CN111136027A - Salted duck egg quality sorting device and method based on convolutional neural network - Google Patents
Salted duck egg quality sorting device and method based on convolutional neural network Download PDFInfo
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- CN111136027A CN111136027A CN202010037406.2A CN202010037406A CN111136027A CN 111136027 A CN111136027 A CN 111136027A CN 202010037406 A CN202010037406 A CN 202010037406A CN 111136027 A CN111136027 A CN 111136027A
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Abstract
The invention discloses a salted duck egg quality sorting device and method based on a convolutional neural network, wherein the salted duck egg quality sorting device comprises a rack, a black box arranged on the rack, a detection device arranged in the black box, a conveying device used for conveying salted duck eggs into the black box for detection and a control system; according to the salted duck egg quality sorting device, smelly salted duck eggs are preferentially removed by detecting gas components in gas emitted by the salted duck eggs, the remaining salted duck eggs are detected by using the convolutional neural network model which is trained in advance and used for detecting the salted duck egg quality, the inferior salted duck eggs and the high-quality salted duck eggs are classified, the traditional manual detection mode is replaced, the labor force is saved, and the production efficiency is improved.
Description
Technical Field
The invention relates to salted duck egg detection equipment, in particular to a salted duck egg quality sorting device and method based on a convolutional neural network.
Background
Salted duck eggs are also called salted duck eggs and are a traditional food in China. The salted duck egg is a reproduced egg prepared by pickling fresh duck eggs serving as main raw materials, is rich in nutrition, is rich in fat, protein and various trace elements, vitamins and the like required by a human body, and is easy to absorb by the human body. The high-quality salted duck eggs are mellow and smooth in appearance, the eggshells are complete and clean, no cracks exist, and the shells are cyan; the bad salted duck eggs have grey shells, more white or black spots on the surfaces, thin and fragile eggshells and easy breakage, even the deteriorated salted duck eggs can generate pungent odor which is mainly derived from chemical gases such as ammonia gas, hydrogen sulfide gas and the like, and because a plurality of tiny air holes are formed on the surfaces of the eggshells, even the salted duck eggs with complete shells can still emit odor.
Poultry eggs such as eggs and duck eggs and egg products are important ways for guaranteeing sufficient nutrition of people, and various grading and detection technologies for poultry eggs are developed, but most of the poultry eggs are researched for fresh eggs, most of the poultry eggs are used for detecting nutrition or harmful ingredients of the poultry eggs, and the poultry eggs and the egg products prepared by processing the salted duck eggs in a certain way are mainly used for detecting the quality and the quality of the salted duck eggs and still are mainly selected and classified manually, so that the method is time-consuming, labor-consuming, low in efficiency and easy to make mistakes. Therefore, devices and methods for detecting and analyzing the quality of salted duck eggs appear in the market, for example, the utility model patent with application publication number CN108051449A discloses an "online visual detection method for surface cracks of salted duck eggs based on morphological edge detection", which can realize online detection and classification of cracks of salted duck eggs by using machine vision for detection, and has low requirements on application environment, low equipment cost and better application and popularization prospects compared with acoustic detection; a single industrial camera is used for photographing salted duck eggs at multiple turnover angles, and the detection range is full; and the cracks are extracted by utilizing morphological edge detection, so that the method is more visual and accurate.
However, the online visual detection method for the surface cracks of the salted duck eggs has the following defects:
although the salted duck eggs which are likely to deteriorate are removed by detecting the surface cracks of the salted duck eggs, the inferior salted duck egg shells are still not cracked but have been deteriorated to different degrees in the market, so that the online visual detection method for the surface cracks of the salted duck eggs is difficult to detect.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides the salted duck egg quality sorting device based on the convolutional neural network, the salted duck egg quality sorting device can be used for more accurately detecting the quality of salted duck eggs, and the detection precision is higher.
The invention also aims to provide a salted duck egg quality sorting method based on the convolutional neural network.
The technical scheme for solving the technical problems is as follows:
a salted duck egg quality sorting device based on a convolutional neural network comprises a rack, a black box arranged on the rack, a detection device arranged in the black box, a conveying device used for conveying salted duck eggs into the black box for detection and a control system, wherein,
two sides of the black box are respectively provided with a salted duck egg inlet and a salted duck egg outlet, wherein the salted duck egg inlet is provided with an inlet baffle and a first driving motor for driving the inlet baffle to rotate so as to enable salted duck eggs to enter the black box one by one, the first driving motor is installed on the black box, and a main shaft of the first driving motor is connected with the inlet baffle;
the conveying device comprises a first conveying mechanism, a second conveying mechanism and a third conveying mechanism, wherein the second conveying mechanism penetrates through the black box, the head end of the second conveying mechanism is connected with the tail end of the first conveying mechanism, and the tail end of the second conveying mechanism is connected with the head end of the third conveying mechanism; the third conveying mechanism is used for conveying the detected salted duck eggs to different collecting mechanisms;
the detection device comprises a first detection module arranged in the black box and a second detection module used for detecting the surface of the salted duck eggs, wherein,
the first detection module comprises an ammonia gas sensor, a hydrogen sulfide gas sensor and a fan which are arranged in a black box, wherein the ammonia gas sensor and the hydrogen sulfide gas sensor are arranged on the inner wall of the black box and are positioned on one side of the second conveying mechanism and used for detecting whether ammonia gas and hydrogen sulfide gas are contained in the gas emitted by salted duck eggs; the fan is arranged on the inner wall of the black box, is arranged opposite to the ammonia gas sensor and the hydrogen sulfide gas sensor, and is used for blowing gas emitted by salted duck eggs into the detection range of the ammonia gas sensor and the hydrogen sulfide gas sensor;
the second detection module comprises an image collection device, and is used for collecting the images of the salted duck eggs detected in the black box, transmitting the images to the control system, and analyzing and processing the images by the control system.
Preferably, the image collecting device comprises an industrial camera, and the industrial camera is arranged on the top of the inner wall of the black box and is positioned above the second conveying mechanism.
Preferably, the image collecting device further comprises light supplement lamps, and the light supplement lamps are installed on two sides of the industrial camera and used for supplementing light.
Preferably, an infrared sensor is arranged between the ammonia gas sensor and the hydrogen sulfide gas sensor and used for detecting whether salted duck eggs are detected.
Preferably, an inner baffle and a second driving motor for driving the inner baffle to rotate are further arranged in the black box, wherein the inner baffle is located above the second conveying mechanism; the second driving motor is installed on the inner wall of the black box, and a main shaft of the second driving motor is connected with the inner baffle.
Preferably, the conveying speed of the first conveying mechanism is lower than that of the second conveying mechanism.
Preferably, the number of the third conveying mechanisms is multiple, the head end of each group of the third conveying mechanisms is communicated with the tail end of the second conveying mechanism, and the tail ends of the third conveying mechanisms are connected with the collecting mechanisms; the end of the second conveying mechanism is provided with a sorting baffle, and the sorting baffle is driven by a third driving motor and is used for conveying salted duck eggs into a corresponding third conveying mechanism.
Preferably, the first conveying mechanism, the second conveying mechanism and the third conveying mechanism are all synchronous belt transmission mechanisms.
A salted duck egg quality sorting method based on a convolutional neural network comprises the following steps:
(1) firstly, the first conveying mechanism drives salted duck eggs to move, the salted duck eggs are conveyed to the second conveying mechanism, and then the salted duck eggs are conveyed to the detection range of the detection device by the second conveying mechanism; then, the first driving motor drives the inlet baffle to move, and the salted duck egg inlet in the black box is blocked;
(2) the control system controls the fan to work, the odor of the salted duck eggs is blown to the ammonia gas sensor and the hydrogen sulfide gas sensor, and the detection information is transmitted to the control system by the ammonia gas sensor and the hydrogen sulfide gas sensor; if the detected contents of ammonia gas and hydrogen sulfide gas emitted by the salted duck eggs exceed the standard values, the salted duck eggs are unqualified; the second conveying mechanism conveys the salted duck eggs to a third conveying mechanism, and the salted duck eggs are conveyed to a collecting mechanism for collecting unqualified salted duck eggs through the third conveying mechanism;
(3) if the detected content of ammonia gas and hydrogen sulfide gas emitted by the salted duck eggs does not exceed the standard value, the control system controls the image collecting device to work, photographs of the salted duck eggs are shot, and the photograph information is sent to the control system; the control system constructs a convolutional neural network model by processing the picture, wherein the construction of the convolutional neural network model comprises the following steps:
(3-1) collecting sample images and establishing a sample library, wherein the collected sample images comprise color photographs of salted duck eggs with different advantages and disadvantages taken at different angles; carrying out category marking on the obtained photos of the salted duck eggs, and the method comprises the following steps: the salted duck eggs with round and smooth appearance, complete and clean eggshells, no cracks and cyan shells are marked as positive type; marking salted duck eggs with dark shells, more white or black spots on the surfaces or cracks on the surfaces as reverse categories; if the input pictures contain pictures which do not contain salted duck eggs, marking the pictures as irrelevant pictures; then saving 70% of the labeled images as a training sample set and 30% as a testing sample set;
(3-2) normalizing the input sample image, and normalizing the input sample image in the training sample set and the test sample set to 227 multiplied by 227 for subsequent input into the convolutional neural network;
(3-3) building a convolutional neural network model; the constructed convolutional neural network model is an AlexNet model, and the network layer of the convolutional neural network model comprises 5 convolutional layers, 3 maximum pooling layers, 3 full-connection layers and 1 output layer; wherein, the first convolution layer adopts convolution kernel with the size of 11 multiplied by 11 and the step length is 4, and then a maximum pooling layer with the size of 3 multiplied by 3 is followed and the step length is 2; the second convolution layer adopts convolution kernel with the size of 5 multiplied by 5, the image size is kept unchanged by adopting image filling operation, and then a maximum pooling layer with the size of 3 multiplied by 3 is followed, and the step length is 2; subsequently, the third, fourth and fifth convolutional layers are three tightly connected identical convolutional layers of size 3 × 3, and the image size is kept unchanged by image filling operation; next to a maximum pooling layer of size 3 × 3, the step size is 2; followed by a fully-connected layer with an output of 9216 dimensions, followed by two identical fully-connected layers with an output of 4096 dimensions, followed by the output layer; the output layer adopts a Softmax function as an excitation function, and the rest network layers adopt a Relu function as an excitation function;
(3-4) initializing a convolution neural network model, initializing by using an Msra algorithm, and when only the input number is considered, initializing the Msra to be Gaussian distribution with the mean value of 0 and the variance of 2/n;
(3-5) training a convolutional neural network model;
(3-6) classifying the salted duck eggs through a trained convolutional neural network model; classifying the normally shot pictures containing the salted duck eggs into a positive type or a negative type; classifying the pictures of the non-salted duck eggs shot by mistake into irrelevant classes;
(4) and the control system controls the third conveying mechanism to convey the salted duck eggs after detection to the corresponding collecting mechanism according to the classification result of the convolutional neural network model.
Preferably, in step (3-5), the step of training the convolutional neural network model is:
(3-51), inputting characteristic variables;
(3-52) carrying out logic calculation on each item of data in the characteristic variables, and adding a normalization item during calculation;
(3-53) calculating the output of each neuron of each layer, and randomly abandoning the output of a part of neurons in the first two fully-connected layers by adopting a Dropout method;
(3-54) calculating a cost function of the logistic regression;
(3-55) calculating a proper weight matrix and a proper bias vector value by using a gradient descent method, and minimizing a cost function of logistic regression;
(3-56) repeating the steps (3-53) - (3-55) until the prediction accuracy meets the requirement;
and (3-57) analyzing and outputting results.
Compared with the prior art, the invention has the following beneficial effects:
1. according to the method, smelly salted duck eggs are preferentially removed by detecting gas components in gas emitted by the salted duck eggs, the remaining salted duck eggs are detected by utilizing the convolution neural network model which is trained in advance and used for detecting the quality of the salted duck eggs, the inferior salted duck eggs and the high-quality salted duck eggs are classified, the traditional manual detection mode is replaced, the labor force is saved, and the production efficiency is improved.
2. According to the invention, the salted duck eggs which are seriously deteriorated are preferentially removed by detecting the gas components emitted by the salted duck eggs, the remaining salted duck eggs are detected by using the convolutional neural network, the surface spots can still be used as the basis for classifying the salted duck eggs with complete shells, and finally the high-quality salted duck eggs and the low-quality salted duck eggs can be classified with higher accuracy, so that the detection precision is improved.
3. The method can be applied to the product quality detection link before salted duck eggs are produced and packaged, replaces the traditional manual detection classification, improves the production efficiency, and effectively controls the outgoing quality of the salted duck eggs.
Drawings
Fig. 1 is a schematic structural diagram of a salted duck egg quality sorting device based on a convolutional neural network according to a first embodiment of the invention.
FIG. 2 is a schematic view of the black box, the detecting device and the second conveying mechanism.
Fig. 3 is a schematic flow chart of the salted duck egg quality sorting method based on the convolutional neural network.
Fig. 4 is a schematic flow chart of the convolutional neural network model constructed in fig. 3.
Fig. 5 is a schematic flow chart of the process of training the convolutional neural network model in fig. 4.
Fig. 6 is a schematic diagram of a network structure of a convolutional neural network model.
Fig. 7 is a schematic configuration diagram of the first conveying mechanism and the second conveying mechanism in the salted duck egg quality sorting device based on the convolutional neural network according to the second embodiment of the present invention.
Fig. 8 is a schematic configuration diagram of a salted duck egg quality sorting device based on a convolutional neural network according to a third embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to examples and drawings, but the present invention is not limited thereto.
Example 1
Referring to fig. 1-2, the salted duck egg quality sorting device based on the convolutional neural network comprises a rack, a black box 7 arranged on the rack, a detection device arranged in the black box 7, a conveying device 11 for conveying salted duck eggs 8 into the black box 7 for detection, and a control system.
Referring to fig. 1-2, a salted duck egg inlet and a salted duck egg outlet are respectively arranged on two sides of the black box 7, wherein the salted duck egg inlet is provided with an inlet baffle 9 and a first driving motor for driving the inlet baffle 9 to rotate so as to promote salted duck eggs 8 to enter the black box 7 one by one, the first driving motor is mounted on the black box 7, and a main shaft is connected with the inlet baffle 9.
Referring to fig. 1-2, the conveying device 11 comprises a first conveying mechanism 11-1, a second conveying mechanism 11-2 and a third conveying mechanism 11-3, wherein the second conveying mechanism 11-2 penetrates through the black box 7, the head end of the second conveying mechanism 11-2 is connected with the tail end of the first conveying mechanism 11-1, and the tail end is connected with the head end of the third conveying mechanism 11-3; the third conveying mechanism 11-3 is used for conveying the salted duck eggs 8 after detection to different collecting mechanisms 11-4.
Referring to fig. 1-2, the detection device comprises a first detection module arranged in a black box 7 and a second detection module used for detecting the surface of the salted duck egg 8, wherein the first detection module comprises an ammonia gas sensor 3, a hydrogen sulfide gas sensor 5 and a fan 13 which are arranged in the black box 7, the ammonia gas sensor 3 and the hydrogen sulfide gas sensor 5 are mounted on the inner wall of the black box 7 and are positioned at the side edge of the second conveying mechanism 11-2 and used for detecting whether ammonia gas and hydrogen sulfide gas are contained in the gas emitted by the salted duck egg 8 or not; the fan is arranged on the inner wall of the black box 7, is arranged opposite to the ammonia gas sensor 3 and the hydrogen sulfide gas sensor 5, and is used for blowing gas emitted by the salted duck eggs 8 into the detection range of the ammonia gas sensor 3 and the hydrogen sulfide gas sensor 5; an infrared sensor 4 is arranged between the ammonia gas sensor 3 and the hydrogen sulfide gas sensor 5 and is used for detecting whether salted duck eggs 8 are detected;
the second detection module comprises an image collection device, the image collection device is used for collecting images of salted duck eggs 8 detected in a black box 7, transmitting the images to a control system, and analyzing and processing the images by the control system, wherein the image collection device comprises an industrial camera 1 and a light supplement lamp 2, the industrial camera 1 is mounted on the top of the inner wall of the black box 7 through a camera support 6 and is positioned above the second conveying mechanism 11-2; the light supplement lamps 2 are installed on two sides of the industrial camera 1 and used for supplementing light.
Referring to fig. 1-2, an inner baffle 10 and a second driving motor for driving the inner baffle 10 to rotate are further disposed inside the black box 7, wherein the inner baffle 10 is located above the second conveying mechanism 11-2; the second driving motor is arranged on the inner wall of the black box 7 and is connected with the inner baffle 10. The inner baffle 10 is driven to rotate by the second driving motor, so that the function of stopping the movement of the salted duck eggs 8 is achieved. When the salted duck eggs 8 are detected, the second driving motor drives the inner baffle 10 to rotate, so that the inner baffle 10 is driven to block the salted duck eggs 8 and enable the salted duck eggs to be located in the detection range of the detection device all the time, and after the salted duck eggs are detected, the second driving motor drives the inner baffle 10 to rotate, so that the salted duck eggs 8 are released, and the detection of the salted duck eggs 8 is facilitated.
Referring to fig. 1-2, the salted duck egg quality sorting device based on the convolutional neural network further comprises two groups of sorting devices mounted on a rack, wherein the two groups of sorting devices are sequentially arranged along the conveying direction of the third conveying mechanism 11-3, each group of sorting device comprises a conveying claw 16, a driving cylinder 17 for driving the conveying claw 16 to move perpendicular to the conveying direction of the third conveying mechanism 11-3, and a fourth conveying mechanism 18 for conveying the salted duck eggs 8 in the third conveying mechanism 11-3 to the corresponding collecting mechanism 11-4, and the conveying claw 16 is connected with a telescopic rod of the driving cylinder 17; the conveying direction of the fourth conveying mechanism 18 is perpendicular to the conveying direction of the third conveying mechanism 11-3, one end of the fourth conveying mechanism 18 is in butt joint with the third conveying mechanism 11-3, and the other end of the fourth conveying mechanism 18 is in butt joint with the collecting mechanism 11-4. After the salted duck eggs 8 are conveyed to the third conveying mechanism 11-3 by the second conveying mechanism 11-2, the salted duck eggs 8 are conveyed to corresponding sorting devices by the third conveying mechanism 11-3 according to different qualities, such as two sorting devices in the embodiment, wherein one of the two sorting devices is used for conveying the salted duck eggs 8 to the unqualified collecting mechanism 11-4; the salted duck eggs 8 are sent into a qualified collecting mechanism 11-4 by the other sorting device; the corresponding driving air cylinder 17 of the sorting device drives the carrying claw 16 to move, so that the salted duck eggs 8 are driven to move in the direction perpendicular to the conveying direction of the third conveying mechanism 11-3, the salted duck eggs 8 are conveyed to the corresponding fourth conveying mechanism 18, and the salted duck eggs are conveyed to the corresponding collecting mechanism 11-4 through the fourth conveying mechanism 18, so that the sorting work of the salted duck eggs 8 is completed.
In addition to the above embodiments, the sorting device may also adopt a mechanical arm sorting and conveying manner to convey salted duck eggs 8 with different qualities to different collecting mechanisms 11-4, wherein the mechanical arm sorting and conveying manner may be implemented by referring to a sorting device existing in the market, for example, an "egg sorting device" disclosed in the invention patent application with application publication number CN 109349164A.
The first conveying mechanism 11-1, the second conveying mechanism 11-2, the third conveying mechanism 11-3 and the fourth conveying mechanism 18 in the embodiment are synchronous belt transmission mechanisms, and a synchronous belt wheel is driven to rotate through a motor so as to drive a synchronous belt to move, so that the salted duck eggs 8 are conveyed, wherein a limiting block 19 is arranged on the synchronous belt, the limiting block 19 can be a shifting tooth on the synchronous belt and used for preventing the salted duck eggs 8 from moving relative to the synchronous belt in the conveying process, the limiting block 19 can be arranged on the front side and the rear side of the salted duck eggs 8, the cross section of the limiting block 19 is semicircular or circular, and therefore the conveying of the salted duck eggs 8 is facilitated, and the limitation on the relative movement between the salted duck eggs 8 and the synchronous belt is facilitated; the first conveying mechanism 11-1, the second conveying mechanism 11-2, the third conveying mechanism 11-3 and the fourth conveying mechanism 18 can be provided with flanges at the left and right sides of the limiting block 19 for preventing salted duck eggs 8 from rolling down from the synchronous belt.
In addition, the advantage of setting the cross section of the limiting block 19 to be semicircular or circular is that: when the salted duck eggs 8 are conveyed to the detection device by the second conveying mechanism 11-2 to be detected, the second driving motor drives the inner baffle plate 10 to rotate, so that the movement of the salted duck eggs 8 along with the synchronous belt of the second conveying mechanism 11-2 is stopped, and in this way, the salted duck eggs 8 and the second conveying mechanism 11-2 can move relatively, but because the section of the limiting block 19 on the synchronous belt of the second conveying mechanism 11-2 is semicircular or circular, when the salted duck eggs 8 and the limiting block 19 move relatively, the salted duck eggs 8 roll along the outer contour of the limiting block 19, the salted duck eggs 8 can be always limited in the detection range of the detection device, and meanwhile, no damage can be caused to the salted duck eggs 8.
Referring to fig. 1-2, the operation principle of the salted duck egg quality sorting device based on the convolutional neural network is as follows:
during work, the first conveying mechanism 11-1 drives the salted duck eggs 8 to move, the salted duck eggs 8 are conveyed to the second conveying mechanism 11-2, and then the salted duck eggs 8 are conveyed to the detection range of the detection device by the second conveying mechanism 11-2; then, the first driving motor drives the inlet baffle 9 to move, so that the salted duck eggs 8 in the black box 7 are blocked; after the salted duck eggs 8 are detected by the infrared sensor 4, the control system controls the fan 13 to work, the smell of the salted duck eggs 8 is blown to the ammonia gas sensor 3 and the hydrogen sulfide gas sensor 5, and the detection information is transmitted to the control system by the ammonia gas sensor 3 and the hydrogen sulfide gas sensor 5; if the detected content of ammonia gas and hydrogen sulfide gas emitted by the salted duck eggs 8 exceeds a standard value, the salted duck eggs 8 are unqualified; the second conveying mechanism 11-2 conveys the salted duck eggs 8 to a third conveying mechanism 11-3, and the salted duck eggs are conveyed to a collecting mechanism 11-4 for collecting unqualified salted duck eggs through the third conveying mechanism 11-3; if the detected content of ammonia gas and hydrogen sulfide gas emitted by the salted duck eggs 8 does not exceed the standard value, the control system controls the image collecting device to work, photographs of the salted duck eggs 8 are taken, and the photograph information is sent to the control system; processing the pictures through a control system, building a convolutional neural network model, and analyzing the quality of the salted duck eggs 8 through the convolutional neural network model; the control system controls the third conveying mechanism 11-3 to convey the detected salted duck eggs 8 to the corresponding collecting mechanism 11-4 according to the analysis result of the convolutional neural network model, so that automation and no humanization of quality sorting work of the salted duck eggs 8 are achieved. And because the data collected in the invention not only comprise the smell of the salted duck egg 8, the cracks of the eggshell of the salted duck egg 8, but also the color, the spots and the like of the eggshell of the salted duck egg 8, the quality analysis of the salted duck egg 8 without cracks can be realized through the data, and the detection precision is higher.
Referring to fig. 1-6, the salted duck egg quality sorting method based on the convolutional neural network comprises the following steps:
(1) firstly, the first conveying mechanism 11-1 drives the salted duck eggs 8 to move, the salted duck eggs 8 are conveyed to the second conveying mechanism 11-2, and then the salted duck eggs 8 are conveyed to the detection range of the detection device by the second conveying mechanism 11-2; the first driving motor drives the inlet baffle 9 to move, so that the salted duck eggs 8 in the black box 7 are blocked from being imported;
(2) the control system controls the fan 13 to work, the odor of the salted duck eggs 8 is blown to the ammonia gas sensor 3 and the hydrogen sulfide gas sensor 5, and the detection information is transmitted to the control system by the ammonia gas sensor 3 and the hydrogen sulfide gas sensor 5; if the detected content of ammonia gas and hydrogen sulfide gas emitted by the salted duck eggs 8 exceeds a standard value, the salted duck eggs 8 are unqualified; the second conveying mechanism 11-2 conveys the salted duck eggs 8 to a third conveying mechanism 11-3, and the salted duck eggs are conveyed to a collecting mechanism 11-4 for collecting unqualified salted duck eggs 8 through the third conveying mechanism 11-3;
(3) if the detected content of ammonia gas and hydrogen sulfide gas emitted by the salted duck eggs 8 does not exceed the standard value, the control system controls the image collecting device to work, shoots the photos of the salted duck eggs 8 and sends the information of the photos to the control system; the control system constructs a convolutional neural network model by processing the picture, wherein the construction of the convolutional neural network model comprises the following steps:
(3-1) sample IMAGE collection and sample library establishment, wherein the collected sample IMAGEs comprise color photographs (namely RGB-IMAGE in the specification of figure 6) of salted duck eggs 8 with different degrees of superiority and inferiority and taken at different angles; carrying out category marking on the obtained photos of the salted duck eggs 8, and specifically comprises the following steps: the salted duck eggs 8 with the eggs of smooth appearance, complete and clean eggshells, no cracks and cyan shells are marked as positive type; marking the salted duck eggs 8 with dark shells, more white or black spots on the surfaces or cracks on the surfaces as the reverse category; if the input pictures contain pictures which do not contain the salted duck eggs 8, marking the pictures as irrelevant pictures; saving 70% of the labeled images as a training sample set and 30% as a testing sample set;
(3-2) normalizing the input samples; normalizing the input samples in the training sample set and the test sample set to 227 multiplied by 227 (pixels) for subsequent input into the convolutional neural network, so as to improve the training efficiency of the convolutional neural network;
(3-3) building a convolutional neural network model; the constructed convolutional neural network model is an AlexNet model, and comprises 5 convolutional layers (CONV), 3 maximum pooling layers (POOL), 3 full-link layers (FC) and 1 output layer; wherein the first convolutional layer uses a convolutional kernel of size 11 × 11 with a step size of 4, followed by a maximum pooling layer of size 3 × 3 (pixels) with a step size of 2 (pixels); the second convolution layer adopts convolution kernels with the size of 5 multiplied by 5, the image size can be compressed by adopting image filling operation to keep the image size unchanged, namely, a circle of blank pixels are filled outside the original image before convolution (the convolution result is not influenced), and the image size after convolution can be kept unchanged; next to a maximum pooling layer of size 3 × 3, the step size is 2; subsequently, the third, fourth and fifth convolutional layers are three tightly connected identical convolutional layers of size 3 × 3, and the image size is kept unchanged by image filling operation; next to a maximum pooling layer of size 3 × 3, the step size is 2; followed by a fully-connected layer with an output of 9216 dimensions, followed by two identical fully-connected layers with an output of 4096 dimensions, followed by the output layer; the output layer adopts a Softmax function as an excitation function, and the rest network layers adopt a Relu function as an excitation function;
(3-4) initializing a convolutional neural network model; initializing by using an Msra method, wherein when only the input number is considered, the Msra initialization is Gaussian distribution with the mean value of 0 and the variance of 2/n;
(3-5) training a convolutional neural network model;
(3-6) classifying the salted duck eggs 8 through a trained convolutional neural network model; classifying the input salted duck egg 8 pictures by a convolutional neural network model, namely classifying the normally shot pictures containing the salted duck egg 8 into a positive type or a negative type; classifying the pictures of the non-salted duck eggs 8 shot by mistake into irrelevant classes;
(4) and the control system controls the third conveying mechanism 11-3 to convey the salted duck eggs 8 after detection to the corresponding collecting mechanism 11-4 according to the classification result of the convolutional neural network model.
Referring to fig. 1 to 6, in step (3-5), the step of training the convolutional neural network model is:
(3-51), inputting characteristic variables;
(3-52) carrying out logic calculation on each item of data in the characteristic variables, and adding a normalization item during calculation;
(3-53) calculating the output of each neuron of each layer, and randomly abandoning the output of a part of neurons in the first two fully-connected layers by adopting a Dropout method;
(3-54) calculating a cost function of the logistic regression;
(3-55) calculating a proper weight matrix and a proper bias vector value by using a gradient descent method, and minimizing a cost function of logistic regression;
(3-56) repeating the steps (3-53) - (3-55) until the prediction accuracy meets the requirement;
and (3-57) analyzing results and outputting the results.
Example 2
Referring to fig. 7, the present embodiment is different from embodiment 1 in that: the conveying speed of the first conveying mechanism 11-1 is less than that of the second conveying mechanism 11-2, namely V2 is greater than V1. Thus, when the salted duck eggs 8 are transferred from the first conveying mechanism 11-1 to the second conveying mechanism 11-2, the conveying speed of the second conveying mechanism 11-2 is greater than that of the first conveying mechanism 11-1, which is equivalent to acceleration of the salted duck eggs 8, and a horizontal forward acting force is generated, so that the salted duck eggs 8 and the subsequent salted duck eggs 8 are pulled apart by a certain distance, for example, when the speed of V2 is twice that of V1, the distance between the salted duck eggs 8 entering the second conveying mechanism 11-2 is twice that of the first conveying mechanism 11-1, so that the inlet baffle 9 can be ensured to smoothly close the inlet of the salted duck eggs without damaging the salted duck eggs 8 by reasonably adjusting the parameters of V1 and V2 according to the detection time; meanwhile, the first driving motor can drive the inlet baffle 9 to rotate, so that the salted duck eggs 8 at the back are smoothly blocked, the salted duck eggs 8 can be detected one by one, and the salted duck eggs 8 can be prevented from being damaged.
In addition to the above-described structure, the remaining structure can be implemented with reference to embodiment 1.
Example 3
Referring to fig. 8, the present embodiment is different from embodiment 1 in that the third conveying mechanisms 11-3 are two groups, an included angle between one group of the third conveying mechanisms 11-3 and the second conveying mechanism 11-2 is 135 degrees, an included angle between the other group of the third conveying mechanisms 11-3 and the second conveying mechanism 11-2 is 225 degrees, and the two groups of the third conveying mechanisms 11-3 are respectively butted with the second conveying mechanism 11-2, wherein a head end of each group of the third conveying mechanisms 11-3 is communicated with a tail end of the second conveying mechanism 11-2, and the tail end is connected with each collecting mechanism 11-4; the tail end of the second conveying mechanism 11-2 is provided with a sorting baffle 14, and the sorting baffle 14 is driven by a third driving motor and is used for conveying salted duck eggs 8 into different third conveying mechanisms 11-3; when the third driving motor drives the sorting baffle plate 14 to rotate to form an included angle of 135 degrees with the second conveying mechanism 11-2, the salted duck eggs 8 coming out of the second conveying mechanism 11-2 are in contact with the sorting baffle plate 14, move to the third conveying mechanism 11-3 forming an included angle of 135 degrees with the second conveying mechanism 11-2 along the inclined direction of the sorting baffle plate 14 under the driving of the second conveying mechanism 11-3, and are conveyed to the corresponding collecting mechanism 11-4 by the third conveying mechanism 11-3; similarly, when the third driving motor drives the sorting baffle 14 to rotate to form an included angle of 225 degrees with the second conveying mechanism 11-2, the salted duck eggs 8 can enter the third conveying mechanism 11-3 which forms an included angle of 225 degrees with the second conveying mechanism 11-2 under the guidance of the sorting baffle 14. Thus, the salted duck eggs 8 with different qualities can be sorted.
In this embodiment, both sides of the synchronous belts of the first conveying mechanism 11-1, the second conveying mechanism 11-2 and the third conveying mechanism 11-3 are provided with flanges, such as the flange 12 at both sides of the first conveying mechanism 11-1 and the flange 15 at both sides of the third conveying mechanism 11-3; this prevents the salted duck eggs 8 from falling down from the timing belt.
In addition to the above-described structure, the remaining structure can be implemented with reference to embodiment 1.
The present invention is not limited to the above embodiments, and any other changes, modifications, substitutions, combinations, and simplifications which do not depart from the spirit and principle of the present invention should be construed as equivalents and are included in the scope of the present invention.
Claims (10)
1. A salted duck egg quality sorting device based on a convolutional neural network is characterized by comprising a rack, a black box arranged on the rack, a detection device arranged in the black box, a conveying device used for conveying salted duck eggs into the black box for detection and a control system, wherein,
two sides of the black box are respectively provided with a salted duck egg inlet and a salted duck egg outlet, wherein the salted duck egg inlet is provided with an inlet baffle and a first driving motor for driving the inlet baffle to rotate so as to enable salted duck eggs to enter the black box one by one, the first driving motor is installed on the black box, and a main shaft of the first driving motor is connected with the inlet baffle;
the conveying device comprises a first conveying mechanism, a second conveying mechanism and a third conveying mechanism, wherein the second conveying mechanism penetrates through the black box, the head end of the second conveying mechanism is connected with the tail end of the first conveying mechanism, and the tail end of the second conveying mechanism is connected with the head end of the third conveying mechanism; the third conveying mechanism is used for conveying the detected salted duck eggs to different collecting mechanisms;
the detection device comprises a first detection module arranged in the black box and a second detection module used for detecting the surface of the salted duck eggs, wherein,
the first detection module comprises an ammonia gas sensor, a hydrogen sulfide gas sensor and a fan which are arranged in a black box, wherein the ammonia gas sensor and the hydrogen sulfide gas sensor are arranged on the inner wall of the black box and are positioned on one side of the second conveying mechanism and used for detecting whether ammonia gas and hydrogen sulfide gas are contained in the gas emitted by salted duck eggs; the fan is arranged on the inner wall of the black box, is arranged opposite to the ammonia gas sensor and the hydrogen sulfide gas sensor, and is used for blowing gas emitted by salted duck eggs into the detection range of the ammonia gas sensor and the hydrogen sulfide gas sensor;
the second detection module comprises an image collection device, and is used for collecting the images of the salted duck eggs detected in the black box, transmitting the images to the control system, and analyzing and processing the images by the control system.
2. The convolutional neural network-based salted duck egg quality sorting device as claimed in claim 1, wherein the image collecting device comprises an industrial camera, the industrial camera is arranged on the top of the inner wall of the black box and is positioned above the second conveying mechanism.
3. The salted duck egg quality sorting device based on the convolutional neural network as claimed in claim 2, wherein the image collecting device further comprises light supplementing lamps, and the light supplementing lamps are installed on two sides of the industrial camera and used for supplementing light.
4. The salted duck egg quality sorting device based on the convolutional neural network as claimed in claim 1, wherein an infrared sensor is arranged between the ammonia gas sensor and the hydrogen sulfide gas sensor for detecting whether salted duck eggs are detected.
5. The salted duck egg quality sorting device based on the convolutional neural network as claimed in claim 1, wherein an inner baffle and a second driving motor for driving the inner baffle to rotate are further arranged inside the black box, and the inner baffle is located above the second conveying mechanism; the second driving motor is installed on the inner wall of the black box, and a main shaft of the second driving motor is connected with the inner baffle.
6. The convolutional neural network-based salted duck egg quality sorting device as claimed in claim 1, wherein the conveying speed of the first conveying mechanism is less than that of the second conveying mechanism.
7. The salted duck egg quality sorting device based on the convolutional neural network as claimed in claim 1, wherein the number of the third conveying mechanisms is multiple, the head end of each group of the third conveying mechanisms is communicated with the tail end of the second conveying mechanism, and the tail ends are connected with the collecting mechanisms; the end of the second conveying mechanism is provided with a sorting baffle, and the sorting baffle is driven by a third driving motor and is used for conveying salted duck eggs into a corresponding third conveying mechanism.
8. The salted duck egg quality sorting device based on the convolutional neural network of claim 1, wherein the first conveying mechanism, the second conveying mechanism and the third conveying mechanism are all synchronous belt transmission mechanisms.
9. A salted duck egg quality sorting method for the convolutional neural network-based salted duck egg quality sorting device according to any one of claims 1 to 8, comprising the steps of:
(1) firstly, the first conveying mechanism drives salted duck eggs to move, the salted duck eggs are conveyed to the second conveying mechanism, and then the salted duck eggs are conveyed to the detection range of the detection device by the second conveying mechanism; then, the first driving motor drives the inlet baffle to move, and the salted duck egg inlet in the black box is blocked;
(2) the control system controls the fan to work, the odor of the salted duck eggs is blown to the ammonia gas sensor and the hydrogen sulfide gas sensor, and the detection information is transmitted to the control system by the ammonia gas sensor and the hydrogen sulfide gas sensor; if the detected contents of ammonia gas and hydrogen sulfide gas emitted by the salted duck eggs exceed the standard values, the salted duck eggs are unqualified; the second conveying mechanism conveys the salted duck eggs to a third conveying mechanism, and the salted duck eggs are conveyed to a collecting mechanism for collecting unqualified salted duck eggs through the third conveying mechanism;
(3) if the detected content of ammonia gas and hydrogen sulfide gas emitted by the salted duck eggs does not exceed the standard value, the control system controls the image collecting device to work, photographs of the salted duck eggs are shot, and the photograph information is sent to the control system; the control system constructs a convolutional neural network model by processing the picture, wherein the construction of the convolutional neural network model comprises the following steps:
(3-1) collecting sample images and establishing a sample library, wherein the collected sample images comprise color photographs of salted duck eggs with different advantages and disadvantages taken at different angles; carrying out category marking on the obtained photos of the salted duck eggs, and the method comprises the following steps: the salted duck eggs with round and smooth appearance, complete and clean eggshells, no cracks and cyan shells are marked as positive type; marking salted duck eggs with dark shells, more white or black spots on the surfaces or cracks on the surfaces as reverse categories; if the input pictures contain pictures which do not contain salted duck eggs, marking the pictures as irrelevant pictures; then saving 70% of the labeled images as a training sample set and 30% as a testing sample set;
(3-2) normalizing the input sample image, and normalizing the input sample image in the training sample set and the test sample set to 227 multiplied by 227 for subsequent input into the convolutional neural network;
(3-3) building a convolutional neural network model; the constructed convolutional neural network model is an AlexNet model, and the network layer of the convolutional neural network model comprises 5 convolutional layers, 3 maximum pooling layers, 3 full-connection layers and 1 output layer; wherein, the first convolution layer adopts convolution kernel with the size of 11 multiplied by 11 and the step length is 4, and then a maximum pooling layer with the size of 3 multiplied by 3 is followed and the step length is 2; the second convolution layer adopts convolution kernel with the size of 5 multiplied by 5, the image size is kept unchanged by adopting image filling operation, and then a maximum pooling layer with the size of 3 multiplied by 3 is followed, and the step length is 2; subsequently, the third, fourth and fifth convolutional layers are three tightly connected identical convolutional layers of size 3 × 3, and the image size is kept unchanged by image filling operation; next to a maximum pooling layer of size 3 × 3, the step size is 2; followed by a fully-connected layer with an output of 9216 dimensions, followed by two identical fully-connected layers with an output of 4096 dimensions, followed by the output layer; the output layer adopts a Softmax function as an excitation function, and the rest network layers adopt a Relu function as an excitation function;
(3-4) initializing a convolution neural network model, initializing by using an Msra algorithm, and when only the input number is considered, initializing the Msra to be Gaussian distribution with the mean value of 0 and the variance of 2/n;
(3-5) training a convolutional neural network model;
(3-6) classifying the salted duck eggs through a trained convolutional neural network model; classifying the normally shot pictures containing the salted duck eggs into a positive type or a negative type; classifying the pictures of the non-salted duck eggs shot by mistake into irrelevant classes;
(4) and the control system controls the third conveying mechanism to convey the salted duck eggs after detection to the corresponding collecting mechanism according to the classification result of the convolutional neural network model.
10. The salted duck egg quality sorting method based on the convolutional neural network as claimed in claim 9, wherein in the step (3-5), the step of training the convolutional neural network model is as follows:
(3-51), inputting characteristic variables;
(3-52) carrying out logic calculation on each item of data in the characteristic variables, and adding a normalization item during calculation;
(3-53) calculating the output of each neuron of each layer, and randomly abandoning the output of a part of neurons in the first two fully-connected layers by adopting a Dropout method;
(3-54) calculating a cost function of the logistic regression;
(3-55) calculating a proper weight matrix and a proper bias vector value by using a gradient descent method, and minimizing a cost function of logistic regression;
(3-56) repeating the steps (3-53) - (3-55) until the prediction accuracy meets the requirement;
and (3-57) analyzing and outputting results.
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