CN113003037A - Intelligent garbage classification system based on cross belt type sorting structure - Google Patents
Intelligent garbage classification system based on cross belt type sorting structure Download PDFInfo
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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
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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
- B65F2210/168—Sensing means
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02W—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO WASTEWATER TREATMENT OR WASTE MANAGEMENT
- Y02W30/00—Technologies for solid waste management
- Y02W30/10—Waste collection, transportation, transfer or storage, e.g. segregated refuse collecting, electric or hybrid propulsion
Abstract
The utility model provides an intelligent waste classification system based on cross belt letter sorting structure, belongs to waste classification technical field for solve the problem that current waste classification system is not high to waste classification's letter sorting efficiency. The system comprises: the garbage collection system comprises a data acquisition module, a main control module, a transmission module and a garbage containing module; the data acquisition module comprises a camera, and the camera is used for acquiring image data; the main control module comprises an image identification submodule and a driving submodule, the image identification submodule is used for identifying the garbage category according to image data, and the driving submodule is used for driving the transmission module to transmit in different modes according to the garbage category information; the conveying module is arranged above the garbage accommodating module and comprises two conveying belts and a motor, wherein the two conveying belts and the motor are vertically crossed and do not intersect through transmission shafts. The garbage conveying system adopts a cross belt type structure, saves the cost of manpower and material resources compared with manual classification, and is more intelligent and higher in classification efficiency.
Description
Technical Field
The invention relates to the technical field of garbage classification, in particular to an intelligent garbage classification system based on a cross belt type sorting structure.
Background
With the steady increase of the consumption level of the modern society, the quantity and the variety of the garbage also show an increasing trend. The current garbage disposal modes in China are mainly two, namely garbage landfill and garbage stacking, and the two disposal modes are essentially to perform simple position transformation on the garbage and still occupy land resources. Land resources are however fixed and the waste contains a large amount of chemicals which, if not properly disposed of, will circulate with the earth throughout the ecosphere.
The garbage classification is an optimal solution for garbage treatment, can effectively improve the environment and promote the recycling of resources. The precise garbage classification system can ensure that the garbage recovery and treatment system can operate efficiently.
The classification garbage can is a feasible scheme, the classification garbage can on the market can only have storage spaces of four basic categories, only ordinary human body induction is achieved in the aspect of intelligence, when people face various types of garbage in the current society, people cannot be helped to recognize the garbage and sort the garbage by themselves in a matched mode, and inconvenience is caused in actual life. The transformation design of most of the existing garbage cans mainly focuses on the aspects of the quantity, the placing form, the personalized design and the like of the garbage cans, and the garbage cans are not sufficient in the aspects of effective garbage identification and intelligent sorting.
Disclosure of Invention
In view of the above problems, the present invention provides an intelligent garbage classification system based on a cross belt type sorting structure, so as to solve the problem that the existing garbage classification system has low sorting efficiency for garbage classification.
An intelligent garbage classification system based on a cross belt type sorting structure comprises a data acquisition module, a main control module, a conveying module and a garbage containing module; wherein the content of the first and second substances,
the data acquisition module comprises a camera, and the camera is arranged at the garbage throwing port and used for acquiring image data and sending the image data to the main control module;
the main control module comprises an image recognition submodule and a driving submodule; the image identification submodule is used for identifying the garbage category according to the image data and sending the identified garbage category information to the driving submodule; the driving submodule is used for driving the transmission module to transmit in different modes according to the garbage category information;
the conveying module is arranged above the garbage accommodating module and comprises two conveying belts and two motors, wherein the transmission shafts of the two conveying belts are vertically crossed and do not intersect;
the main control module is respectively and electrically connected with the data acquisition module and the transmission module.
The system further comprises a serial port display interaction module, wherein the serial port display interaction module comprises a storage submodule, a display submodule, a voice playing submodule and an interaction submodule; the storage submodule is used for storing video data and audio data; the display submodule is used for playing and displaying the video data; the voice playing submodule is used for playing audio data, and the audio content is a garbage classification result; the interaction submodule is used for man-machine interaction; the serial port display interaction module is electrically connected with the main control module.
Furthermore, the data acquisition module also comprises an ultrasonic sensor which is arranged above the garbage containing module and below the conveying module and used for carrying out full load detection on the garbage containing module and sending real-time garbage height data to the main control module; the main control module further comprises a utilization rate calculation submodule and an alarm submodule, wherein the utilization rate calculation submodule is used for calculating the utilization rate of the garbage containing module according to the real-time garbage height data and sending alarm information to the alarm submodule when the garbage containing module is fully loaded; the alarm submodule is used for receiving alarm information and sending an alarm signal.
Further, the image recognition sub-module recognizes the garbage category by using a deep learning-based YOLOV3 algorithm, and analyzes the recognition result by using a reliability weighting algorithm, wherein the reliability weighting algorithm specifically comprises the following steps: analyzing the garbage category information contained in the identification result of each frame of image shot by the camera, if the same identification result continuously appears in the multi-frame images, increasing the reliability of the identification result, if the same identification result does not continuously appear in the multi-frame images, namely other different identification results appear in the middle, reducing the reliability of the identification result, and when the reliability is greater than a preset maximum threshold value, determining that the result is reliable, and determining the identification result with the maximum continuous occurrence frequency as the final identification result; and when the reliability is smaller than a preset minimum threshold value, repeating the analysis process on the recognition result with the largest continuous occurrence frequency.
Further, the driving submodule controls the speed of the motor driving the conveyor belt to transmit by adopting a trapezoidal acceleration and deceleration motion control algorithm, and the trapezoidal acceleration and deceleration motion control algorithm comprises driving frequencies obtained by calculation in three stages, namely a trapezoidal acceleration stage, a uniform speed stage and a deceleration stage.
Furthermore, two conveyor belts in the conveying module are divided into an upper conveyor belt and a lower conveyor belt, and a baffle is fixedly arranged between the upper conveyor belt and the lower conveyor belt; the garbage containing module comprises four garbage cans with the same size.
Further, the usage in the usage calculation submodule includes a measured usage u1And evaluating the usage u2Said usage calculation submodule depending on the measured usage u1And evaluating the usage u2The actual utilization rate of the garbage containing module is obtained through calculation of different weights.
Further, the measured usage u1The following equation is used:
wherein d represents the distance between the ultrasonic sensor and the uppermost garbage; i represents the distance between the ultrasonic sensor and the top of the garbage can; h represents the height of the garbage can;
the estimated usage u2The volume of the current existing garbage in the garbage can is estimated, and the volume and the total capacity of the garbage can are calculated to obtain the current estimated utilization rate u of the garbage can2。
Further, the different modes of transmission in the drive sub-module are: the upper conveyor belt and the lower conveyor belt are driven clockwise; the upper conveyor belt and the lower conveyor belt are in anticlockwise transmission; the upper conveyor belt is driven clockwise, and the lower conveyor belt is driven anticlockwise; the upper conveying belt is in anticlockwise transmission, and the lower conveying belt is in clockwise transmission.
Further, the system also comprises a human body induction module and an illumination module, wherein the human body induction module is used for detecting human body information and sending the information to the image identification submodule after detecting the human body information; the illumination module is used for illuminating the area of the garbage throwing port and comprises a photosensitive sensor and a cold light lamp, and when the photosensitive sensor detects that light is too dark, the cold light lamp is turned on to illuminate; the human body induction module and the lighting module are respectively electrically connected with the main control module.
The beneficial technical effects of the invention are as follows:
the invention provides an intelligent garbage classification system based on a cross belt type sorting structure, which comprehensively uses embedded control and image recognition to realize classification of garbage. The garbage can sorting system adopts a cross belt type structure, automatic sorting can be realized only by sequentially putting garbage into the system during sorting, and further full load detection can be realized, namely whether the garbage can at the bottom is full or not is automatically detected, and an alarm is given out when the garbage can at the bottom is full; furthermore, the driving control adopts a trapezoidal acceleration and deceleration control algorithm, so that the conveyor belt can be driven to move accurately and rapidly, and the situations of overshooting and step losing of the stepping motor in the starting and stopping processes can be prevented; furthermore, the human body induction module can induce whether human body activities exist nearby, and compared with manual classification, the human body induction module saves the cost of manpower and material resources, and is more intelligent and higher in efficiency.
Drawings
The invention may be better understood by referring to the following description in conjunction with the accompanying drawings, in which like reference numerals are used throughout the figures to indicate like or similar parts. The accompanying drawings, which are incorporated in and form a part of this specification, illustrate preferred embodiments of the present invention and, together with the detailed description, serve to further explain the principles and advantages of the invention.
FIG. 1 is a schematic structural diagram of an intelligent garbage classification system based on a cross-belt sorting structure according to the present invention;
FIG. 2 is an overall isometric view of a particular embodiment of an intelligent waste sorting system based on a cross-belt sorting structure according to the present invention;
FIG. 3 is an overall elevation view of an embodiment of the intelligent waste sorting system of the present invention based on a crossbelt sorting structure;
FIG. 4 is a schematic top view of an upper conveyor belt of an embodiment of an intelligent waste sorting system based on a crossbelt sorting structure of the present invention;
FIG. 5 is a schematic top view of a lower conveyor belt of an embodiment of the intelligent waste sorting system of the present invention based on a cross-belt sorting structure;
fig. 6 is a schematic top view of the arrangement of the trash cans of the embodiment of the intelligent trash classification system based on the cross-belt sorting structure.
Detailed Description
Exemplary embodiments of the present invention will be described hereinafter with reference to the accompanying drawings. In the interest of clarity and conciseness, not all features of an actual implementation are described in the specification. It should be noted that, in order to avoid obscuring the present invention with unnecessary details, only the device structures and/or processing steps closely related to the solution according to the present invention are shown in the drawings, and other details not so relevant to the present invention are omitted.
As shown in fig. 1, an intelligent garbage classification system based on a cross-belt sorting structure includes a data acquisition module 110, a main control module 120, a transmission module 130, a garbage accommodating module 140, a serial port display interaction module 150, a human body induction module 160 and an illumination module 170; wherein the content of the first and second substances,
the data acquisition module 110 comprises a camera 1110 and an ultrasonic sensor 1120; the camera 1110 is disposed at the trash input port, and is configured to collect image data and send the image data to the main control module 120; the ultrasonic sensor 1120 is arranged above the garbage accommodating module 140 and below the conveying module 130, and is used for detecting the full load of the garbage accommodating module 140 and sending real-time garbage height data to the main control module 120;
the main control module 120 comprises an image recognition sub-module 1210, a driving sub-module 1220, a utilization rate calculation sub-module 1230 and an alarm sub-module 1240; wherein the content of the first and second substances,
the image identification submodule 1210 is configured to identify a garbage category according to the image data, and send the identified garbage category information to the drive submodule 1220; identifying the garbage category by adopting a deep learning-based YOLOV3 algorithm, and analyzing an identification result by adopting a reliability weighting algorithm, wherein the reliability weighting algorithm comprises the following specific steps: analyzing the garbage category information contained in the identification result of each frame of image shot by the camera, if the same identification result continuously appears in the multi-frame images, increasing the reliability of the identification result, if the same identification result does not continuously appear in the multi-frame images, namely other different identification results appear in the middle, reducing the reliability of the identification result, and when the reliability is greater than a preset maximum threshold value, determining that the result is reliable, and determining the identification result with the maximum continuous occurrence frequency as the final identification result; when the reliability is smaller than a preset minimum threshold value, repeating the analysis process on the recognition result with the largest continuous occurrence frequency;
the driving sub-module 1220 is used for driving the transmitting module 130 to perform transmission in different modes according to the garbage category information; the trapezoidal acceleration and deceleration motion control algorithm is adopted to control the speed of the motor driving the conveyor belt to transmit, and the trapezoidal acceleration and deceleration motion control algorithm comprises driving frequencies obtained by calculation in three stages, namely a trapezoidal acceleration stage, a uniform speed stage and a deceleration stage;
the utilization rate calculating submodule 1230 is configured to calculate the utilization rate of the garbage accommodating module 140 according to the real-time garbage height data, and send alarm information to the alarm submodule 1240 when the garbage accommodating module 140 is fully loaded; usage includes measured usage u1And evaluating the usage u2And according to the measured utilization rate u1And evaluating the usage u2Calculating different weights to obtain the actual utilization rate of the garbage accommodating module; measured usage u1The following equation is used:
wherein d represents the distance between the ultrasonic sensor and the uppermost garbage; l represents the distance between the ultrasonic sensor and the top of the garbage can; h represents the height of the garbage can;
evaluating usage u2The volume of the current existing garbage in the garbage can is estimated, and the volume and the total capacity of the garbage can are calculated to obtain the current estimated utilization rate u of the garbage can2；
The alarm submodule 1240 is used for receiving alarm information and sending an alarm signal;
the conveying module 130 is arranged above the garbage accommodating module 140 and comprises two conveying belts and two motors, wherein the transmission shafts of the two conveying belts are vertically crossed and do not intersect; the two conveyor belts are divided into an upper conveyor belt and a lower conveyor belt, and a baffle is fixedly arranged between the upper conveyor belt and the lower conveyor belt;
the trash holding module 140 includes four trash cans of the same size;
the serial port display interaction module 150 comprises a storage sub-module 1510, a display sub-module 1520, a voice playing sub-module 1530 and an interaction sub-module 1540; wherein the content of the first and second substances,
the storage submodule 1510 is configured to store video data and audio data;
the display sub-module 1520 is configured to play and display the video data;
the voice playing sub-module 1530 is used for playing the audio data; wherein the audio content is a garbage classification result;
the interaction submodule 1540 is for human-machine interaction including selection of automatic/manual classification and image display;
the human body sensing module 160 is configured to detect human body information and send the information to the image recognition sub-module 1210 after detecting the human body information;
the illumination module 170 is used for illuminating the area of the garbage throwing port, and comprises a photosensitive sensor and a cold light lamp, wherein when the photosensitive sensor detects that light is too dark, the cold light lamp is turned on to illuminate;
the main control module 120 is electrically connected to the data acquisition module 110, the transmission module 130, the serial display interaction module 150, the human body induction module 160, and the illumination module 170, respectively.
Further, the different modes of transmission in the drive sub-module 1220 are: the upper conveying belt and the lower conveying belt are driven clockwise; the upper conveying belt and the lower conveying belt are in anticlockwise transmission; the upper conveyor belt is driven clockwise, and the lower conveyor belt is driven anticlockwise; the upper conveyor belt is driven anticlockwise, and the lower conveyor belt is driven clockwise.
Detailed description of the preferred embodiment
As shown in fig. 2 and fig. 3, an embodiment of the present invention provides a specific structure diagram of an intelligent garbage classification system based on a cross-belt sorting structure, where the intelligent garbage classification system includes a hardware structure and a software system, where the hardware structure mainly includes an upper conveyor belt, a lower conveyor belt, a garbage can, and the software system mainly includes a main body control module, an image recognition module, and a voice playing module based on STM 32.
The intelligent garbage classification system is 840mm high, 480mm long and 480mm wide in whole, and a garbage inlet with the diameter phi of 300mm is arranged at the top of the intelligent garbage classification system. The length of the upper conveyor belt 1 is 400mm, the shaft spacing is 200mm, the diameter of the rotating shaft is phi 36mm, the distance between the upper conveying surface and the box body framework 2 is 175mm, the speed of the upper conveyor belt 1 during operation is 80mm/s, and front and back respective conveying can be realized. The length of the lower conveyor belt 7 is 360mm, the shaft distance is 240mm, the diameter of the rotating shaft is phi 28mm, the distance between the upper conveying surface and the bottom surface of the upper conveyor belt 1 is 180mm, the speed of the lower conveyor belt 7 is 80mm/s when the lower conveyor belt runs, and left and right separate conveying can be realized.
Well accuse body 5 has contained the camera, the STM32 control panel, K210 chip etc, a running for supporting software system, display screen 4 and well accuse body 5 are located box skeleton 2 top, go up conveyer belt 1 and lower conveyer belt 7 and pass through the bolt fastening on box skeleton 2, SR602 human induction sensor 3 is located box skeleton 2 and goes up between the conveyer belt 1, baffle 6 passes through the bolt fastening in the middle of last conveyer belt 1 and lower conveyer belt 7, garbage bin 8 is located box skeleton 2 bottom, and put according to certain classification rule, show door 9 passes through the hinge and is connected with box skeleton 2. The ultrasonic sensor 10 is placed above the trash can 8.
As shown in fig. 4, 5 and 6, when garbage is thrown in, the upper conveyor belt 1 and the lower conveyor belt 7 both clockwise garbage enter the No. 1 can, the upper conveyor belt 1 clockwise and the lower conveyor belt 7 counterclockwise enter the No. 2 can, the upper conveyor belt 1 counterclockwise and the lower conveyor belt 7 clockwise garbage enter the No. 3 can, and the upper conveyor belt 1 and the lower conveyor belt 7 clockwise garbage enter the No. 4 can.
The software control system is provided with a main body control module, a picture and video playing module, a voice playing module, a motor driving module, an image recognition module and a human body induction module in common. The main body control module adopts STM32 and is responsible for comprehensively controlling the whole intelligent garbage classification system, is a bridge of each module, and can realize mutual communication with the image recognition module, decode pictures and videos and send the pictures and the video playing module, decode audios and send the audios to the audio playing module and control the operation of a motor in the motor driving module.
And the main body control module processes the data transmitted by the image recognition module by adopting a credibility weighting algorithm. In view of the fact that the image recognition module is limited in the type of garbage to be transmitted, the recognized information is transmitted to the main body control module in a single-byte format, four different bytes represent four types of garbage respectively, and the main body control module recognizes the received byte information by adopting a reliability weighting algorithm. The algorithm comprises the following steps: the image recognition module transmits the recognition result to the main control module, the recognition result is called as a current pre-judgment result, if the same result continuously appears, the reliability of the result is increased, and when the reliability is greater than a maximum threshold value, the result is determined to be reliable; if other results appear in the process, the reliability of the current pre-judgment result is reduced, and when the reliability is less than a minimum threshold value, the current pre-judgment result is replaced, wherein the replacement result is the result with the largest occurrence number in the identification process. The reliability increasing and attenuation functions are established according to the stability degree of the signals and the availability degree of different time periods.
The picture and video playing module is responsible for playing the picture and video data decoded by the main body control module, and the picture or video acquired by the camera in the central control body 5 is displayed on the display screen 4. The picture and video playing module adopts a USART HMI serial port screen, and adopts a CRC-16/MODBUS checking algorithm and an error retransmission mechanism in data transmission. The operation mechanism is as follows: the sending equipment carries out CRC-16/MODBUS check on the data to be sent, calculates a CRC code, places the CRC code at the tail of a sent data frame and sends the CRC code; and the receiving equipment also adopts CRC-16/MODBUS check on the received data, calculates a CRC code, compares the CRC code with the CRC code at the tail of the data frame, receives the data if the CRC code is consistent with the CRC code at the tail of the data frame, and discards the data and sends a retransmission request if the CRC code is not consistent with the CRC code at the tail of the data frame.
The motor drive module is used for driving the upper conveyor belt 1 and the lower conveyor belt 7, the conveyor belts are driven by the stepping motors, the stepping motors are driven by A4988, the motor rotation speed is controlled by the pulse input pins STEP (pulse frequency), the motor rotation direction is controlled by the direction control pins DIR (high and low level), and the start and stop of the drive module are controlled by the ENABLE pins ENABLE (high and low level). Pulse input pin STEP: by inputting a square wave to the foot, the motor is rotated one step, i.e.
Degree (for example, a 1.8-degree motor 16 is subdivided), when a square wave is continuously input into the foot, the motor continuously rotates, and the frequency of the square wave determines the speed of the motor rotation.
The single chip microcomputer judges the current garbage type according to the data sent by the identification module, and respectively pulls down or pulls up the DIR foot driven by the upper and lower motors according to the judgment result so as to control the rotating direction of the upper and lower tracks; calculating pulse frequency according to trapezoidal acceleration and deceleration, and inputting the pulse frequency to a STEP foot driven by a stepping motor so as to control the rotating speed of the upper and lower tracks; the operation or stop of the crawler belt is controlled by giving high and low levels to the ENABLE foot of the motor drive, so that the power consumption is reduced, and the service life of the motor drive is prolonged.
The motor drive adopts a trapezoidal acceleration and deceleration motion control algorithm. The trapezoidal acceleration and deceleration motion control algorithm is divided into an acceleration stage, a constant speed stage and a deceleration stage, so that the situations of overshoot and step loss in the starting and stopping processes of the stepping motor can be prevented. The total number of the motor operation steps is as follows: step, acceleration magnitude: acel, deceleration: decel, maximum velocity ωmaxAnd the acceleration stage is that the velocity and displacement formula is used, and under the condition that the initial velocity is zero:
where theta is the displacement angle and theta is the displacement angle,
is the step angle and n is the current number of steps (pulse number). Thus, the number of steps n required to accelerate to maximum speed1：
Similarly, the number of steps n before the deceleration starts can be obtained2The formula is as follows:
if n is2<n1It is stated that the acceleration phase is limited by the maximum speed ωmaxAnd the deceleration is started before the required speed is reached, and the method comprises the following steps:
n1·accel＝(step-n1)·decel
the number of steps n required for the acceleration stage can be obtained1And the number of steps n before the start of deceleration2：
Thus, if the first step calculates n2>n1Then in n ∈ (0, n)1) For the acceleration phase, n ∈ (n)1，n2) For uniform velocity stage, n is an element (n)2Step) is a deceleration stage; if the first step calculates to obtain n2<n1Then in n ∈ (0, n)1) For the acceleration phase, n ∈ (n)1Step) is the deceleration phase. In the acceleration phase, the following equation is satisfied:
in the formula, TsIs the pulse period; f. ofsIs the pulse frequency. In conjunction with the above formula, one can obtain:
discretizing the acceleration curve into m by adopting a discretizing method1And in the stage, the speed is increased in a stepping mode after discretization, so that the speed lag caused by the rotational inertia of the rotor of the stepping motor is overcome, and the realization of a single chip microcomputer is facilitated. Frequency of each gear after the acceleration stage is dispersed:
similarly, the frequency of each gear after the speed reduction stage is dispersed:
Δ t varies with time and pulse frequency to reduce dispersion errors; when the total steps are calculated, the motor speed is corrected to eliminate static (final value) errors caused by discrete errors. After the interval and the frequency of each section of the trapezoid are obtained, the main body control module can be used for driving the motor driving module to realize the acceleration and deceleration of the trapezoid.
The voice playing module is responsible for playing voice of the audio data decoded by the main body control module, and the audio is classified as garbage. The pure audio data is obtained by text-to-speech software or recording according to project requirements, for example, obtaining a wav prompt sound file which indicates that garbage is about to be fully loaded and is required to be cleaned in time through the text-to-speech software. And the obtained audio data is stored in Flash of the serial port screen. The serial port screen is provided with an audio decoding module and is externally connected with an audio power amplifier module (loudspeaker). And the main control module sends a corresponding instruction to the serial port screen to play the related audio resources. The video file to be played is generally stored in an SD card extended from the serial port screen, and the serial port screen also has a video decoding function. The input operation of the user is also carried out on the serial port screen, the serial port screen is in a capacitive touch type, and a high-end human-computer interaction interface can be manufactured by programming the serial port screen.
The human body induction module is responsible for detecting whether people throw away rubbish, adopts SR602 human body induction sensor 3 to detect the human body, and SR602 human body induction sensor 3 is the automatic control product based on infrared ray technique, and it has sensitivity height, strong reliability, small, and operating voltage is low advantage. The SR602 is configured to be triggered repeatedly with a delay time period of 2 s: after sensing the high level output by the human body, in the delay time period, if the human body moves in the sensing range, the output keeps the high level all the time, and the high level is delayed to be changed into the low level until the human body leaves (after the sensing module detects each movement of the human body, the sensing module automatically delays for a delay time period, and the time of the next movement is the starting point of the delay time). When the program is designed, the human body sensing signal is used as a trigger signal of external interruption, the external interruption selects a lower edge trigger mode, and when the main control system detects a lower edge, a main event A of the system is considered to occur, so that the main control system informs the K210 of identifying the garbage.
The full load detection adopts ultrasonic measurement and integral evaluation. The specific detection mode is that the ultrasonic sensors 10 above the four garbage cans are detected by a time-sharing method, and acquired data are processed by mean value filtering. The utilization rate of the garbage can be obtained according to the following formula:
in the formula u1Represents the measured usage rate of the trash can, d represents the distance measured by the ultrasonic module, l represents the distance between the ultrasonic sensor 10 and the top of the trash can 8, and h represents the height of the trash can.
The image recognition module judges the material and the size of delivered garbage when the delivered garbage is processed, the main body controls to record the quantity of the garbage in real time, the size of the currently loaded garbage is estimated by combining the characteristics of four types of garbage, specifically, the distance D between the ultrasonic sensor and the top of the garbage can and the distance D0 between the ultrasonic sensor and the upper edge of the garbage can are subtracted from the distance D between the ultrasonic sensor and the bottom of the garbage can, and the obtained result is multiplied by the bottom area of the garbage can, so that the current volume of the currently loaded garbage is obtained, and then the current estimated utilization rate u of the garbage can is calculated by calculating the total capacity of the garbage can2. According to u1And u2And (4) calculating the actual utilization rate of the current garbage can comprehensively according to different weights, wherein the measured utilization rate is a main judgment standard and has a great weight. And reporting abnormal conditions when the difference between the measured utilization rate and the estimated utilization rate is too large.
The working process is as follows: the system uses the human body induction module to realize the full-automatic work of the garbage can, when a user throws garbage, the human body induction module of the garbage throwing port can detect a human body signal and output a high level; when the user throws away the rubbish, the sensing module can not detect the human body signal and output low level. Will be put into intelligent waste classification system by categorised rubbish, rubbish falls into and goes up conveyer belt 1, and the camera in the well accuse body 5 shoots rubbish, uses image recognition module to handle the picture and judges the classification of rubbish. According to the classification of rubbish, the main body control module controls the picture and video playing module to display the picture of rubbish in the USART HMI serial port screen, controls the voice playing module to play the corresponding classification category, and controls the motor driving module to control the cooperation of clockwise or anticlockwise rotation of the upper conveyor belt 1 and the lower conveyor belt 7 so as to put the rubbish into the corresponding garbage can. The baffle 6, which is located intermediate the upper conveyor 1 and the lower conveyor 7, effectively shields the waste to encourage it to fall from the upper conveyor 1 onto the lower conveyor 7. The ultrasonic sensor 10 detects the full load of the garbage can 8, and the main body control module gives a warning when the garbage can is full according to the measured utilization rate and the estimated utilization rate. The operation of the intelligent garbage classification system can be checked by opening the display door 9.
While the invention has been described with respect to a limited number of embodiments, those skilled in the art, having benefit of this description, will appreciate that other embodiments can be devised which do not depart from the scope of the invention as described herein. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the appended claims. The present invention has been disclosed in an illustrative rather than a restrictive sense, and the scope of the present invention is defined by the appended claims.
Claims (10)
1. An intelligent garbage classification system based on a cross belt type sorting structure is characterized by comprising a data acquisition module, a main control module, a conveying module and a garbage containing module; wherein the content of the first and second substances,
the data acquisition module comprises a camera, and the camera is arranged at the garbage throwing port and used for acquiring image data and sending the image data to the main control module;
the main control module comprises an image recognition submodule and a driving submodule; the image identification submodule is used for identifying the garbage category according to the image data and sending the identified garbage category information to the driving submodule; the driving submodule is used for driving the transmission module to transmit in different modes according to the garbage category information;
the conveying module is arranged above the garbage accommodating module and comprises two conveying belts and two motors, wherein the transmission shafts of the two conveying belts are vertically crossed and do not intersect;
the main control module is respectively and electrically connected with the data acquisition module and the transmission module.
2. The intelligent garbage classification system based on the cross-belt type sorting structure as claimed in claim 1, further comprising a serial display interaction module, wherein the serial display interaction module comprises a storage sub-module, a display sub-module, a voice playing sub-module and an interaction sub-module; the storage submodule is used for storing video data and audio data; the display submodule is used for playing and displaying the video data; the voice playing submodule is used for playing audio data, and the audio content is a garbage classification result; the interaction submodule is used for man-machine interaction; the serial port display interaction module is electrically connected with the main control module.
3. The intelligent garbage classification system based on the cross-belt type sorting structure as claimed in claim 1 or 2, wherein the data acquisition module further comprises an ultrasonic sensor, the ultrasonic sensor is arranged above the garbage containing module and below the conveying module, and is used for detecting full load of the garbage containing module and sending real-time garbage height data to the main control module; the main control module further comprises a utilization rate calculation submodule and an alarm submodule, wherein the utilization rate calculation submodule is used for calculating the utilization rate of the garbage containing module according to the real-time garbage height data and sending alarm information to the alarm submodule when the garbage containing module is fully loaded; the alarm submodule is used for receiving alarm information and sending an alarm signal.
4. The intelligent garbage classification system based on the cross-belt sorting structure as claimed in claim 1, wherein the image recognition sub-module uses YOLOV3 algorithm based on deep learning to recognize the garbage category and uses confidence weighting algorithm to analyze the recognition result, and the confidence weighting algorithm includes the following specific steps: analyzing the garbage category information contained in the identification result of each frame of image shot by the camera, if the same identification result continuously appears in the multi-frame images, increasing the reliability of the identification result, if the same identification result does not continuously appear in the multi-frame images, namely other different identification results appear in the middle, reducing the reliability of the identification result, and when the reliability is greater than a preset maximum threshold value, determining that the result is reliable, and determining the identification result with the maximum continuous occurrence frequency as the final identification result; and when the reliability is smaller than a preset minimum threshold value, repeating the analysis process on the recognition result with the largest continuous occurrence frequency.
5. The intelligent garbage classification system based on the cross belt type sorting structure as claimed in claim 1, wherein the driving submodule controls the speed of the motor driving the conveyor belt to drive by adopting a trapezoidal acceleration and deceleration motion control algorithm, and the trapezoidal acceleration and deceleration motion control algorithm comprises calculating and obtaining the driving frequency of three stages, namely a trapezoidal acceleration stage, a uniform speed stage and a deceleration stage.
6. The intelligent garbage classification system based on the cross-belt type sorting structure as claimed in claim 3, wherein two conveyor belts in the conveying module are divided into an upper conveyor belt and a lower conveyor belt, and a baffle is fixedly installed between the upper conveyor belt and the lower conveyor belt; the garbage containing module comprises four garbage cans with the same size.
7. The intelligent garbage classification system based on the cross-belt sorting structure as claimed in claim 6, wherein the utilization rate calculation submodule includes a measured utilization rate u1And evaluating the usage u2Said usage computation submodular rootAccording to the measured utilization rate u1And evaluating the usage u2The actual utilization rate of the garbage containing module is obtained through calculation of different weights.
8. The intelligent garbage classification system based on the cross-belt type sorting structure as claimed in claim 7,
the measured usage u1The following equation is used:
wherein d represents the distance between the ultrasonic sensor and the uppermost garbage; l represents the distance between the ultrasonic sensor and the top of the garbage can; h represents the height of the garbage can;
the estimated usage u2The volume of the current existing garbage in the garbage can is estimated, and the volume and the total capacity of the garbage can are calculated to obtain the current estimated utilization rate u of the garbage can2。
9. The intelligent garbage classification system based on the cross-belt type sorting structure as claimed in claim 8, wherein the different modes of transmission in the driving sub-module are: the upper conveyor belt and the lower conveyor belt are driven clockwise; the upper conveyor belt and the lower conveyor belt are in anticlockwise transmission; the upper conveyor belt is driven clockwise, and the lower conveyor belt is driven anticlockwise; the upper conveying belt is in anticlockwise transmission, and the lower conveying belt is in clockwise transmission.
10. The intelligent garbage classification system based on the cross-belt type sorting structure as claimed in claim 1, further comprising a human body sensing module and an illumination module, wherein the human body sensing module is used for detecting human body information and sending the information to the image identification sub-module after detecting the human body information; the illumination module is used for illuminating the area of the garbage throwing port and comprises a photosensitive sensor and a cold light lamp, and when the photosensitive sensor detects that light is too dark, the cold light lamp is turned on to illuminate; the human body induction module and the lighting module are respectively electrically connected with the main control module.
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