Cutting dust removal method and platform based on image processing

Abstract

The application provides a cutting dust removal method and platform based on image processing, and relates to data processing technology, wherein the method comprises the following steps: collecting the wood to be cut located in the cutting processing area, and determining the wood size of the wood to be cut based on the obtained first image; in response to the cutting unit cutting the wood to be cut, obtaining the real-time cutting position of the cutting tool included in the cutting unit on the wood to be cut, and controlling the dust removal unit to remove dust from the cutting processing area based on the initial dust removal parameters determined based on the wood size; when the current cutting chip production rate of the wood to be cut at the real-time cutting position meets the preset mutation condition based on the wood size, collecting the cutting processing area based on the real-time cutting position to obtain a second image; and updating the initial dust removal parameters based on the wood chip residue determined based on the second image to obtain target dust removal parameters. The application at least improves the dust removal efficiency.

Description

Technical Field

[0001] This invention relates to data processing technology, and more particularly to a cutting and dust removal method and platform based on image processing. Background Technology

[0002] In wood processing, cutting operations usually generate a large amount of wood dust. In order to ensure the cleanliness of the processing environment and the normal operation of machine tools, corresponding dust removal units are usually installed in the cutting area.

[0003] In related technologies, most cutting dust removal operations adopt a fixed parameter dust removal mode. That is, after the cutting equipment is started, the dust removal unit runs continuously with a pre-set single fixed power. Although some conventional dust removal platforms can perform simple opening and closing control according to the start and stop status of the machine tool, the dust removal air volume remains basically unchanged throughout the cutting process.

[0004] However, the above-mentioned conventional dust removal methods have certain limitations in practical applications. That is, since the size of the wood to be cut often varies, if uniform fixed dust removal parameters are used, when dealing with smaller wood with a lower basic cutting amount, the dust removal load will be excessive, resulting in unnecessary energy consumption; while when dealing with larger wood, the basic suction power is easily insufficient.

[0005] Therefore, there is an urgent need to provide an image processing-based cutting dust removal method and platform that can improve dust removal efficiency. Summary of the Invention

[0006] In view of the above problems, the present invention is proposed to provide an image processing-based cutting and dust removal method and platform that overcomes or at least partially solves the above problems.

[0007] According to one aspect of the present invention, a cutting and dust removal method based on image processing is provided, comprising the following steps: The wood to be cut in the cutting and processing area is collected, and the wood size of the corresponding wood to be cut is determined based on the obtained first image; The response cutting unit cuts the wood to be cut, obtains the real-time cutting position of the cutting tool in the cutting unit corresponding to the wood to be cut, and controls the dust removal unit to remove dust from the cutting area based on the initial dust removal parameters determined by the wood size. When the rate of change of the current cutting chips at the real-time cutting position of the wood to be cut, determined based on the wood size, meets the preset abrupt change condition, the cutting processing area is collected based on the real-time cutting position to obtain the second image; The initial dust removal parameters are updated based on the amount of sawdust residue determined by the second image to obtain the target dust removal parameters.

[0008] Optionally, in the method according to the invention, the wood to be cut located in the cutting processing area is collected, and the wood size corresponding to the wood to be cut is determined based on the obtained first image, including: The light projection unit is controlled to emit illumination light towards the cutting area, so that the wood to be cut forms wood projections located on different reference stops based on the illumination light. All reference stops are arranged in an array at different cutting feed positions along the cutting feed direction of the corresponding cutting area. The image acquisition unit is controlled to acquire images of each reference stop bar to obtain the first image; Along the direction perpendicular to the cutting feed direction, the projection occlusion length of each reference stop bar occluded by the wood projection is determined based on the first image, and the cutting section width of the wood to be cut corresponding to different cutting feed positions is determined based on the projection occlusion length. The distribution spacing between adjacent reference stops and the width of each cutting section corresponding to different cutting feed positions are determined as the wood size of the wood to be cut.

[0009] Optionally, in the method according to the invention, determining the projection occlusion length of each reference stop being occluded by the wood projection based on the first image includes: Determine each fluorescent marker that is pre-set in an array on each reference stop bar and distributed in a direction perpendicular to the cutting feed direction; When it is determined from the first image that there is a fluorescent marking area located on any reference barrier and indicating any fluorescent marker, the marking area is defined as a visible marking area; Determine the lateral marking distances between all visible marking areas located on the same reference stop and the wood projection along a direction perpendicular to the cutting feed direction, and determine the visible marking area with the smallest corresponding lateral marking distance as the boundary marking area; Based on the first image, fluorescent markers that correspond to the boundary marker area and are located on the same reference bar, and that do not have fluorescent marker areas, are identified as target markers, and the marker length of the corresponding target marker is identified as the projection occlusion length.

[0010] Optionally, in the method according to the present invention, obtaining the real-time cutting position of the cutting tool of the cutting unit corresponding to the wood to be cut, and controlling the dust removal unit to remove dust from the cutting area based on initial dust removal parameters determined by the wood size, includes: Based on the width of each cutting section corresponding to different cutting feed positions of the wood to be cut, different initial dust removal air volume values ​​are matched, and all initial dust removal air volume values ​​are combined into initial dust removal parameters. The fluorescent detection probe, which controls the movement of the cutting tool along the cutting feed direction, is used for detection. When the fluorescence detection probe passes any reference baffle arranged in an array along the cutting feed direction, a travel pulse count is generated based on the generated fluorescence signal; If the number of travel pulses is the same as the position sequence number corresponding to any cutting feed position, the cutting feed position is determined as the real-time cutting position of the corresponding cutting tool. The initial dust removal air volume value is retrieved based on the initial dust removal parameters and the corresponding real-time cutting position is controlled to remove dust from the cutting area based on the initial dust removal air volume value.

[0011] Optionally, in the method according to the invention, when it is determined that the fluorescence detection probe passes through any of the reference stops arranged in an array along the cutting feed direction, generating a travel pulse count based on the generated fluorescence signal includes: Determine the bar attributes corresponding to each reference bar, and define the reference bars with corresponding bar attributes as calibration attributes and normal attributes as calibration bars and normal bars, respectively. The fluorescent markers included in the calibration bars have a greater physical extension length along the cutting feed direction than those in the normal bars. Determine the duration of the same fluorescence signal output by the fluorescence detection probe, and compare the duration with a preset duration threshold. When the duration of the signal is determined to be less than the preset duration threshold, the reference bar corresponding to the fluorescence signal is determined to be a normal bar, and the travel pulse count is accumulated to obtain the updated travel pulse count; When the duration of the signal is determined to be not less than the preset duration threshold, the reference bar corresponding to the fluorescence signal is identified as the calibration bar, and the fluorescence signal is identified as the calibration signal. Obtain the calibration count for all corresponding calibration signals, and iterate through the retrieved bar position mapping table to correct the travel pulse count by adjusting the calibration mapping count for the corresponding calibration count.

[0012] Optionally, in the method according to the present invention, when the rate of change of the current cutting chips at the real-time cutting position corresponding to the wood to be cut, determined based on the wood size, satisfies a preset abrupt change condition, the cutting processing area is acquired based on the real-time cutting position to obtain a second image, including: The amount of cutting chips at different cutting feed positions is determined based on the distribution spacing and the width of the cutting section, and the amount of cutting chips at the corresponding real-time cutting position is determined as the real-time chip value. The average chip production of each cutting feed position corresponding to the preset cutting quantity, located before the real-time cutting position, is calculated along the cutting feed direction to obtain the historical chip production. The ratio of the difference between the real-time chip production value and the historical chip production value to the historical chip production value is calculated to obtain the chip production change rate. If the absolute value of the corresponding change rate of debris production is greater than the preset mutation threshold, it is determined that the preset mutation condition is met, and the interval time of the fluorescence detection probe passing through the adjacent reference baffle is obtained. The cutting feed speed is determined based on the interval duration and distribution spacing, and the cutting feed speed is multiplied by the falling time of the collected wood chips to obtain the falling chip offset length. The position corresponding to the real-time cutting position and the chip offset length is determined as the acquisition center along the direction opposite to the cutting feed direction, and the image acquisition unit is controlled to acquire the cutting processing area based on the acquisition center to obtain the second image.

[0013] Optionally, in the method according to the present invention, controlling the image acquisition unit to acquire images of the cutting processing area based on the acquisition center to obtain a second image includes: The acquisition length for the corresponding cutting feed direction is determined based on all cutting feed positions corresponding to the chip production change rate. When the chip production rate is determined to be a positive value, the width of the cutting section at the corresponding real-time cutting position is multiplied by the chip production rate, and the resulting width extension value is summed with the width of the cutting section at the corresponding real-time cutting position to obtain the first width in the direction perpendicular to the cutting feed direction. Based on the acquisition center, a sub-region for acquisition is determined within the cutting and processing area, corresponding to the first width and acquisition length; When the chip production rate is determined to be a negative value, the width of the cutting section at the corresponding real-time cutting position is determined as the second width in the direction perpendicular to the cutting feed direction, and a sub-region of acquisition corresponding to the second width and acquisition length is determined based on the acquisition center in the cutting processing area. The image acquisition unit is controlled to acquire images of the acquisition sub-region to obtain a second image.

[0014] Optionally, in the method according to the invention, updating the initial dust removal parameters based on the amount of sawdust residue determined by the second image to obtain target dust removal parameters includes: Determine each image pixel that makes up the second image, and if any image pixel is located in the same preset pixel range as the corresponding sawdust pixel retrieved, determine that image pixel as the acquisition pixel. The acquisition sub-region is divided into arrays, and the proportion of debris distribution of the acquisition pixels corresponding to each unit of evaluation grid is determined. If any proportion of debris distribution exceeds a preset proportion threshold, the unit evaluation grid corresponding to that proportion of debris distribution will be determined as the primary evaluation grid; otherwise, it will be determined as the secondary evaluation grid. Adjacent primary evaluation grids are identified as central stacking groups, and based on the second image, all secondary evaluation grids of adjacent central stacking groups are identified as edge dispersion groups that have a cooperative relationship with the central stacking group. Obtain the number of primary evaluation grids corresponding to all primary evaluation grids located in the same central accumulation group, and calculate the average of the secondary evaluation grids based on the proportion of debris distribution for all secondary evaluation grids located in the same edge dispersion group to obtain the average proportion of secondary evaluation grids. The number of primary grids and the average proportion of secondary grids corresponding to the same collaborative relationship are weighted and summed based on normalization. The amount of residual wood chips is determined based on the obtained accumulation characteristic value. The initial dust removal parameters are then updated based on the amount of residual wood chips to obtain the target dust removal parameters.

[0015] Optionally, in the method according to the invention, determining the residual amount of sawdust based on the obtained stacking characteristic value, and updating the initial dust removal parameters based on the residual amount of sawdust to obtain the target dust removal parameters, includes: The amount of sawdust residue is obtained by summing all the stacking characteristic values ​​corresponding to different cooperative relationships. The ratio of the largest corresponding accumulation characteristic value to the residual amount of sawdust is calculated to obtain the residual concentration coefficient. When it is determined that the amount of residual wood chips is greater than the preset qualified threshold, the coefficient is adjusted based on the proportion of the amount of residual wood chips exceeding the preset qualified threshold. When the residual concentration coefficient is determined to be greater than the preset concentration threshold, the basic adjustment coefficient is multiplied by the first multiplier to obtain the first air volume adjustment coefficient; otherwise, it is multiplied by the second multiplier which is less than the first multiplier to obtain the second air volume adjustment coefficient. When it is determined that the residual amount of wood chips is less than the preset energy-saving threshold, the air volume reduction coefficient is obtained based on the lower proportion of the residual amount of wood chips corresponding to the preset qualified threshold. The initial dust removal parameters are updated based on the air volume adjustment coefficient or the air volume reduction coefficient to obtain the target dust removal parameters.

[0016] According to another aspect of the present invention, an image processing-based cutting and dust removal platform is provided, comprising: The size determination module is configured to acquire images of the wood to be cut located in the cutting processing area and determine the wood size of the corresponding wood to be cut based on the obtained first image. The initial dust removal module is configured to respond to the cutting unit cutting the wood to be cut, obtain the real-time cutting position of the cutting blades included in the cutting unit corresponding to the wood to be cut, and control the dust removal unit to remove dust from the cutting processing area based on the initial dust removal parameters determined by the wood size. The mutation determination module is configured to acquire a second image by collecting data from the cutting processing area based on the real-time cutting position when the rate of change of the current cutting chips at the real-time cutting position corresponding to the wood to be cut, which is determined based on the wood size, meets the preset mutation condition. The dust removal module is updated and configured to update the initial dust removal parameters based on the amount of sawdust residue determined by the second image, so as to obtain the target dust removal parameters.

[0017] According to the solution of the present invention, the present invention has the following beneficial effects: First, the present invention configures the initial dust removal parameters based on the size of the wood to be cut, replacing the single-power dust removal method, and achieves a reasonable match between dust removal energy consumption and wood size. At the same time, by monitoring the chip production change rate in real time and triggering image acquisition, the initial dust removal parameters are updated based on the residual amount of wood chips determined by the second image, so that the dust removal unit has the ability to adaptively compensate for abnormal chip production fluctuations and improves dust removal efficiency. Secondly, the present invention uses a light projection unit to make the wood to be cut form a wood projection on the reference stop bar, and uses various fluorescent markers to help determine the projection occlusion length, thereby realizing the quantitative measurement of the width of the cutting section. This transforms the recognition of complex wood contours into feature extraction of fluorescent marker areas, reducing the computational power requirement for visual processing and effectively suppressing the interference of dust on recognition accuracy. Next, the present invention generates a travel pulse count by using a fluorescent detection probe that moves with the cutting tool and each reference baffle. It then corrects the travel pulse count by combining the physical extension length of the calibrated baffle and the baffle position mapping table. This effectively eliminates the cumulative error in the travel pulse count caused by sawdust adhesion or long-term operation, ensuring that the dust removal unit can accurately trace the real-time cutting position and synchronously call the dust removal air volume value. Then, when the chip production rate meets the preset abrupt change condition, the present invention can combine the cutting feed speed and the chip falling time to determine the chip offset length, thereby accurately locating the collection center, and dynamically expanding and contracting the geometric boundary of the collection sub-region according to the chip production rate, thereby avoiding blind collection of the cutting processing area. Finally, this invention establishes a unit evaluation grid to collaboratively evaluate the average number of primary grids in the central accumulation group and the secondary proportion of the peripheral dispersion group, thereby calculating the amount of wood chips residue and the residue concentration coefficient. Based on the residue concentration coefficient, the air volume adjustment coefficient is multiplied. While ensuring the cleaning effect of high-density accumulation areas, the air volume adjustment coefficient effectively reduces the equipment energy consumption of corresponding low-pollution working conditions. Attached Figure Description

[0018] Figure 1 A flowchart of an image processing-based cutting dust removal method according to an embodiment of the present invention is shown; Figure 2 A schematic diagram of the corresponding reference stop bar setting in this embodiment is shown; Figure 3 A structural block diagram of an image processing-based cutting and dust removal platform according to another embodiment of the present invention is shown. Detailed Implementation

[0019] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0020] To address the problems existing in the prior art, the inventors proposed the solution of this invention. One embodiment of this invention provides a cutting and dust removal method based on image processing. This method can be executed in a computing device, wherein the computing device can be understood as a terminal with data processing capabilities, such as a computer.

[0021] Figure 1 A flowchart of an image processing-based cutting dust removal method according to an embodiment of the present invention is shown, such as... Figure 1 As shown, the method begins with step S1, which includes the following: The wood to be cut in the cutting and processing area is collected, and the wood size of the corresponding wood to be cut is determined based on the obtained first image.

[0022] For example, this embodiment can be based on a server to execute a corresponding image processing-based cutting and dust removal method. Specifically, in step S1, when the server receives a cutting instruction for the wood to be cut, in order to ensure the safe operation of subsequent processing and the efficient implementation of dust removal, the server can control a preset image acquisition unit to acquire images of the wood to be cut currently placed in the cutting area, thereby obtaining a first image containing the wood to be cut before it has been cut. Subsequently, the server will analyze the acquired first image to determine the wood size of the wood to be cut. Here, the determined wood size is mainly used to reflect the spatial occupancy data of the wood to be cut in the cutting area.

[0023] It should be noted that, in this embodiment, the cutting processing area can be understood as the cutting processing area on the machine tool equipment used to place wood and for the cutting action to be performed by the cutting tool, while the first image is mainly used to record the corresponding scene of the wood to be cut before it is cut.

[0024] It can be noted that, in this embodiment, by obtaining the wood dimensions in advance through this step, the server can know in advance the space occupied by the wood to be cut.

[0025] Furthermore, in this embodiment, the aforementioned "collecting images of the wood to be cut located in the cutting processing area and determining the wood size of the corresponding wood to be cut based on the obtained first image" may further include the following steps: The light projection unit is controlled to emit illumination light towards the cutting area, so that the wood to be cut forms wood projections located on different reference stops based on the illumination light. All reference stops are arranged in an array at different cutting feed positions along the cutting feed direction of the corresponding cutting area. The image acquisition unit is controlled to acquire images of each reference stop bar to obtain the first image; Along the direction perpendicular to the cutting feed direction, the projection occlusion length of each reference stop bar occluded by the wood projection is determined based on the first image, and the cutting section width of the wood to be cut corresponding to different cutting feed positions is determined based on the projection occlusion length. The distribution spacing between adjacent reference stops and the width of each cutting section corresponding to different cutting feed positions are determined as the wood size of the wood to be cut.

[0026] For example, Figure 2 This embodiment shows a schematic diagram of the corresponding reference stop bar configuration, where, for example... Figure 2 As shown, in this embodiment, when it is necessary to obtain the dimensions of the wood to be cut, the server can first control the light projection unit pre-set at the top of the cutting processing area to emit irradiation light towards the cutting processing area. It can be explained that as the irradiation light is emitted, the wood to be cut placed on the cutting processing area will be physically blocked by the irradiation light, thus leaving a shadow outline on the cutting processing area below it. At this time, since multiple reference baffles are pre-set in the cutting processing area, and these reference baffles are arranged in an array along the direction in which the wood to be cut will be pushed, the shadow outline generated by the wood to be cut can be projected and covered on the reference baffles at different cutting feed positions, forming corresponding wood projections. Thus, the wood outline in three-dimensional space can be mapped onto the two-dimensional baffle surface. Here, as... Figure 2 As shown, the reference stop can be embedded into the surface of the cutting area; Next, the server controls the image acquisition unit to acquire images of the current cutting area, obtaining a first image. This first image records the projection distribution on each reference stop; thus, the identification of the wood's dimensions is converted into the extraction of the occlusion features of the reference stops. Then, along the direction perpendicular to the cutting feed direction, the server can calculate the corresponding size of each reference bar occluded by the wood projection based on the first image, and use this as the length of each projection occlusion. It can be explained that, based on the physical characteristics of vertical light projection, the physical edge of the wood entity and the shadow boundary on the corresponding reference bar are mapped in the vertical direction. Based on this relationship, the server can effectively determine the obtained projection occlusion length as the width of the cutting section of the wood to be cut at the corresponding cutting feed position. Finally, based on the distribution spacing between adjacent reference bars, the server can use the fixed distribution spacing as the longitudinal length reference, and splice and combine it with the width of each cutting section located at different cutting feed positions obtained above, thereby determining the overall wood size of the corresponding wood to be cut. The distribution spacing can be set based on actual needs, and this embodiment does not limit it.

[0027] It should be noted that in this embodiment, the light projection unit can be an illumination device that provides a stable light source, the reference baffle is a rigid reference component fixed on the cutting processing area and arranged at specific intervals, and the wood projection is a physical occlusion area formed on the surface of the baffle after the wood block the irradiated light. It can be explained that, here, this embodiment uses the measurement logic of the arrayed reference baffles and optical projection to realize the quantitative measurement of the shape of the wood to be cut by utilizing the physical occlusion relationship, effectively reducing the computing power requirement for global image feature extraction and improving the visual inspection anti-interference capability in the processing site environment.

[0028] It can be noted that in this embodiment, the detection logic that combines the array of reference baffles with optical projection reduces the computational power requirement for visual processing, while the physical occlusion relationship enables the quantitative measurement of various irregular wood shapes, which meets the corresponding requirements of industrial sites for response speed and anti-interference capability.

[0029] Furthermore, in this embodiment, the aforementioned "determining the projection occlusion length of each reference stop bar occluded by the wood projection based on the first image" may further include the following steps: Determine each fluorescent marker that is pre-set in an array on each reference stop bar and distributed in a direction perpendicular to the cutting feed direction; When it is determined from the first image that there is a fluorescent marking area located on any reference barrier and indicating any fluorescent marker, the marking area is defined as a visible marking area; Determine the lateral marking distances between all visible marking areas located on the same reference stop and the wood projection along a direction perpendicular to the cutting feed direction, and determine the visible marking area with the smallest corresponding lateral marking distance as the boundary marking area; Based on the first image, fluorescent markers that correspond to the boundary marker area and are located on the same reference bar, and that do not have fluorescent marker areas, are identified as target markers, and the marker length of the corresponding target marker is identified as the projection occlusion length.

[0030] For example, in this embodiment, the server determines each fluorescent marker pre-set on each reference bar; wherein each fluorescent marker is distributed in an array with equal spacing along a direction perpendicular to the cutting feed direction; Next, since the projection of the wood to be cut will partially block the reference bar, the fluorescent features of the corresponding area will be blocked. Based on this, the server can identify the display area on the reference bar that still has fluorescent features by extracting features from the first image. Once the fluorescent marking area is determined to exist, the server will identify it as a visible marking area to characterize the exposed part of the bar that is not blocked by the wood entity. Then, along the direction perpendicular to the cutting feed direction, the server can calculate the lateral marking distance between all visible marking areas on the same reference stop and the edge of the wood projection, and filter out the visible marking area with the smallest corresponding lateral marking distance, and determine it as the boundary marking area; it can be explained that by determining the corresponding visible marking area with the smallest lateral marking distance, the marking feature points adjacent to the wood projection boundary can be accurately determined. Finally, the server uses the boundary marker area as a reference, and extracts and integrates the occluded fluorescent markers that have lost fluorescence feedback and do not have fluorescent marker areas on the corresponding reference bar based on the first image, and uniformly determines them as target markers; based on the known physical length dimensions of each fluorescent marker, the server calculates the total marker length by summarizing and calculating the number of markers within the target marker range, and uses it as the corresponding projection occlusion length.

[0031] It should be noted that in this embodiment, the fluorescent marker can be a physically luminescent scale that is set on the surface of the baffle and has visual recognition. The visible marking area is the exposed part that is not obscured by the wood projection. It can be noted that this embodiment can effectively resist the visual interference of the dusty environment at the processing site by introducing the high contrast characteristics of fluorescent material to assist in determining the obscuration range, thereby improving the accuracy of the projection obscuration length calculation.

[0032] Step S2 includes the following: The response cutting unit cuts the wood to be cut, obtains the real-time cutting position of the cutting blades in the cutting unit corresponding to the wood to be cut, and controls the dust removal unit to remove dust from the cutting area based on the initial dust removal parameters determined by the wood size.

[0033] For example, in this embodiment, when the server controls the cutting unit to start performing cutting operations on the wood to be cut, the server synchronously obtains the current travel position of the cutting tool inside the cutting unit, and then determines the real-time cutting position of the corresponding wood to be cut; it can be explained that by obtaining the real-time cutting position, the server can determine the dynamic source of the current chip generation, so that the dust removal and monitoring operations are coordinated with the cutting progress. Simultaneously, the server retrieves the previously determined wood dimensions, assesses the expected chip production scale under normal cutting conditions based on the wood dimensions, and then matches the corresponding initial dust removal parameters; subsequently, the server can control the dust removal unit to perform dust removal operations on the cutting processing area based on the initial dust removal parameters, wherein the dust removal unit can be a device with a dust suction function; It should be noted that in this embodiment, the real-time cutting position refers to the dynamic position of the cutting tool on the processing path, and the initial dust removal parameter refers to the basic dust removal value used by the server under normal processing conditions. It can be explained that since the amount of basic wood chips generated during cutting varies for wood entities with different cutting cross-sectional widths, this embodiment dynamically determines the initial dust removal parameter based on the wood size, avoiding the energy waste caused by using a single fixed dust removal power, and achieving a precise match between the dust removal energy consumption and the actual chip load in the basic processing stage.

[0034] Furthermore, in this embodiment, the aforementioned "obtaining the real-time cutting position of the cutting tool in the cutting unit corresponding to the wood to be cut, and controlling the dust removal unit to remove dust from the cutting area based on the initial dust removal parameters determined by the wood size" may further include the following steps: Based on the width of each cutting section corresponding to different cutting feed positions of the wood to be cut, different initial dust removal air volume values ​​are matched, and all initial dust removal air volume values ​​are combined into initial dust removal parameters. The fluorescent detection probe, which controls the movement of the cutting tool along the cutting feed direction, is used for detection. When the fluorescence detection probe passes any reference baffle arranged in an array along the cutting feed direction, a travel pulse count is generated based on the generated fluorescence signal; If the number of travel pulses is the same as the position sequence number corresponding to any cutting feed position, the cutting feed position is determined as the real-time cutting position of the corresponding cutting tool. The initial dust removal air volume value is retrieved based on the initial dust removal parameters and the corresponding real-time cutting position is controlled to remove dust from the cutting area based on the initial dust removal air volume value.

[0035] For example, in this embodiment, the server first matches the corresponding initial dust removal air volume value for each cutting section width at different cutting feed positions based on the wood size obtained in the aforementioned steps; based on the physical law that the section width is related to the expected amount of chips, the server matches the corresponding air volume value for different widths; then, the server splices and combines all the initial dust removal air volume values ​​matched at each cutting feed position in the order of movement to construct the initial dust removal parameters; As the cutting tool advances along the cutting feed direction, the server can synchronously control the fluorescent detection probe that moves with the cutting tool to perform real-time detection. When the fluorescent detection probe passes any of the arrayed reference bars, the fluorescent detection probe can be excited by the fluorescent features on the reference bar and feed back a fluorescent signal. At this time, the server can accumulate and generate a corresponding travel pulse count based on the fluorescent signal. Furthermore, since each cutting feed position corresponds to a known position sequence number, the server can compare and verify the real-time accumulated travel pulse count with each position sequence number. When the current travel pulse count is found to be consistent with the position sequence number of any cutting feed position, the server can determine that cutting feed position as the current real-time cutting position of the corresponding cutting tool. Finally, after determining the current real-time cutting position of the tool, the server retrieves the initial dust removal airflow value corresponding to the real-time cutting position based on the pre-built initial dust removal parameters, and controls the dust removal unit to perform dynamic dust removal operations on the current cutting processing area based on the initial dust removal airflow value.

[0036] It should be noted that in this embodiment, the fluorescence detection probe refers to a photoelectric sensor used to identify luminescent features, the traveling pulse count refers to a counting parameter that converts continuous physical displacement into discrete digital signals, and the initial dust removal air volume value refers to the basic dust removal control amount allocated to a specific width of wood under the condition of no chip production abnormality. Its specific value can be set based on actual hardware parameters. It can be noted that this embodiment achieves precise linkage between dust removal power and real-time physical position of the tool by presetting the dust removal air volume in a spatial sequence and dynamically retrieving it in combination with pulse positioning.

[0037] Furthermore, in this embodiment, the aforementioned "when it is determined that the fluorescence detection probe passes through any of the reference stops arranged in an array along the cutting feed direction, generating a travel pulse count based on the generated fluorescence signal" may further include the following steps: Determine the bar attributes corresponding to each reference bar, and define the reference bars with corresponding bar attributes as calibration attributes and normal attributes as calibration bars and normal bars, respectively. The fluorescent markers included in the calibration bars have a greater physical extension length along the cutting feed direction than those in the normal bars. Determine the duration of the same fluorescence signal output by the fluorescence detection probe, and compare the duration with a preset duration threshold. When the duration of the signal is determined to be less than the preset duration threshold, the reference bar corresponding to the fluorescence signal is determined to be a normal bar, and the travel pulse count is accumulated to obtain the updated travel pulse count; When the duration of the signal is determined to be not less than the preset duration threshold, the reference bar corresponding to the fluorescence signal is identified as the calibration bar, and the fluorescence signal is identified as the calibration signal. Obtain the calibration count for all corresponding calibration signals, and iterate through the retrieved bar position mapping table to correct the travel pulse count by adjusting the calibration mapping count for the corresponding calibration count.

[0038] For example, in this embodiment, in order to eliminate the cumulative error of pulses caused by environmental factors such as wood chips covering the surface and to ensure the long-term stability of spatial positioning, the server can predetermine the attributes of each reference bar. It should be noted that, in terms of physical layout, the bar attributes are divided into calibration attributes and ordinary attributes, corresponding to calibration bars and ordinary bars. The physical extension length of the fluorescent marker on the calibration bar along the cutting feed direction is significantly greater than that of the ordinary bar. Next, as the probe moves with the cutting tool, the server acquires the duration of the same fluorescence signal output by the fluorescence detection probe in real time, and compares the measured duration of the signal with a preset duration threshold. It can be noted that the preset duration threshold can be determined based on the physical extension length of the corresponding calibration bar, but this embodiment does not limit it. In one case, when it is determined that the duration of the signal is less than a preset duration threshold, the reference bar that excites the fluorescence signal is determined to be a normal bar. At this time, the server can execute the conventional accumulation logic to accumulate the original travel pulse count and obtain the updated travel pulse count. In another scenario, when the duration of the signal is determined to be not less than the preset duration threshold, the server determines that the corresponding reference bar is a calibration bar and identifies the fluorescence signal as a calibration signal. Subsequently, the server can obtain the calibration count of all calibration signals triggered during the processing, and iterate through the pre-stored bar position mapping table to extract the calibration mapping count corresponding to the calibration count. The calibration mapping count is then used to cover and correct the current travel pulse count that may have deviations.

[0039] It should be noted that in this embodiment, the calibration bar refers to the physical reference point used to eliminate positioning errors, the signal duration refers to the time span of the probe sensing fluorescence feedback, and the bar position mapping table is a pre-set position coordinate lookup table, which can be stored in the server in advance. It can be explained that this embodiment effectively eliminates the cumulative positioning errors caused by long-term operation and physical obstruction by combining the long and short physical scales and the signal duration lookup table correction mechanism, thereby improving the positioning reliability in complex environments.

[0040] To illustrate with a specific application scenario: Assume that in the set baffle array, one calibration baffle is set every 9 ordinary baffles (i.e., the 10th baffle is the first calibration baffle), and the baffle position mapping table records the calibration mapping count corresponding to the first calibration signal as 10; In actual processing, if the first four ordinary baffles are detected normally, the pulse count accumulates to 4. When the fifth ordinary baffle is covered by dust, causing the probe to miss a reading, the pulse count does not trigger accumulation and remains at 4. When the probe continues to pass the sixth to ninth ordinary baffles, the pulse count accumulates from 4 to 5 to 8 respectively. At this time, the system coordinate record deviates from the actual physical position. Subsequently, when the probe passes the 10th calibration baffle, based on its longer physical extension, the server detects that the signal duration is not less than the preset duration threshold, confirms the triggering of the first calibration signal, and updates the calibration count to 1. The server then uses this calibration count to traverse the baffle position mapping table, extracts the corresponding calibration mapping count 10, and directly overwrites the current deviation travel pulse count 8 with this value 10. It can be explained that through this correction mechanism, the server resets the deviation position coordinates to accurate physical coordinates, avoids the accumulation of errors, and ensures the accuracy of subsequent dynamic retrieval of dust removal airflow parameters.

[0041] Step S3 includes the following: When the rate of change of the current cutting chips at the real-time cutting position of the wood to be cut, determined based on the wood size, meets the preset abrupt change condition, the cutting processing area is collected based on the real-time cutting position to obtain the second image.

[0042] For example, in this embodiment, as the cutting tool advances along the cutting feed direction, the server can continuously monitor the chip production characteristics at the current cutting point by combining the pre-acquired wood dimensions. Since the geometric width of different parts of the wood to be cut is different, the actual amount of chips produced during the cutting process will fluctuate dynamically. Based on this, when the server determines that the chip production rate of the wood to be cut at the current real-time cutting position exceeds the normal processing fluctuation range, that is, when the preset sudden change condition is met, it indicates that an abnormal increase or large accumulation of wood chips has occurred at the current cutting position. In addition, to obtain on-site images of this abnormal working condition, the server can perform coordinate tracing based on the real-time cutting position. That is, the server can control the image acquisition unit to acquire images of the current cutting processing area to obtain a second image.

[0043] It should be noted that in this embodiment, the sawdust production change rate is a dynamic numerical indicator that indicates a sudden change in the amount of sawdust produced during spatial propagation. The preset mutation condition refers to the abnormal judgment threshold used to filter reasonable fluctuations in normal cutting. Here, the second image is different from the first image that records the wood to be cut. Since the second image is based on the cutting tool after cutting the wood, its content may include splashed or scattered sawdust. It can be noted that this embodiment effectively obtains the corresponding image required for dust removal intervention by triggering directional image acquisition at the sawdust production mutation node, providing a data basis for subsequent calculation of sawdust residue and dynamic adjustment of dust removal strategy.

[0044] Furthermore, in this embodiment, the aforementioned "when the rate of change of the current cutting chips at the real-time cutting position corresponding to the wood to be cut, determined based on the wood size, meets the preset abrupt change condition, and the cutting processing area is acquired based on the real-time cutting position to obtain a second image" may further include the following steps: The amount of cutting chips at different cutting feed positions is determined based on the distribution spacing and the width of the cutting section, and the amount of cutting chips at the corresponding real-time cutting position is determined as the real-time chip value. The average chip production of each cutting feed position corresponding to the preset cutting quantity, located before the real-time cutting position, is calculated along the cutting feed direction to obtain the historical chip production. The ratio of the difference between the real-time chip production value and the historical chip production value to the historical chip production value is calculated to obtain the chip production change rate. If the absolute value of the corresponding change rate of debris production is greater than the preset mutation threshold, it is determined that the preset mutation condition is met, and the interval time of the fluorescence detection probe passing through the adjacent reference baffle is obtained. The cutting feed speed is determined based on the interval duration and distribution spacing, and the cutting feed speed is multiplied by the falling time of the collected wood chips to obtain the falling chip offset length. The position corresponding to the real-time cutting position and the chip offset length is determined as the acquisition center along the direction opposite to the cutting feed direction, and the image acquisition unit is controlled to acquire the cutting processing area based on the acquisition center to obtain the second image.

[0045] For example, in this embodiment, the server can calculate the amount of cutting chips corresponding to different cutting feed positions based on the preset distribution spacing of adjacent reference bars and the aforementioned determined cutting section width, and determine the amount of cutting chips corresponding to the real-time cutting position as the real-time chip value. Subsequently, along the cutting feed direction, the server selects each cutting feed position corresponding to the preset cutting quantity before the real-time cutting position, calculates the average amount of cutting chips at each cutting feed position to obtain the historical chip production amount; then, the chip production difference between the real-time chip production value and the historical chip production amount is calculated as a ratio to the historical chip production amount to obtain the chip production change rate. When the absolute value of the chip production change rate is greater than the preset mutation threshold, it indicates that the chip production at the current cutting position has undergone a significant step change compared to the historical stable state. The original initial dust removal parameters can no longer match the current chip production load, which means that the corresponding preset mutation condition is met. At this time, the server immediately obtains the interval time between the fluorescent detection probe passing through two adjacent reference baffles, and calculates the cutting feed speed by the ratio of the distribution spacing to the interval time. Further, the server can multiply the cutting feed speed with the pre-retrieved chip falling time to obtain the chip offset length. It can be noted that the chip falling time can be set based on actual needs, and this embodiment does not limit it. Based on the physical characteristics of material stagnation, the server can determine the location of the chip offset length corresponding to the real-time cutting position as the acquisition center along the direction opposite to the cutting feed direction, and control the image acquisition unit to acquire the cutting processing area based on the acquisition center to obtain the second image.

[0046] It should be noted that, in this embodiment, historical chip production refers to the average chip production value maintained by the machine tool before the sudden change in chip production. Chip fall time refers to the physical settling constant of the chips due to gravity and the exhaust airflow. Chip offset length characterizes the spatial physical misalignment distance caused by material stagnation. Furthermore, the aforementioned preset cutting quantity and chip fall time parameters can be set based on actual application requirements; this embodiment does not impose specific limitations on them.

[0047] Furthermore, in this embodiment, the aforementioned "controlling the image acquisition unit to acquire images of the cutting processing area based on the acquisition center to obtain a second image" may further include the following steps: The acquisition length for the corresponding cutting feed direction is determined based on all cutting feed positions corresponding to the chip production change rate. When the chip production rate is determined to be a positive value, the width of the cutting section at the corresponding real-time cutting position is multiplied by the chip production rate, and the resulting width extension value is summed with the width of the cutting section at the corresponding real-time cutting position to obtain the first width in the direction perpendicular to the cutting feed direction. Based on the acquisition center, a sub-region for acquisition is determined within the cutting and processing area, corresponding to the first width and acquisition length; When the chip production rate is determined to be a negative value, the width of the cutting section at the corresponding real-time cutting position is determined as the second width in the direction perpendicular to the cutting feed direction, and a sub-region of acquisition corresponding to the second width and acquisition length is determined based on the acquisition center in the cutting processing area. The image acquisition unit is controlled to acquire images of the acquisition sub-region to obtain a second image.

[0048] For example, in this embodiment, in order to reduce the image acquisition range and improve data processing efficiency, the server can determine the longitudinal acquisition length along the cutting feed direction based on all cutting feed positions corresponding to the chip production change rate. Subsequently, the server can determine the horizontal data collection boundary based on the specific trend of the chip production change rate. In one scenario, when the rate of change in wood chips is determined to be positive, it indicates that the wood chips exhibit a physical trend of expanding and splashing outwards. In this case, the server multiplies the width of the cutting section corresponding to the real-time cutting position with the rate of change in wood chips. Furthermore, the obtained width expansion value can be summed with the width of the cutting section to obtain a first width corresponding to the direction perpendicular to the cutting feed direction. Further, the server can define a sub-region of acquisition corresponding to the geometric boundary within the cutting processing area based on the aforementioned determined acquisition center and in combination with the first width and the longitudinal acquisition length. In another case, when the rate of change of chip production is determined to be a negative value, it indicates that the amount of chip production is weakening and the corresponding lateral scattering range is shrinking. In this case, the server can use and determine the width of the cutting section corresponding to the real-time cutting position as the second width corresponding to the direction perpendicular to the cutting feed direction. Similarly, in this case, the server can define the corresponding acquisition sub-region based on the acquisition center, combined with the second width and the longitudinal acquisition length. Furthermore, after determining the two-dimensional spatial boundary of the corresponding acquisition sub-region, the server can control the image acquisition unit to perform directional acquisition of the acquisition sub-region, thereby obtaining a second image focused on the location of the debris.

[0049] It should be noted that in this embodiment, the collection sub-region is a geometric rectangular region whose length and width dimensions dynamically expand and contract with the degree of physical dust splashing. The first width corresponding to the positive value reflects the expansion boundary when a large amount of material is ejected outward, while the second width corresponding to the negative value reflects the normal boundary when the scattering abnormally weakens. It can be explained that this embodiment can achieve precise focusing on abnormal dust production areas by dynamically delineating the collection sub-region by combining the positive and negative values ​​of the dust production change rate.

[0050] Step S4 includes the following: The initial dust removal parameters are updated based on the amount of sawdust residue determined by the second image to obtain the target dust removal parameters.

[0051] For example, in this embodiment, after acquiring the second image, the server can perform image analysis on the second image to calculate the actual accumulation scale of the sawdust currently remaining in the cutting and processing area, and then determine the corresponding sawdust residue; thereby, intuitive image features can be transformed into numerical indicators that can be used to quantify dust load. Subsequently, the server can dynamically adjust the original initial dust removal parameters based on the specific value of the residual wood chips, generate target dust removal parameters that match the current abnormal accumulation conditions, and send the target dust removal parameters to the dust removal unit to control it to perform the corresponding dust removal operation.

[0052] It should be noted that in this embodiment, the residual amount of sawdust refers to the total amount of sawdust physically retained in the cutting and processing area that has not been discharged by the conventional dust removal airflow, and the target dust removal parameter refers to the dust removal execution command that has been reconfigured after evaluation. It can be explained that this embodiment achieves adaptive linkage between the energy consumption output of the dust removal unit and the degree of dust pollution on site by dynamically updating the dust removal parameters based on the residual amount of sawdust after determining a sudden change in sawdust production. This effectively removes abnormal sawdust accumulation while taking into account the energy-saving needs of the dust removal unit.

[0053] Furthermore, in this embodiment, the aforementioned "updating the initial dust removal parameters based on the amount of residual wood chips determined by the second image to obtain the target dust removal parameters" may further include the following steps: Determine each image pixel that makes up the second image, and if any image pixel is located in the same preset pixel range as the corresponding sawdust pixel retrieved, determine that image pixel as the acquisition pixel. The acquisition sub-region is divided into arrays, and the proportion of debris distribution of the acquisition pixels corresponding to each unit of evaluation grid is determined. If any proportion of debris distribution exceeds a preset proportion threshold, the unit evaluation grid corresponding to that proportion of debris distribution will be determined as the primary evaluation grid; otherwise, it will be determined as the secondary evaluation grid. Adjacent primary evaluation grids are identified as central stacking groups, and based on the second image, all secondary evaluation grids of adjacent central stacking groups are identified as edge dispersion groups that have a cooperative relationship with the central stacking group. Obtain the number of primary evaluation grids corresponding to all primary evaluation grids located in the same central accumulation group, and calculate the average of the secondary evaluation grids based on the proportion of debris distribution for all secondary evaluation grids located in the same edge dispersion group to obtain the average proportion of secondary evaluation grids. The number of primary grids and the average proportion of secondary grids corresponding to the same collaborative relationship are weighted and summed based on normalization. The amount of residual wood chips is determined based on the obtained accumulation characteristic value. The initial dust removal parameters are then updated based on the amount of residual wood chips to obtain the target dust removal parameters.

[0054] For example, in this embodiment, the server extracts each image pixel that makes up the second image and compares the pixel value of any image pixel with a preset pixel range. When the pixel value of any image pixel falls into the preset pixel range, it indicates that the image pixel reflects the presence of wood chips. At this time, the server can determine it as the collection pixel that represents the wood chips. Next, the server can divide the collection sub-region into a two-dimensional array to obtain multiple unit evaluation grids, and determine the number of collection pixels contained in each unit evaluation grid in turn, thereby calculating the proportion of debris distribution corresponding to each unit evaluation grid. Subsequently, the server compares the debris distribution ratio of each unit evaluation grid with the retrieved preset ratio threshold. If any debris distribution ratio is greater than the preset ratio threshold, the server can determine the unit evaluation grid corresponding to the debris distribution ratio as the primary evaluation grid; otherwise, if it is not greater than the preset ratio threshold, it is determined as the secondary evaluation grid. Here, the preset ratio threshold can be set based on actual needs, and this embodiment does not limit it. Furthermore, the server can identify adjacent primary evaluation grids as central stacking groups, and based on the second image, divide all secondary evaluation grids that are adjacent to the central stacking group and have the corresponding periphery into edge dispersion groups, while determining that the central stacking group and its corresponding edge dispersion group have a cooperative relationship. Furthermore, the server can obtain the number of primary evaluation grids in all primary evaluation grids located in the same central accumulation group, and calculate the average proportion of wood chip distribution in all secondary evaluation grids located in the same edge dispersion group to obtain the average proportion of secondary grids. At the same time, the server can perform a normalized weighted summation of the number of primary grids corresponding to the same cooperative relationship and the average proportion of secondary grids to obtain the accumulation characteristic value, and determine the amount of wood chip residue based on the accumulation characteristic value. Thus, the initial dust removal parameters can be updated based on the amount of wood chip residue, and the target dust removal parameters can be output. It should be noted that in this embodiment, the central accumulation group corresponds to the high-density sawdust aggregation area, while the edge dispersion group corresponds to the peripheral dispersion area formed by sawdust splashing. In addition, the number of primary grids characterizes the physical coverage scale of the aggregation area, while the average secondary proportion characterizes the dispersion concentration of the peripheral dispersion area. It can be explained that this embodiment comprehensively quantifies the spatial accumulation pattern of abnormal sawdust by synergistically weighting the central accumulation scale and the peripheral dispersion concentration, thereby improving the accuracy of sawdust residue calculation. Furthermore, the aforementioned preset pixel range, preset proportion threshold, and other parameters can all be set based on actual needs, and this embodiment does not impose specific limitations on them.

[0055] Furthermore, in this embodiment, the aforementioned "determining the amount of residual sawdust based on the obtained accumulation characteristic value, updating the initial dust removal parameters based on the amount of residual sawdust, and obtaining the target dust removal parameters" may further include the following steps: The amount of sawdust residue is obtained by summing all the stacking characteristic values ​​corresponding to different cooperative relationships. The ratio of the largest corresponding accumulation characteristic value to the residual amount of sawdust is calculated to obtain the residual concentration coefficient. When it is determined that the amount of residual wood chips is greater than the preset qualified threshold, the coefficient is adjusted based on the proportion of the amount of residual wood chips exceeding the preset qualified threshold. When the residual concentration coefficient is determined to be greater than the preset concentration threshold, the basic adjustment coefficient is multiplied by the first multiplier to obtain the first air volume adjustment coefficient; otherwise, it is multiplied by the second multiplier which is less than the first multiplier to obtain the second air volume adjustment coefficient. When it is determined that the residual amount of wood chips is less than the preset energy-saving threshold, the air volume reduction coefficient is obtained based on the lower proportion of the residual amount of wood chips corresponding to the preset qualified threshold. The initial dust removal parameters are updated based on the air volume adjustment coefficient or the air volume reduction coefficient to obtain the target dust removal parameters.

[0056] For example, in this embodiment, in order to quantify the overall dust load of the cutting and processing area, the server can sum up all the stacking characteristic values ​​corresponding to different collaborative relationships to obtain the amount of wood chips remaining. Subsequently, in order to further evaluate the spatial distribution pattern of dust, the server can obtain the corresponding maximum accumulation characteristic value and calculate the ratio with the residual amount of sawdust to obtain the residual concentration coefficient. Here, the residual concentration coefficient can characterize whether the sawdust presents a highly concentrated single-point accumulation or a large-area diffuse and uniform distribution. Next, when determining the adjustment range of the dust removal parameters, if it is determined that the amount of residual wood chips is greater than the preset qualified threshold, the server can obtain a basic adjustment coefficient based on the proportion of the residual wood chips exceeding the preset qualified threshold, thereby realizing the transitional adjustment of the dust removal air volume based on the actual degree of pollution. Based on this, the server can tilt the cleaning intensity distribution according to the residual concentration coefficient. When the residual concentration coefficient is determined to be greater than the preset concentration threshold, it indicates that the debris is in an aggregated state. At this time, the server can multiply the basic adjustment coefficient with the larger first multiplier to obtain the first airflow adjustment coefficient to provide cleaning airflow to cope with the aggregated state. Conversely, if the residual concentration coefficient is determined to be less than the preset concentration threshold, it indicates that the debris is in a scattered state. At this time, the server can multiply the basic adjustment coefficient with the smaller second multiplier to obtain the second airflow adjustment coefficient to match the cleaning airflow in the scattered state. In addition, to control energy consumption, when it is determined that the amount of residual wood chips is less than the preset energy-saving threshold, it means that the cutting and processing area is relatively clean and there may be only a small amount of wood chips. At this time, the server can obtain the air volume reduction coefficient based on the relatively low proportion of the amount of residual wood chips that is lower than the preset qualified threshold. Finally, the server can update the initial dust removal parameters based on the obtained air volume adjustment coefficient or air volume reduction coefficient to obtain the target dust removal parameters. In addition, when the amount of wood chips remaining is between the preset qualified threshold and the preset energy-saving threshold, the server can determine that the current wood chip production is in a stable range. At this time, the initial dust removal parameters can be used as the target dust removal parameters.

[0057] It should be noted that in this embodiment, the preset qualified threshold and the preset energy-saving threshold together define the stable processing range under normal cutting conditions. This embodiment introduces a dual judgment mechanism based on the amount of wood chips remaining and the concentration coefficient of residue, which not only ensures directional dust removal under extremely polluted conditions but also maintains the stability of the fan operation within a slightly fluctuating range, effectively balancing dust removal efficiency and overall energy consumption control at the processing site. Furthermore, the aforementioned preset thresholds and multiplier parameters can be set based on actual needs, and this embodiment does not impose specific limitations on them.

[0058] Another embodiment of the present invention provides a cutting and dust removal platform based on image processing. Figure 3 Its corresponding platform block diagram includes: The size determination module is configured to acquire images of the wood to be cut located in the cutting processing area and determine the wood size of the corresponding wood to be cut based on the obtained first image. The initial dust removal module is configured to respond to the cutting unit cutting the wood to be cut, obtain the real-time cutting position of the cutting blades included in the cutting unit corresponding to the wood to be cut, and control the dust removal unit to remove dust from the cutting processing area based on the initial dust removal parameters determined by the wood size. The mutation determination module is configured to acquire a second image by collecting data from the cutting processing area based on the real-time cutting position when the rate of change of the current cutting chips at the real-time cutting position corresponding to the wood to be cut, which is determined based on the wood size, meets the preset mutation condition. The dust removal module is updated and configured to update the initial dust removal parameters based on the amount of sawdust residue determined by the second image, so as to obtain the target dust removal parameters.

[0059] In the specification provided herein, the algorithms and displays are not inherently related to any particular computer, virtual system, or other device. Various general-purpose systems can also be used with the examples of this invention. The required structure for constructing such systems is apparent from the above description. Furthermore, this invention is not directed to any particular programming language. It should be understood that the contents of the invention described herein can be implemented using various programming languages, and the above description of specific languages ​​is for the purpose of disclosing preferred embodiments of the invention.

[0060] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0061] Similarly, it should be understood that, in order to streamline this disclosure and aid in understanding one or more of the various aspects of the invention, in the above description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof.

[0062] Those skilled in the art will understand that modules, units, or components of the devices disclosed in the examples herein can be arranged in the devices described in this embodiment, or alternatively, can be located in one or more devices different from the devices in this example. The modules in the foregoing examples can be combined into a single module or, in addition, can be divided into multiple sub-modules.

[0063] Those skilled in the art will understand that the modules in the device of the embodiment can be adaptively changed and placed in one or more devices different from that embodiment. Modules, units, or components in the embodiment can be combined into a single module, unit, or component, and further, they can be divided into multiple sub-modules, sub-units, or sub-components.

[0064] Furthermore, those skilled in the art will understand that although some embodiments described herein include certain features included in other embodiments but not others, combinations of features from different embodiments are meant to be within the scope of the invention and form different embodiments.

[0065] Furthermore, some of the embodiments described herein are methods or combinations of method elements that can be implemented by a processor of a computer system or by other means of performing the functions. Therefore, a processor having the necessary instructions for implementing the methods or method elements forms means for implementing the methods or method elements. Furthermore, the elements described herein in the apparatus embodiments are examples of means for implementing the functions performed by elements for the purposes of carrying out the invention.

[0066] As used herein, unless otherwise specified, the use of ordinal numbers such as “first,” “second,” “third,” etc., to describe ordinary objects merely indicates different instances of similar objects and is not intended to imply that the objects being described must have a given order in time, space, ordering, or any other manner.

[0067] Although the invention has been described with reference to a limited number of embodiments, those skilled in the art will understand from the foregoing description that other embodiments are conceivable within the scope of the invention described herein. Furthermore, it should be noted that the language used in this specification has been chosen primarily for readability and edibility purposes, and not for the purpose of explaining or limiting the subject matter of the invention.

Claims

1. A cutting and dust removal method based on image processing, characterized in that, include: The wood to be cut in the cutting and processing area is collected, and the wood size of the corresponding wood to be cut is determined based on the obtained first image; The response cutting unit cuts the wood to be cut, obtains the real-time cutting position of the cutting tool in the cutting unit corresponding to the wood to be cut, and controls the dust removal unit to remove dust from the cutting area based on the initial dust removal parameters determined by the wood size. When the rate of change of the current cutting chips at the real-time cutting position of the wood to be cut, determined based on the wood size, meets the preset abrupt change condition, the cutting processing area is collected based on the real-time cutting position to obtain the second image; The initial dust removal parameters are updated based on the amount of sawdust residue determined by the second image to obtain the target dust removal parameters.

2. The method according to claim 1, characterized in that, The wood to be cut in the cutting area is collected, and the wood size is determined based on the obtained first image, including: The light projection unit is controlled to emit irradiation light toward the cutting processing area so that the wood to be cut forms wood projections on different reference stops based on the irradiation light. All reference stops are arranged in an array at different cutting feed positions along the cutting feed direction of the corresponding cutting processing area. The image acquisition unit is controlled to acquire images of each reference stop bar to obtain the first image; Along the direction perpendicular to the cutting feed direction, the projection occlusion length of each reference stop bar occluded by the wood projection is determined based on the first image, and the cutting section width of the wood to be cut corresponding to different cutting feed positions is determined based on the projection occlusion length. The distribution spacing between adjacent reference stops and the width of each cutting section corresponding to different cutting feed positions are determined as the wood size of the wood to be cut.

3. The method according to claim 2, characterized in that, Based on the first image, determine the projection occlusion length of each reference stop bar that is occluded by the wood projection, including: Determine each fluorescent marker that is pre-set in an array on each reference stop bar and distributed in a direction perpendicular to the cutting feed direction; When it is determined from the first image that there is a fluorescent marking area located on any reference barrier and indicating any fluorescent marker, the marking area is defined as a visible marking area; Determine the lateral marking distances between all visible marking areas located on the same reference stop and the wood projection along a direction perpendicular to the cutting feed direction, and determine the visible marking area with the smallest corresponding lateral marking distance as the boundary marking area; Based on the first image, fluorescent markers that correspond to the boundary marker area and are located on the same reference bar, and that do not have fluorescent marker areas, are identified as target markers, and the marker length of the corresponding target marker is identified as the projection occlusion length.

4. The method according to claim 3, characterized in that, The cutting unit acquires the real-time cutting position of the cutting blades corresponding to the wood to be cut, and controls the dust removal unit to remove dust from the cutting area based on initial dust removal parameters determined by the wood size, including: Based on the width of each cutting section corresponding to different cutting feed positions of the wood to be cut, different initial dust removal air volume values ​​are matched, and all initial dust removal air volume values ​​are combined into initial dust removal parameters. The fluorescent detection probe, which controls the movement of the cutting tool along the cutting feed direction, is used for detection. When the fluorescence detection probe passes any reference baffle arranged in an array along the cutting feed direction, a travel pulse count is generated based on the generated fluorescence signal; If the number of travel pulses is the same as the position sequence number corresponding to any cutting feed position, the cutting feed position is determined as the real-time cutting position of the corresponding cutting tool. The initial dust removal air volume value is retrieved based on the initial dust removal parameters and the corresponding real-time cutting position is controlled to remove dust from the cutting area based on the initial dust removal air volume value.

5. The method according to claim 4, characterized in that, When the fluorescence detection probe passes any of the reference stops arranged in an array along the cutting feed direction, a travel pulse count is generated based on the generated fluorescence signal, including: Determine the bar attributes corresponding to each reference bar, and define the reference bars with corresponding bar attributes as calibration attributes and normal attributes as calibration bars and normal bars, respectively. The fluorescent markers included in the calibration bars have a greater physical extension length along the cutting feed direction than those in the normal bars. Determine the duration of the same fluorescence signal output by the fluorescence detection probe, and compare the duration with a preset duration threshold. When the duration of the signal is determined to be less than the preset duration threshold, the reference bar corresponding to the fluorescence signal is determined to be a normal bar, and the travel pulse count is accumulated to obtain the updated travel pulse count; When the duration of the signal is determined to be not less than the preset duration threshold, the reference bar corresponding to the fluorescence signal is identified as the calibration bar, and the fluorescence signal is identified as the calibration signal. Obtain the calibration count for all corresponding calibration signals, and iterate through the retrieved bar position mapping table to correct the travel pulse count by adjusting the calibration mapping count for the corresponding calibration count.

6. The method according to claim 4, characterized in that, When the rate of change of chip production at the current cutting position corresponding to the real-time cutting location of the wood to be cut, determined based on the wood size, meets a preset abrupt change condition, the cutting area is acquired based on the real-time cutting position to obtain a second image, including: The amount of cutting chips at different cutting feed positions is determined based on the distribution spacing and the width of the cutting section, and the amount of cutting chips at the corresponding real-time cutting position is determined as the real-time chip value. The average chip production of each cutting feed position corresponding to the preset cutting quantity, located before the real-time cutting position, is calculated along the cutting feed direction to obtain the historical chip production. The ratio of the difference between the real-time chip production value and the historical chip production value to the historical chip production value is calculated to obtain the chip production change rate. If the absolute value of the corresponding change rate of debris production is greater than the preset mutation threshold, it is determined that the preset mutation condition is met, and the interval time of the fluorescence detection probe passing through the adjacent reference baffle is obtained. The cutting feed speed is determined based on the interval duration and distribution spacing, and the cutting feed speed is multiplied by the falling time of the collected wood chips to obtain the falling chip offset length. The position corresponding to the real-time cutting position and the chip offset length is determined as the acquisition center along the direction opposite to the cutting feed direction, and the image acquisition unit is controlled to acquire the cutting processing area based on the acquisition center to obtain the second image.

7. The method according to claim 6, characterized in that, The control image acquisition unit acquires images of the cutting area based on the acquisition center to obtain a second image, including: The acquisition length for the corresponding cutting feed direction is determined based on all cutting feed positions corresponding to the chip production change rate. When the chip production rate is determined to be a positive value, the width of the cutting section at the corresponding real-time cutting position is multiplied by the chip production rate, and the resulting width extension value is summed with the width of the cutting section at the corresponding real-time cutting position to obtain the first width in the direction perpendicular to the cutting feed direction. Based on the acquisition center, a sub-region for acquisition is determined within the cutting and processing area, corresponding to the first width and acquisition length; When the chip production rate is determined to be a negative value, the width of the cutting section at the corresponding real-time cutting position is determined as the second width in the direction perpendicular to the cutting feed direction, and a sub-region of acquisition corresponding to the second width and acquisition length is determined based on the acquisition center in the cutting processing area. The image acquisition unit is controlled to acquire images of the acquisition sub-region to obtain a second image.

8. The method according to claim 1, characterized in that, The initial dust removal parameters are updated based on the amount of sawdust residue determined from the second image to obtain the target dust removal parameters, including: Determine each image pixel that makes up the second image, and if any image pixel is located in the same preset pixel range as the corresponding sawdust pixel retrieved, determine that image pixel as the acquisition pixel. The acquisition sub-region is divided into arrays, and the proportion of debris distribution of the acquisition pixels corresponding to each unit of evaluation grid is determined. If any proportion of debris distribution exceeds a preset proportion threshold, the unit evaluation grid corresponding to that proportion of debris distribution will be determined as the primary evaluation grid; otherwise, it will be determined as the secondary evaluation grid. Adjacent primary evaluation grids are identified as central stacking groups, and based on the second image, all secondary evaluation grids of adjacent central stacking groups are identified as edge dispersion groups that have a cooperative relationship with the central stacking group. Obtain the number of primary evaluation grids corresponding to all primary evaluation grids located in the same central accumulation group, and calculate the average of the secondary evaluation grids based on the proportion of debris distribution for all secondary evaluation grids located in the same edge dispersion group to obtain the average proportion of secondary evaluation grids. The number of primary grids and the average proportion of secondary grids corresponding to the same collaborative relationship are weighted and summed based on normalization. The amount of residual wood chips is determined based on the obtained accumulation characteristic value. The initial dust removal parameters are then updated based on the amount of residual wood chips to obtain the target dust removal parameters.

9. The method according to claim 8, characterized in that, The amount of residual sawdust is determined based on the obtained accumulation characteristic values. The initial dust removal parameters are then updated based on the amount of residual sawdust to obtain the target dust removal parameters, including: The amount of sawdust residue is obtained by summing all the stacking characteristic values ​​corresponding to different cooperative relationships. The ratio of the largest corresponding accumulation characteristic value to the residual amount of sawdust is calculated to obtain the residual concentration coefficient. When it is determined that the amount of residual wood chips is greater than the preset qualified threshold, the coefficient is adjusted based on the proportion of the amount of residual wood chips exceeding the preset qualified threshold. When the residual concentration coefficient is determined to be greater than the preset concentration threshold, the basic adjustment coefficient is multiplied by the first multiplier to obtain the first air volume adjustment coefficient; otherwise, it is multiplied by the second multiplier which is less than the first multiplier to obtain the second air volume adjustment coefficient. When it is determined that the residual amount of wood chips is less than the preset energy-saving threshold, the air volume reduction coefficient is obtained based on the lower proportion of the residual amount of wood chips corresponding to the preset qualified threshold. The initial dust removal parameters are updated based on the air volume adjustment coefficient or the air volume reduction coefficient to obtain the target dust removal parameters.

10. A cutting and dust removal platform based on image processing, characterized in that, include: The size determination module is configured to acquire images of the wood to be cut located in the cutting processing area and determine the wood size of the corresponding wood to be cut based on the obtained first image. The initial dust removal module is configured to respond to the cutting unit cutting the wood to be cut, obtain the real-time cutting position of the cutting blades included in the cutting unit corresponding to the wood to be cut, and control the dust removal unit to remove dust from the cutting processing area based on the initial dust removal parameters determined by the wood size. The mutation determination module is configured to acquire a second image by collecting data from the cutting processing area based on the real-time cutting position when the rate of change of the current cutting chips at the real-time cutting position corresponding to the wood to be cut, which is determined based on the wood size, meets the preset mutation condition. The dust removal module is updated and configured to update the initial dust removal parameters based on the amount of sawdust residue determined by the second image, so as to obtain the target dust removal parameters.

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