Intelligent dust removal system and method for raw material conveying system

Abstract

The invention discloses an intelligent dust removal system and method for a raw material conveying system, solves the problems that an induced draft fan is started for a long time and the working state is not intelligent enough during dust removal in the prior art, and has the beneficial effects that the energy consumption of the raw material conveying system is reduced, and the good energy-saving effect is achieved. According to the specific scheme, the intelligent dust removal system of the raw material conveying system comprises a dust collection component, and the dust collection component comprises a dust collection cover installed between every two adjacent raw material conveying belts; the data acquisition part comprises a camera and a smoke dust sensor arranged in the dust collection cover; the camera, the smoke sensor, the valve and the induced draft fan are separately connected with the controller, the controller judges the opening and closing state of the dust suction inlet valve according to the working condition, collected by the camera, of the raw material conveying belt, and the smoke sensor obtains the smoke concentration of each dust collection hood and sends the smoke concentration to the controller; the controller adjusts the frequency of the induced draft fan according to the smoke concentration, collected by the smoke sensor, in the dust hood.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial raw material conveying and dust removal, and in particular to an intelligent dust removal system and method for a raw material conveying system. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] In industrial production, the raw material conveying system is a key link in material transportation. Smoke and dust are easily generated at the conveyor belt conversion nodes, which poses a serious threat to the on-site environment and the health of workers. Dust removal is required. The existing technology has the following problems: First, existing fans typically operate at a fixed frequency or with simple timing control, which makes it difficult to precisely control dust collection and fan operation based on the actual conditions of different material delivery nodes. This leads to numerous drawbacks: The fan remains on regardless of whether there is material passing through, causing the fan operating frequency to remain high and resulting in a large amount of unnecessary energy waste. Second, the fan operates at a fixed frequency and cannot dynamically adjust the air volume according to the actual amount of smoke and dust generated. This can neither guarantee a good dust removal effect nor achieve energy conservation. The existing system cannot monitor the status of raw material delivery in real time, making it difficult to finely control the dust collection and removal process. Third, some plans include a dust hood with a valve installed on it. The valve switch needs to be manually adjusted by the staff. The switch status of the dust suction port valve is not linked to the fan frequency, making it difficult to achieve the dual goals of accurate dust removal and energy saving. Summary of the Invention

[0004] In view of the shortcomings of the existing technology, the purpose of the present invention is to provide an intelligent dust removal system for a raw material conveying system, which can accurately identify the raw material conveying status, realize the precise switching of the dust suction port valve and the intelligent dynamic adjustment of the induced draft fan frequency, thereby improving the dust removal efficiency and reducing energy consumption.

[0005] In order to achieve the above object, the present invention is implemented through the following technical solutions: An intelligent dust removal system for a raw material conveying system includes a dust collecting component, the dust collecting component including a dust collecting hood installed between two adjacent raw material conveying belts, the dust collecting hood covering the end of the previous raw material conveying belt and the input end of the next raw material conveying belt, the dust collecting hood connected to a smoke duct, a valve is provided at the connection between each dust collecting hood and the smoke duct, i.e., the dust suction port, the smoke duct is connected to a dust collector, and the dust collector is connected to a chimney via an induced draft fan; A data acquisition component, comprising a camera and a smoke sensor disposed in the dust collecting hood; The controller, camera, smoke sensor, valve and induced draft fan are separately connected to the controller. The controller determines the switch state of the dust suction port valve according to the working conditions of the raw material conveyor belt collected by the camera. The smoke sensor obtains the smoke concentration at each dust collection hood and sends it to the controller. The controller adjusts the frequency of the induced draft fan according to the smoke concentration in the dust collection hood collected by the smoke sensor.

[0006] In the intelligent dust removal system of a raw material conveying system as described above, the controller receives image data of the raw materials at the raw material conveyor belt captured by the camera, processes the image data according to a pre-trained deep learning model and obtains image recognition results to judge the working condition of the raw material conveyor belt, and controls the actions of the valve and the induced draft fan according to the judged working condition of the raw material conveyor belt.

[0007] In the intelligent dust removal system for a raw material conveying system as described above, the controller can determine the working status of the corresponding raw material conveying belt based on the image data sent by the camera, including whether the raw material conveying belt is working or closed, and whether there is raw material being conveyed on the raw material conveying belt; If the raw material conveyor belt is in the closed state, the controller closes the valve at the dust suction port of the corresponding raw material conveyor belt; If the raw material conveyor belt is in operation and there is no raw material on the raw material conveyor belt, the controller closes the valve at the dust suction port of the corresponding raw material conveyor belt and turns off the induced draft fan; If the raw material conveyor belt is in operation and there is raw material on the raw material conveyor belt, the controller opens the valve at the dust suction port corresponding to the raw material conveyor belt and turns on the induced draft fan.

[0008] In the intelligent dust removal system of the raw material conveying system as described above, a mapping relationship between the smoke concentration in the dust hood and the frequency of the induced draft fan is established in the controller, and the controller gradually adjusts the frequency of the induced draft fan according to the smoke concentration in the dust hood.

[0009] In the intelligent dust removal system for a raw material conveying system as described above, the controller establishes a mapping relationship between the smoke concentration in the dust hood and the frequency of the induced draft fan based on the smoke sensor arranged in the dust hood.

[0010] In the intelligent dust removal system of the raw material conveying system as described above, after the controller receives the image data transmitted by the camera for a set time, the controller receives the data sent by the smoke sensor to obtain the dust concentration in the dust collecting hood to adjust the frequency of the induced draft fan.

[0011] In the intelligent dust removal system of the raw material conveying system as described above, the controller determines the following contents based on the established mapping relationship between the smoke concentration in the dust hood and the induced draft fan frequency: If the dust concentration in all dust hoods is less than the set value, the controller controls the induced draft fan to operate at the first frequency gear. If the dust concentration in some dust hoods is greater than the set value, the controller controls the induced draft fan to operate at the second frequency gear. If the dust concentration in all dust hoods is greater than the set value, the controller controls the induced draft fan to operate at the third frequency gear.

[0012] In the intelligent dust removal system of the raw material conveying system as described above, the camera is installed above the raw material conveying belt, the camera head is aimed at the raw material conveying belt, and the camera head is rotatable.

[0013] In a second aspect, the present invention further provides an intelligent dust removal method for a raw material conveying system, comprising the following contents: A dust collecting hood is provided between two adjacent raw material conveyor belts, the dust collecting hood covers the end of the previous raw material conveyor belt and the input end of the next raw material conveyor belt, and a smoke sensor is provided in the dust collecting hood; The dust collecting hood is connected to the smoke duct. A valve is installed at the connection between each dust collecting hood and the smoke duct, i.e., the dust suction port. The smoke duct is connected to the dust collector, and the dust collector is connected to the chimney through the induced draft fan. The smoke sensor obtains the smoke concentration at each dust hood and sends it to the controller. When the controller detects that the smoke concentration in one of the dust hoods is greater than the set value, the controller controls the corresponding valve and induced draft fan to open.

[0014] The intelligent dust removal method for a raw material conveying system as described above includes the following contents: A camera is set above the raw material conveyor belt. After the smoke sensor transmits data for a set time, the controller receives the raw material image data on the raw material conveyor belt sent by the camera and sends it to the controller; The controller processes the image data according to the pre-trained deep learning model and obtains image recognition results to judge the working condition of the raw material conveyor belt. The controller controls the action of the valve and induced draft fan according to the judged working condition of the raw material conveyor belt.

[0015] The beneficial effects of the present invention are as follows: 1) In the present invention, a dust collecting hood is arranged at a place where smoke and dust are easily generated, that is, between two adjacent raw material conveyor belts. A smoke sensor is arranged in the dust collecting hood. The smoke sensor can obtain the concentration of smoke and dust in the dust collecting hood and send it to the controller. The controller controls the opening of the corresponding valve and the induced draft fan according to the data sent by the smoke sensor, effectively avoiding excessive smoke and dust in the dust collecting hood, and realizing the opening of the valve and the induced draft fan according to the actual situation without manual operation, which is more efficient.

[0016] 2) The present invention is provided with a camera, which obtains image data of raw materials at the raw material conveyor belt and sends it to the controller. The controller adjusts the working status of the valve and the induced draft fan according to the working conditions at the raw material conveyor belt, so that the dust collection process is closely matched with the smoke concentration and the raw material transportation conditions, effectively improving the dust removal effect, avoiding the energy waste caused by the induced draft fan running for a long time at a fixed frequency, and significantly reducing the energy consumption of the raw material conveying system.

[0017] 3) The present invention realizes intelligent and automated control of the entire dust removal process without manual intervention, thereby improving production efficiency and system reliability. It is applicable to a variety of industrial raw material transportation scenarios, such as mining, metallurgy, building materials and other industries. It can achieve effective dust removal control for raw materials of different types and particle sizes, and has wide promotion and application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0019] Figure 1 Schematic diagram of an intelligent dust removal system for a raw material conveying system according to one or more embodiments of the present invention.

[0020] In the figure: the distances or sizes between parts are exaggerated to show the positions of various parts, and the schematic diagram is for reference only.

[0021] Among them: 1. Raw material conveyor belt; 2. Dust collection hood; 3. Valve; 4. Fume duct; 5. Dust collector; 6. Induced draft fan; 7. Chimney; 8. Camera; 9. Signal converter; 10. Computer host; 11. PLC controller; 12. Frequency converter. DETAILED DESCRIPTION

[0022] It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used in the present invention have the same meaning as commonly understood by those skilled in the art to which the present invention belongs.

[0023] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present invention. As used herein, unless otherwise clearly indicated in the present invention, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "include" and / or "comprising" are used in this specification, they indicate the presence of features, steps, operations, devices, components and / or their combinations; As introduced in the background technology, in the prior art, the induced draft fan is always turned on at the set power, resulting in high energy consumption and the inability to perform intelligent adjustment according to actual conditions. In order to solve the above technical problems, the present invention proposes an intelligent dust removal system for a raw material conveying system.

[0024] Example 1 In a typical embodiment of the present invention, referring to Figure 1 As shown, an intelligent dust removal system for a raw material conveying system includes a dust collection component, which includes a dust collection hood 2 installed between two adjacent raw material conveyor belts. The dust collection hood 2 covers the end of the previous raw material conveyor belt 1 and the input end of the next raw material conveyor belt. The dust collection hood 2 is connected to a smoke duct 4. A valve 3 is provided at the connection between each dust collection hood 2 and the smoke duct 4, i.e., at the dust suction port. The smoke duct 4 is connected to a dust collector 5, and the dust collector 5 is connected to a chimney 7 through an induced draft fan 6. Data collection component, the data collection component includes a smoke sensor and a camera 8 provided in the dust collecting cover 2; The controller, the smoke sensor, the camera 8, the valve 3 and the induced draft fan 6 are separately connected to the controller. The controller determines the switch state of the dust suction port valve according to the working conditions of the raw material conveyor belt collected by the camera. The smoke sensor obtains the smoke concentration at each dust hood 2 and sends it to the controller. The controller adjusts the frequency of the induced draft fan 6 according to the smoke concentration in the dust hood 2 collected by the smoke sensor.

[0025] Among them, the upper side of the dust hood 2 is conical, the middle and lower parts of the dust hood 2 are cylindrical, and the dust hood 2 is provided with an opening to connect with the two adjacent raw material conveyor belts 1; the smoke sensor adopts the existing dust sensor, which can obtain the concentration information of the smoke in the dust hood 2 and send it to the controller.

[0026] In this embodiment, in order to further achieve the control of the valve 3 in accordance with the working conditions of the raw material conveyor belt 1, the data acquisition component also includes a camera, which is installed above each raw material conveyor belt to obtain raw material image data at the raw material conveyor belt, and each camera is connected to the controller respectively.

[0027] Specifically, the camera uses an existing high-definition industrial camera 8, which has high resolution (1080p and above) and high frame rate (above 30 frames per second), and can clearly capture the working status of the raw material conveyor belt 1 and whether the raw materials exist. The lens of the high-definition industrial camera has a suitable focal length and viewing angle, and can cover the entire raw material conveyor belt area.

[0028] High-definition industrial cameras are equipped with a protective housing and mounting bracket. The protective housing protects the camera from harsh environmental factors such as dust and moisture. The mounting bracket should allow for flexible adjustment of the camera's angle and height to ensure optimal shooting angles. For example, a rotatable, retractable metal bracket made of stainless steel or aluminum alloy should be used. Additionally, auxiliary lighting devices such as LED light bars or infrared lamps are used in the material conveying area. LED light bars provide stable visible light illumination, while infrared lamps enable night vision in low-light or no-light conditions, ensuring continuous image acquisition.

[0029] It should be noted that the controller receives image data of the raw materials at the raw material conveyor belt collected by the camera and sends the collected image data to the controller. The controller processes the image data according to the pre-trained deep learning model and obtains image recognition results to judge the working condition of the raw material conveyor belt. The controller controls the action of the valve and the induced draft fan according to the judged working condition of the raw material conveyor belt.

[0030] Based on the image data sent by the camera, the controller can determine the working status of the corresponding raw material conveyor belt, including whether the raw material conveyor belt is working or closed, and whether there is any raw material being conveyed on the raw material conveyor belt.

[0031] The controller includes a PLC controller 11 and a host computer 10. Host computer 10 is equipped with a dedicated graphics processing unit (GPU) or a high-performance central processing unit (CPU). GPUs have powerful parallel computing capabilities, making them suitable for processing large amounts of image data. They can accelerate the execution of image recognition algorithms and efficiently process images. Host computer 10 also requires image recognition algorithm software, developed based on machine learning or deep learning algorithms. Machine learning algorithms can include support vector machines and random forests, while deep learning algorithms often use convolutional neural networks (CNNs), such as AlexNet, VGG, and ResNet. These algorithm software runs on the host computer and provides model training, parameter adjustment, and real-time image recognition capabilities. The storage device in host computer 10 is a high-capacity hard drive (such as a mechanical hard drive or solid-state drive) for storing training image data, trained model parameters, and intermediate calculation results. RAM (RAM) is also required to temporarily store the image data being processed. The RAM capacity should be sufficient (16GB or above) to ensure the efficient operation of the image recognition algorithm.

[0032] Computer host 10 includes a data analysis processor with high-performance computing capabilities for processing large amounts of image feature data. The processor should have a multi-core architecture (eight cores) to rapidly execute data analysis and algorithmic operations. Computer host 10 is installed with database software to store historical image data, the status of vacuum inlet valves at each node, and induced draft fan operating frequency data. The database can be a relational database (such as MySQL) or a non-relational database (such as MongoDB), offering large storage capacity and fast query capabilities to support long-term data storage and real-time retrieval.

[0033] The inverter 12 receives signals from the PLC controller and converts them into the voltage and frequency of the induced draft fan 6 motor, thereby changing the speed of the induced draft fan 6. The inverter 12 should have a wide speed regulation range (e.g., 0-50 Hz or wider), high-precision frequency control (frequency resolution of 0.01 Hz or higher), and good overload protection. The PLC controller 11 coordinates communication and control logic between the inverter 12 and other modules (the host computer 10). The PLC controller 11 can also be another microcontroller. The PLC controller 11 receives instructions from the host computer 10 and transmits them to the inverter 12. It also monitors the operating status of the inverter 12 and the induced draft fan 6, such as current, voltage, and speed, to ensure safe and stable operation of the system. The PLC controller 11 is used to open and close the vacuum inlet valve and transmits information received from sensors to the host computer.

[0034] In addition, the computer host 10 is also connected to the display screen, and the camera is connected to the computer host 10 via the signal converter 9.

[0035] The image recognition software is set in the host computer. The host computer, also known as the controller, processes the image data, including the following: X1. Grayscale the captured image, converting the color image to a grayscale image. This reduces the amount of data and simplifies subsequent calculations. Perform filtering to remove noise from the image. Select the appropriate filtering method based on the type of noise, such as Gaussian filtering for Gaussian noise or median filtering for salt and pepper noise. Gaussian filtering smoothes the image by taking a weighted average of each pixel and its neighborhood. Median filtering replaces the center pixel's value with the median value of its neighborhood.

[0036] X2. Use edge detection algorithms (such as the Canny operator) to extract edge features of the raw materials and the conveyor belt. The Canny operator determines edges by finding the maximum gradient value in the image. These edge features help determine whether there is raw material on the conveyor belt and the operating status of the conveyor belt.

[0037] X3. Mark the raw material conveyor belt based on whether there is raw material and the working status of the raw material conveyor belt to match the corresponding relationship between the vacuum port valve switch and the induced draft fan control information.

[0038] The extracted features are labeled into different categories, such as "the raw material conveyor belt is running and contains raw materials", "the raw material conveyor belt is running but has no raw materials", "the raw material conveyor belt is stopped", etc.

[0039] X4. Divide the dataset into training, validation, and test sets, generally in a ratio of 7:2:1. Use the training set to train the selected deep learning model (such as a deep convolutional neural network (CNN)). Use the backpropagation algorithm to continuously adjust the network weights, enabling the model to accurately classify different categories. During training, use the validation set to monitor model performance and prevent overfitting. Finally, use the test set to evaluate the model's final performance.

[0040] X5. Use fuzzy control to determine the range of the fuzzy set. For the number of valve openings, the fuzzy set can be defined as "low," "medium," and "high." For the induced draft fan operating frequency, the fuzzy set can be defined as "low" (first frequency range), "medium" (second frequency range), and "high" (third frequency range).

[0041] X6. Determine a first correspondence between the image features of the raw materials on the raw material conveyor belt, the image features of the raw material conveyor belt's operating state, and the vacuum port valve switch, namely: If the raw material conveyor belt is in the closed state, the controller closes the valve at the dust suction port of the corresponding raw material conveyor belt; If the raw material conveyor belt is in operation and there is no raw material on the raw material conveyor belt, the controller closes the valve at the dust suction port of the corresponding raw material conveyor belt and turns off the induced draft fan; If the raw material conveyor belt is in operation and there is raw material on the raw material conveyor belt, the controller opens the valve at the corresponding raw material conveyor belt dust suction port and turns on the induced draft fan; Determine the second corresponding relationship between each valve point and valve state and the induced draft fan frequency, that is, the mapping relationship between the smoke concentration in the dust hood and the induced draft fan frequency. The controller establishes the mapping relationship between the smoke concentration in the dust hood and the induced draft fan frequency based on the smoke sensor arranged in the dust hood: If the dust concentration in all dust hoods is less than the set value, the controller controls the induced draft fan to operate at the first frequency gear. If the dust concentration in some dust hoods is greater than the set value, the controller controls the induced draft fan to operate at the second frequency gear. If the dust concentration in all dust hoods is greater than the set value, the controller controls the induced draft fan to operate at the third frequency gear.

[0042] The system provided in this embodiment realizes the switching control of the valve through the camera, monitors the raw material conveyor belt area in real time, can accurately open or close the dust suction port valve, and detects the dust concentration at the dust collecting hood through the dust sensor to realize the control of the fan operating frequency so that the dust collection process is closely matched with the dust concentration and the raw material conveying situation, effectively improves the dust removal effect, reduces the pollution of the environment by the dust and the harm to the equipment and personnel by the dust, and dynamically adjusts the operating frequency of the induced draft fan according to the actual switching state of the dust suction port valve, avoids the energy waste caused by the induced draft fan running at a fixed frequency for a long time, significantly reduces the energy consumption of the raw material conveying system, has a good energy-saving effect, brings economic benefits to the enterprise, and also meets the requirements of sustainable development.

[0043] Example 2 This embodiment provides an intelligent dust removal method for a raw material conveying system, which uses the intelligent dust removal system for a raw material conveying system in Example 1 and includes the following contents: A dust collecting hood is provided between two adjacent raw material conveyor belts, the dust collecting hood covers the end of the previous raw material conveyor belt and the input end of the next raw material conveyor belt, and a smoke sensor is provided in the dust collecting hood; The dust collecting hood is connected to the smoke duct. A valve is installed at the connection between each dust collecting hood and the smoke duct, i.e., the dust suction port. The smoke duct is connected to the dust collector, and the dust collector is connected to the chimney through the induced draft fan. A camera is installed above the raw material conveyor belt. After the smoke sensor transmits data for a set time, the controller obtains the raw material image data at the raw material conveyor belt through the camera and sends it to the controller. In this way, the working status of the valve is determined by the working status of the raw material conveyor belt. The controller processes the image data according to the pre-trained deep learning model and obtains image recognition results to judge the working condition of the raw material conveyor belt. The controller controls the action of the valve and induced draft fan according to the judged working condition of the raw material conveyor belt.

[0044] Based on the image data sent by the camera, the controller can determine the working status of the corresponding raw material conveyor belt, including whether the raw material conveyor belt is working or closed, and whether there is raw material being conveyed on the raw material conveyor belt; If the raw material conveyor belt is in the closed state, the controller closes the valve at the dust suction port of the corresponding raw material conveyor belt; If the raw material conveyor belt is in operation and there is no raw material on the raw material conveyor belt, the controller closes the valve at the dust suction port of the corresponding raw material conveyor belt and turns off the induced draft fan; If the raw material conveyor belt is in operation and there is raw material on the raw material conveyor belt, the controller opens the valve at the dust suction port corresponding to the raw material conveyor belt and turns on the induced draft fan.

[0045] Finally, the smoke sensor obtains the smoke concentration at each dust hood and sends it to the controller. When the controller detects that the smoke concentration in one of the dust hoods is greater than the set value, the controller controls the corresponding valve and induced draft fan to open the induced draft fan operating frequency.

[0046] If the dust concentration in all dust hoods is less than the set value, the controller controls the induced draft fan to operate at the first frequency gear. If the dust concentration in some dust hoods is greater than the set value, the controller controls the induced draft fan to operate at the second frequency gear. If the dust concentration in all dust hoods is greater than the set value, the controller controls the induced draft fan to operate at the third frequency gear.

[0047] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. An intelligent dust removal system for a raw material conveying system, characterized in that: Includes the following: The dust collecting component includes a dust collecting hood installed between two adjacent raw material conveyor belts. The dust collecting hood covers the end of the previous raw material conveyor belt and the input end of the next raw material conveyor belt. The dust collecting hood is connected to the smoke duct. A valve is provided at the connection between each dust collecting hood and the smoke duct, i.e., the dust suction port. The smoke duct is connected to the dust collector, and the dust collector is connected to the chimney through the induced draft fan. A data acquisition component, comprising a camera and a smoke sensor disposed in the dust collecting hood; The controller, camera, smoke sensor, valve and induced draft fan are separately connected to the controller. The controller determines the switch state of the dust suction port valve according to the working conditions of the raw material conveyor belt collected by the camera. The smoke sensor obtains the smoke concentration at each dust collection hood and sends it to the controller. The controller adjusts the frequency of the induced draft fan according to the smoke concentration in the dust collection hood collected by the smoke sensor.

2. The intelligent dust removal system for a raw material conveying system according to claim 1, characterized in that: The controller receives image data of raw materials at the raw material conveyor belt captured by the camera. The controller processes the image data according to a pre-trained deep learning model and obtains an image recognition result to judge the working condition of the raw material conveyor belt. The controller controls the operation of the valve and the induced draft fan according to the judged working condition of the raw material conveyor belt.

3. The intelligent dust removal system for a raw material conveying system according to claim 2, characterized in that: The controller can determine the working status of the corresponding raw material conveyor belt based on the image data sent by the camera, including whether the raw material conveyor belt is working or closed, and whether there is raw material being conveyed on the raw material conveyor belt; If the raw material conveyor belt is in the closed state, the controller closes the valve at the dust suction port of the corresponding raw material conveyor belt; If the raw material conveyor belt is in operation and there is no raw material on the raw material conveyor belt, the controller closes the valve at the dust suction port of the corresponding raw material conveyor belt and turns off the induced draft fan; If the raw material conveyor belt is in operation and there is raw material on the raw material conveyor belt, the controller opens the valve at the dust suction port corresponding to the raw material conveyor belt and turns on the induced draft fan.

4. The intelligent dust removal system for a raw material conveying system according to claim 2, characterized in that: A mapping relationship between the dust concentration in the dust hood and the frequency of the induced draft fan is established in the controller, and the controller gradually adjusts the frequency of the induced draft fan according to the dust concentration in the dust hood.

5. The intelligent dust removal system for a raw material conveying system according to claim 4, characterized in that: The controller establishes a mapping relationship between the smoke concentration in the dust collecting hood and the frequency of the induced draft fan according to the smoke sensor arranged in the dust collecting hood.

6. The intelligent dust removal system for a raw material conveying system according to claim 5, characterized in that: After receiving the image data transmitted by the camera and setting the time, the controller receives the data sent by the smoke sensor to obtain the dust concentration in the dust collecting hood so as to adjust the frequency of the induced draft fan.

7. The intelligent dust removal system for a raw material conveying system according to claim 6, characterized in that: The controller determines the following contents based on the established mapping relationship between the smoke concentration in the dust hood and the induced draft fan frequency: If the dust concentration in all dust hoods is less than the set value, the controller controls the induced draft fan to operate at the first frequency gear. If the dust concentration in some dust hoods is greater than the set value, the controller controls the induced draft fan to operate at the second frequency gear. If the dust concentration in all dust hoods is greater than the set value, the controller controls the induced draft fan to operate at the third frequency gear.

8. The intelligent dust removal system for a material conveying system according to claim 1, characterized in that: The camera is installed above the raw material conveyor belt, the camera head of the camera is aimed at the raw material conveyor belt, and the camera head of the camera is rotatable.

9. An intelligent dust removal method for a raw material conveying system, characterized in that: Includes the following: A dust collecting hood is provided between two adjacent raw material conveyor belts, the dust collecting hood covers the end of the previous raw material conveyor belt and the input end of the next raw material conveyor belt, and a smoke sensor is provided in the dust collecting hood; The dust collecting hood is connected to the smoke duct. A valve is installed at the connection between each dust collecting hood and the smoke duct, i.e., the dust suction port. The smoke duct is connected to the dust collector, and the dust collector is connected to the chimney through the induced draft fan. The controller determines the switch status of the dust suction port valve according to the working conditions of the raw material conveyor belt collected by the camera. The smoke sensor obtains the smoke concentration at each dust collection hood and sends it to the controller. The controller adjusts the frequency of the induced draft fan according to the smoke concentration in the dust collection hood collected by the smoke sensor.

10. The intelligent dust removal method for a material conveying system according to claim 9, characterized in that: Includes the following: A camera is set above the raw material conveyor belt. After the smoke sensor transmits data for a set time, the controller receives the raw material image data on the raw material conveyor belt sent by the camera and sends it to the controller; The controller processes the image data according to the pre-trained deep learning model and obtains image recognition results to judge the working condition of the raw material conveyor belt. The controller controls the action of the valve and induced draft fan according to the judged working condition of the raw material conveyor belt.

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