A crayfish sorting system and method

Abstract

The present application relates to crayfish sorting field, disclose a kind of crayfish sorting system and sorting method, including whole line conveying unit, identification check unit, classification decision unit and sorting execution unit.Whole line conveying unit is used to adjust crayfish posture;Identification check unit is used to obtain crayfish image data, size data and weight data;Classification decision unit adjusts each data weight proportion according to the weight data of crayfish and determines the grade information of crayfish;Sorting execution unit is used to sort crayfish according to grade information;The data of crayfish is obtained by visual equipment in the present application, and then the crayfish is first partitioned by classification decision unit to adjust each data proportion, and then the grade information of crayfish is determined according to crayfish data, which greatly improves the sorting stability and sorting efficiency of crayfish.

Description

Technical Field

[0001] This invention relates to the field of aquatic product classification technology, and in particular to a crayfish sorting system and sorting method. Background Technology

[0002] Currently, crayfish sorting mainly relies on manual visual sorting. However, manual sorting lacks fixed sorting standards and is highly subjective. When faced with crayfish of varying weights and sizes, or those with broken limbs, manual sorting often leads to confusion and unclear grading. Furthermore, manual crayfish sorting suffers from low efficiency and high costs. Although some crayfish sorting devices exist, these devices generally suffer from slow sorting efficiency, low accuracy in identification and sorting, and unclear grading. Summary of the Invention

[0003] The purpose of this invention is to overcome the above-mentioned technical deficiencies and propose a crayfish sorting system and sorting method to solve the technical problems of low sorting efficiency and accuracy and low stability of grade classification in the existing technology.

[0004] To achieve the above-mentioned technical objectives, the present invention adopts the following technical solution: This invention provides a crayfish sorting system, including a lining conveyor unit, an identification and verification unit, a classification decision unit, and a sorting execution unit. The lining conveyor unit is configured to transport the crayfish in a sequential order. The identification and verification unit includes a camera recognition mechanism and a weighing conveyor line. The weighing conveyor line is located on one side of the lining conveyor unit, and the camera recognition mechanism is located above the weighing conveyor line. The camera recognition mechanism is used to acquire image data and size data of the crayfish; the weighing conveyor line is used to transport the crayfish and acquire their weight data. The classification decision unit is electrically connected to the camera recognition mechanism and the weighing conveyor line. The classification decision unit is configured to determine the grade information of the crayfish based on their weight data, size data, and image data; and the classification decision unit is configured to adjust the proportions of weight data, size data, and image data during the grade information calculation process based on the crayfish's weight data. The sorting execution unit includes a sorting conveyor line and a sorting mechanism. The sorting conveyor line is located on the side of the weighing conveyor line away from the entire conveyor unit. The sorting mechanism is located above the sorting conveyor line and is electrically connected to the classification decision unit. The sorting mechanism is used to sort the crayfish according to the grade information.

[0005] Preferably, the assemblies conveying unit includes a flexible vibratory feeder.

[0006] Preferably, the identification and verification unit further includes a cleaning mechanism, which is disposed above the weighing conveyor line and is used to clean the crayfish to be identified.

[0007] Preferably, the sorting mechanism includes a plurality of sorting components arranged sequentially along the extension direction of the sorting conveyor line. Each sorting component includes a sorting baffle and a sorting chute. The sorting baffle is disposed above the sorting conveyor line, and the sorting chute is disposed on the side of the sorting conveyor line. The sorting baffle is used to guide the crayfish into the corresponding sorting chute.

[0008] Preferably, the sorting baffle includes an arc-shaped baffle, the side of the arc-shaped baffle away from the sorting slide is rotatably connected to the frame of the sorting conveyor line, and the outer arc surface of the arc-shaped baffle faces the weighing conveyor line.

[0009] The present invention also provides a crayfish sorting method for the crayfish sorting system described above, comprising the following steps: S1. Feed the crayfish to be sorted into the sorting conveyor unit, adjust the state of the crayfish in the sorting conveyor unit so that the crayfish are arranged in order, and convey the crayfish to the weighing conveyor line. S2. The camera recognition mechanism takes pictures of the crayfish to obtain image data and size data of the crayfish; the weighing conveyor line obtains the weight data of the crayfish and conveys the crayfish along its extension direction; S3. The classification decision unit divides the crayfish into regions based on their weight data, and adjusts the weight ratio of image data, size data, and weight data according to the region division results. Then, it calculates and outputs the grade information of the crayfish based on the image data, size data, and weight data after adjusting the weight ratio. S4. The sorting conveyor line transports the identified crayfish, and the sorting mechanism sorts the crayfish according to their grade information.

[0010] Preferably, when the camera recognition mechanism fails to identify the boundary of the crayfish in the image data or the size data error of the identified crayfish exceeds a first threshold, a recognition failure is determined to have occurred, and the following steps are executed: The cleaning mechanism of the identification and verification unit cleans the crayfish; The camera recognition agency re-captures and verifies the crayfish by taking a second photo of it, and then re-identifies it.

[0011] Preferably, in step S3, the classification decision unit predicts the weight data of the crayfish based on the size data of the crayfish. When the deviation between the predicted weight data and the actual weight data exceeds the second threshold, an anomaly is detected and the camera recognition mechanism is controlled to take a second picture of the crayfish.

[0012] Preferably, step S3 includes the following steps: The classification decision unit divides the crayfish into zones based on their weight data. If the weight data of the crayfish is not less than the first weight threshold, it is classified into the large crayfish zone; if the weight data of the crayfish is less than the first weight threshold but not greater than the second weight threshold, it is classified into the medium crayfish zone; if the weight data of the crayfish is less than the second weight threshold, it is classified into the small crayfish zone. When the crayfish is classified as a large crayfish, the classification decision unit calculates the grade information with weight data accounting for 70%, size data accounting for 20%, and image data accounting for 10%. When the crayfish is in the medium-sized crayfish range, the classification decision unit calculates the grade information with weight data accounting for 50%, size data accounting for 40%, and image data accounting for 10%. When the crayfish is in the small crayfish category, the classification decision unit calculates the grade information with weight data accounting for 30%, size data accounting for 50%, and image data accounting for 20%.

[0013] Preferably, in step S2, when the camera recognition mechanism identifies that the crayfish has broken claws, molted shells, or is dead in the image data, the classification decision unit outputs the grade information of the corresponding crayfish as defective.

[0014] Compared with the prior art, the crayfish sorting system and method provided in this embodiment of the invention have the following advantages: In this invention, the position of the crayfish is first adjusted by the aligning conveyor unit, so that the crayfish can be transported in sequence to avoid stacking, thereby facilitating the subsequent identification and detection work. The identification and verification unit can obtain the size data, image data, and weight data of the crayfish. The classification decision unit first divides the crayfish into zones according to the weight data to adjust the weight ratio of each data in the grading process. Then, the grade information of the crayfish is determined by the weight data, size data, and image data after adjusting the weight ratio. This avoids the interference of subjective factors in manual classification, improves the stability and reliability of crayfish classification, and improves the efficiency of crayfish classification. Attached Figure Description

[0015] Figure 1 This is a perspective view of the present invention; Figure 2 This is a schematic diagram of the steps of the present invention; Figure 3 This is a flowchart illustrating the process of this invention.

[0016] In the diagram: 1. Array conveyor unit; 2. Identification and verification unit; 21. Camera recognition mechanism; 22. Weighing conveyor line; 23. Cleaning mechanism; 3. Sorting execution unit; 31. Sorting conveyor line; 32. Sorting mechanism; 321. Sorting baffle; 322. Sorting chute. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0018] To address the technical problems of slow crayfish sorting efficiency and poor sorting stability due to subjective interference in existing technologies, this invention provides a crayfish sorting system and method that can achieve efficient sorting of crayfish and stable classification of crayfish.

[0019] like Figure 1 As shown, a preferred embodiment of the present invention provides a crayfish sorting system, which includes a lining conveyor unit 1, an identification and verification unit 2, a classification decision unit, and a sorting execution unit 3. The lining conveyor unit 1 is configured to transport crayfish in a sequential manner. The identification and verification unit 2 includes a camera identification mechanism 21 and a weighing conveyor line 22. The weighing conveyor line 22 is disposed on one side of the lining conveyor unit 1, and the camera identification mechanism 21 is disposed above the weighing conveyor line 22. The camera identification mechanism 21 is used to acquire image data and size data of the crayfish; the weighing conveyor line 22 is used to transport the crayfish and acquire their weight data. The classification decision unit (not shown in the figure, its core being a control chip installed in an industrial machine or computer) is electrically connected to the camera identification mechanism 21 and the weighing conveyor line 22. The classification decision unit is configured to determine the grade information of the crayfish based on their weight data, size data, and image data; and the classification decision unit is configured to adjust the proportions of weight data, size data, and image data during the grade information calculation process based on the crayfish's weight data. The sorting execution unit 3 includes a sorting conveyor line 31 and a sorting mechanism 32. The sorting conveyor line 31 is located on the side of the weighing conveyor line 22 away from the whole-line conveyor unit 1. The sorting mechanism 32 is located above the sorting conveyor line 31. The sorting mechanism 32 is electrically connected to the classification decision unit. The sorting mechanism 32 is used to sort crayfish according to grade information.

[0020] Specifically, in this embodiment, the aligning conveyor unit 1 is used to sort and arrange the crayfish in a neat manner, so that the crayfish to be detected and identified are transported sequentially to the weighing conveyor line 22 of the identification and verification unit 2, avoiding the crayfish from piling up and ensuring the smooth progress of subsequent identification and detection. The camera recognition mechanism 21 includes a vision camera, an infrared size sensor, and a movable supplementary light. The vision camera can take pictures of the crayfish, and together with the infrared size sensor, it can obtain the size data and image data of the crayfish. The size data includes the length, width, and head-to-tail ratio of the crayfish, while the image data includes the appearance and posture of the crayfish, such as whether the crayfish has broken claws or is damaged after molting, whether the color of the crayfish has changed, and whether the posture of the crayfish is abnormal. The weighing conveyor line 22 consists of two parts: the conveyor line and the weighing sensor. The weighing sensor is located inside the conveyor line and can detect the weight of the crayfish on the conveyor line, thereby sending the weight data of the crayfish to the classification decision unit. This is existing technology, and its internal structure will not be described in detail. Subsequently, the classification decision unit can first divide the crayfish into zones based on the acquired weight data to determine the weight ratio of weight data, image data, and size data in the subsequent grading process. After completing the zoning of the crayfish, the classification decision unit then accurately judges the grade information of the crayfish based on the comprehensive score of the crayfish image data, size data, and weight data. The subsequent sorting execution unit 3 sorts the crayfish according to the crayfish grade information output by the classification decision unit, thereby achieving accurate and stable sorting, avoiding the interference of subjective factors in the manual sorting process, and also improving the sorting efficiency of crayfish.

[0021] In one embodiment, the conveying unit 1 includes a flexible vibrating plate. Specifically, the flexible vibrating plate is existing technology, and its internal structure and working principle will not be detailed here. In this embodiment, the flexible vibrating plate can automatically organize the randomly stacked crayfish into a single row for forward conveying, limiting the lateral displacement and random movement of the crayfish, thereby ensuring that each crayfish moves to the area below the camera recognition mechanism 21 with its belly down and head forward. The surface of the flexible vibrating plate can be specifically made of food-grade silicone material and an elastic buffer layer to reduce the damage rate and limb breakage rate of the crayfish shells. Furthermore, the material level sensor and counting sensor built into the flexible vibrating plate can monitor problems such as empty material, crayfish jamming, and crayfish stacking in real time, and solve these problems by adjusting the vibration frequency and other vibration states of the flexible vibrating plate. In other embodiments, a removable odor-releasing groove can be set inside the exit section track of the flexible vibrating plate, and a feeding-inducing slow-release agent can be placed in the odor-releasing groove. This utilizes the crayfish's natural attraction to odors to guide them to actively crawl towards the exit direction of the flexible vibrating plate, thereby further reducing the problem of crayfish stacking. In addition, this embodiment also designs the conveying track inside the flexible vibrating plate. The inlet section of the conveying track at the bottom of the flexible vibrating plate adopts a wider channel to facilitate the crayfish to enter the conveying track of the flexible vibrating plate. At the same time, the width of the conveying track gradually narrows until the outlet section of the conveying track only allows a single crayfish to pass through.

[0022] In one embodiment, the identification and verification unit 2 further includes a cleaning mechanism 23, which is disposed above the weighing conveyor line 22 and is used to clean the crayfish to be identified.

[0023] Specifically, the cleaning mechanism 23 can be either a spray device or a water rinsing device. When the camera recognition mechanism 21 takes a picture of the crayfish, but the image features are blurry and the camera recognition mechanism 21 cannot accurately identify the boundaries of the crayfish, or when the camera recognition mechanism 21 takes multiple pictures of the same crayfish and uses an infrared size sensor to calibrate and obtain crayfish size data, and the size error exceeds 2%, it can be determined that the detection has failed. At this time, the spray device or water rinsing device can spray or rinse the crayfish. On the one hand, this avoids keeping the surface of the crayfish wet, cleans the crayfish, and prevents the dry reflection or dirt on the crayfish shell from interfering with the visual camera's recognition, thus improving recognition accuracy. On the other hand, it can also put the crayfish into a short dormant state, preventing problems such as crayfish running around or piling up during the sorting process. Moreover, the water rinsing can also wash away some of the piled-up crayfish, thereby improving the accuracy of detection and recognition.

[0024] In one embodiment, the sorting mechanism 32 includes a plurality of sorting components arranged sequentially along the extension direction of the sorting conveyor line 31. Each sorting component includes a sorting baffle 321 and a sorting chute 322. The sorting baffle 321 is disposed above the sorting conveyor line 31, and the sorting chute 322 is disposed on the side of the sorting conveyor line 31. The sorting baffle 321 is used to guide the crayfish into the corresponding sorting chute 322.

[0025] Specifically, after the classification decision unit outputs the grade information of the crayfish, the sorting mechanism 32 can sort the crayfish according to the grade information. Depending on the grade, the crayfish will be blocked and guided by different sorting baffles 321, thus sliding into the corresponding sorting chute 322, thereby completing the accurate sorting of the crayfish. Depending on the actual grade of the crayfish, multiple sorting components can be set up, such as Grade 1, Grade 2, Grade 3, and defective products, thus requiring four sets of sorting components. Of course, in other embodiments, more grades can also be set up, such as premium grade, or a separate sorting component can be set up for sorting dead crayfish. Furthermore, for more complex sorting environments and needs, such as different varieties of crayfish, the classification decision unit can first identify the crayfish variety based on image data, then divide the crayfish into intervals based on weight data, and finally perform a comprehensive score based on all data to determine the grade information of the crayfish. In this case, more sorting components can be set up to cooperate with the sorting of different varieties of crayfish.

[0026] In one embodiment, the sorting baffle 321 includes an arc-shaped baffle. The side of the arc-shaped baffle away from the sorting chute 322 is rotatably connected to the frame of the sorting conveyor line 31, and the outer arc surface of the arc-shaped baffle faces the weighing conveyor line 22. Specifically, the arc-shaped baffle is driven to rotate by a pneumatic structure, and its outer arc surface faces the weighing conveyor line 22, so that its outer arc surface can contact the crayfish immediately and guide the crayfish, allowing the crayfish to move along its outer arc surface into the sorting chute 322, avoiding problems such as crayfish piling up. Of course, in some other alternative embodiments, the sorting baffle 321 may also adopt an inclined flat plate structure.

[0027] It is understandable that the sorting chute 322 is inclined, allowing crayfish to slide down along it under gravity to the other end. In some embodiments, a receiving box (not shown in the figure) is provided at the end of the sorting chute 322 away from the sorting conveyor line 31, and a pressure sensor is installed inside the receiving box. When the pressure sensor detects that the weight of the crayfish in the receiving box reaches a threshold, it will issue an alarm to remind staff to promptly move the receiving box and replace it with an empty one. In other embodiments, the downstream conveyor line may receive the signal from the pressure sensor, thereby automatically moving the full receiving box and replacing it with an empty one, further improving the sorting efficiency of crayfish.

[0028] Furthermore, in some other embodiments, after the classification decision unit outputs the grade information of the crayfish, the crayfish are transported to the corresponding sorting component. The sorting component is equipped with an infrared size sensor and a weight sensor (not shown in the figure). The infrared size sensor detects the size of the crayfish to be sorted at the sorting baffle 321 and compares it with the size data monitored by the camera recognition mechanism 21. If the difference is too large, such as 15%, an anomaly is detected, and an alarm is issued to remind staff to check. The crayfish with the detection failure are then returned to the weighing conveyor line 22 for secondary image capture and recognition. The weight sensor works similarly. If the weight sensor detects a significant difference between the weight of the crayfish at the sorting baffle 321 and the weight data detected by the weighing sensor, an anomaly is also detected, and an alarm is issued to remind staff to handle the situation. This avoids grading errors caused by sensor errors, abnormal crayfish posture, or stacking problems.

[0029] like Figure 2 As shown, the present invention also provides a crayfish sorting method for the crayfish sorting system described above, comprising the following steps: S1. Feed the crayfish to be sorted into the sorting conveyor unit 1, adjust the state of the crayfish in the sorting conveyor unit so that the crayfish are arranged in order, and convey the crayfish to the weighing conveyor line 22. S2, the camera recognition mechanism 21 takes pictures of the crayfish to obtain image data and size data of the crayfish; the weighing conveyor line 22 obtains the weight data of the crayfish and conveys the crayfish along its extension direction; S3. The classification decision unit divides the crayfish into regions based on their weight data, and adjusts the weight ratio of image data, size data, and weight data according to the region division results. Then, it calculates and outputs the grade information of the crayfish based on the image data, size data, and weight data after adjusting the weight ratio. S4. The sorting conveyor line 31 transports the identified crayfish, and the sorting mechanism 32 sorts the crayfish according to their grade information.

[0030] Specifically, in this embodiment, the position and posture of the crayfish are first adjusted by the flexible vibrating plate in the aligning conveyor unit 1, so that the crayfish can be conveyed in sequence, reducing the problem of crayfish stacking. Then, the camera recognition mechanism 21 takes pictures of the crayfish to obtain image data, and the size data of the crayfish is obtained in conjunction with the infrared size sensor. It is understood that in some embodiments, multiple pictures of a single crayfish will be taken, and the image data from multiple pictures will be combined by an algorithm structure to obtain more accurate size data. At the same time, the weight sensor built into the weighing conveyor line 22 will also obtain the weight data of the corresponding crayfish. Then, the image data, size data, and weight data are all sent to the classification decision unit in the chip. The classification decision unit divides the crayfish into zones according to the weight information and adjusts the weight ratio of each data in the subsequent grade information calculation process. Then, the data after adjusting the weight ratio is used to calculate a comprehensive score, and the grade information of the crayfish is output according to the final comprehensive score. The subsequent sorting mechanism 32 then sorts the crayfish according to the grade information. This achieves objective and stable crayfish sorting, improves sorting efficiency, and avoids the problems of subjective interference and low efficiency caused by manual sorting.

[0031] In one embodiment, if the camera recognition mechanism 21 fails to recognize the boundary of the crayfish in the image data or the size data error of the crayfish after recognition exceeds a first threshold, it determines that a recognition failure has occurred and performs the following steps: The cleaning mechanism 23 of the identification and verification unit 2 cleans the crayfish; The camera recognition agency 21 re-captured and verified the crayfish by taking a second photo of them.

[0032] Specifically, in the actual detection process, due to dirt, reflections on the crayfish shells, and the stacking of multiple crayfish, the camera recognition mechanism 21 cannot always accurately identify the size of the crayfish. Therefore, when the image captured by the camera recognition mechanism 21 is too blurry and the crayfish boundaries are unclear, it indicates a recognition failure. In this case, the crayfish needs to be cleaned by the cleaning mechanism 23, and a second image capture should be performed using a movable supplementary light to obtain more accurate cleaned crayfish image and size data. Understandably, the first image capture will take multiple photos of the same crayfish. The multiple image data, combined with data from multiple infrared size sensors, will be used to calculate multiple size data points. Then, an algorithm will be used to remove noise to obtain the final size data. If the size data error of the same crayfish in the multiple image captures exceeds a first threshold, a recognition failure is also determined, and the crayfish needs to be cleaned again, followed by a second image capture to recalculate the crayfish's size data. In some embodiments, the first threshold is 2%.

[0033] In one embodiment, in step S3, the classification decision unit predicts the weight data of the crayfish based on the size data of the crayfish. When the deviation between the predicted weight data and the actual weight data exceeds a second threshold, the unit determines that an anomaly has been detected and controls the camera recognition mechanism 21 to take a second picture of the crayfish.

[0034] Specifically, in addition to setting infrared size and weight sensors at the sorting baffle 321 to verify and correct the size and weight data of the crayfish, the classification decision unit in this embodiment also predicts the possible weight of the crayfish based on the correspondence between size and weight data in historical data. That is, it predicts the weight data of the crayfish based on the size data and compares the predicted weight data with the actual weight data of the crayfish obtained by the weighing conveyor line 22. When the deviation between the two exceeds a second threshold, an anomaly is detected and an alarm is issued. This may be due to a sensor malfunction or crayfish stacking. If the crayfish are stacked, they are manually removed and placed back on the weighing conveyor line 22. The camera recognition mechanism 21 takes a second picture of the crayfish and obtains the predicted weight data again based on the size data. The weighing conveyor line 22 also re-collects the weight data of the crayfish and compares it with the predicted weight data. If the crayfish are not stacked, it may be due to a sensor malfunction, requiring shutdown for maintenance.

[0035] like Figure 3 As shown, in one embodiment, step S3 includes the following steps: The classification decision unit divides the crayfish into zones based on their weight data. If the weight data of the crayfish is not less than the first weight threshold, it is classified into the large crayfish zone; if the weight data of the crayfish is less than the first weight threshold but not greater than the second weight threshold, it is classified into the medium crayfish zone; if the weight data of the crayfish is less than the second weight threshold, it is classified into the small crayfish zone. When crayfish are classified as large crayfish, the weight of weight data accounts for 70%, the weight of size data accounts for 20%, and the weight of image data accounts for 10% when the classification decision unit calculates the grade information. When the crayfish is in the medium-sized crayfish range, the classification decision unit calculates the grade information with weight data accounting for 50%, size data accounting for 40%, and image data accounting for 10%. When crayfish are classified as small, the weight of the classification decision unit is 30%, the weight of the size data is 50%, and the weight of the image data is 20% when calculating the grade information.

[0036] Specifically, in the actual production and sales process, the size and price of crayfish are closely related. The classification decision unit divides crayfish into large, medium, and small ranges based on their weight. For example, crayfish weighing at least 7 qian (approximately 35 grams) are classified as large; those between 4 and 7 qian are classified as medium; and those under 4 qian are classified as small. If a crayfish weighs more than 10 qian and shows no abnormalities such as broken claws, molting, or death, the classification decision unit can directly output its grade as premium. Subsequently, the grading algorithm varies depending on the size range, specifically the weighting of each data point. When a crayfish is in the large range, its actual weight is more important, so weight has a higher weighting, for example, 70%. As the weight decreases, size becomes more important; therefore, when a crayfish is in the medium range, size has a higher weighting, for example, 40%. As crayfish become smaller, falling into the "small crayfish" category, their appearance becomes even more important than size. Therefore, the weighting of size and appearance increases; for example, size might account for 50%, while appearance accounts for 20%. The classification decision unit then calculates a score based on these adjusted data, categorizing crayfish into Grade 1, Grade 2, and Grade 3 based on their score range. It's important to note that the specific calculation formula, score assignment, and score division can be determined based on the actual situation. A 10-point or 100-point system can be used. Differences in shell wear, tail notches, and color within the appearance data can all be assigned different scores, depending on the specific circumstances, and will not be elaborated upon here.

[0037] Furthermore, in step S2, when the camera recognition mechanism 21 identifies a crayfish with broken claws, molted shell, or dead in the image data, the classification decision unit directly outputs the corresponding crayfish's grade information as defective, without performing subsequent partitioning and weight adjustment. Molting can be determined based on the crayfish's color and the state of its empty shell, while the death of a crayfish can be confirmed by its color and posture.

[0038] The above are merely preferred embodiments of the present invention. It should be noted that those skilled in the art can make several improvements and substitutions without departing from the technical principles of the present invention, and these improvements and substitutions should also be considered within the scope of protection of the present invention.

Claims

1. A crayfish sorting system for sorting crayfish, characterized in that, include: A column conveying unit, configured to convey the crayfish in a sequential arrangement; The identification and verification unit includes a camera recognition mechanism and a weighing conveyor line. The weighing conveyor line is located on one side of the entire conveyor unit, and the camera recognition mechanism is located above the weighing conveyor line. The camera recognition mechanism is used to acquire image data and size data of the crayfish; the weighing conveyor line is used to transport the crayfish and acquire the weight data of the crayfish. A classification decision unit is electrically connected to the camera recognition mechanism and the weighing conveyor line. The classification decision unit is configured to determine the grade information of the crayfish based on the weight data, size data, and image data of the crayfish. The classification decision unit is also configured to adjust the proportion of weight data, size data, and image data in the grade information calculation process based on the weight data of the crayfish. The sorting execution unit includes a sorting conveyor line and a sorting mechanism. The sorting conveyor line is located on the side of the weighing conveyor line away from the entire conveyor unit. The sorting mechanism is located above the sorting conveyor line and is electrically connected to the classification decision unit. The sorting mechanism is used to sort the crayfish according to the grade information.

2. The crayfish sorting system according to claim 1, characterized in that, The entire conveyor unit includes a flexible vibratory feeder.

3. The crayfish sorting system according to claim 1, characterized in that, The identification and verification unit also includes a cleaning mechanism, which is located above the weighing conveyor line and is used to clean the crayfish to be identified.

4. The crayfish sorting system according to claim 1, characterized in that, The sorting mechanism includes a plurality of sorting components arranged sequentially along the extension direction of the sorting conveyor line. Each sorting component includes a sorting baffle and a sorting chute. The sorting baffle is located above the sorting conveyor line, and the sorting chute is located on the side of the sorting conveyor line. The sorting baffle is used to guide the crayfish into the corresponding sorting chute.

5. The crayfish sorting system according to claim 4, characterized in that, The sorting baffle includes an arc-shaped baffle, the side of which is away from the sorting chute is rotatably connected to the frame of the sorting conveyor line, and the outer arc surface of the arc-shaped baffle faces the weighing conveyor line.

6. A method for sorting crayfish, used in the crayfish sorting system as described in claims 1 to 5, characterized in that, Includes the following steps: S1. Feed the crayfish to be sorted into the sorting conveyor unit, adjust the state of the crayfish in the sorting conveyor unit so that the crayfish are arranged in order, and convey the crayfish to the weighing conveyor line. S2. The camera recognition mechanism takes pictures of the crayfish to obtain image data and size data of the crayfish; the weighing conveyor line obtains the weight data of the crayfish and conveys the crayfish along its extension direction; S3. The classification decision unit divides the crayfish into regions based on their weight data, and adjusts the weight ratio of image data, size data, and weight data according to the region division results. Then, it calculates and outputs the grade information of the crayfish based on the image data, size data, and weight data after adjusting the weight ratio. S4. The sorting conveyor line transports the identified crayfish, and the sorting mechanism sorts the crayfish according to their grade information.

7. The crayfish sorting method according to claim 6, characterized in that, If the camera recognition agency fails to identify the boundary of the crayfish in the image data or the size data error of the crayfish after recognition exceeds the first threshold, a recognition failure is determined and the following steps are executed: The cleaning mechanism of the identification and verification unit cleans the crayfish; The camera recognition agency re-captures and verifies the crayfish by taking a second photo of it, and then re-identifies it.

8. The crayfish sorting method according to claim 6, characterized in that, In step S3, the classification decision unit predicts the weight data of the crayfish based on the size data of the crayfish. When the deviation between the predicted weight data and the actual weight data exceeds the second threshold, it determines that an anomaly has been detected and controls the camera recognition mechanism to take a second picture of the crayfish.

9. The crayfish sorting method according to claim 6, characterized in that, Step S3 includes the following steps: The classification decision unit divides the crayfish into zones based on their weight data. If the weight data of the crayfish is not less than the first weight threshold, it is classified into the large crayfish zone; if the weight data of the crayfish is less than the first weight threshold but not greater than the second weight threshold, it is classified into the medium crayfish zone; if the weight data of the crayfish is less than the second weight threshold, it is classified into the small crayfish zone. When the crayfish is classified as a large crayfish, the classification decision unit calculates the grade information with weight data accounting for 70%, size data accounting for 20%, and image data accounting for 10%. When the crayfish is in the medium-sized crayfish range, the classification decision unit calculates the grade information with weight data accounting for 50%, size data accounting for 40%, and image data accounting for 10%. When the crayfish is in the small crayfish category, the classification decision unit calculates the grade information with weight data accounting for 30%, size data accounting for 50%, and image data accounting for 20%.

10. The crayfish sorting method according to claim 9, characterized in that, In step S2, when the camera recognition agency identifies that the crayfish has broken claws, molted shells, or is dead in the image data, the classification decision unit outputs the grade information of the corresponding crayfish as defective.

Images