A method and system for identifying and cleaning dirt on filter plates
By using the minimum circumcircle and inverse kinematics algorithms to identify and clean filter plate contaminants at specific points, the problem of low intelligence in filter plate cleaning in existing technologies is solved, achieving efficient, targeted, and energy-saving filter plate contaminant cleaning.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SHANDONG UNIV
- Filing Date
- 2024-04-10
- Publication Date
- 2026-05-26
AI Technical Summary
In the existing technology, the level of intelligence in cleaning plate and frame filter presses is low, and it is unable to effectively clean different types of dirt on the filter plates, resulting in low cleaning effect and efficiency, and serious waste of resources.
The minimum circumcircle method is used to identify dirt on the filter plate, key points are determined and cleaned by a robotic arm, and the cleaning sequence is optimized by combining inverse kinematics algorithm to achieve targeted cleaning of dirt.
It improves the effectiveness and efficiency of cleaning filter plates, reduces energy consumption, is applicable to filter plates of different specifications, and avoids resource waste and equipment damage.
Smart Images
Figure CN118122002B_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of dirt cleaning technology, and in particular relates to a method and system for identifying and cleaning dirt on filter plates. Background Technology
[0002] A plate and frame filter press is a solid-liquid separation device commonly used for the filtration and dewatering of suspensions with high solid particle content. It mainly consists of filter frames, filter plates, a pressing device, and a liquid collection system. The filter plates, as a key component of the plate and frame filter press, play a crucial role in the filtration process. However, after the press has been running for a period of time, a large amount of impurities and solid matter often accumulates on the filter plates. The presence of these contaminants can significantly impact the filtration efficiency and product quality. If the filter plates are not cleaned in a timely manner, it may lead to a reduction in filtration efficiency or even damage to the equipment. Therefore, it is necessary to clean the filter plates of the plate and frame filter press regularly.
[0003] Cleaning filter plates in plate and frame filter presses is a challenging task, characterized by a large quantity of debris, difficulty in cleaning, and diverse types of contaminants. Furthermore, the high stickiness and adsorption of some filter plate contaminants make cleaning difficult, impacting efficiency. Current cleaning methods include manual cleaning, vibration-assisted material removal, and high-pressure water washing, but these methods often result in incomplete cleaning and low efficiency. In recent years, to meet the growing demand for plate and frame filter press cleaning, a series of new methods have emerged, such as pneumatic cleaning, high-pressure water jet cleaning, ultrasonic cleaning, and chemical cleaning, which have proven effective in cleaning filter plates.
[0004] Many scholars have conducted extensive research on cleaning filter plates in plate and frame filter presses, and filter plate cleaning equipment is available on the market, primarily using high-pressure water washing to clean all areas of the filter plates. The inventors have discovered that while these methods can achieve the goal of cleaning filter plates, the following technical problems still exist:
[0005] (1) The level of intelligence is poor. It can only perform irregular cleaning on the entire area of the filter plate. It cannot determine the specific location, size, shape, etc. of the dirt on the filter plate. It cannot effectively clean different types of dirt on the filter plate. It lacks specificity, which greatly reduces the cleaning effect and efficiency.
[0006] (2) It does not have automatic identification function for dirt, so the dirt cleaning operation of the filter plate often results in waste of resources, high energy consumption, and inability to meet higher cleaning requirements. Summary of the Invention
[0007] To overcome the shortcomings of the prior art, this invention provides a filter plate contaminant identification and cleaning method and system. The method utilizes the minimum circumscribed circle method to cover a single contaminant and determines multiple key points. A robotic arm is then controlled to perform targeted cleaning of the contaminant based on these key points. Following a predetermined cleaning sequence, all contaminants are cleaned. This approach enables targeted cleaning of contaminants, improving the effectiveness, efficiency, and overall quality of cleaning, particularly for filter plate contaminants with high viscosity and adsorption.
[0008] To achieve the above objectives, one or more embodiments of the present invention provide the following technical solutions:
[0009] The first aspect of this invention provides a method for identifying and cleaning dirt on filter plates.
[0010] A method for identifying and cleaning dirt on a filter plate includes the following steps:
[0011] The filter plate is identified to determine the location, size, and shape of individual dirt particles. The smallest circumscribed circle method is used to cover the individual dirt particles, and the coordinates and radius of the smallest circumscribed circle of the individual dirt particles are determined.
[0012] Establish a coordinate system and determine the cleaning sequence of all individual dirt blocks based on the center coordinates of the smallest circumcircle of each dirt block;
[0013] Within the minimum circumcircle of each individual piece of dirt, multiple key points are determined. Based on the inverse kinematics algorithm of the robotic arm, the joint angles of the robotic arm at each key point of the individual piece of dirt are calculated. The optimal pose of each key point of the robotic arm when cleaning all individual pieces of dirt is obtained.
[0014] Based on the optimal pose of each key point when the robotic arm cleans all individual pieces of dirt, the robotic arm is controlled to perform fixed-point cleaning on multiple key points corresponding to each piece of dirt. Based on the cleaning order of individual pieces of dirt, multiple pieces of dirt are cleaned sequentially until all individual pieces of dirt are cleaned.
[0015] A second aspect of the present invention provides a filter plate dirt identification and cleaning system.
[0016] A filter plate contaminant identification and cleaning system, comprising:
[0017] The identification and coverage module is configured to: identify dirt on the filter plate, determine the position, size and shape of a single piece of dirt, cover the single piece of dirt using the minimum circumscribed circle method, and determine the coordinates and radius of the minimum circumscribed circle of the single piece of dirt;
[0018] The cleaning sequence determination module is configured to: establish a coordinate system and determine the cleaning sequence of all individual dirt blocks based on the center coordinates of the smallest circumscribed circle of each dirt block;
[0019] The key point optimal pose determination module is configured to: determine multiple key points within the minimum outer circle of each single piece of dirt; solve the robot joint angles at each key point of the robot arm when the robot arm reaches each single piece of dirt according to the inverse kinematics algorithm of the robot arm; and obtain the optimal pose of each key point when the robot arm cleans all single pieces of dirt.
[0020] The cleaning module is configured to: control the robotic arm to perform fixed-point cleaning on multiple key points corresponding to a single piece of dirt based on the optimal pose of each key point when the robotic arm cleans all single pieces of dirt, and clean multiple single pieces of dirt sequentially based on the cleaning order of the single pieces of dirt, until all single pieces of dirt have been cleaned.
[0021] A third aspect of the present invention provides a computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the steps of the filter plate dirt identification and cleaning method as described in the first aspect of the present invention.
[0022] The fourth aspect of the present invention provides an electronic device including a memory, a processor, and a program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the filter plate dirt identification and cleaning method as described in the first aspect of the present invention.
[0023] The above one or more technical solutions have the following beneficial effects:
[0024] This invention provides a method and system for identifying and cleaning filter plates. It utilizes the minimum circumscribed circle method to cover a single piece of dirt, then determines multiple key points within the minimum circumscribed circle corresponding to that piece. Based on these key points, a robotic arm is controlled to perform targeted cleaning, thus completing the cleaning of the single piece of dirt. Finally, according to a determined cleaning sequence, all dirt is cleaned. This invention enables targeted cleaning of dirt, improving the effectiveness, efficiency, and overall quality of cleaning, especially for filter plates with high viscosity and adsorption.
[0025] Based on preset optimal pose constraints for the robotic arm, this invention obtains the optimal poses of each key point when the robotic arm cleans all individual pieces of dirt: under the premise that the main components of the robotic arm will not collide, the pose with the best dirt cleaning effect of the robotic arm is taken as the optimal pose for the robotic arm to perform cleaning operations at a certain key point, which can further ensure the dirt cleaning effect.
[0026] This invention controls a robotic arm to clean a single piece of dirt at a time using a linear feed and oscillation method. The robotic arm has high motion control precision, making the cleaning operation highly accurate and effective.
[0027] This invention is suitable for various application scenarios. The length of the robotic arm is designed for different specifications of filter plates, making it applicable to cleaning operations on filter plates of different sizes. At the same time, this invention also takes into account the difference in distance between the origin of the robotic arm and the upper edge of the filter plate during actual installation, ensuring that the robotic arm can be used for cleaning operations in different application scenarios.
[0028] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description
[0029] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.
[0030] Figure 1 This is a flowchart of the method in the first embodiment.
[0031] Figure 2 This is a flowchart of the logic judgment in the first embodiment.
[0032] Figure 3 This is a schematic diagram of the minimum circumcircle of the contaminated area.
[0033] Figure 4 This diagram defines the filter plate area and shows the structure of the robotic arm.
[0034] Figure 5 This is a schematic diagram of key points in the contaminated area.
[0035] Figure 6 This is a schematic diagram of a robotic arm's linear feed and oscillating cleaning process. Detailed Implementation
[0036] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.
[0037] It should be noted that the terminology used herein is for the purpose of describing particular implementations only and is not intended to limit the exemplary implementations of the present invention.
[0038] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.
[0039] The overall concept proposed in this invention is as follows:
[0040] This invention proposes a method for identifying and cleaning filter plates by combining image recognition and analysis of filter plate contaminants with motion control algorithms. This method is applicable to cleaning filter plates of different specifications. The invention mainly comprises the following seven stages:
[0041] The first stage is the image recognition and preprocessing of filter plate contaminants, which uses image recognition technology to identify and preprocess the contaminants on the filter plate.
[0042] The second stage is the location and analysis of dirt areas on the filter plate. By analyzing the pre-processed image recognition information, the center coordinates and radius of the smallest circumscribed circle of all individual dirt areas within the filter plate area are given in turn.
[0043] The third stage is to determine the cleaning order of dirt. The control system sorts and optimizes the dirt on the filter plate according to the center coordinates of the smallest circumscribed circle of all individual dirt pieces obtained by image recognition, in order to determine the cleaning order of all dirt on the filter plate.
[0044] The fourth stage is the determination of the optimal pose of the key points for the robotic arm to clean up dirt. The control system obtains the different poses of the robotic arm to each key point in each dirt area according to the inverse kinematics algorithm of the robotic arm. Then, according to the constraints such as the optimal pose determination principle of the robotic arm, the optimal pose of each key point of the robotic arm to clean up all single dirt blocks is obtained.
[0045] The fifth stage is to perform the cleaning operation of a single piece of dirt. The control system sends a single cleaning operation control signal according to the dirt cleaning sequence of the filter plate, and then performs a series of cleaning operations for a single piece of dirt. After the single cleaning operation is completed, a completion signal is sent.
[0046] The sixth stage is to perform all the dirt cleaning operations. After receiving the signal that a single cleaning operation is completed, the control system will perform the cleaning operation for the next dirt. The steps of the fifth stage are repeated, and all dirt cleaning operations are performed in sequence until all dirt is cleaned. After all dirt is cleaned, the control system sends a signal that all dirt is cleaned and the robotic arm resets.
[0047] The seventh stage is the evaluation of the filter plate dirt cleaning effect. After completing all the cleaning operation steps, the control system performs image recognition on the filter plate dirt again to evaluate the cleaning effect.
[0048] This invention uses image recognition technology to identify and locate dirt on the filter plate, ensuring the accuracy of dirt location judgment. The inverse kinematics algorithm of the robotic arm can obtain the joint angle of the robotic arm at any position within the filter plate area, ensuring the flexibility of the cleaning operation. The control algorithm has a high degree of intelligence, ensuring the cleaning effect and efficiency, while also making the control system highly stable.
[0049] Example 1
[0050] This embodiment discloses a method for identifying and cleaning dirt on filter plates.
[0051] like Figure 1 , Figure 2 As shown, a method for identifying and cleaning dirt on a filter plate includes the following steps:
[0052] The filter plate is identified to determine the location, size, and shape of individual dirt particles. The smallest circumscribed circle method is used to cover the individual dirt particles, and the coordinates and radius of the smallest circumscribed circle of the individual dirt particles are determined.
[0053] Establish a coordinate system and determine the cleaning sequence of all individual dirt blocks based on the center coordinates of the smallest circumcircle of each dirt block;
[0054] Within the minimum circumcircle of each individual piece of dirt, multiple key points are determined. Based on the inverse kinematics algorithm of the robotic arm, the joint angles of the robotic arm at each key point of the individual piece of dirt are calculated, and the optimal pose of each key point of the robotic arm when cleaning all individual pieces of dirt is obtained.
[0055] Based on the optimal pose of each key point when the robotic arm cleans all individual pieces of dirt, the robotic arm is controlled to perform fixed-point cleaning on multiple key points corresponding to each piece of dirt. Based on the cleaning order of individual pieces of dirt, multiple pieces of dirt are cleaned sequentially until all individual pieces of dirt are cleaned.
[0056] Specifically, such as Figure 1 , Figure 2 As shown, steps S1-S7 are included:
[0057] In step S1, when performing image recognition of filter plate contaminants, image preprocessing operations were performed in combination with image correction, coordinate transformation, and image processing techniques.
[0058] In step S2, the dirt area of the filter plate was located and analyzed. The minimum circumcircle algorithm was used to analyze the preprocessed dirt image to obtain the position and size of the dirt area, ensuring that the entire range of each dirt area could be covered during image processing, thus ensuring the accurate location of the dirt.
[0059] In step S3, the cleaning sequence of the filter plate dirt was determined according to relevant rules, and the dirt cleaning sequence was optimized to ensure the efficiency of dirt cleaning.
[0060] In step S4, the optimal pose of the key points for the robotic arm to clean all individual pieces of dirt is determined by combining the inverse kinematics algorithm of the robotic arm and the optimal pose determination principle, thus ensuring the effectiveness of the dirt cleaning operation.
[0061] In step S5, an operation method for the robotic arm to clean up dirt was designed, which takes into account both the effectiveness and efficiency of the dirt cleaning operation.
[0062] In step S6, the overall dirt cleaning operation steps of the robotic arm filter plate are determined, making the overall filter plate cleaning operation process more systematic and greatly improving the cleaning efficiency.
[0063] In step S7, image recognition and analysis were performed again after the cleaning operation to evaluate the cleaning effect of the filter plate dirt and ensure the cleaning effect of the filter plate dirt.
[0064] Furthermore, steps S1-S7 are as follows:
[0065] S1: Image recognition and preprocessing of dirt on filter plates.
[0066] Image recognition and preprocessing of filter plate contaminants are fundamental to subsequent cleaning operations. Only by ensuring accurate image recognition can the robotic arm move precisely, enabling smooth cleaning. This invention employs different image recognition methods. Image preprocessing mainly includes: defining the image recognition region, performing image correction on the recognition region, performing coordinate transformation on the corrected region, and processing the transformed image information. During image recognition, for cases with relatively high color contrast between contaminants and the filter plate, image segmentation and other related algorithms can be used to detect and locate the contaminants. For cases that are difficult to distinguish, deep learning-based image segmentation and other related algorithms can be used to achieve accurate recognition and location.
[0067] S2: Location and analysis of dirt areas on filter plates.
[0068] The first step in cleaning filter plates is to determine the location and size of the debris. Because the size and shape of the debris are highly variable, neglecting to address it can significantly impact subsequent cleaning operations.
[0069] This step mainly involves in-depth analysis of the image information after image recognition and preprocessing to determine the location information of the dirt and obtain the size and shape of the dirt area. For example... Figure 3 As shown, this embodiment uses a minimum circumcircle algorithm to cover the dirt area. This algorithm provides the center coordinates and radius of the minimum circumcircle of all individual dirt particles within the overall area of the filter plate.
[0070] The diagram of the minimum circumcircle of the contaminated area is shown below. Figure 3 As shown, Figure 3 (a) Figure 3 (b) and Figure 3 (c) in the figure shows the minimum circumcircle of three different sizes and shapes of dirt.
[0071] S3: Determine the order of cleaning up the dirt.
[0072] The order in which filter plate contaminants are cleaned has a significant impact on the efficiency and energy consumption of the cleaning operation, and also affects the transition movement of the robotic arm when cleaning two contaminants. This is of great importance in practical applications. This step mainly involves the control system sorting and optimizing the contaminants on the filter plate according to rules based on the center coordinates of the smallest circumscribed circle of all individual contaminants obtained from image recognition, in order to determine the cleaning sequence of all contaminants on the filter plate.
[0073] like Figure 4 As shown, the cleaning sequence for filter plates is as follows:
[0074] After identifying the center coordinates of the smallest circumcircle of all individual dirt particles, sort all the center coordinates (assuming x is the x-coordinate and y is the y-coordinate). The sorting rule is as follows: first, distinguish all the center coordinates according to the sign of y, process the regions where y ≥ 0 first, and then process the regions where y < 0.
[0075] For regions where y≥0, first compare the x-coordinates of all dirt and sort them in ascending order of x-coordinate. For dirt with the same x-coordinate, then compare the y-coordinate and sort them in ascending order of y-coordinate.
[0076] For regions where y < 0, first compare the x-coordinates of all the dirt and sort them in descending order of x-coordinate. For dirt with the same x-coordinate, compare the absolute values of the y-coordinate and sort them in ascending order of absolute values of y-coordinate. The cleaning order of all dirt can be obtained from the above rules.
[0077] like Figure 4 As shown, the robotic arm in this embodiment is a three-axis robotic arm, including joint 1, joint 2 and joint 3. Joint 1 and joint 2 are connected by a connecting rod 1, and joint 2 and joint 3 are connected by a connecting rod 2. A connecting rod 3 is connected to joint 3, and the end of the connecting rod 3 can be connected to a cleaning execution device.
[0078] S4: Determine the optimal pose of key points for robotic arm cleaning of dirt.
[0079] Based on the actual cleaning effect, the number and distribution of key points of the minimum circumcircle of each single piece of dirt are determined, each key point is numbered, and the multiple poses of the robotic arm reaching each key point are solved based on the inverse kinematics algorithm.
[0080] Based on the preset optimal pose constraints of the robotic arm, the optimal poses of each key point when the robotic arm cleans all single pieces of dirt are obtained: under the premise that the main body parts of the robotic arm will not collide, the pose with the best dirt cleaning effect of the robotic arm is taken as the optimal pose for the robotic arm to perform cleaning operation at a certain key point.
[0081] The robotic arm used in this invention for cleaning operations is a planar robotic arm with three rotational degrees of freedom. The range of motion of each rotational joint is 0-360 degrees, and the length of the robotic arm link can be appropriately selected according to the size of the filter plate.
[0082] like Figure 5 As shown, after the coordinates and radius of the center of the smallest circumscribed circle of all individual dirt in the filter plate area are given, the control system calculates the coordinates of n key points in each dirt area (the number and distribution rules of key points are set according to the actual cleaning effect). Then, the control system obtains the joint angle of the robotic arm at each key point in each dirt area based on the inverse kinematics algorithm of the planar three-axis robotic arm.
[0083] Because the size of the filter plate and the type of dirt on the filter plate are uncertain during the actual cleaning process, the specific method of dividing the key points and the numbering order need to be set by the user based on experience to achieve the best cleaning effect. After numbering the key points, multiple key points are cleaned in number order. Based on the inverse kinematics algorithm, the various poses of the robotic arm from the current position to the first key point, from the first key point to the second key point, from the second key point to the third key point, and so on, as well as from the (n-1)th key point to the nth key point, are solved.
[0084] The inverse kinematics algorithm for a planar three-axis robotic arm: Assuming the robotic arm's end effector needs to reach a certain point, the three joint angles of the robotic arm are treated as unknowns. Then, based on the coordinates of the point reached by the end effector and parameters such as the length of the robotic arm's links, a set of parametric equations for the robotic arm is established according to geometric relationships. Solving these equations yields the three joint angles corresponding to the point reached by the robotic arm. Because the robotic arm has many degrees of freedom, there are often multiple different solutions, meaning the robotic arm can have various poses.
[0085] When using a robotic arm to clean up dirt, there is often an optimal pose for the cleaning operation, and different robotic arm poses have a certain impact on the cleaning effect. The robotic arm used in this invention has multiple degrees of freedom, so there may be several different poses for the robotic arm to reach the dirt area and perform the cleaning operation. Therefore, it is necessary to determine the optimal pose for the robotic arm to clean up dirt.
[0086] Optimal pose determination method for robotic arm to clean key points of dirt:
[0087] Provided that the main components of the robotic arm do not collide, the pose that minimizes the movement distance of the robotic arm and the cleaning time is taken as the optimal pose for the robotic arm to perform cleaning operations at a certain key point.
[0088] Given the coordinates and radius of the minimum circumscribed circle of all individual dirt particles within the filter plate area, the control system calculates the coordinates of several key points within each dirt particle area. Then, based on the inverse kinematics algorithm of the planar three-axis robotic arm, the control system obtains the joint angles of the robotic arm reaching each key point within each dirt particle area, thereby obtaining the different poses of the robotic arm at each key point within each dirt particle area. Finally, based on constraints such as the optimal pose determination principle of the robotic arm, the control system obtains the optimal pose of the robotic arm at each key point within each dirt particle area, thus obtaining the optimal pose of the robotic arm at each key point for cleaning all individual dirt particles.
[0089] S5: Perform a single block of dirt cleaning operation.
[0090] This step mainly involves the control system sending a single cleaning operation control signal according to the cleaning sequence of the filter plate dirt, executing the cleaning operation for a single dirt block, and sending a completion signal after the single cleaning operation is completed.
[0091] Different cleaning operations applied to a single piece of dirt can lead to varying cleaning results. Therefore, it is necessary to determine which cleaning operation the robotic arm should perform to achieve satisfactory results. Based on practical considerations, this invention selects an optimal method for cleaning dirt using a robotic arm.
[0092] Single cleaning operation method of robotic arm: The robotic arm cleans the single piece of dirt on the filter plate by adopting a linear feed and oscillation method according to the optimal pose of each key point in a single dirt area.
[0093] Cleaning method for linear feed with oscillation: such as Figure 6 As shown, for a certain area of contamination on the filter plate, assume there are n key points within the smallest circumcircle of the contamination area:
[0094] Based on the optimal pose of the robotic arm corresponding to each of the n key points in the contaminated area, the end of the robotic arm first moves to the point corresponding to the optimal pose of the first key point, and then the link 3 performs a swing cleaning operation at the point according to the set number of swings and swing amplitude.
[0095] Then the end of the robotic arm moves to the optimal pose corresponding to the second key point, and then the link 3 performs a swing cleaning operation at that point according to the set number of swings and swing amplitude.
[0096] Repeat the above operation until the oscillating cleaning operation at the nth key point is completed. Then the linear feed plus oscillating cleaning operation for a certain dirty area is completed.
[0097] S6: Perform all dirt and grime removal operations.
[0098] This step mainly involves the control system performing a cleaning operation for the next contaminant after receiving a signal indicating that a single cleaning operation has been completed. Step S5 is repeated to perform cleaning operations for all contaminants in sequence until all contaminants have been cleaned. Once all contaminants have been cleaned, the control system sends a signal indicating that all contaminants have been cleaned, and the robotic arm resets.
[0099] The following are the steps for cleaning the entire filter plate with a robotic arm:
[0100] Assuming there are m contaminants on a single filter plate, the control system first sends a single-cleaning control signal based on the minimum circumscribed circle of the first contaminant and the corresponding optimal pose of the robotic arm, initiating the cleaning operation for the first contaminant. After the first contaminant is cleaned, a completion signal is sent to the control system. Upon receiving the completion signal, the control system performs a single-cleaning operation based on the minimum circumscribed circle of the second contaminant and the corresponding optimal pose of the robotic arm, using the single-cleaning control signal. This process is repeated for the remaining contaminants until all contaminants are cleaned. Once all cleaning operations are completed, the control system sends a signal indicating that all contaminants on the filter plate have been cleaned, and the robotic arm resets.
[0101] S7: Evaluation of the cleaning effect of filter plate dirt.
[0102] Because cleaning filter plates is quite difficult, there's a possibility that a complete cleaning operation might not completely remove all the dirt. The effectiveness of filter plate cleaning is crucial for improving control algorithms; therefore, it's necessary to evaluate the cleaning effect after the operation. This step involves the control system performing image recognition on the filter plate dirt again after all cleaning operations have been completed to assess the cleaning effect.
[0103] The beneficial effects of this invention are as follows:
[0104] 1) High level of intelligence. This invention can effectively clean the dirt on the filter plate according to the location, size, shape and other information of the dirt. It is highly targeted, consumes less energy and has high practical value.
[0105] 2) High accuracy in identifying dirt on the filter plate. This invention employs multiple image processing algorithms in the image recognition section, and performs in-depth analysis and processing on the identified images to ensure that the image recognition of dirt on the filter plate achieves high accuracy.
[0106] 3) High precision in robotic arm motion control. This invention uses a servo motor to complete the cleaning operation of the robotic arm, ensuring the precision of the robotic arm's movement and making the cleaning operation highly accurate.
[0107] 4) High adaptability, suitable for various application scenarios. The automatic identification and cleaning method for filter plates proposed in this invention can design the length of the robotic arm for filter plates of different specifications, ensuring that this invention can be applied to the cleaning operation of filter plates of different sizes. At the same time, this invention also considers the difference in distance between the origin of the robotic arm and the upper edge of the filter plate during actual installation, ensuring that the robotic arm can be applied to the cleaning operation of different application scenarios.
[0108] 5) The robotic arm has an ingenious design, simple structure, and wide applicability. The robotic arm in this invention automatically resets after all cleaning operations are completed, occupies a small volume, and avoids collisions between its main components during movement, thus ensuring high safety.
[0109] 6) The control system is highly integrated and systematic. The automatic identification and cleaning method for dirt on the filter plates of a plate and frame filter press proposed in this invention takes a holistic approach, adopts a systematic structure, and optimizes the process from different angles to ensure that the control system has a good cleaning effect.
[0110] Example 2
[0111] This embodiment discloses a filter plate dirt identification and cleaning system.
[0112] A filter plate contaminant identification and cleaning system, comprising:
[0113] The identification and coverage module is configured to: identify dirt on the filter plate, determine the position, size and shape of a single piece of dirt, cover the single piece of dirt using the minimum circumscribed circle method, and determine the coordinates and radius of the minimum circumscribed circle of the single piece of dirt;
[0114] The cleaning sequence determination module is configured to: establish a coordinate system and determine the cleaning sequence of all individual dirt blocks based on the center coordinates of the smallest circumscribed circle of each dirt block;
[0115] The key point optimal pose determination module is configured to: determine multiple key points within the minimum outer circle of each single piece of dirt; solve the robot arm joint angles at each key point of the robot arm when the robot arm reaches each single piece of dirt according to the inverse kinematics algorithm of the robot arm; and obtain the optimal pose of each key point when the robot arm cleans all single pieces of dirt.
[0116] The cleaning module is configured to: control the robotic arm to perform fixed-point cleaning on multiple key points corresponding to a single piece of dirt based on the optimal pose of each key point when the robotic arm cleans all single pieces of dirt, and clean multiple single pieces of dirt sequentially based on the cleaning order of the single pieces of dirt, until all single pieces of dirt have been cleaned.
[0117] Example 3
[0118] The purpose of this embodiment is to provide a computer-readable storage medium.
[0119] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the filter plate dirt identification and cleaning method as described in Embodiment 1 of this disclosure.
[0120] Example 4
[0121] The purpose of this embodiment is to provide an electronic device.
[0122] An electronic device includes a memory, a processor, and a program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps in the filter plate dirt identification and cleaning method as described in Embodiment 1 of this disclosure.
[0123] The steps and methods involved in the apparatuses of Embodiments 2, 3, and 4 above correspond to those in Embodiment 1. For specific implementation details, please refer to the relevant description section of Embodiment 1. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood as including any medium capable of storing, encoding, or carrying an instruction set for execution by a processor and enabling the processor to perform any of the methods in this invention.
[0124] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computer devices. Optionally, they can be implemented using computer-executable program code, thereby allowing them to be stored in a storage device for execution by a computer device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. The present invention is not limited to any particular combination of hardware and software.
[0125] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.
Claims
1. A method for identifying and cleaning dirt on a filter plate, characterized in that, Includes the following steps: The filter plate is identified to determine the location, size, and shape of individual dirt particles. The smallest circumscribed circle method is used to cover the individual dirt particles, and the coordinates and radius of the smallest circumscribed circle of the individual dirt particles are determined. Establish a coordinate system and determine the cleaning sequence of all individual dirt blocks based on the center coordinates of the smallest circumcircle of each dirt block; Within the minimum circumcircle of each individual piece of dirt, multiple key points are determined. Based on the inverse kinematics algorithm of the robotic arm, the joint angles of the robotic arm at each key point of the individual piece of dirt are calculated, and the optimal pose of each key point of the robotic arm when cleaning all individual pieces of dirt is obtained. Based on the optimal pose of each key point when the robotic arm cleans all individual pieces of dirt, the robotic arm is controlled to perform fixed-point cleaning on multiple key points corresponding to each piece of dirt. Based on the cleaning order of individual pieces of dirt, multiple pieces of dirt are cleaned sequentially until all individual pieces of dirt are cleaned.
2. The filter plate dirt identification and cleaning method as described in claim 1, characterized in that, The process involves acquiring images of dirt on the filter plate, determining the color contrast between the dirt and the filter plate, and then using image segmentation algorithms or deep learning-based image segmentation methods to identify the dirt on the filter plate.
3. The filter plate dirt identification and cleaning method as described in claim 2, characterized in that, Establish a coordinate system on the filter plate dirt image, setting x as the horizontal axis and y as the vertical axis. The specific cleaning sequence for a single dirt block is as follows: Determine the regions where y ≥ 0 and y < 0, process the region where y ≥ 0 first, then process the region where y < 0; Compare the x-coordinates of all individual dirt particles within the region where y≥0, and sort them in ascending order of x-coordinate. For dirt particles with the same x-coordinate, compare their y-coordinates and sort them in ascending order of y-coordinate. Compare the x-coordinates of all individual dirt particles within the region where y < 0, and sort them in descending order of x-coordinate. For dirt particles with the same x-coordinate, compare the absolute values of their y-coordinates and sort them in ascending order of absolute values of their y-coordinates.
4. The filter plate dirt identification and cleaning method as described in claim 1, characterized in that: Based on the actual cleaning effect, the number and distribution of key points of the minimum circumcircle of each single piece of dirt are determined, each key point is numbered, and the multiple poses of the robotic arm reaching each key point are solved based on the inverse kinematics algorithm. Based on the preset optimal pose constraints of the robotic arm, the optimal poses of each key point when the robotic arm cleans all single pieces of dirt are obtained: under the premise that the main body parts of the robotic arm will not collide, the pose with the minimum movement distance of the robotic arm and the shortest cleaning time is taken as the optimal pose of the robotic arm to perform cleaning operation at a certain key point.
5. The filter plate dirt identification and cleaning method as described in claim 4, characterized in that, The robotic arm is controlled to clean one piece of dirt at a time using a linear feed and oscillation method. Assuming there are n key points within the smallest outer circle of the current single piece of dirt, control the robotic arm to reach the first key point according to the numbering order of the key points and the corresponding optimal pose; At this critical point, the robotic arm is controlled to perform a swing cleaning operation according to the set number of swings and swing amplitude; After the current key point is cleaned, proceed to the next key point according to the corresponding optimal pose, until all n key points within the smallest circumcircle of a single piece of dirt are cleaned.
6. The filter plate contaminant identification and cleaning method as described in claim 5, characterized in that, After all n key points within the smallest circumcircle of a single piece of dirt have been cleaned, the robotic arm is controlled to clean the next piece of dirt based on the cleaning sequence of the single piece of dirt.
7. The filter plate dirt identification and cleaning method as described in claim 1, characterized in that, After all individual dirt has been cleaned, the filter plate is re-image-recognized to determine if dirt still exists on the filter plate. If so, the dirt is cleaned again.
8. A filter plate contaminant identification and cleaning system, characterized in that: include: The identification and coverage module is configured to: identify dirt on the filter plate, determine the position, size and shape of a single piece of dirt, cover the single piece of dirt using the minimum circumscribed circle method, and determine the coordinates and radius of the minimum circumscribed circle of the single piece of dirt; The cleaning sequence determination module is configured to: establish a coordinate system and determine the cleaning sequence of all individual dirt blocks based on the center coordinates of the smallest circumscribed circle of each dirt block; The key point optimal pose determination module is configured to: determine multiple key points within the minimum outer circle of each single piece of dirt; solve the robot arm joint angles at each key point of the robot arm when the robot arm reaches each single piece of dirt according to the inverse kinematics algorithm of the robot arm; and obtain the optimal pose of each key point when the robot arm cleans all single pieces of dirt. The cleaning module is configured to: control the robotic arm to perform fixed-point cleaning on multiple key points corresponding to a single piece of dirt based on the optimal pose of each key point when the robotic arm cleans all single pieces of dirt, and clean multiple single pieces of dirt sequentially based on the cleaning order of the single pieces of dirt, until all single pieces of dirt have been cleaned.
9. A computer-readable storage medium having a program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps in the filter plate dirt identification and cleaning method as described in any one of claims 1-7.
10. An electronic device, comprising a memory, a processor, and a program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps in the filter plate dirt identification and cleaning method as described in any one of claims 1-7.