective operating state and may convert the sensed operating state to a digital signal.

 The first operation state data collection unit 350 stores the first operation state data for the first operation state variable 340. The first operation state data collecting unit 350 according to an aspect may include communication means such as short-range wireless communication to directly receive and store the first operation state data from the first operation state sensor. The first operation state data collection unit 350 according to another aspect may be connected to the first operation state sensor on a circuit to receive and store the first operation state data from the first operation state sensor on a wire.

 The target air flow rate determiner 330 may analyze the first operating state data received from the first operating state sensor according to an aspect of the present invention to determine a target air flow rate capable of maximizing the efficiency of the dust collecting system. For example, the efficiency of the dust collection system for each variable of the first operating state variable 340 may be analyzed and output in each graph, so that the target air volume for achieving the target efficiency can be set automatically or manually.

 The target air flow rate determination unit 330 includes a machine learning algorithm for inputting the first operation state variable 340 and outputting the fan motor 081 air volume using the first operation state data according to another aspect, It is possible to determine the target air flow rate of the fan motor 081 by learning to be optimized for the dust concentration.

 The dust collection system control device 002 according to an embodiment can use an appropriate algorithm in the above-described machine learning algorithm according to the accuracy, the learning time, the linearity, and the number of parameters. The indoor dust concentration, the temperature, the humidity, and the pressure of the dust collector outlet (070) are inputted as the input, and the indoor dust And outputting the target air flow rate of the fan motor 081 so as to be optimized for the concentration. In this case, there are six parameters, which require relatively high accuracy and less learning time, and the linearity between parameters is not high, so that machine learning algorithms such as decision trees, support vector computers, and neural networks can be used. In addition, the target air flow rate can be determined using an appropriate machine learning algorithm according to the type and number of the operating state variables 300 to be used. FIG. 10 is a block diagram of an embodiment of a PID controller of a dust collection system control apparatus according to an embodiment.

 As shown in FIG. 10, the apparatus for controlling dust collection system according to an embodiment includes:

And a fan motor driving unit for driving the fan motor (081) in accordance with the output of the target airflow determining unit (330). The dust collecting system further includes a PID controller (360). The PID controller 360 is connected between the output of the target airflow determining unit 330 and the fan motor driving unit to control the PID (proportional integral ratio).

 The fan motor driving unit may PWM (Pulse Width Modulation) the fan motor driving unit according to an output of the target airflow determining unit 330 to drive the fan motor 081. For example, the target airflow determining unit 330 may be a fan motor driving current.

 PID control is a known technique in which an output value of a target to be controlled is measured and an error is calculated by comparing the output value with a reference value or a setpoint to be desired, And calculates a control value necessary for the control. The PID controller 360 of the dust collecting system controller 002 according to an exemplary embodiment uses the output value of the target to be controlled as the current fan motor purge air amount or the fan motor drive current 700 and outputs the reference value to the target air flow rate determiner The fan motor driving unit can be controlled so as to reach the reference value as soon as possible through the PID control with the output of the fan motor 330. [ In the dust collection system control device 002, the PID control unit 360 controls the dust collecting system control unit 360 so that the air volume produced by the fan driven by the fan motor 081 reaches the target air volume of the fan motor 081 as soon as possible, 11 is a graph showing the relationship between the second operation state variable 370 of the dust collection system control device 002 and the second operation state data 370 of the second operation state data collection unit 380 according to the embodiment. And FIG.

 11, the operation state variable 300 of the dust collection system control device 002 according to an embodiment includes a second operation state variable 370, 2 operation state data collection unit 380. The exhaust emission determination unit 320 determines whether or not the air jet injector 040 is exhausted based on a value obtained by comparing the reference differential pressure threshold value with the current dust collector differential pressure.

 The second operating state variable 370 includes the dust separator differential pressure which is the differential pressure between the dust collector inlet 020 and the dust collector outlet 070 as one variable. The second operation state data collection unit 380 stores the second operation state data for the second operation state variable 370 from the operation state sensor.

 As described above, the conventional filter dust collector exhausts the air jet in spite of the fact that dust is not sufficiently collected in the dust collector of the filter dust collector, resulting in an unnecessary cost of operating the filter dust collector. In order to solve this problem, the dust removal determination unit 320 of the dust collection system control device 002 according to an embodiment can efficiently exhaust the air jet by selecting a criterion for determining the dust exhaustion.

 11, the dust removal determination unit 320 receives the present dust separator pressure directly from the second operation status sensor or from the second operation status data collection unit 380 and compares it with the reference differential pressure threshold. The exhaust emission determining unit 320 may generate a signal for determining to exhaust the air jet when the current dust collector differential pressure is equal to or greater than the reference differential pressure threshold as a result of comparison according to one aspect. For example, the dust removal determination unit 320 may input the dust collector differential pressure and the reference differential pressure threshold to the comparator and output a logic value 0 if the output value is 0 or a logical value 1 if the output value is 0 or more.

 According to another aspect, the exhaust emission determination unit 320 may generate a signal for determining to exhaust the air jet when the comparison value of the reference differential pressure threshold and the present dust collector differential pressure is within a predetermined range. This can be achieved by configuring two comparators in series on a circuit or by using a microprocessor.

 The reference differential pressure threshold value may be a value preset by the exhaust emission determination unit 320 based on the accumulated experience of the operator of the dust collection system according to an aspect. The reference differential pressure threshold is determined by analyzing the second operating state data and the number of air jet discharging times or the efficiency of the dust collecting system received from the second operating state sensor for a predetermined period according to another aspect or through the microprocessor FIG. 12 is a block diagram of an exhaust emission determining unit 320 of the dust collecting system control apparatus according to an embodiment of the present invention. Referring to FIG.

 As shown in FIG. 12, the dust collection system control device 002 according to an embodiment further includes a first exhaustion count counter 390, and the exhaust emission determination unit 320 includes a depletion timing determination unit 400 ). The second operating state variable 370 also includes the number of open hoods 010, temperature, humidity, dust collector inlet 020 pressure, dust collector outlet 070 pressure, stack 090 exhaust dust concentration, fan motor drive current 700 ). ≪ / RTI >

1 The discharging count counter counts the number of times the air jet discharges the bag filter 050 (bag filter) during a predetermined period. The exhaustion-timing determining unit 400 includes a machine learning algorithm that receives the second operating state variable 370 as input and determines whether the air jet injector 040 is exhausted or not, So that the air jet exhaustion timing can be determined.

 The machine learning algorithm to be used in the exhaustion-timing determining unit 400 can select an appropriate machine learning algorithm according to the type and characteristics of the operation state parameter 300 selected as the input of the exhaustion-timing determining unit 400.

 Meanwhile, the dust removal determination unit 320 of the dust collection system control apparatus according to an embodiment may determine whether or not the air jet is exhausted based on a result of comparing the dust separator pressure difference with the reference differential pressure threshold according to an aspect have. When the signal is determined to match the air jet evacuation timing determined by the evacuation timing determiner 400 based on the comparison result between the dust separator differential pressure and the reference differential pressure threshold, the difference between the dust separator pressure and the reference differential pressure threshold is compared Based on the result, whether or not the air jet is exhausted can be determined according to the determination result. If the two results do not match, the exhaust emission determination unit 320 may be programmed to exhaust the air jet injector 040 at the air jet exhaustion timing determined by the exhaustion timing determination unit 400. Alternatively, the exhaust emission determination unit 320 may be programmed to be used as one of two types of air jet exhaustion determination methods.

 Or the exhaust emission determining unit 320 determines whether or not the air jet is exhausted based on the comparison result of the dust separator differential pressure and the reference differential pressure threshold according to another aspect, And may be programmed to determine whether or not the air jet is exhausted when the air jet is selected to be exhausted or not. FIG. 13 is a diagram illustrating another aspect of the exhaust emission determination unit 320 of the dust collecting system control device 002 according to the embodiment. Fig.

 As shown in FIG. 13, the dust collecting system control device 002 according to an embodiment further includes a second exhaustion count counter 410, and the exhaust emission determination unit 320 includes a jumping- ). The second discharging count counter 410 counts the number of times of discharging the bag filter 050 (bag filter) during the preset period. The jumping-off part 420 at the time of draining can analyze the trend of the second driving-state data of the second driving-state data collection part 380 and the number of times of exhaustion counts counted by the number-of- .

 The jumping-off part 420 in the exhausting operation may analyze the above-described trends in the form of a graph or correct the exhaust timing of the air jet on the basis of the result of calculation using a predetermined analysis program. For example, if the temperature is too high or the humidity is too high, the air jet may be predicted to advance the time of exhaustion to correct the air jet ejection time. In other words, correcting the exhaustion point by reflecting the result of analyzing the data of the operation state variable (300) of the dust collection system on the result of the air jet exhaustion determined based on the comparison of the reference differential pressure threshold value and the current dust collector pressure, It is possible to minimize the number of exhaustion as much as possible while considering the operating environment of the collection system. The operation state sensor unit of the dust collection system control device 002 according to an embodiment may be connected via Ethernet according to an aspect.

 Accordingly, the operation state sensor unit can transmit and receive information on the operation state data for each operation state variable 300 between the respective sensors in real time. Accordingly, the dust collection system control device (002) according to the embodiment can provide information on the target air flow rate determination of the fan motor (081) and the time of exhaustion of the air jet. In addition to this role, data can be exchanged between the sensors to determine the current operating status of the dust collection system. Furthermore, it is possible to control the operation state of the dust collecting system to be in an optimal state based on the detected current operating state.

 In order to control the operation state as described above, each sensor of the operation state sensor unit may be equipped with means such as a wireless transmitting / receiving chip, a microcontroller, etc. according to an aspect. In addition, the dust collection system control device 002 according to one embodiment can use predetermined platform software for this purpose. Or the dust collection system to which the dust collection system control device 002 is applied may be able to control the operation state by using the platform software which is conventionally used.

 For example, the temperature is too high. The dust collection system may include a temperature control device such as a temperature sensor or a cooler. The control unit of the dust collection system receives temperature information from the operation state sensor unit via Ethernet in real time, compares the temperature information with a preset reference temperature, Signal to the chiller. The cooler can start the drive by receiving the temperature control signal and maintain the optimum operation state by driving the cooler or the on-state until the temperature data received from the operation state sensor coincides with the reference temperature. Alternatively, the control unit of the dust collection system may increase or decrease the number of open hoods 010 by comparing the indoor dust concentration with the reference indoor dust concentration in real time. Also, the controller of the dust collection system can adjust the humidity of the dust collection system by generating a signal for controlling the damp by comparing the reference humidity and the humidity state data received from the operation state sensor unit in real time.

 Also, the dust collection system control device 002 according to one embodiment may include a driving state control unit. The operation state control unit may perform the role of the control unit of the above-described dust collection system.

 The operation state sensor unit may be an Internet of things (IoT) according to another state. Accordingly, the dust collection system control unit 002 according to the embodiment controls the number of open hoods 010, temperature, humidity, and the like based on the signals sensed by the operation state sensor unit, The efficiency of operation of the device 002 can be optimized. Accordingly, the operation status sensor unit can use existing WiFi, 3G (Generation) / 4G (4 Generation), LTE (Long Term Evolution), Bluetooth or the like as wired or wireless communication or network devices in addition to Ethernet FIG. 14 is a block diagram of an embodiment of a first rainfall learning data classifier 430 of the dust collection system control device 002 according to an embodiment.

 As shown in FIG. 14, the apparatus 600 for controlling dust collection system according to an embodiment may further include a first rainfall training data classifier 430.

 The first rainfall learning data classifier 430 is connected between the output of the first operation state data collector 350 and the target wind amount determiner 330 to determine the influences on the target wind speed determination among the first operation state variables 340 This high variable can be extracted.

 The first rainfall training data classifier 430 can extract a variable having a strong influence on the target wind volume determination using various algorithms. The reason for extracting such influential variables is to calculate the target air volume more timely. The computation time of the computer may take an excessive amount of time to learn by using the first operating state data in the target airflow determining unit 330. [ Accordingly, the first good learning data classifier 430 can use a predetermined algorithm to reduce the heavy computation time. It is possible to remove unnecessary elements, that is, unnecessary first operating state variables 340, by classifying the results of the first operating state variables, that is, factors that are not related to indoor dust concentration, using a predetermined algorithm.

 In order to achieve the above object, the first rainfall training data classifier 430 can find the variables which are advantageous factors in the target wind volume calculation by using the genetic algorithm according to one aspect. In addition, other systems such as a neural network may be used in combination.

 Accordingly, the first superior learning data classifier 430 classifies variables that are advantageous for obtaining an accurate result by using a predetermined algorithm or a combination of predetermined algorithms, and provides them to the target wind amount determiner 330 to increase the efficiency of data processing, Time can be reduced, and as a result, the target air volume can be determined in a timely manner, so that the dust collection system control device 002 can obtain high accuracy in performing the task.

 In addition, the first rainfall learning data classifier 430 receives the first operation state variable 340 and the first operation state data extracted as shown in FIG. 14 according to another aspect, 340 as the input data to the target airflow determining unit 330 as input data. FIG. 15 is a block diagram of an exemplary embodiment of the second rainfall learning data classifier 440 of the dust capture system control apparatus according to an embodiment of the present invention.

 As shown in FIG. 15, the dust collection system control device 002 may further include a second rich learning data classification unit 440. The second well learning data classification unit 440 is connected between the output of the second operation state data collection unit 380 and the depression determining unit 320 to determine whether the second operation state variable 370 has a high influence Variables can be extracted.

 The second well learning data classifier 440 can extract variables with high influences at the time of exhaustion using various algorithms. The calculation time of the computer may take an excessive amount of time to learn by using the second driving state data in the exhaustion timing determination unit 400. [ Therefore, the second good learning data classifier 440 can use a predetermined algorithm to reduce the heavy computing time. By using a predetermined algorithm, it is possible to classify factors that are not related to the number of times that the air jet is exhausted for a preset period which is the output of the second operation state variable, that is, the output of the first exhaustion number counter 390, 2 < / RTI >

 In order to achieve the above-described goal, the second well learning data classifier 440 can use the genetic algorithm according to an aspect of the present invention to find variables that are favorable factors for determining the burnout timing. The second well learning data classification unit 440 may use a mixture of systems such as a neural network, for example, in addition to the genetic algorithm according to another aspect.

 Accordingly, in the second superior learning data classifier 440, variables favorable for obtaining an accurate result by a predetermined algorithm or a combination of predetermined algorithms are culled out and provided to the debubbing-time determiner 400, thereby improving efficiency of data processing, The time can be reduced, and as a result, it is possible to determine the timing of exhaustion in a timely manner, so that the dust collection system control device 002 can obtain high accuracy in performing the task.

In addition, the second superior learning data classifier 440 may classify the extracted second operating state variable 370 by receiving the extracted second operating state variable 370 and second operating state data as shown in FIG. 15 according to another aspect 370 to the target air flow rate determination unit 330 as inputs.

 While the present invention has been described in connection with what is presently considered to be practical exemplary embodiments, it is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, It is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, is intended to cover various modifications and similarities. Accordingly, the scope of the present invention should be construed as being limited to the embodiments described, and it is intended that the scope of the present invention encompasses not only the following claims, but also equivalents thereto.

 The present invention is industrially applicable in the field of dust collecting technology, specifically filtration and dust collecting technology using a pulse-jet cleaning method.

Dust collection system: 001
Dust collection system control device: 002
Open hood number sensor: 003
Dust collector inlet sensor: 004
Dust collector inlet sensor: 005
Dust collector differential pressure sensor: 006
Temperature sensor: 007
Humidity sensor: 008
Purge air flow sensor on the stack: 500
Stack discharge Dust concentration: 550
Indoor dust concentration sensor: 600
Fan motor drive current: 700
Hood: 010
Dust collector inlet: 020
Dust collector: 030
Air Jet Injector: 040
Bag filter: 050
Refuse to dust: 060
Dust collector outlets: 070
Fans: 080
Fan motor: 081
Stack: 090
Control section: 100
Operating state variable: 110
First operating state variable: 120
Second operating state sensor: 130
First storage unit: 140
First operation state data: 150
Target air volume determination section: 160
PID control section: 161
Fan Motor Drive: 170
Second operating state variable: 180
Dust Collector Foreclosures: 190
Second operating state sensor: 200
Second storage section 210
Second operating state data: 220
Exhaustion determination section: 230
Exhaustion point determination part: 240
First Exhaustion Count Counter: 241
Second Exhaustion Count Counter: 250
Jumbo government when draining: 260
Operating state variable: 300
Operation state data collection section: 310
Exhaustion determination section: 320
Target airflow determining section: 330
First operating state variable: 340
The first operation state data collection unit 350: 350
PID control unit: 360
Second operating state variable 370: 370
Second operation state data collection section: 380
First Exhaustion Count Counter: 390
Exhaustion point determination part: 400
Second Exhaustion Count Counter: 410
Jumbo government during burnout: 420
First well learning data classification section 430
Second Excellent Learning Data Classification Section: 440

Claims (15)

A hood installed near the dust source; The hood is connected to the dust collector inlet through a duct, and is provided with a bag filter, an air jet injector for spraying gas to exhaust the bag filter, and a dust collector for collecting dust separated by filtering. A dust collector; A fan connected to the dust collector outlet through a duct and driven by a fan motor; A stack connected to the outlet of the fan, the dust collection system comprising:
A controller for determining whether or not the air jet injector is exhausted and the fan motor target air flow rate according to operating state variables of the dust collecting system;
Wherein the dust collecting system comprises: The method according to claim 1,
The operating state variable is:
The number of open hoods, the pressure difference between the dust collector inlet and the dust collector outlet, and the indoor dust concentration as variables
A first operating state variable further comprising at least one of a temperature, a humidity, a pressure of a dust collector outlet, a fan motor driving current, a purge airflow of a stack, and a dust collector design parameter,
The dust collection system is:
And a first operation state sensor for sensing an operation state of the first operation state variable,
The control unit includes:
A first storage unit for storing first operation state data for a first operation state variable from a first operation state sensor;
A target air flow rate determination unit for determining a target air flow rate of the fan motor by learning to optimize the indoor dust concentration using the first operating state data and a machine learning algorithm for inputting a first operating state variable and outputting a fan motor air flow rate, ;
Wherein the dust collecting system comprises:
3. The method of claim 2,
The dust collection system is:
And a fan motor driving unit for driving the fan motor in accordance with the output of the target airflow determining unit,
The control unit includes:
A PID control unit connected between the output of the target airflow determining unit and the fan motor driving unit to perform proportional integral calculator (PID) control;
Further comprising: a dust collecting system.
4. The method according to any one of claims 1 to 3,
Wherein the operating state variable includes a second operating state variable including a dust collector inlet pressure and a dust separator pressure difference which is a pressure difference between the outlet of the dust collector as one variable,
The dust collection system is:
And a second operating state sensor for detecting an operating state of the second operating state variable,
The control unit includes:
A second storage unit for storing second operation state data for a second operation state variable from a second operation state sensor,
A dust removal determining unit that determines whether or not the air jet sprayer is exhausted based on a value obtained by comparing a reference differential pressure threshold value and a current dust collector pressure;
Wherein the dust collecting system comprises:
5. The method of claim 4,
The dust collection system is:
And a first discharging count counter for counting the number of discharging discharges, which is the number of times the air jet has exhausted the bag filter during a predetermined period of time,
The second operating state variable further includes at least one of a number of open hoods, a temperature, a humidity, a dust collector inlet pressure, a dust collector outlet pressure, a stack exhaust dust concentration, and a fan motor driving current,
The exhaustion determination section includes:
And a machine learning algorithm in which the second operation state variable is input and the air jet injector is exhausted or not, and the second learning state data is used to minimize the number of exhaustion times, thereby determining an air jet exhaustion timing A time point determination unit;
Wherein the dust collecting system comprises:
5. The system of claim 4, wherein the dust collection system comprises:
And a second discharging count counter for counting the number of discharging times, which is the number of times that the air jet has exhausted the bag filter during a predetermined period of time,
The exhaustion determination section includes:
A jumping-off jumper configured to analyze a trend of the number of times of exhaustion counted by the second operation state data and the second exhaustion count counter of the second storage unit to correct the exhaustion timing;
Wherein the dust collecting system comprises:
A hood installed near the dust source; The hood is connected to the dust collector inlet through a duct, and is provided with a bag filter, an air jet injector for spraying gas to exhaust the bag filter, and a dust collector for collecting dust separated by filtering. A dust collector; A fan connected to the dust collector outlet through a duct and driven by a fan motor; A control device for a dust collecting system, comprising: a stack connected to an outlet of a fan; and a driving state sensor part including at least one sensor for sensing a driving state of each of the components,
An operation state data collection unit for collecting operation state data on operation state variables of the dust collection system from the operation state sensor unit;
Determining whether the air jet injector is exhausted or not based on the driving state data, and outputting the determined result;
A target air flow rate determining section for determining a target air flow rate by driving the fan motor based on the operating state data;
Wherein the dust collecting system control device comprises:
8. The method of claim 7,
The operating state variable is:
The number of open hoods, the pressure difference between the dust collector inlet and the dust collector outlet, and the indoor dust concentration as variables
A first operating state variable further comprising at least one of a temperature, a humidity, a pressure of a dust collector outlet, a fan motor driving current, a purge airflow of a stack, and a dust collector design parameter,
The operation state data collecting unit includes:
And a first operation state data collection unit for storing the first operation state data for the first operation state variable from the operation state sensor,
The target air flow rate determination section includes:
And a machine learning algorithm in which the first operating state variable is input and the fan motor air flow rate is output, and the fan motor target air flow rate is determined by learning to optimize the indoor dust concentration using the first operating state data
Dust collection system control device.
9. The method of claim 8,
And a fan motor driving unit for driving the fan motor in accordance with the output of the target air flow rate determination unit,
The dust collection system control device comprises:
A PID control unit connected between the output of the target airflow determining unit and the fan motor driving unit to perform proportional integral calculator (PID) control;
Further comprising: a dust collection system control unit for controlling the dust collection system.
10. The method according to any one of claims 7 to 9,
And a second operating state variable including a dust separator differential pressure which is a differential pressure between the dust collector inlet and the dust collector outlet as one variable,
The operation state data collecting unit includes:
And a second operation state data collection unit for storing second operation state data for a second operation state variable from the operation state sensor,
The exhaustion determination section includes:
Determining whether or not the air jet injector is exhausted based on a value obtained by comparing the reference differential pressure threshold value and the present dust collector differential pressure
Dust collection system control device.
11. The method of claim 10,
The dust collection system control device comprises:
And a first discharging count counter for counting the number of discharging discharges, which is the number of times the air jet has exhausted the bag filter during a predetermined period of time,
The second operating state variable further includes at least one of a number of open hoods, a temperature, a humidity, a dust collector inlet pressure, a dust collector outlet pressure, a stack exhaust dust concentration, and a fan motor driving current,
The exhaustion determination section includes:
And a machine learning algorithm in which the second operation state variable is input and the air jet injector is exhausted or not, and the second learning state data is used to minimize the number of exhaustion times, thereby determining an air jet exhaustion timing A time point determination unit;
Wherein the dust collecting system control device comprises:
11. The system of claim 10, wherein the dust collection system control device comprises:
And a second discharging count counter for counting the number of discharging times, which is the number of times that the air jet has exhausted the bag filter during a predetermined period of time,
The exhaustion determination section includes:
A jumping-off jumper configured to analyze a trend of the number of times of exhaustion counts counted by the second operation state data of the second operation state data collecting unit and the number of exhaustion times counter to correct the exhaustion timing;
Wherein the dust collecting system control device comprises:
10. The dust collection system control apparatus according to any one of claims 7 to 9, wherein the operation state sensor unit is connected via Ethernet.
10. The system according to claim 9, wherein the dust collection system control device comprises:
And a second air-fuel ratio control unit connected between the output of the first operating state data collecting unit and the target air-
A first excellent learning data classifier for extracting a variable having a high influence on the determination of the target air flow rate among the first operating state variables;
Further comprising: a dust collection system control unit for controlling the dust collection system.
12. The apparatus according to claim 11, wherein the dust collection system control apparatus comprises:
Connected between the output of the second operating state data collecting unit and the exhaust emission determining unit,
A second well learning data classifier for extracting a variable having a high influence on the determination of the exhaustion timing among the second operating state variables;
Further comprising: a dust collection system control unit for controlling the dust collection system.

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