Intelligent acoustic vibration decoking device

Abstract

The invention discloses an intelligent acoustic vibration decoking device, and relates to the technical field of boiler furnace flue decoking. The decoking device comprises an acoustic vibration sounder, a motion control mechanism, a monitoring photographing device, a deep learning algorithm device and the like. After the monitoring photographing device obtains an in-furnace coke deposition image, the monitoring control and image comparison analysis device carries out comparison analysis, the deep learning algorithm device calculates the thickness and speed of the deposited ash, and then the decoking strength and frequency of the sound vibration sounder and the displacement of the motion control mechanism are controlled. In addition, the split type sound wave amplifying device is matched with a motion control mechanism through a hollow rotating ball structure, and 360-degree circumferential rotation can be achieved. And a sealing box mounting mechanism and a high-temperature-resistant material ensure stable operation of the equipment. Through real-time monitoring, intelligent analysis and dynamic adjustment, the decoking efficiency and precision are improved, the coverage range is expanded, the method adapts to complex working conditions, manual intervention is reduced, and refinement, automation and intellectualization of the decoking process are achieved.

Description

Technical Field

[0001] The present application relates to the technical field of boiler furnace flue decoking, and in particular to an intelligent acoustic vibration decoker. Background Art

[0002] During the coal combustion process in power generation boilers, a large amount of coke is produced and attached to the heat exchange tubes, causing a significant decrease in the boiler's heat exchange efficiency. Traditional decoking technology uses steam decoking technology, which has certain shortcomings. For example, the decoking is not clean and thorough, which can easily cause safety hazards such as blowing the tubes. Acoustic vibration decoking technology uses an acoustic vibration sounder to generate specific sound waves, and uses the sound wave energy to generate vibrations to loosen and fall off the coke blocks. Online decoking keeps the heat exchange tubes clean, greatly improves boiler efficiency, and achieves good results in energy conservation and emission reduction. Summary of the Invention

[0003] In order to improve the efficiency of removing coke from industrial boilers and realize the refinement, automation and intelligence of the decoking process, the present application provides an intelligent acoustic vibration decoker.

[0004] An intelligent acoustic vibration decoker, comprising an acoustic vibration sounder 6, a motion control mechanism 4, a monitoring and photographing device 5, a monitoring control and image comparison and analysis device 7, a deep learning algorithm device 8, and an acoustic vibration sounder control device 9;

[0005] The acoustic vibration sounder control device 9 is respectively connected to the split sound wave amplifier 1, the monitoring camera device 5, the monitoring control and image comparison and analysis device 7, the deep learning algorithm device 8, the acoustic vibration sounder 6, and the motion control mechanism 4;

[0006] After acquiring the coke accumulation image in the furnace, the monitoring and photographing device 5 transmits the coke accumulation image in the furnace to the monitoring control and image comparison and analysis device 7. The monitoring control and image comparison and analysis device 7 compares the coke accumulation image in the furnace with the reference image library and inputs the comparison result into the deep learning algorithm device 8.

[0007] After calculating the dust accumulation thickness and speed based on the comparison results, the deep learning algorithm device 8 analyzes and learns the dust accumulation thickness and speed, adjusts the decoking strategy, and outputs the decoking strategy to the acoustic vibration sounder control device 9;

[0008] The vibroacoustic sounder control device 9 controls the defocusing intensity and defocusing frequency of the vibroacoustic sounder 6 according to the defocusing strategy, and controls the displacement parameters of the motion control mechanism 4 .

[0009] Furthermore, the acoustic vibration sound generator 6 is connected to the split sound wave amplifier 1, which includes a large speaker 11, a small speaker 14 and a hollow rotating ball structure connecting the two;

[0010] The hollow rotating ball structure includes an outer ball head 12 and an inner ball head 13. The outer ball head 12 wraps the inner ball head 13. A rotating shaft 15 is fixedly mounted on the surface of the outer ball head 12.

[0011] The sound wave input end of the large speaker 11 is connected to the outer ball head 12, and the sound wave output end extends deep into the inner side of the furnace;

[0012] The sound wave input end of the small speaker 14 is connected to the sound outlet of the acoustic vibration sound generator 6 , and the sound wave output end is connected to the inner ball head 13 .

[0013] Furthermore, the motion control mechanism 4 includes a power unit 41, which is an electric cylinder, a pneumatic cylinder or a hydraulic cylinder. The power unit 41 can provide driving force on the X-axis and the Y-axis to realize the movement of the speaker. The power unit 41 is connected to the support arm 43 through the mounting seat 42.

[0014] Furthermore, the split sound wave amplifier 1 is fixed to the furnace wall mounting hole through a sealing box mounting mechanism 2. The sealing box mounting mechanism 2 includes a connecting push plate 21, a protective cover 22 and a sealing box 23. The sealing box 23 is a box body, which is fixedly connected to the furnace wall on all sides and tightly bonded. The rear end of the sealing box 23 is connected to the pushing plate 21. A protective cover 22 is arranged between the pushing plate 21 and the sealing box 23. The protective cover 22 is made of aerogel felt or aluminum silicate fiber.

[0015] Furthermore, a plurality of heat exchange avoidance pipes 24 are provided on the surface of the sealing box 23 facing the furnace. The heat exchange avoidance pipes 24 are bent to both sides, and their diameters match the outer diameters of the water cooling pipes inside the furnace wall.

[0016] Furthermore, it also includes a mobile mechanism protection cover 3, which is welded and fixed on the sealing box 23. The hollow rotating ball structure is accommodated inside the mobile mechanism protection cover 3, wherein the upper plate 31 and the side plate 33 are provided with movable holes for the rotating shaft 15, and the size and length of the holes are sufficient to meet the range of motion of the power mechanism. The front plate 32 is provided with a circular hole, and the large speaker 11 is on the circular hole and enters the sealing box mounting mechanism 2 to provide a rotation space for the large speaker 11.

[0017] Furthermore, the acoustic vibration sounder control device 9 is a PLC control execution system. According to the decoking strategy output by the deep learning algorithm device 8, the PLC control execution system controls the decoking intensity and decoking frequency of the acoustic vibration sounder 6, and flexibly controls the displacement parameters of the motion control mechanism 4, so as to enable the split-type sound wave amplifier 1 to accurately point to the position where decoking and ash removal are required.

[0018] Furthermore, the deep learning algorithm device 8 analyzes the coke accumulation image in the furnace and learns and summarizes experience. It uses algorithms to dynamically analyze operating data, predict faults, optimize parameters, and automatically adjust the frequency, power, and speaker direction of the sonicator 6 to achieve refined control of the decoking process, reduce manual intervention, and improve decoking efficiency and accuracy.

[0019] The deep learning algorithm device 8 has a built-in communication module and is equipped with a SIM card to realize two-way data interaction with the power plant control center, provide data reference and remote modification, transmit furnace images, coke accumulation analysis reports and equipment operation logs in real time, share them to all operating equipment data centers, and receive remote control instructions.

[0020] Furthermore, the monitoring and photographing device 5 uses a wide-angle lens as a camera, and the camera compartment 51 and the front end penetration tube 52 are made of high-temperature resistant materials such as tungsten alloy, and compressed gas is introduced to take away the internal high temperature and keep the camera working at the working temperature; the rear end tube 53 of the monitoring and photographing device 5 has a built-in temperature sensor for monitoring the furnace temperature and feeding it back to the deep learning algorithm device 8.

[0021] In summary, the beneficial technical effects of this application are as follows:

[0022] 1. The intelligent acoustic-vibration decoking device uses a monitoring and photographing device 5 to obtain real-time images of coke deposits in the furnace. The monitoring, control, and image comparison and analysis device 7 monitors furnace coking parameter data based on a reference image library. Combined with a deep learning algorithm device 8, the device analyzes and learns the data. The algorithm dynamically analyzes operating data, predicts faults, optimizes parameters, and automatically adjusts the frequency and power of the acoustic-vibration sounder 6 and the direction of the loudspeaker 11. This enables refined control of the decoking process, reduces manual intervention, and improves decoking efficiency and accuracy.

[0023] 2. The design of the split sound wave amplifier (1) enables installation in confined spaces, eliminating the difficulty of installing large components. The hollow channel created by the hollow rotating ball structure ensures unimpeded transmission of sound waves, achieving near-100% energy utilization. The hollow rotating ball structure, combined with two sets of vertically intersecting motion control mechanisms (4), enables 360° circumferential rotation of the speaker end. This, combined with the speaker's inherent amplification range, creates a wide spatial angle range, enabling multi-angle precision operation against coke accumulation at different locations, expanding the decoking coverage area.

[0024] 4. The surface of the mobile mechanism protective cover 3 is provided with an oblong movable hole compatible with the displacement range of each component of the motion control mechanism 4. The equipment can move synchronously with the furnace body, adapting to the complex working conditions of industrial boilers and reducing the difficulty of installation and maintenance.

[0025] 5. The sealing box installation mechanism 2 is provided with a protective cover 22 made of aerogel felt material to provide high temperature resistance and dustproof protection; the heat exchange avoidance pipe 24 is set by bending to create space and movement space for the large speaker 11 to pass through the furnace wall, ensuring that the large speaker 11 does not interfere with any other structure during work, and ensuring that the equipment operates stably in the high temperature environment in the furnace, while avoiding equipment damage caused by furnace displacement, thereby improving reliability.

[0026] 6. By adopting the above technical solution, the front end penetration tube 52 and the camera chamber 51 can penetrate deep into the furnace to carry out image monitoring. The material setting can be selected from high-temperature resistant materials to ensure its normal operation under high temperature conditions in the furnace. The monitoring and photographing device 5 uses a wide-angle lens, which allows the shooting equipment to observe the overall coke accumulation situation in the furnace without rotating. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a schematic diagram of the overall structure of the intelligent acoustic vibration decoking device;

[0028] Figure 2 It is a structural diagram of a split-type sound wave amplifier 1;

[0029] Figure 3 is a schematic structural diagram of the motion control mechanism 4;

[0030] Figure 4 It is a structural diagram of the mobile mechanism protective cover 3

[0031] Figure 5 It is a structural diagram of the sealing box mounting mechanism 2;

[0032] Figure 6 It is a structural diagram of the monitoring and photographing device 5.

[0033] Explanation of the accompanying symbols: 1. Split sound wave amplifier; 11. Large speaker; 12. Outer ball head; 13. Inner ball head; 14. Small speaker; 15. Rotating axis; 2. Sealing box mounting mechanism; 21. Push plate; 22. Protective cover; 23. Sealing box; 24. Heat exchange avoidance tube; 3. Protective cover of moving mechanism; 31. Upper plate; 32. Front plate; 33. Side plate; 4. Motion control mechanism; 41. Power unit; 42. Mounting seat; 43. Support arm; 44. Moving bearing; 5. Monitoring and photographing device; 51. Camera compartment; 52. Front end penetration tube; 53. Rear end tube; 54. Input hole; 6. Acoustic vibration sounder; 7. Monitoring control and image comparison and analysis device; 8. Deep learning algorithm device; 9. Acoustic vibration sounder control device. DETAILED DESCRIPTION

[0034] The following will refer to Figures 1-6A specific embodiment will be described below. This embodiment is a preferred embodiment of the present invention, and other embodiments should not be limited by this embodiment. It will be understood that the described embodiments can be modified in various ways without departing from the spirit or scope of this application. Therefore, the drawings and description are to be regarded as illustrative in nature and not restrictive.

[0035] Combined with attachment Figure 1-6 The intelligent acoustic vibration decoker of the present invention is described.

[0036] like Figure 1 As shown, the main body of the overall hardware structure is the acoustic vibration sounder 6, which can output 0.1-10MPa compressed gas to generate 20-200Hz sound waves.

[0037] Specifically, the split sound wave amplifier 1 is connected to the acoustic vibration sounder 6 through a flange, and the sound wave is directionally amplified and then introduced into the furnace. The motion control mechanism 4 drives the split sound wave amplifier 1 to achieve spatial steering. The sealing box mounting mechanism 2 is welded to the furnace wall. The monitoring and photographing device 5 is the image acquisition hardware in the furnace, mainly including a camera compartment 51, a front end penetration tube 52, and a rear end tube 53. The mobile mechanism protective cover 3 protects the motion control mechanism 4 and the hollow rotating ball structure, including an upper plate 31, a front plate 32, and a side plate 33. The intelligent control equipment includes a monitoring control and image comparison and analysis device 7, a deep learning algorithm device 8, and an acoustic vibration sounder control device 9, all of which are deployed on an industrial computer and connected to the hardware equipment through cables.

[0038] like Figure 2 The structure of the split-type sound wave amplifier 1 shown here primarily comprises a large speaker 11, a small speaker 14, and a hollow rotating ball structure. The hollow rotating ball structure comprises an outer ball head 12, an inner ball head 13, and an externally mounted rotating shaft 15. This structure allows the connection between the large and small speakers 11, 14 to simultaneously amplify sound waves while enabling multi-angle steering of the large speaker 11. The gap between the outer and inner ball heads 12, 13 is filled with graphite lubricant. The rotating shaft 15 is fixed perpendicularly to the surface of the outer ball head 12.

[0039] The large speaker 11 consists of three high-temperature resistant alloy blades, which are welded in a furnace through a sealed box mounting mechanism 2, with a diffusion angle of 60°. The input end of the small speaker 14 is connected to the acoustic vibrator 6 through a flange, and the output end is rigidly connected to the inner ball head 13.

[0040] The transmission path of the sound wave energy is: the acoustic vibration sounder 6 → the small speaker 14 → the inner ball head 13 → the hollow channel → the outer ball head 12 → the large speaker 11 → the coke layer in the furnace.

[0041] like Figure 3As shown, the motion control mechanism 4 is driven by two power units 41. Depending on the operating situation, linear actuators such as servo electric cylinders, pneumatic cylinders, or hydraulic cylinders can be selected. The two power units 41 are arranged at 90°, defining the X-axis and Y-axis. The outputs of the power units 41, distributed along the X-axis and Y-axis, drive the rotating shaft 15 via movable bearings 44. This in turn coordinates with the hollow rotating ball mechanism to achieve three-dimensional rotation, thus enabling three-dimensional steering of the end of the loudspeaker 11.

[0042] The terminal steering range of the large speaker 11 is driven by the power unit 41. Specifically, a single power unit 41 can achieve a ±30° pitch angle; a dual power unit 41 can achieve 360° circumferential coverage.

[0043] The installation process of the motion control mechanism 4 is as follows: the end of the power unit 41 is connected to the mounting seat 42 via a rotating pair → the mounting seat 42 is hinged to the support arm 43 → the support arm 43 is welded to the mobile mechanism protection cover 3.

[0044] like Figure 4 As shown, the mobile mechanism protective cover 3 is composed of an upper plate 31, a front plate 32 and a side plate 33, wherein the upper plate 31 and the side plate 33 on one side are provided with an oblong movable shaft hole, through which the rotating shaft 15 of the hollow rotating ball structure can be connected to the movable bearing 44, and the size and length of the hole meet the range of motion of the power mechanism.

[0045] The movable mechanism protective cover 3 is welded and fixed to the sealing box 23. The front plate 32 has a circular hole, which allows the small speaker 14 to pass through and be welded and fixed to provide indirect support for the acoustic vibration sound generator 6, and can also protect the hollow rotating ball structure contained inside. The rear end of the movable mechanism protective cover 3 is open, and the edge is welded and fixed to the sealing box mounting mechanism 2. During the decoking operation, the movable mechanism protective cover 3 can protect the acoustic vibration sound generator 6 from contact with the outside world, causing collisions and noise. The motion control mechanism 4 can use the hollow rotating ball structure, and the rotating shaft 15 can move within the track of the oblong hole set in the side plate 33 of the movable mechanism protective cover 3, thereby accurately controlling the speaker end to achieve steering movement.

[0046] like Figure 5 As shown, the sealing box mounting mechanism 2 provides high-temperature protection. The sealing box 23 is welded to the furnace wall. The bent tubes on both sides of the heat exchange avoidance tube 24 align with the water-cooled wall pipes, creating a physical avoidance design. The protective cover 22 is made of spirally folded aerogel felt (available with a temperature resistance of ≥1200°C) and connects the push plate 21 to the sealing box 23.

[0047] like Figure 6As shown, the monitoring camera device 5 is installed to the side of the fire viewing hole. The main body uses an infrared wide-angle camera lens with a resolution of 1920×1080@30fps and a field of view of 120°. The outer layer is equipped with a camera chamber 51 and a front end deep tube 52, both of which are tungsten alloy shells. Compressed gas is introduced to remove the internal high temperature and maintain the camera at the operating temperature. The rear end tube 53 is equipped with a built-in K-type thermocouple for monitoring the furnace temperature and feeding it back to the deep learning algorithm device 8.

[0048] The monitoring control and image comparison and analysis device 7 is developed based on existing image libraries such as OpenCV. It pre-segments the furnace image provided by the monitoring and photographing device 5, extracts the coke accumulation area, compares the real-time image with the database, and outputs the coke accumulation position and thickness coke parameters with an accuracy of ±2mm.

[0049] The deep learning algorithm device 8 adopts the TensorFlow / PyTorch framework, analyzes the coking parameters in the furnace obtained by the image acquisition module through CNN, and identifies the distribution of the coke layer; dynamically adjusts the decoking strategy according to the coking parameters; generates control instructions based on the adjustable decoking strategy and transmits them to the acoustic vibration sounder control device 9; executes the data interaction mechanism, sends JSON format reports to the power plant DCS every 30 minutes, and receives remote instructions (such as forced start and stop) at the same time, and synchronously updates them to the local decision model.

[0050] The acoustic vibration sounder control device 9 is developed based on the Siemens S7-1500 series, receives and executes the control instructions provided by the deep learning algorithm device 8, and automatically triggers the decoking operation when the coke accumulation reaches a threshold. For example, if the coke layer thickness is greater than the threshold, the acoustic vibration sounder 6 is started, set to the frequency and intensity of the preset strategy, and controls the motion control mechanism 4 to coordinate with the control of the end of the large speaker 11 to turn to the target position.

[0051] Workflow: The monitoring and photographing device 5 captures the image inside the furnace → transmits it to the monitoring control and image comparison and analysis device → the monitoring control and image comparison and analysis device 7 calls the OpenCV algorithm to identify the coke accumulation area → outputs the coordinates and thickness data → the deep learning algorithm device 8 generates the corresponding control instructions by formulating an adjustable decoking strategy and outputs them to the acoustic vibration sounder control device 9 → the acoustic vibration sounder control device 9 controls the corresponding working parameters of the acoustic vibration sounder 6 and the motion control mechanism 4 according to the control instructions → the decoking result data is sent back to the deep learning algorithm device 8 to update the decoking strategy → the deep learning algorithm device 8 has a built-in communication module and is equipped with a SIM card to realize two-way data interaction with the power plant control center, transmit the furnace image, coke accumulation analysis report and equipment operation log in real time, and receive remote control instructions.

[0052] The above embodiments are only preferred examples of this application and are not intended to limit the scope of protection. Any equivalent replacement or structural improvement based on the technical solution of this application should be included in the scope of patent protection of this application.

Claims

1. An intelligent acoustic vibration decoker, characterized in that: include: Acoustic vibration sound generator (6), motion control mechanism (4), monitoring camera device (5), monitoring control and image comparison and analysis device (7), deep learning algorithm device (8), acoustic vibration sound generator control device (9); The acoustic vibration sound generator control device (9) is respectively connected to the split sound wave amplifier (1), the monitoring camera device (5), the monitoring control and image comparison and analysis device (7), the deep learning algorithm device (8), the acoustic vibration sound generator (6), and the motion control mechanism (4); wherein, after acquiring the coke accumulation image in the furnace, the monitoring and photographing device (5) transmits the coke accumulation image in the furnace to the monitoring control and image comparison and analysis device (7); the monitoring control and image comparison and analysis device (7) compares the coke accumulation image in the furnace with a reference image library, and inputs the comparison result into the deep learning algorithm device (8); The deep learning algorithm device (8) calculates the dust accumulation thickness and speed based on the comparison result, analyzes and learns the dust accumulation thickness and speed, adjusts the decoking strategy, and outputs the decoking strategy to the acoustic vibration sounder control device (9); The sonicator control device (9) controls the defocusing intensity and defocusing frequency of the sonicator (6) according to the defocusing strategy, and controls the displacement parameters of the motion control mechanism (4).

2. The intelligent acoustic vibration decoker according to claim 1, wherein: The acoustic vibration sound generator (6) is connected to a split-type sound wave amplifier (1), and the split-type sound wave amplifier (1) includes a large speaker (11), a small speaker (14), and a hollow rotating ball structure connecting the two. The hollow rotating ball structure comprises an outer ball head (12) and an inner ball head (13), wherein the outer ball head (12) wraps the inner ball head (13), and a rotating shaft (15) is fixedly mounted on the surface of the outer ball head (12); The sound wave input end of the large speaker (11) is connected to the outer ball head (12), and the sound wave output end extends deep into the inner side of the furnace; The sound wave input end of the small speaker (14) is connected to the sound output port of the acoustic vibration sound generator (6), and the sound wave output end is connected to the inner ball head (13).

3. The intelligent acoustic vibration decoker according to claim 2, wherein: The motion control mechanism (4) includes a power unit (41), which is an electric cylinder, a pneumatic cylinder or a hydraulic cylinder. The power unit (41) can provide driving force on the X-axis and the Y-axis to achieve the movement of the speaker. The power unit (41) is connected to the support arm (43) through the mounting seat (42).

4. The intelligent acoustic vibration decoker according to claim 3, wherein: The split sound wave amplifier (1) is fixed to the furnace wall mounting hole through a sealing box mounting mechanism (2). The sealing box mounting mechanism (2) comprises a connecting push plate (21), a protective cover (22) and a sealing box (23). The sealing box (23) is a box body, the four sides of which are fixedly connected to the furnace wall and tightly bonded. The rear end of the sealing box (23) is connected to the pushing plate (21). A protective cover (22) is provided between the pushing plate (21) and the sealing box (23). The protective cover (22) is made of aerogel felt or aluminum silicate fiber.

5. The intelligent acoustic vibration decoker according to claim 4, characterized in that: The surface of the sealing box (23) facing the furnace is provided with a plurality of heat exchange avoidance pipes (24), the heat exchange avoidance pipes (24) are bent to both sides, and the diameter thereof matches the outer diameter of the water cooling pipe inside the furnace wall.

6. The intelligent acoustic vibration decoker according to claim 5, characterized in that: The invention also includes a mobile mechanism protection cover (3), which is welded and fixed on the sealing box (23). The hollow rotating ball structure is accommodated inside the mobile mechanism protection cover (3), wherein the upper plate (31) and the side plate (33) are provided with movable holes for the rotating shaft (15), the size and length of the holes being provided satisfy the range of motion of the power mechanism, and the front plate (32) is provided with a circular hole. The large speaker (11) is placed on the circular hole and enters the sealing box mounting mechanism (2), thereby providing a rotation space for the large speaker (11).

7. The intelligent acoustic vibration decoker according to claim 6, wherein: The acoustic vibration sounder control device (9) is a PLC control execution system. According to the decoking strategy output by the deep learning algorithm device (8), the PLC control execution system controls the decoking intensity and decoking frequency of the acoustic vibration sounder (6), and flexibly controls the displacement parameters of the motion control mechanism (4), so as to achieve the accurate pointing of the split-type sound wave amplifier (1) to the position where decoking and ash removal is required.

8. The intelligent acoustic vibration decoker according to claim 7, wherein: The deep learning algorithm device (8) analyzes the coke accumulation image in the furnace and learns and summarizes the experience, uses the algorithm to dynamically analyze the operation data, predicts faults, optimizes parameters, and automatically adjusts the frequency, power and speaker direction of the acoustic vibration sounder (6) to achieve a decoking strategy, thereby achieving refined control of the decoking process, reducing manual intervention, and improving decoking efficiency and accuracy; The deep learning algorithm device (8) has a built-in communication module and is equipped with a SIM card to realize two-way data interaction with the power plant control center, provide data reference and remote modification, transmit furnace images, coke accumulation analysis reports and equipment operation logs in real time, share them with all operating equipment data centers, and receive remote control instructions.

9. The intelligent acoustic vibration decoker according to claim 8, wherein: The monitoring and photographing device (5) uses a wide-angle lens as a camera, and the camera chamber (51) and the front end deep tube (52) are made of high-temperature resistant materials such as tungsten alloy, and compressed gas is introduced to remove the internal high temperature and keep the camera working at the working temperature; the rear end tube (53) of the monitoring and photographing device (5) is built with a temperature sensor for monitoring the furnace temperature and feeding it back to the deep learning algorithm device (8).

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