CN111634572A - Special intelligent medical waste classification device of nurse station - Google Patents
Special intelligent medical waste classification device of nurse station Download PDFInfo
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- CN111634572A CN111634572A CN202010585609.5A CN202010585609A CN111634572A CN 111634572 A CN111634572 A CN 111634572A CN 202010585609 A CN202010585609 A CN 202010585609A CN 111634572 A CN111634572 A CN 111634572A
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- 239000002906 medical waste Substances 0.000 title claims abstract description 58
- 238000012545 processing Methods 0.000 claims abstract description 37
- 239000002699 waste material Substances 0.000 claims abstract description 12
- 238000013527 convolutional neural network Methods 0.000 claims description 16
- 238000012549 training Methods 0.000 claims description 15
- 238000012360 testing method Methods 0.000 claims description 12
- 230000008878 coupling Effects 0.000 claims description 7
- 238000010168 coupling process Methods 0.000 claims description 7
- 238000005859 coupling reaction Methods 0.000 claims description 7
- 230000000007 visual effect Effects 0.000 claims description 7
- 238000005192 partition Methods 0.000 claims description 5
- 230000003993 interaction Effects 0.000 claims description 3
- 230000000474 nursing effect Effects 0.000 claims description 2
- 238000013461 design Methods 0.000 abstract description 2
- 230000001960 triggered effect Effects 0.000 abstract 1
- 238000010586 diagram Methods 0.000 description 9
- 238000000034 method Methods 0.000 description 4
- 239000003814 drug Substances 0.000 description 3
- 229920000742 Cotton Polymers 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 238000001802 infusion Methods 0.000 description 2
- 208000035473 Communicable disease Diseases 0.000 description 1
- 239000003570 air Substances 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
- 238000000968 medical method and process Methods 0.000 description 1
- 238000011176 pooling Methods 0.000 description 1
- 239000002689 soil Substances 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65F—GATHERING OR REMOVAL OF DOMESTIC OR LIKE REFUSE
- B65F1/00—Refuse receptacles; Accessories therefor
- B65F1/0033—Refuse receptacles; Accessories therefor specially adapted for segregated refuse collecting, e.g. receptacles with several compartments; Combination of receptacles
- B65F1/004—Refuse receptacles; Accessories therefor specially adapted for segregated refuse collecting, e.g. receptacles with several compartments; Combination of receptacles the receptacles being divided in compartments by partitions
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65F—GATHERING OR REMOVAL OF DOMESTIC OR LIKE REFUSE
- B65F1/00—Refuse receptacles; Accessories therefor
- B65F1/14—Other constructional features; Accessories
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65F—GATHERING OR REMOVAL OF DOMESTIC OR LIKE REFUSE
- B65F1/00—Refuse receptacles; Accessories therefor
- B65F1/0033—Refuse receptacles; Accessories therefor specially adapted for segregated refuse collecting, e.g. receptacles with several compartments; Combination of receptacles
- B65F2001/008—Means for automatically selecting the receptacle in which refuse should be placed
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65F—GATHERING OR REMOVAL OF DOMESTIC OR LIKE REFUSE
- B65F2210/00—Equipment of refuse receptacles
- B65F2210/138—Identification means
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65F—GATHERING OR REMOVAL OF DOMESTIC OR LIKE REFUSE
- B65F2210/00—Equipment of refuse receptacles
- B65F2210/176—Sorting means
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- Mechanical Engineering (AREA)
- Processing Of Solid Wastes (AREA)
Abstract
The invention provides a special intelligent medical waste classification device for a nurse station, which comprises a shell and various functional modules arranged inside the shell, wherein the input of medical waste is recognized through an infrared sensor, a vision acquisition processing module OpenMV is triggered to acquire image information of the waste, a machine vision algorithm is adopted to perform intelligent classification of the waste, the recognized classification result is transmitted to a main control module Arduino, the classification result is transmitted to a driving module through the main control module Arduino, the driving module drives a large rotating motor to work, when a storage chamber rotary drum rotates for a certain angle, a storage space needing to be put in is just positioned under the waste, the driving module controls a small rotating motor to work, fan blades are opened, and the fan blades are automatically closed under the elastic force of a spring after the waste falls into the storage space. The device combines a machine vision algorithm to realize intelligent classification of medical waste, adopts the elasticity of the spring to enable the fan blades to return to the original positions in structural design, and has the advantages of simple structure, strong practicability, electric energy saving and low use cost.
Description
Technical Field
The invention relates to the field of medical artificial intelligence, in particular to a special intelligent medical waste classification device for a nurse station.
Background
The medical garbage refers to garbage generated by directly or indirectly contacting patients in the medical process, belongs to harmful garbage, and has extremely strong infectivity, biotoxicity and corrosivity. The random disposal of medical waste causes pollution to air, soil and water, and simultaneously has harm to human bodies, and may become a source of infectious diseases. In the process of nursing patients, nurses can generate various medical wastes such as infusion tubes, needles, cotton swabs, medicament bottles, syringes, masks and the like. In order to avoid the problem of medical waste generation, it is necessary to classify medical waste and perform different treatment methods for different types. At present, classify to medical waste and mostly be medical personnel manual completion, not only increased medical personnel's work load and working strength, also reduced categorised accuracy simultaneously, efficiency is lower.
Disclosure of Invention
In order to achieve the purpose, the invention provides an intelligent medical waste sorting device which is specially used for a nurse station and can automatically finish waste sorting. A special intelligent medical waste classification device for a nurse station comprises a shell and functional modules inside the shell;
the shell comprises a feeding box, a storage chamber door and a bottom counterweight in sequence from top to bottom, and the storage box comprises a support shaft, a partition and a storage chamber drum;
each functional module in the shell comprises: the system comprises a vision acquisition processing module OpenMV, a main control module Arduino, a driving module, a power supply module, a lighting module, an infrared sensor, a network interface, a system rotating device and a gate opening and closing device, wherein the system rotating device comprises a large rotating motor, a rotating shaft and a coupling; the gate opening and closing device consists of a small rotating motor, a motor gear, a belt I, a belt II, a spring, a fan blade I and a fan blade II;
the middle position of the inner side of the top of the throwing box is provided with a groove, the circumferential surface of the throwing box is provided with a garbage throwing inlet, the throwing box is arranged at the top of the storage box, the bottom of the storage box is provided with a bottom counterweight, the supporting shaft is arranged at the central symmetrical shaft position of the storage box, the top of the storage chamber rotating drum is provided with a hexagonal groove, a hollow pipe structure is welded by taking the central symmetrical shaft of the storage chamber rotating drum as a central shaft, the storage chamber rotating drum is arranged in the storage box, the supporting shaft is nested in the hollow pipe of the storage chamber rotating drum, the bottom end of the supporting shaft is fixed at the bottom of the storage box and is used for supporting the storage chamber rotating drum to stably rotate, the partition is fixed between the inner wall of the storage chamber rotating drum and the outer wall of the hollow pipe, the large rotating motor is fixed in the middle of the bottom of the throwing box, a rotating shaft with one end processed into a hexagonal shape is embedded into a hexagonal groove at the top of the storage chamber rotating cylinder to be clamped, the other end of the rotating shaft is connected with a gear shaft of the large rotating motor by a coupling, the large rotating motor drives the storage chamber rotating cylinder to rotate through the rotating shaft, a power supply module is arranged in the groove in the middle of the top of the throwing box, an infrared sensor is arranged at one side of the rotating shaft corresponding to a garbage throwing inlet, a small rotating motor is fixed at the inner side of the throwing box opposite to the garbage throwing inlet, the tail end of a belt I is respectively fixed at one side of a fan blade I and the gear shaft of the small rotating motor, the tail end of another belt II is respectively fixed at one side of a fan blade II and the gear shaft of the small, two identical fan blades I and II are connected through a pin shaft, and a spring provides power for the closing of the fan blades I and II;
the vision collection processing module OpenMV is installed on the inner side wall close to the top of the input box, the driving module is installed on the other inner side wall close to the top of the input box, the main control module Arduino is installed above the driving module, the lighting module is fixed on the vision collection processing module OpenMV, the infrared sensor is connected with the vision collection processing module OpenMV through a single bus, the vision collection processing module OpenMV is connected with the main control module Arduino through a bus, the main control module Arduino is respectively connected with the driving module and the lighting module through buses, the driving module is respectively connected with the large rotating motor and the small rotating motor through buses, the power supply module is respectively connected with the vision collection processing module OpenMV, the main control module Arduino, the driving module, the lighting module, the infrared sensor, the large rotating motor and the small rotating motor through power lines, the network interface is installed on one side of the main control module Arduino, is connected with the main control module Arduino through a single wire;
the infrared sensor is used for identifying whether medical waste is input at the waste input port;
the vision acquisition processing module OpenMV is integrated with a camera and is used for acquiring medical waste images and intelligently classifying the input medical waste through a machine vision algorithm;
the main control module Arduino is used for converting the received classification result into a corresponding rotation angle value and transmitting the rotation angle value to the driving module;
the driving module is used for driving the large rotating motor to drive the storage chamber rotating drum to rotate by a certain angle value and is also used for driving the small rotating motor to drive the fan blade I and the fan blade II to be opened;
the master control module Arduino is also used for receiving a working stop signal of the large rotating motor fed back by the driving module; when the master control module Arduino receives a stop signal of the large rotating motor, the driving module controls the small rotating motor to drive the fan blade I and the fan blade II to be opened;
the main control module Arduino is also used for controlling the working time of the small rotating motor, and when the working time of the small rotating motor reaches the preset working time for s seconds, the driving module controls the small rotating motor to stop working;
the network interface is used for realizing the image data interaction between the main control module Arduino and external PC equipment.
The vision acquisition and processing module OpenMV realizes intelligent classification of medical waste input through a machine vision algorithm, and the method specifically comprises the following steps:
s1: constructing a VGG16 convolutional neural network model by utilizing Python software;
s2: constructing a training set by using M medical waste images, constructing a test set by using N medical waste images, inputting the training set into a VGG16 convolutional neural network model for training, testing the training set in the test set after the training is finished, and obtaining an optimal VGG16 convolutional neural network model with correct output classification results when the accuracy of the output classification results obtained in the test set reaches a preset accuracy;
s3: and classifying the actually input medical waste by using the optimal VGG16 convolutional neural network model, and outputting a classification result.
The working principle of the device is as follows: when medical waste is thrown in from an inlet of a throw-in box, the medical waste temporarily falls on fan blades I and II which are in an overlapped state, after an infrared sensor arranged on one side of a rotating shaft identifies the throw-in of the medical waste, signals are sent to a vision acquisition processing module OpenMV and a main control module Arduino, the vision acquisition processing module OpenMV starts a camera to work after receiving the signals, the main control module Arduino triggers a lighting module to work after receiving the signals, a clear image acquisition environment is provided for the camera to work, medical waste images acquired by the camera are intelligently classified through a machine vision algorithm in the vision acquisition processing module OpenMV, then classification results corresponding to the medical waste are output to the main control module Arduino, the main control module Arduino receives the classification result information and then outputs corresponding rotation angle values to a driving module through calculation, the large rotating motor is driven by the driving module to drive the storage chamber rotating cylinder to rotate by a corresponding rotating angle value and then stop working, after the large rotating motor stops working, the storage chamber rotating cylinder is required to meet the condition that the storage space required to be thrown in by the current medical waste is just positioned under the fan blades I and II, after the main control module Arduino receives a stop working signal fed back by the large rotating motor, the driving module controls the small rotating motor to drive the fan blades I and II to be opened for s seconds, the waste falls into the corresponding storage space in the storage chamber under the storage chamber, after the s seconds, the main control module Arduino controls the small rotating motor to stop working by the driving module, and simultaneously the large rotating motor drives the storage chamber rotating cylinder to return to the initial state, wherein the initial state is a state that the rotating angle of the rotating motor is 0, and after the small rotating motor stops working, the fan blades I and II automatically close under the elastic force of a, waiting for the next garbage input.
The invention has the beneficial effects that:
1. the device realizes automatic classification of medical waste by combining a machine vision algorithm, can effectively reduce the workload and the working strength of medical staff at a nurse station, and improves the working efficiency of the medical staff;
2. the device realizes the throwing of the garbage by matching the motor and the spring, when the garbage is thrown in, the motor drives the corresponding storage space in the storage chamber rotary drum to rotate to the position under the garbage, and after the garbage is opened by the fan blades and falls into the corresponding storage space, the spring force of the spring enables the fan blades to return to the original position; the design has simple structure, strong practicability, electric energy saving and low use cost;
3. the device is only provided with a garbage throwing-in opening, so that the problem of secondary pollution of medical garbage can be effectively reduced.
Drawings
FIG. 1 is a schematic view of the external structure of the present invention;
FIG. 2 is a schematic view of the internal structure of the present invention;
fig. 3 is a schematic diagram of the closing and opening states of the gate opening and closing device in the present invention, wherein fig. (a) is a schematic diagram of the closing state of the gate opening and closing device, and fig. (b) is a schematic diagram of the opening state of the gate opening and closing device;
FIG. 4 is a block diagram of a system of the present invention;
FIG. 5 is a schematic diagram of the circuit of the present invention;
fig. 6 is a programming flow chart of the machine vision algorithm in the invention, wherein (a) is a flow chart of a training program of the VGG16 convolutional neural network model, and (b) is a programming flow chart of a main program of the machine vision algorithm.
The reference numbers in FIGS. 1-3 indicate: 1. putting into a box; 2. a storage box; 3. a storage compartment door; 4. bottom counterweight; 5. a support shaft; 6. separating the gear; 7. a storage chamber drum; 8. a vision acquisition processing module OpenMV; 9. a main control module Arduino; 10. a drive module; 11. a power supply module; 12. a lighting module; 13. an infrared sensor; 14. a network interface; 15. a large rotating electrical machine; 16. a rotating shaft; 17. a small rotating electrical machine; 18. a motor gear; 19-1, a belt I; 19-2, a belt II; 20. a spring; 21-1, fan blade I; 21-2 and fan blades II; 22. a coupling is provided.
Detailed Description
The following is a detailed description of the technical solution of the present invention with reference to the accompanying drawings.
As shown in fig. 1 to 3, a special intelligent medical waste sorting device for a nurse station comprises a shell and functional modules inside the shell;
the shell comprises a feeding box 1, a storage box 2, a storage chamber door 3 and a bottom counterweight 4 from top to bottom in sequence, wherein the storage box 2 comprises a supporting shaft 5, a partition 6 and a storage chamber drum 7;
each functional module in the shell comprises: the system comprises a vision acquisition processing module OpenMV8, a main control module Arduino9, a driving module 10, a power supply module 11, a lighting module 12, an infrared sensor 13, a network interface 14, a system rotating device and a gate opening and closing device, wherein the system rotating device comprises a large rotating motor 15, a rotating shaft 16 and a coupling 22; the gate opening and closing device consists of a small rotating motor 17, a motor gear 18, a belt I19-1, a belt II19-2, a spring 20, a fan blade I21-1 and a fan blade II 21-2;
the middle position of the inner side of the top of the throw-in box 1 is processed with a groove, the circumferential surface of the throw-in box 1 is provided with a garbage throw-in opening, the throw-in box 1 is arranged at the top of the storage box 2, the bottom of the storage box 2 is provided with a bottom counterweight 4, the support shaft 5 is arranged at the central symmetrical axis position of the storage box 2, the top of the storage chamber rotary drum 7 is processed with a hexagonal groove, a hollow pipe structure is welded by taking the central symmetrical axis of the storage chamber rotary drum 7 as a central axis, the storage chamber rotary drum 7 is arranged in the storage box 2, the support shaft 5 is nested in the hollow pipe of the storage chamber rotary drum 7, the bottom end of the support shaft 5 is fixed at the bottom of the storage box 2, the support shaft 5 is used for supporting the storage chamber rotary drum 7 to stably rotate, the partition 6 is fixed between the inner wall, n is determined according to the classification number of medical wastes, a storage chamber door 3 is arranged on the circumference of a storage box 2 corresponding to each storage space, a large rotating motor 15 is fixed at the middle position of the bottom of an input box 1, a rotating shaft 16 with one end processed into a hexagonal shape is embedded into a hexagonal groove at the top of a storage chamber rotary drum 7 to be clamped, the other end of the rotating shaft 16 is connected with a gear shaft of the large rotating motor 15 through a coupling 22, the large rotating motor 15 drives the storage chamber rotary drum 7 to rotate through the rotating shaft 16, a power supply module 11 is installed in the groove in the middle of the top of the input box 1, an infrared sensor 13 is installed on one side of the rotating shaft 16 corresponding to a waste input port, a small rotating motor 17 is fixed on the inner side of the input box 1 corresponding to the waste input port, the tail end of a belt I19-1 is respectively fixed on one side of a fan blade I21-1 and the gear shaft of the small rotating motor 17 Two identical belts I19-1 and II19-2 are symmetrically arranged on a gear shaft, a small rotating motor 17 drives a fan blade I21-1 and a fan blade II21-2 to be opened through the belts I19-1 and II (19-2), two ends of a spring 20 are respectively connected to rear end extension rods of the fan blade I21-1 and the fan blade II21-2, the two identical fan blades I21-1 and II21-2 are connected through a pin shaft, and the spring 20 provides power for the closing of the fan blade I21-1 and the fan blade II 21-2;
the vision acquisition processing module OpenMV8 is installed on the inner side wall close to the top of the input box 1, the driving module 10 is installed on another inner side wall close to the top of the input box 1, the master control module Arduino9 is installed above the driving module 10, the lighting module 12 is fixed on the vision acquisition processing module OpenMV8, the infrared sensor 13 is connected with the vision acquisition processing module OpenMV8 through a single bus, the vision acquisition processing module OpenMV8 is connected with the master control module Arduino9 through a bus, the master control module Arduino9 is respectively connected with the driving module 10 and the lighting module 12 through a bus, the driving module 10 is respectively connected with the large rotating motor 15 and the small rotating motor 17 through a bus, the power supply module 11 is respectively connected with the vision acquisition processing module OpenMV8, the master control module Arduino9, the driving module 10, the lighting module 12, the infrared sensor 13, the large rotating motor 15 and the small rotating motor 17 through power lines, network interface 14 install in master control module Arduino9 one side, link to each other with master control module Arduino9 through the single line.
The infrared sensor 13 is used for identifying whether medical waste is input at the waste input port;
the vision acquisition processing module OpenMV8 is integrated with a camera and used for acquiring medical waste images and realizing intelligent classification of the input medical waste through a machine vision algorithm;
the vision acquisition processing module OpenMV8 realizes intelligent classification of medical waste input through a machine vision algorithm, and the method specifically comprises the following steps:
s1: constructing a VGG16 convolutional neural network model by utilizing Python software;
s2: constructing a training set by using M medical waste images, constructing a test set by using N medical waste images, inputting the training set into a VGG16 convolutional neural network model for training, testing the training set in the test set after the training is finished, and obtaining an optimal VGG16 convolutional neural network model with correct output classification results when the accuracy of the output classification results obtained in the test set reaches a preset accuracy;
s3: and classifying the actually input medical waste by using the optimal VGG16 convolutional neural network model, and outputting a classification result.
The machine vision algorithm in the embodiment is programmed by adopting python software, a specific programming flow chart is shown in fig. 6(a) - (b), firstly, the VGG16 convolutional neural network is trained through a large amount of medical waste data sets, and an optimal VGG16 convolutional neural network model with correct output classification results is obtained; after garbage is thrown in, the acquired medical garbage images are transmitted to an optimal VGG16 convolutional neural network model, the characteristics of the medical garbage images are extracted through 13 convolutional layers and 5 pooling layers in the model, and finally the medical garbage images are input to 3 full-connection layers to complete medical garbage classification and send classification result information to a main control module Arduino 9.
The main control module Arduino9 is configured to convert the received classification result into a corresponding rotation angle value, and transmit the rotation angle value to the driving module 10;
the driving module 10 is used for driving the large rotating motor 15 to drive the storage chamber drum 7 to rotate by a certain angle value, and is also used for driving the small rotating motor 17 to drive the fan blade I21-1 and the fan blade II21-2 to be opened;
the main control module Arduino9 is further configured to receive a work stop signal of the large rotating electrical machine 15 fed back by the driving module 10; when the master control module Arduino9 receives a stop signal of the large rotating motor 15, the small rotating motor 17 is controlled by the driving module 10 to drive the fan blade I21-1 and the fan blade II21-2 to be opened;
the main control module Arduino9 is further configured to control the working time of the small rotating electrical machine 17, and when the working time of the small rotating electrical machine 17 reaches a preset working time s seconds, the driving module 10 controls the small rotating electrical machine 17 to stop working;
the network interface 14 is used for realizing the image data interaction between the main control module Arduino9 and an external PC device.
In this embodiment, the specific model of the adopted vision acquisition processing module OpenMV8 is OpenMV H7, the specific model of the main control module Arduino9 is Arduino mega 2560, the specific model of the driving module 10 is TB6612, the specific model of the large rotating motor 15 is a60KTYZ-K7042, the specific model of the small rotating motor 17 is ZB4124-300, the specific model of the infrared sensor 13 is DYS412, the specific circuit schematic diagram is shown in fig. 5, the system block diagram of the device is shown in fig. 4, and the specific control principle is as follows: when medical waste is thrown in from an inlet of the throw-in box 1, the medical waste temporarily falls on the fan blades I21-1 and II21-2 which are in an overlapped state, after the infrared sensor 13 arranged on one side of the rotating shaft 16 identifies the throw-in of the medical waste, signals are sent to the vision acquisition processing module OpenMV8 and the main control module Arduino9, the vision acquisition processing module OpenMV8 starts a camera to work after receiving the signals, the main control module Arduino9 triggers the illumination module 12 to work after receiving the signals, a clearer image acquisition environment is provided for the camera to work, medical waste images acquired by the camera are intelligently classified through a machine vision algorithm in the vision acquisition processing module OpenMV8, then classification results corresponding to the medical waste are output to the main control module Arduino9, after the main control module Arduino9 receives the classification result information, corresponding rotation angle values are output to the driving module 10 through calculation, the driving module 10 drives the large rotating motor 15 to drive the storage chamber rotary drum 7 to rotate by a corresponding rotation angle value and then stop working, after the large rotating motor 15 stops working, the storage chamber rotary drum 7 is required to meet the condition that the storage space required to be thrown in by the current medical waste is just positioned under the fan blade I21-1 and the fan blade II21-2, when the main control module Arduino9 receives a stop working signal fed back by the large rotating motor 15, the driving module 10 drives the small rotating motor 17 to drive the fan blade I21-1 and the fan blade II21-2 to be opened for s seconds, s is determined according to the specific practical conditions, in the embodiment, s is selected to be 3, wherein the structural schematic diagram of the fan blade I21-1 and the fan blade II21-2 in the opened state is shown in fig. 3(b), the waste falls into the corresponding storage space in the storage chamber under the storage chamber, and after 3 seconds, the main control module Arduino9 controls the small rotating motor 17 to stop working through the driving module, meanwhile, the large rotating motor 15 drives the storage chamber drum 7 to return to an initial state, the initial state is a state that the rotating angle of the rotating motor is 0, after the small rotating motor 17 stops working, the fan blade I21-1 and the fan blade II21-2 are automatically closed under the elastic force of the spring 20 to wait for the next garbage input, wherein the structural schematic diagram of the fan blade I21-1 and the fan blade II21-2 in the closed state is shown in fig. 3 (a).
The master control module Arduino9 in this embodiment is used for converting the received classification result into a corresponding rotation angle value, and is specifically expressed as: the main control module Arduino9 monitors the vision collection processing module OpenMV8 in real time, converts the information into a motor rotation angle value ang1 after receiving the specific classification result information of the vision collection processing module OpenMV8, the driving module 10 sends a rotation angle ang1 driving instruction to the large rotating motor 15, the main control module Arduino9 sends a rotation angle ang2(ang2 ═ 60 ℃) driving instruction to the small rotating motor 17 after receiving the rotation stop signal fed back by the large rotating motor 15, and after timing for 3 seconds, the main control module Arduino9 sends a driving signal of a reverse rotation angle ang2 of the small rotating motor 17 through the driving module 10, and simultaneously sends a driving signal of a reverse rotation angle ang1 of the large rotating motor 15 through the driving module 10, so as to drive the large rotating motor 15 and the small rotating motor 17 to return to the initial state respectively.
In this embodiment, the medical waste to be classified is 6 kinds, that is, N is 6, specifically, an infusion tube, a needle, a medicine bottle, an injector, a cotton swab, and a mask, and according to the six classification results, the main control module Arduino9 receives the motor rotation angle value ang1 (clockwise is positive) corresponding to the information of the specific classification result of the visual capture processing module OpenMV8, as shown in table 1, for example, when the classification result output by the visual capture processing module OpenMV8 is a medicine bottle, the main control module Arduino9 controls the rotation angle ang1 of the large rotation motor 15 to be 120 °.
TABLE 1 corresponding table of classification result and rotation angle value
Claims (7)
1. A special intelligent medical waste classification device for a nurse station is characterized by comprising a shell and functional modules inside the shell;
the shell comprises a feeding box (1), a storage box (2), a storage chamber door (3) and a bottom counterweight (4) from top to bottom in sequence, wherein a supporting shaft (5), a baffle (6) and a storage chamber rotating cylinder (7) are arranged in the storage box (2);
each functional module in the shell comprises: the system comprises a vision acquisition processing module OpenMV (8), a main control module Arduino (9), a driving module (10), a power supply module (11), a lighting module (12), an infrared sensor (13), a network interface (14), a system rotating device and a gate opening and closing device, wherein the system rotating device comprises a large rotating motor (15), a rotating shaft (16) and a coupling (22); the gate opening and closing device consists of a small rotating motor (17), a motor gear (18), a belt I (19-1), a belt II (19-2), a spring (20), a fan blade I (21-1) and a fan blade II (21-2);
the garbage storage device is characterized in that a groove is processed in the middle of the inner side of the top of the storage box (1), a garbage throwing-in opening is formed in the circumferential surface of the storage box (1), the storage box (1) is installed at the top of the storage box (2), a bottom counterweight (4) is installed at the bottom of the storage box (2), a supporting shaft (5) is installed at the position of a central symmetry axis of the storage box (2), a hexagonal groove is processed at the top of a storage chamber rotating cylinder (7), a hollow pipe structure is welded by taking the central symmetry axis of the storage chamber rotating cylinder (7) as a central axis, the storage chamber rotating cylinder (7) is installed inside the storage box (2), the supporting shaft (5) is embedded in the hollow pipe of the storage chamber rotating cylinder (7), the bottom end of the supporting shaft (5) is fixed at the bottom of the storage box (2), the supporting shaft (5) is used for supporting the rotating cylinder, the storage chamber rotary drum (7) is uniformly divided into N storage spaces through N-1 partition bars (6), a storage chamber door (3) is arranged on the circumference of the storage box (2) opposite to each storage space, a large rotating motor (15) is fixed at the middle position of the bottom of the throwing-in box (1), a rotating shaft (16) with one end processed into a hexagonal shape is embedded into a hexagonal groove at the top of the storage chamber rotary drum (7) to be clamped, the other end of the rotating shaft (16) is connected with a gear shaft of the large rotating motor (15) through a coupling (22), the large rotating motor (15) drives the storage chamber rotary drum (7) to rotate through the rotating shaft (16), a power supply module (11) is arranged in the groove in the middle of the top of the throwing-in box (1), an infrared sensor (13) is arranged on one side of the rotating shaft (16) corresponding to a garbage throwing-in inlet, a small rotating motor (17) is fixed on the inner side of the, the tail end of a belt I (19-1) is respectively fixed on one side of a fan blade I (21-1) and a gear shaft of a small rotating motor (17), the tail end of another belt II (19-2) is respectively fixed on one side of the fan blade II (21-2) and the gear shaft of the small rotating motor (17), the two identical belts I (19-1) and II (19-2) are symmetrically arranged, two ends of a spring (20) are respectively connected to rear end extension rods of the fan blade I (21-1) and the fan blade II (21-2), the two identical fan blades I (21-1) and II (21-2) are connected through a pin shaft, and the spring (20) provides power for the closing of the fan blade I (21-1) and the fan blade II (21-2);
visual collection processing module OpenMV (8) install on being close to the inside wall of throwing into case (1) top, drive module (10) install on being close to another inside wall of throwing into case (1) top, master control module Arduino (9) install in the top of drive module (10), lighting module (12) fix on visual collection processing module OpenMV (8), infrared sensor (13) link to each other with visual collection processing module OpenMV (8) through the monobus, visual collection processing module OpenMV (8) are connected with master control module Arduino (9) through the bus, master control module Arduino (9) link to each other with drive module (10), lighting module (12) respectively through the bus, drive module (10) link to each other with big rotating electrical machines (15), little rotating electrical machines (17) respectively through the bus, power module (11) gather processing module OpenMV (8) through power cord and visual respectively, Master control module Arduino (9), drive module (10), lighting module (12), infrared sensor (13), big rotating electrical machines (15) and little rotating electrical machines (17) link to each other, network interface (14) install in master control module Arduino (9) one side, link to each other with master control module Arduino (9) through the single line.
2. The nursing station dedicated intelligent medical waste sorting device as claimed in claim 1, wherein the infrared sensor (13) is used for identifying whether medical waste is thrown into the waste throwing port.
3. The intelligent medical waste classification device special for nurses' stations as claimed in claim 1, wherein the vision collection processing module OpenMV (8) is integrated with a camera for collecting medical waste images and implementing intelligent classification of the input medical waste by a machine vision algorithm.
4. The intelligent medical waste sorting device special for nurses' station as claimed in claim 1, wherein the main control module Arduino (9) is used for converting the received sorting result into a corresponding rotation angle value and transmitting the rotation angle value to the driving module (10); the master control module Arduino (9) is also used for receiving a work stop signal of the large rotating motor (15) fed back by the driving module (10); after the master control module Arduino (9) receives a stop signal of the large rotating motor (15), the small rotating motor (17) is controlled by the driving module (10) to drive the fan blade I (21-1) and the fan blade II (21-2) to be opened; master control module Arduino (9) still be used for controlling the operating duration of little rotating electrical machines (17), when the operating duration of little rotating electrical machines (17) reaches and predetermines operating duration s seconds after, control little rotating electrical machines (17) stop work through drive module (10).
5. The intelligent medical waste sorting device special for nurses' station according to claim 1, wherein the driving module (10) is used for driving the large rotating motor (15) to drive the storage chamber drum (7) to rotate for a certain angle value, and is also used for driving the small rotating motor (17) to drive the fan blades I (21-1) and II (21-2) to open.
6. The intelligent medical waste sorting device special for nurses' station as claimed in claim 1, wherein the network interface (14) is used for realizing the image data interaction between the master control module Arduino (9) and an external PC device.
7. The intelligent medical waste classification device special for nurses' stations as claimed in claim 3, wherein the vision collection processing module OpenMV (8) realizes intelligent classification of medical waste input through a machine vision algorithm, specifically expressed as:
s1: constructing a VGG16 convolutional neural network model by utilizing Python software;
s2: constructing a training set by using M medical waste images, constructing a test set by using N medical waste images, inputting the training set into a VGG16 convolutional neural network model for training, testing the training set in the test set after the training is finished, and obtaining an optimal VGG16 convolutional neural network model with correct output classification results when the accuracy of the output classification results obtained in the test set reaches a preset accuracy;
s3: and classifying the actually input medical waste by using the optimal VGG16 convolutional neural network model, and outputting a classification result.
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