CN118125011A

CN118125011A - Vehicle-mounted mechanism controller of non-floor garbage truck and control method

Info

Publication number: CN118125011A
Application number: CN202410263142.0A
Authority: CN
Inventors: 陈文强; 朱越
Original assignee: Nanjing Zhuodao Environmental Protection Technology Co ltd
Current assignee: Nanjing Zhuodao Environmental Protection Technology Co ltd
Priority date: 2024-03-08
Filing date: 2024-03-08
Publication date: 2024-06-04

Abstract

The invention discloses a vehicle-mounted mechanism controller and a control method of a non-floor-standing garbage truck, which relate to the field of garbage transportation and solve the problem that the conventional non-floor-standing garbage truck is often judged by a driver when judging the trafficability, so that larger deviation between a judgment result and an actual situation is easily caused.

Description

Vehicle-mounted mechanism controller of non-floor garbage truck and control method

Technical Field

The invention belongs to the field of garbage transportation, relates to an intelligent control technology, and particularly relates to a vehicle-mounted mechanism controller of a non-floor garbage truck and a control method.

Background

The non-floor garbage truck is capable of automatically collecting garbage without the need of falling to the ground, and under normal conditions, the traditional garbage truck is required to be stopped, then a worker can manually collect the garbage, the non-floor garbage truck body and the box body can be separated and automatically connected, and in the garbage collection process, the garbage is not contacted with the ground in the whole process, so that the non-floor garbage collection is realized;

In the prior art, when the vehicle-mounted mechanism of the garbage truck is controlled, the following defects exist:

1. when the garbage truck carries out garbage transportation, a driver often depends on subjective judgment when carrying out trafficability judgment on a road in front, so that a large deviation between a judgment result and an actual situation is caused;

2. when the existing floor-free garbage truck is connected with a box body, the vehicle body is connected in a reversing mode by means of driving experience of a driver, and the connection process is difficult to be successfully connected at one time, so that the garbage transportation time is prolonged.

Therefore, we propose a vehicle-mounted mechanism controller and a control method of the non-floor garbage truck.

Disclosure of Invention

Aiming at the defects of the prior art, the invention aims to provide a vehicle-mounted mechanism controller and a control method of a non-floor garbage truck, and in order to achieve the purposes, the invention obtains basic control data based on obtaining road surface basic data, running basic data, work monitoring data and box basic data, analyzes the basic control data to obtain an obstacle blocking coefficient reference value, a vehicle body stability reference value and a box reversing connection path, defines the obstacle blocking coefficient reference value, the vehicle body stability reference value and the box reversing connection path as control analysis data, processes the basic control data and the control analysis data to obtain control management data, carries out movement control on the garbage truck according to road trafficability grading data and the garbage truck moving path, carries out connection of the vehicle body and the box through the box reversing connection path, and carries out overweight monitoring, compression management and leakage monitoring on the garbage truck through the work monitoring data;

In order to achieve the above purpose, the present invention adopts the following technical scheme: the specific working process of each module of the vehicle-mounted mechanism controller of the non-floor garbage truck is as follows:

and a data acquisition module: the method comprises the steps of acquiring basic control data;

And a data analysis module: the control analysis data are used for analyzing the basic control data to obtain control analysis data;

and a data processing module: the control management data are used for processing basic control data and control analysis data to obtain control management data;

The non-floor garbage truck is controlled and managed according to the control management data and the control analysis data;

And the vehicle-mounted control module: and controlling and managing the non-floor garbage truck according to the control management data and the control analysis data.

Further, the data acquisition module acquires basic control data, specifically as follows:

the data acquisition module comprises a pavement unit, a running unit, a working unit and a box body unit;

the road surface unit acquires road surface basic data;

the running unit obtains the running basic data, and the running unit obtains the running basic data, specifically as follows:

The running unit comprises a first position sensor, a gyroscope, an accelerometer and a vehicle body vibration sensor;

Acquiring current position data of the non-floor garbage truck through a first position sensor;

acquiring a transverse inclination angle of a vehicle body of the floor garbage truck in real time through a gyroscope;

respectively acquiring an acceleration value of a vehicle body of the floor garbage vehicle in an X-axis, an acceleration value of a Y-axis and an acceleration value of a Z-axis in real time through an accelerometer;

Calculating an X-axis acceleration value, a Y-axis acceleration value and a Z-axis acceleration value to obtain an average absolute value of the vehicle body acceleration;

Acquiring the value of the vibration frequency of the vehicle body in real time through a vehicle body vibration sensor;

Defining current position data, a vehicle body transverse inclination angle, a vehicle body vibration frequency value and a vehicle body acceleration average absolute value as driving basic data;

The working unit acquires working monitoring data, and the working unit comprises the following specific steps:

the working unit comprises a temperature sensor, a voltage sensor and a pressure sensor;

the battery temperature value of the non-floor garbage truck is obtained in real time by using a temperature sensor;

acquiring the circuit working voltage value of the non-floor garbage truck in real time through a voltage sensor;

acquiring a real-time pressure value of a hydraulic pump of the non-floor garbage truck through a pressure sensor;

defining a battery temperature value, a circuit working voltage value and a hydraulic pump real-time pressure value as working monitoring data;

The box unit acquires box basic data, and the box basic data is specifically as follows:

the box body unit comprises a second position sensor and a second high-definition camera;

Acquiring box position data through a second position sensor;

Acquiring environmental image data of the position of the box body through a second high-definition camera;

acquiring real-time position data of the obstacle through a laser radar;

defining obstacle real-time position data, box position data and environment image data as box base data;

Road surface base data, running base data, work monitoring data, and box base data are defined as base control data.

Further, the road surface unit acquires road surface basic data, which is specifically as follows:

The pavement unit comprises a first high-definition camera and a laser range finder;

acquiring road image data of a road where the non-floor garbage truck is located through a first high-definition camera;

Judging the obstacle in front of the road according to the road image data;

If no obstacle exists in front of the road, the average width value and the minimum width value of the road are acquired as follows:

Selecting n groups of road characteristic points on the front road of the non-floor garbage truck, wherein each group of road characteristic points comprises a road left characteristic point and a road right characteristic point, the road left characteristic point is positioned on the road left side road edge, and the road right characteristic point is positioned on the road right side road edge and is parallel to the road left characteristic point;

Respectively obtaining horizontal distance values of n groups of road feature points, namely Jl1, jl2 and Jl3 … … Jln by using a laser range finder;

calculating the horizontal distance values of the n groups of road feature points to obtain a road average width value;

comparing the values of the horizontal distances of the n groups of road feature points to obtain a minimum width value of the road;

If an obstacle exists in front of the road, the minimum width value and the average width value of the road are acquired, and the method specifically comprises the following steps:

Transmitting two laser beams simultaneously from the same laser transmitting point to two sides of a road by using a laser range finder, namely a first laser beam and a second laser beam, acquiring laser parameter information by using the laser range finder, acquiring length values of the first laser beam and the second laser beam by using the laser parameter information, acquiring the length values of the first laser beam and the second laser beam, and acquiring a laser included angle value formed by the first laser beam and the second laser beam by using the laser parameter information, thereby acquiring a laser included angle value;

Calculating the first laser beam length value, the second laser beam length value and the laser beam included angle value to obtain a road width value;

Repeating the above process, respectively using a laser range finder to emit m groups of laser beams with different angles, wherein any one group of laser beams consists of two laser beams, the two laser beams respectively form two laser points on the ground, calculating to obtain m different road width values, comparing the m different road width values, defining the road width value with the minimum value as the minimum road width value, and calculating m different road width values to obtain the average road width value;

Road image data, a road minimum width value, and a road average width value are defined as road surface base data.

Further, the data analysis module analyzes the basic control data, specifically as follows:

the data analysis module comprises a pavement analysis unit, a running analysis unit and a box analysis unit;

the road surface analysis unit acquires a reference value of the barrier coefficient;

The driving analysis unit obtains a vehicle body stability reference value;

acquiring a transverse inclination angle of the vehicle body, a vehicle body vibration frequency value and a vehicle body acceleration average absolute value through the driving basic data;

Calculating the transverse inclination angle of the vehicle body, the value of the vibration frequency of the vehicle body and the average absolute value of the acceleration of the vehicle body to obtain a reference value of the stability of the vehicle body;

The box analysis unit acquires box analysis data, specifically as follows:

the data stored in the database includes vehicle size data and turning radius;

Acquiring real-time position data of the obstacle, box position data and environment image data through the box base data;

analyzing the environmental image data by using a computer vision technology, and identifying the placement angle of the garbage truck box in the environmental image data;

calculating a reverse connection path of the box body through real-time position data of the obstacle, vehicle size data and turning radius by using an APS automatic parking technology;

and defining the reference value of the barrier blocking coefficient, the reference value of the vehicle body stability and the box body reversing connection path as control analysis data.

Further, the road surface analysis unit obtains the reference value of the obstacle blocking coefficient, specifically as follows:

Acquiring road image data and road average width values according to the driving basic data;

Monitoring an obstacle on the road surface in the road image data by using a target detection algorithm, and obtaining an obstacle quantity value;

Identifying an overlapping area of the obstacle image and the road image through an image identification algorithm, and acquiring an area value of the overlapping area and an area value of the road area;

And calculating the average road width value, the obstacle quantity value, the overlapping area value and the road area value to obtain an obstacle blocking coefficient reference value.

Further, the data processing module processes the basic control data and the control analysis data, and specifically comprises the following steps:

the data processing module comprises a path planning unit and a pass judgment unit;

the path planning unit performs moving path planning, specifically as follows:

acquiring current position data and box position data through basic control data;

Map positioning is carried out on the current position data and the box position data, and a garbage truck moving path is generated according to the map positioning;

Judging the trafficability of the garbage truck through a judging unit;

the garbage truck moving path and road passing classification data are defined as control management data.

Further, the passing judgment unit is used for judging the passing performance of the garbage truck, and specifically comprises the following steps:

the data stored in the database also comprises a vehicle body width value, a vehicle body stability critical reference value, a cell road design width value and an obstacle blocking critical coefficient reference value;

acquiring a minimum width value and an average width value of a road through basic control data, and acquiring a barrier coefficient reference value and a vehicle body stability reference value through control analysis data;

Acquiring a vehicle body width value through a database;

comparing the vehicle body width value with the minimum road width value;

when the value of the width of the vehicle body is larger than or equal to the value of the minimum width of the road, judging that the road is on the first trafficability grading road at the moment;

obtaining a road passing reference value by comparing the vehicle body width value, the road average width value, the obstacle blocking coefficient reference value and the vehicle body stability reference value when the vehicle body width value is smaller than the road minimum width value;

acquiring a vehicle body stability critical reference value, a cell road design width value and an obstacle blocking critical coefficient reference value Dt through a database;

obtaining a road passing reference threshold value Dt1 through a road with a vehicle width value, a vehicle stability critical reference value, a district road design width value and an obstacle blocking critical coefficient reference value;

The road passing reference value is subjected to numerical judgment by using the road passing reference threshold value, and the method concretely comprises the following steps:

When Dt is more than or equal to Dt1, judging that the road is on a second trafficability grading road;

when Dt is less than Dt1, judging that the road is in a first trafficability grading road;

The judgment result obtained according to the road trafficability reference threshold and the road trafficability reference value is defined as road trafficability grading data.

Further, the vehicle-mounted control module performs work control on the garbage truck, and specifically comprises the following steps:

The data stored in the database also comprises a rated load capacity of the box body, a reference value of the battery temperature, a reference value of the circuit working voltage and a reference value of the real-time pressure of the hydraulic pump;

the vehicle-mounted control module comprises a through control unit, a box body installation unit, a work monitoring unit and a leakage monitoring unit;

The passing control is carried out by the control unit according to the road passing classification data, and the method concretely comprises the following steps:

Acquiring road trafficability grading data;

aiming at the first trafficability grading road, the garbage truck stops passing through the current road and re-plans the route;

aiming at a second passability classification road, the garbage truck normally moves according to a garbage truck moving path;

The box body installation unit is used for automatically connecting a vehicle with the box body and carrying out overload early warning, and the concrete steps are as follows:

The box body mounting unit comprises a weight sensor;

The garbage truck connects the box body according to the box body reversing connection path, and obtains the box body weight value through the weight sensor;

acquiring the rated load capacity of the box body through a database;

When the weight value of the box body is larger than the rated load capacity of the box body, overweight early warning is issued;

When the box body weight value is smaller than or equal to the rated load capacity of the box body, marking the garbage box body as a compression monitoring box body;

The compression monitoring box body is subjected to garbage compression management, and the method is as follows:

Selecting j surface feature points on the surface of garbage loaded in the compression monitoring box body, respectively acquiring the vertical height distance values of the j surface feature points and the bottom of the compression monitoring box body by using a height measuring instrument, respectively marking the vertical height distance values as first to j vertical height values, calculating the average value of the first to j vertical height values, and marking the average value as the garbage stacking height value;

Acquiring a bottom area value inside the compression monitoring box body, and acquiring a stacking gap volume value corresponding to the inside of the compression monitoring box body through a 3D laser scanner;

Calculating the internal bottom area value, stacking clearance volume value and garbage stacking height value of the compression monitoring box body to obtain a compressible reference coefficient corresponding to the compression monitoring box body;

acquiring a compressible reference coefficient threshold value, and carrying out numerical comparison on the compressible reference coefficient and the compressible reference coefficient threshold value;

if the compressible reference coefficient is larger than or equal to the compressible reference coefficient threshold value, the garbage truck is normally connected with the box body;

If the compressible reference coefficient is smaller than the compressible reference coefficient threshold value, compressing the garbage in the compression monitoring box body until the compressible reference coefficient is equal to the compressible reference coefficient threshold value or the box body weight value is equal to the rated load capacity of the box body;

the work monitoring unit monitors work safety according to the work monitoring data;

The leakage monitoring unit is used for carrying out leakage monitoring on the garbage truck box body, and specifically comprises the following steps:

after the garbage truck normally connects the box bodies, acquiring image data of the parking ground of the garbage truck box body, and marking the image data as the ground image data of the parking position of the box body;

judging a first box leakage monitoring interval if liquid accumulation marks exist in the box parking position ground image data;

Judging a second box leakage monitoring interval if the liquid accumulation trace does not exist in the box parking position ground image data;

the method comprises the following steps of further monitoring leakage of the garbage truck box body in a first box body leakage monitoring zone:

the garbage truck selects a road surface in front of running as a dry detection road surface;

Acquiring image data corresponding to a dry detection road surface when the garbage truck does not travel to the dry detection road surface through a camera at the bottom of the carriage, and marking the image data as a first detection image;

acquiring corresponding dry detection pavement image data of the garbage truck after the garbage truck runs through a camera at the bottom of the carriage, and marking the dry detection pavement image data as a second detection image;

Comparing the first detection image with the second detection image, if the first detection image is consistent with the second detection image, no liquid leakage exists in the garbage truck box, if the first detection image is inconsistent with the second detection image, the liquid leakage exists in the garbage truck box, and the box leakage early warning is issued.

Further, the operation monitoring unit monitors the operation safety according to the operation monitoring data, specifically as follows:

acquiring a battery temperature value, a circuit working voltage value and a hydraulic pump real-time pressure value through working monitoring data;

acquiring a battery temperature reference value, a circuit working voltage reference value and a hydraulic pump real-time pressure reference value through a database;

The working monitoring reference value Gj of the garbage truck is obtained through the battery temperature value, the circuit working voltage value, the hydraulic pump real-time pressure value, the battery temperature reference value, the circuit working voltage reference value and the hydraulic pump real-time pressure reference value;

Acquiring a battery temperature range extremum, a circuit working voltage range extremum and a hydraulic pump real-time range extremum;

Obtaining a garbage truck working monitoring reference threshold Gj1 through a battery temperature range extremum, a circuit working voltage range extremum, a hydraulic pump real-time range extremum, a battery temperature reference value, a circuit working voltage reference value and a hydraulic pump real-time pressure reference value;

The working state of the garbage truck is judged according to the working monitoring reference value of the garbage truck and the working monitoring reference threshold value of the garbage truck, and the working state judgment method specifically comprises the following steps:

When Gj is more than or equal to Gj1, judging that the garbage truck works abnormally, and stopping working of the garbage truck;

when 0 is more than Gj1 is more than Gj, judging that the garbage truck works normally, and continuing to work.

The vehicle-mounted mechanism control method of the non-floor garbage truck further comprises the following steps of:

step S1: basic control data are obtained;

step S11: the road surface basic data is acquired, and the method concretely comprises the following steps:

Step S111: acquiring road image data of a road where the non-floor garbage truck is located through a first high-definition camera;

Step S112: judging the obstacle in front of the road according to the road image data;

Step S1121: if no obstacle exists in front of the road, the minimum width value and the average width value of the road are acquired as follows:

Step S11211: selecting n groups of road characteristic points on the front road of the non-floor garbage truck, wherein each group of road characteristic points comprises a road left characteristic point and a road right characteristic point, the road left characteristic point is positioned on the road left side road edge, and the road right characteristic point is positioned on the road right side road edge and is parallel to the road left characteristic point;

Step S11212: respectively obtaining horizontal distance values of n groups of road feature points, namely Jl1, jl2 and Jl3 … … Jln by using a laser range finder;

Step S11213: calculating the horizontal distance values of the n groups of road feature points to obtain a road average width value;

Step S11214: comparing the values of the horizontal distances of the n groups of road feature points to obtain a minimum width value of the road;

step S1122: if an obstacle exists in front of the road, the minimum width value and the average width value of the road are acquired, and the method specifically comprises the following steps:

Step S11221: transmitting two laser beams simultaneously from the same laser transmitting point to two sides of a road by using a laser range finder, namely a first laser beam and a second laser beam, acquiring laser parameter information by using the laser range finder, acquiring length values of the first laser beam and the second laser beam by using the laser parameter information, acquiring the length values of the first laser beam and the second laser beam, and acquiring a laser included angle value formed by the first laser beam and the second laser beam by using the laser parameter information, thereby acquiring a laser included angle value;

Step S11222: calculating the first laser beam length value, the second laser beam length value and the laser beam included angle value to obtain a road width value;

Step S11223: repeating the above process, respectively using a laser range finder to emit m groups of laser beams with different angles, wherein any one group of laser beams consists of two laser beams, the two laser beams respectively form two laser points on the ground, calculating to obtain m different road width values, comparing the m different road width values, defining the road width value with the minimum value as the minimum road width value, and calculating m different road width values to obtain the average road width value;

Step S113: defining road image data, a road minimum width value and a road average width value as road surface base data;

step S12: the driving basic data is acquired, and the method concretely comprises the following steps:

Step S121: acquiring current position data of the non-floor garbage truck through a first position sensor;

Step S122: acquiring a transverse inclination angle of a vehicle body of the floor garbage truck in real time through a gyroscope;

step S123: respectively acquiring an acceleration value of a vehicle body of the floor garbage vehicle in an X-axis, an acceleration value of a Y-axis and an acceleration value of a Z-axis in real time through an accelerometer;

step S124: calculating an X-axis acceleration value, a Y-axis acceleration value and a Z-axis acceleration value to obtain an average absolute value of the vehicle body acceleration;

step S124: acquiring the value of the vibration frequency of the vehicle body in real time through a vehicle body vibration sensor;

Step S125: defining current position data, a vehicle body transverse inclination angle, a vehicle body vibration frequency value and a vehicle body acceleration average absolute value as driving basic data;

Step S13: the method comprises the following steps of:

step S131: the battery temperature value of the non-floor garbage truck is obtained in real time by using a temperature sensor;

step S132: acquiring the circuit working voltage value of the non-floor garbage truck in real time through a voltage sensor;

step S133: acquiring a real-time pressure value of a hydraulic pump of the non-floor garbage truck through a pressure sensor;

Step S134: defining a battery temperature value, a circuit working voltage value and a hydraulic pump real-time pressure value as working monitoring data;

step S14: the basic data of the box body are acquired, and the method comprises the following steps:

step S141: acquiring box position data through a second position sensor;

step S142: acquiring environmental image data of the position of the box body through a second high-definition camera;

Step S143: acquiring real-time position data of the obstacle through a laser radar;

step S144: defining obstacle real-time position data, box position data and environment image data as box base data;

Step S15: defining pavement basic data, driving basic data, work monitoring data and box basic data as basic control data;

step S2: analyzing the basic control data to obtain control analysis data;

step S21: the reference values of the barrier coefficients are obtained, and the reference values are specifically as follows:

step S211: acquiring road image data and road average width values according to the driving basic data;

Step S212: monitoring an obstacle on the road surface in the road image data by using a target detection algorithm, and obtaining an obstacle quantity value;

Step S213: identifying an overlapping area of the obstacle image and the road image through an image identification algorithm, and acquiring an area value of the overlapping area and an area value of the road area;

Step S214: calculating the average road width value, the obstacle quantity value, the overlapping area value and the road area value to obtain an obstacle blocking coefficient reference value;

step S22: acquiring a vehicle body stability reference value;

step S221: acquiring a transverse inclination angle of the vehicle body, a vehicle body vibration frequency value and a vehicle body acceleration average absolute value through the driving basic data;

step S222: calculating the transverse inclination angle of the vehicle body, the value of the vibration frequency of the vehicle body and the average absolute value of the acceleration of the vehicle body to obtain a reference value of the stability of the vehicle body;

Step S23: the box analysis data is obtained, and the method comprises the following steps:

step S231: acquiring real-time position data of the obstacle, box position data and environment image data through the box base data;

Step S232: analyzing the environmental image data by using a computer vision technology, and identifying the placement angle of the garbage truck box in the environmental image data;

step S233: calculating a reverse connection path of the box body through real-time position data of the obstacle, vehicle size data and turning radius by using an APS automatic parking technology;

step S24: defining an obstacle blocking coefficient reference value, a vehicle body stability reference value and a box body reversing connection path as control analysis data;

step S3: processing the basic control data and the control analysis data to obtain control management data;

step S31: planning a moving path, specifically as follows:

step S311: acquiring current position data and box position data through basic control data;

Step S312: map positioning is carried out on the current position data and the box position data, and a garbage truck moving path is generated according to the map positioning;

step S32: the trafficability judgment of the garbage truck is carried out, and the trafficability judgment method specifically comprises the following steps:

step S321: acquiring a minimum width value and an average width value of a road through basic control data, and acquiring a barrier coefficient reference value and a vehicle body stability reference value through control analysis data;

step S322: acquiring a vehicle body width value through a database;

step S323: comparing the vehicle body width value with the minimum road width value;

Step S3231: when the value of the width of the vehicle body is larger than or equal to the value of the minimum width of the road, judging that the road is on the first trafficability grading road at the moment;

step S3232: when the vehicle body width value is smaller than the minimum road width value, calculating the vehicle body width value, the average road width value, the obstacle blocking coefficient reference value and the vehicle body stability reference value to obtain a road trafficability reference value;

step S3233: acquiring a vehicle body stability critical reference value, a cell road design width value and an obstacle blocking critical coefficient reference value through a database;

Step S3234: calculating a vehicle body width value, a vehicle body stability critical reference value, a district road design width value and an obstacle blocking critical coefficient reference value to obtain a road trafficability reference threshold value;

step S3235: the road passing reference value is subjected to numerical judgment by using the road passing reference threshold value, and the method concretely comprises the following steps:

step S324: defining a judging result obtained according to the road passing reference threshold value and the road passing reference value as road passing classification data;

Step S325: defining the garbage truck moving path and road passing classification data as control management data;

Step S4: the garbage truck is subjected to work control and work monitoring;

Step S41: the road passing quality classification data is used for carrying out passing control according to the road passing quality classification data, and the method is concretely as follows:

step S411: acquiring road trafficability grading data;

step S412: aiming at the first trafficability grading road, the garbage truck stops passing through the current road and re-plans the route;

Step S413: aiming at a second passability classification road, the garbage truck normally moves according to a garbage truck moving path;

step S42: the vehicle and the box body are automatically connected and overload early warning is carried out, and the method specifically comprises the following steps:

step S421: the garbage truck connects the box body according to the box body reversing connection path, and obtains the box body weight value through the weight sensor;

step S422: acquiring the rated load capacity of the box body through a database;

Step S4221: when the box body weight value is larger than the rated load capacity of the box body, marking the garbage box body as a compression monitoring box body;

Step S423: the compression monitoring box body is subjected to garbage compression management, and the method is as follows:

Step S4231: selecting j surface feature points on the surface of garbage loaded in the compression monitoring box body, respectively acquiring the vertical height distance values of the j surface feature points and the bottom of the compression monitoring box body by using a height measuring instrument, respectively marking the vertical height distance values as first to j vertical height values, calculating the average value of the first to j vertical height values, and marking the average value as the garbage stacking height value;

Step S4232: acquiring a bottom area value inside the compression monitoring box body, and acquiring a stacking gap volume value corresponding to the inside of the compression monitoring box body through a 3D laser scanner;

Step S4233: calculating the internal bottom area value, stacking clearance volume value and garbage stacking height value of the compression monitoring box body to obtain a compressible reference coefficient corresponding to the compression monitoring box body;

Step S4234: acquiring a compressible reference coefficient threshold value, and carrying out numerical comparison on the compressible reference coefficient and the compressible reference coefficient threshold value;

Step S42341: if the compressible reference coefficient is larger than or equal to the compressible reference coefficient threshold value, the garbage truck is normally connected with the box body;

Step S42342: if the compressible reference coefficient is smaller than the compressible reference coefficient threshold value, compressing the garbage in the compression monitoring box body until the compressible reference coefficient is equal to the compressible reference coefficient threshold value or the box body weight value is equal to the rated load capacity of the box body;

Step S4222: when the weight value of the box body is smaller than or equal to the rated load capacity of the box body, the garbage truck is normally connected with the box body;

step S43: the working safety monitoring is carried out according to the working monitoring data, and the working safety monitoring method specifically comprises the following steps:

step S431: acquiring a battery temperature value, a circuit working voltage value and a hydraulic pump real-time pressure value through working monitoring data;

step S432: acquiring a battery temperature reference value, a circuit working voltage reference value and a hydraulic pump real-time pressure reference value through a database;

Step S433: calculating a battery temperature value, a circuit working voltage value, a hydraulic pump real-time pressure value, a battery temperature reference value, a circuit working voltage reference value and a hydraulic pump real-time pressure reference value to obtain a garbage truck working monitoring reference value;

Step S434: acquiring a battery temperature range extremum, a circuit working voltage range extremum and a hydraulic pump real-time range extremum;

step S435: calculating a battery temperature range extremum, a circuit working voltage range extremum, a hydraulic pump real-time range extremum, a battery temperature reference value, a circuit working voltage reference value and a hydraulic pump real-time pressure reference value to obtain a garbage truck working monitoring reference threshold;

Step S436: the working state of the garbage truck is judged according to the working monitoring reference value of the garbage truck and the working monitoring reference threshold value of the garbage truck, and the working state judgment method specifically comprises the following steps:

when the value of 0 is more than Gj1 and more than Gj, judging that the garbage truck works normally, and continuing to work;

step S44: the garbage truck box body is subjected to leakage monitoring, and the concrete steps are as follows:

step S441: after the garbage truck normally connects the box bodies, acquiring image data of the parking ground of the garbage truck box body, and marking the image data as the ground image data of the parking position of the box body;

step S4411: judging a first box leakage monitoring interval if liquid accumulation marks exist in the box parking position ground image data;

Step S4412: judging a second box leakage monitoring interval if the liquid accumulation trace does not exist in the box parking position ground image data;

step S442: the method comprises the following steps of further monitoring leakage of the garbage truck box body in a first box body leakage monitoring zone:

step S4421: the garbage truck selects a road surface in front of running as a dry detection road surface;

Step S4422: acquiring image data corresponding to a dry detection road surface when the garbage truck does not travel to the dry detection road surface through a camera at the bottom of the carriage, and marking the image data as a first detection image;

Step S4423: acquiring corresponding dry detection pavement image data of the garbage truck after the garbage truck runs through a camera at the bottom of the carriage, and marking the dry detection pavement image data as a second detection image;

Step S444: comparing the first detection image with the second detection image, if the first detection image is consistent with the second detection image, no liquid leakage exists in the garbage truck box, if the first detection image is inconsistent with the second detection image, the liquid leakage exists in the garbage truck box, and the box leakage early warning is issued.

In summary, due to the adoption of the technical scheme, the beneficial effects of the invention are as follows:

1. According to the invention, the trafficability of the front road is automatically judged by the garbage truck, and compared with the traditional garbage truck which needs to be judged manually, the driving safety is improved while the judging efficiency is improved;

2. According to the invention, the automatic connection between the body and the box body of the non-floor garbage truck is realized by automatically planning the reversing line, and the connection efficiency of the body and the box body is improved.

Drawings

The present invention is further described below with reference to the accompanying drawings for the convenience of understanding by those skilled in the art.

FIG. 1 is an overall system block diagram of the present invention;

FIG. 2 is a diagram of steps for implementing the present invention;

FIG. 3 is a schematic view of the road width obtained in the present invention;

FIG. 4 is a schematic diagram of the operation of the non-floor refuse vehicle of the present invention;

Fig. 5 is a schematic diagram of the connection of the case in the present invention.

Detailed Description

The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

Example 1

Referring to fig. 1 and 2, the present invention provides a technical solution: the vehicle-mounted mechanism controller of the landless garbage truck comprises a data acquisition module, a data analysis module, a data processing module and a vehicle-mounted control module, wherein the data acquisition module, the data analysis module, the data processing module and the vehicle-mounted control module are respectively connected with a server;

Also includes a database;

the data acquisition module acquires basic control data;

the road surface unit acquires road surface basic data, and the road surface basic data are specifically as follows:

Judging the obstacle in front of the road according to the road image data;

If no obstacle exists in front of the road, the minimum width value and the average width value of the road are acquired as follows:

calculating the horizontal distance values of the n groups of road feature points through a road average width calculation formula to obtain a road average width value;

the road average width calculation formula is specifically configured as:

wherein Jlp is the average width value of the road, and Jl1, jl2 and Jl3 … … Jln are the horizontal distance values of n groups of road feature points respectively;

Referring to fig. 3, a laser range finder is used to emit two laser beams from the same laser emission point to two sides of a road simultaneously, namely a first laser beam and a second laser beam, laser parameter information is acquired through the laser range finder, length values of the first laser beam and the second laser beam are acquired through the laser parameter information, a first laser beam length value and a second laser beam length value are obtained, and a laser included angle value formed by the first laser beam and the second laser beam is acquired through the laser parameter information, so that a laser included angle value is obtained;

calculating the first laser beam length value, the second laser beam length value and the laser beam included angle value through a road width value calculation formula to obtain a road width value;

the road width calculation formula is specifically configured as:

wherein Dk is a road width value, gu1 is a first laser beam length value, gu2 is a second laser beam length value, and A is a laser beam included angle value;

What needs to be explained here is:

The laser range finder used in the method can acquire the length value of the emitted laser beam and the value of the included angle formed by the two laser beams at the emitting point, and can store the length value and the included angle as laser parameter information;

if obstacles exist on two sides of the road, the first laser beam end point and the second laser beam end point both have obstacle surfaces, the first laser beam length value is the distance value from the laser emission point to the first laser beam end point, and the second laser beam length value is the distance value from the laser emission point to the second laser beam end point;

If any side of the road has an obstacle, a first laser beam endpoint exists on the surface of the obstacle, a second laser beam endpoint exists on the other side of the road, the projection of the first laser beam endpoint on the ground is used as a first laser beam endpoint projection, the first laser beam length value is a distance value from the laser emission point to the first laser beam endpoint projection, and the second laser beam length value is a distance value from the laser emission point to the second laser beam endpoint;

Defining road image data, a road minimum width value and a road average width value as road surface base data;

what needs to be explained here is: the road width value is specifically defined as the width value at the narrowest part of the road within 10 meters in front of the vehicle;

The running unit acquires running basic data, specifically as follows:

Calculating an X-axis acceleration value, a Y-axis acceleration value and a Z-axis acceleration value through an acceleration average absolute value calculation formula to obtain an average absolute value of the vehicle body acceleration;

the acceleration average absolute value calculation formula is specifically configured as follows:

Wherein Jv is the average absolute value of the acceleration of the vehicle body, xj is the value of the acceleration of the X axis, yj is the value of the acceleration of the Y axis, and Zj is the value of the acceleration of the Z axis;

What needs to be explained here is: in this embodiment, the battery temperature value is specifically defined as the internal cell temperature value of the battery, and the circuit operating voltage value is specifically defined as the voltage value of the battery input end;

Acquiring box position data through a second position sensor;

acquiring real-time position data of the obstacle through a laser radar;

What needs to be explained here is:

The box body position data comprise position data of the current placement position of the box body and position data of the position to be placed of the box body;

defining pavement basic data, driving basic data, work monitoring data and box basic data as basic control data;

the data acquisition module acquires basic control data and transmits the basic control data to the data analysis module and the data processing module;

the data analysis module analyzes the basic control data to obtain control analysis data;

The data analysis module acquires road surface basic data, driving basic data, work monitoring data and box body basic data through basic control data;

The road surface analysis unit obtains the reference value of the barrier coefficient, and the specific steps are as follows:

Calculating the average road width value, the obstacle quantity value, the overlapping area value and the road area value through an obstacle blocking coefficient reference value calculation formula to obtain an obstacle blocking coefficient reference value;

The obstacle blocking coefficient reference value calculation formula is specifically configured as:

Wherein Za is the reference value of the barrier coefficient, jlp is the average width value of the road, scd is the area value of the overlapping area, sdl is the area value of the road area, and Zd is the value of the barrier quantity;

What needs to be explained here is:

image recognition algorithms are a technique for identifying content or features in an image by analyzing and processing the image, which typically involves the use of computer vision and machine learning techniques to identify objects, scenes in the image;

The object detection algorithm is a specific form of image recognition algorithm that focuses on locating and recognizing a specific object of interest in an image;

The driving analysis unit obtains a vehicle body stability reference value;

Calculating the transverse inclination angle of the vehicle body, the value of the vibration frequency of the vehicle body and the average absolute value of the acceleration of the vehicle body through a vehicle body stability reference value calculation formula to obtain a vehicle body stability reference value;

The vehicle body stability reference value calculation formula is specifically configured as:

Wherein Cw is a vehicle body stability reference value, jv is a vehicle body acceleration average absolute value, hq is a vehicle body transverse inclination angle, zd is a vehicle body vibration frequency value, a1 is a set proportionality coefficient, and a1 is larger than 0;

The box analysis unit acquires box analysis data, specifically as follows:

the data stored in the database includes vehicle size data and turning radius;

What needs to be explained here is:

computer vision refers to the technology of analyzing, processing, identifying and understanding images and videos by using computer and digital image processing technologies;

APS (Automated PARKING SYSTEM) automatic parking technology is an advanced intelligent parking system for automobiles, which allows a vehicle to automatically perform a parking operation without an operation by a driver;

Defining an obstacle blocking coefficient reference value, a vehicle body stability reference value and a box body reversing connection path as control analysis data;

The data analysis module acquires control analysis data and transmits the control analysis data to the data processing module and the vehicle-mounted control module;

The data processing module processes the basic control data and the control analysis data to obtain control management data;

the path planning unit performs moving path planning, specifically as follows:

The judgment unit is used for judging the trafficability of the garbage truck, and the trafficability is specifically as follows:

What needs to be explained here is: the vehicle body stability critical reference value, the district road design width value and the obstacle blocking critical coefficient reference value are all specifically set by professionals in the related field and are stored in a database;

Acquiring a vehicle body width value through a database;

comparing the vehicle body width value with the minimum road width value;

When the vehicle body width value is smaller than the minimum road width value, calculating the vehicle body width value, the average road width value, the obstacle blocking coefficient reference value and the vehicle body stability reference value through a road trafficability reference value calculation formula to obtain a road trafficability reference value;

the road trafficability reference value calculation formula is specifically configured as:

Wherein Dt is a road trafficability reference value, cw is a vehicle body stability reference value, za is an obstacle blocking coefficient reference value, jlp is a road average width value, and Ck is a vehicle body width value;

acquiring a vehicle body stability critical reference value, a cell road design width value and an obstacle blocking critical coefficient reference value through a database;

calculating a vehicle body width value, a vehicle body stability critical reference value, a cell road design width value and an obstacle blocking critical coefficient reference value through a road passing reference threshold calculation formula to obtain a road passing reference threshold;

the road trafficability reference threshold calculation formula is specifically configured as:

wherein Dt1 is a road passing reference threshold, cw1 is a vehicle body stability critical reference value, za1 is an obstacle blocking critical coefficient reference value, jlp is a cell road design width value, and Ck is a vehicle body width value;

What needs to be explained here is:

The first trafficability grading road garbage truck cannot normally pass;

The second passability classification road garbage truck can normally pass through;

Defining a judging result obtained according to the road passing reference threshold value and the road passing reference value as road passing classification data;

Defining the garbage truck moving path and road passing classification data as control management data;

the data management module acquires control management data and transmits the control management data to the vehicle-mounted control module;

the vehicle-mounted control module is used for controlling the work of the garbage truck;

Acquiring road trafficability grading data;

the box body mounting unit comprises a weight sensor, a 3D laser scanner and a height measuring instrument;

Referring to fig. 5, the garbage truck connects the boxes according to the box reversing connection path, and obtains the box weight value through the weight sensor;

acquiring the rated load capacity of the box body through a database;

in the file, three-dimensional data in the garbage truck box body can be obtained through the 3D laser scanner, the three-dimensional data comprise the volume of the stacking gap, the 3D laser scanner can accurately scan the space in the garbage truck box body, and three-dimensional coordinate information of the stacking gap at different positions is obtained, so that the volume value of the stacking gap is calculated.

the compressible reference coefficient corresponding to the compression monitoring box body is calculated, and the specific formula is configured as follows:

Wherein Ysx is a compressible reference coefficient corresponding to the compression monitoring box, gdd is a garbage stacking height value, ndj is a bottom area value inside the compression monitoring box, and Djx is a stacking gap volume value;

what needs to be explained here is: the stacking gap volume value referred to herein is specifically volume data corresponding to mutual gaps existing between the garbage in the garbage can;

what needs to be explained here is: the compressible reference coefficient threshold referred herein may be set accordingly according to the garbage type and compression mode, and in this embodiment, the compressible reference coefficient threshold is set to 0.4;

What needs to be explained here is:

the liquid accumulation marks referred to herein are particularly liquid residue marks left by the truck box, which marks are usually caused by liquid waste leakage inside the truck or liquid leakage outside the truck, and particularly liquid accumulation mark sources include, but are not limited to, dirt, water marks, oil marks;

The garbage truck box corresponding to the second box leakage monitoring interval has no leakage condition;

Comparing the first detection image with the second detection image, if the first detection image is consistent with the second detection image, no liquid leakage exists in the garbage truck box, if the first detection image is inconsistent with the second detection image, the liquid leakage exists in the garbage truck box, and a box leakage early warning is issued;

The work monitoring unit monitors work safety according to the work monitoring data, and specifically comprises the following steps:

Calculating a battery temperature value, a circuit working voltage value, a hydraulic pump real-time pressure value, a battery temperature reference value, a circuit working voltage reference value and a hydraulic pump real-time pressure reference value through a garbage truck working monitoring reference value calculation formula to obtain a garbage truck working monitoring reference value;

The calculation formula of the garbage truck working monitoring reference value is specifically configured as follows:

Gj＝|(Dw-Dwj)+(Dy-Dyj)*b1+(Yb-Ybj)|；

Wherein Gj is a working monitoring reference value of the garbage truck, dw is a battery temperature value, dy is a circuit working voltage value, yb is a real-time pressure value of the hydraulic pump, dwj is a battery temperature reference value, dyj is a circuit working voltage reference value, and Ybj is a real-time pressure reference value of the hydraulic pump;

Calculating a battery temperature range extremum, a circuit working voltage range extremum, a hydraulic pump real-time range extremum, a battery temperature reference value, a circuit working voltage reference value and a hydraulic pump real-time pressure reference value through a garbage truck working monitoring reference threshold calculation formula to obtain a garbage truck working monitoring reference threshold;

The calculation formula of the garbage truck working monitoring reference threshold is specifically configured as follows:

Gj1＝|(Dw1-Dwj)+(Dy1-Dyj)*b1+(Yb1-Ybj)|；

Wherein Gj1 is a garbage truck working monitoring reference threshold, dw1 is a battery temperature range extremum, dy1 is a circuit working voltage range extremum, yb1 is a hydraulic pump real-time range extremum, dwj is a battery temperature reference value, dyj is a circuit working voltage reference value, and Ybj is a hydraulic pump real-time pressure reference value;

What needs to be explained here is: the battery temperature range extreme value is the maximum absolute value of the battery normal temperature range, the circuit working voltage range extreme value is the maximum absolute value of the circuit normal voltage range, the hydraulic pump real-time range extreme value is the maximum absolute value of the hydraulic pump normal pressure range value, and the battery temperature range extreme value, the circuit working voltage range extreme value and the hydraulic pump real-time range extreme value are specifically set by workers in related fields;

specifically described are: the technical scheme of the invention can be suitable for controlling the automatic driving garbage truck;

In the application, if a corresponding calculation formula appears, the calculation formulas are all dimensionality-removed and numerical calculation, and the weight coefficient, the proportion coefficient and other coefficients in the formulas are set to be a result value obtained by quantizing each parameter, so long as the proportion relation between the parameter and the result value is not influenced.

Example two

Based on another conception of the same invention, a control method of a vehicle-mounted mechanism of a non-floor garbage truck is provided, which comprises the following steps:

step S1: basic control data are obtained;

Step S13: the method comprises the following steps of:

step S141: acquiring box position data through a second position sensor;

step S2: analyzing the basic control data to obtain control analysis data;

step S22: acquiring a vehicle body stability reference value;

step S31: planning a moving path, specifically as follows:

step S322: acquiring a vehicle body width value through a database;

Step S4: the garbage truck is subjected to work control and work monitoring;

step S411: acquiring road trafficability grading data;

step S4221: when the weight value of the box body is larger than the rated load capacity of the box body, overweight early warning is issued;

step S4222: when the box body weight value is smaller than or equal to the rated load capacity of the box body, marking the garbage box body as a compression monitoring box body;

The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.

Claims

1. A vehicle-mounted mechanism controller of a non-floor refuse vehicle, comprising:

And a data acquisition module: the method comprises the steps of collecting road image data of a non-floor garbage truck, judging whether an obstacle exists, and measuring n groups of road characteristic points through a laser range finder to obtain a road average width value and a road minimum width value when the obstacle exists, so as to obtain road base data; the system is also responsible for collecting driving basic data, work monitoring data and box basic data, and combining the driving basic data, the work monitoring data and the box basic data with road surface basic data to obtain basic control data;

And a data analysis module: the control method comprises the steps of analyzing basic control data to obtain an obstacle blocking coefficient reference value, a vehicle body stability reference value and a box body reversing connection path, and defining the basic control data as control analysis data;

And a data processing module: the method comprises the steps of comprehensively processing basic control data and control analysis data, planning a garbage truck moving path, comparing the obtained minimum width value of a road with vehicle body width, stability standards and road design parameters in a database based on the obtained minimum width value of the road and the control analysis data, and determining the trafficability classification of the road to obtain road trafficability classification data; defining the obtained garbage truck moving path and road trafficability grading data as control management data;

and the vehicle-mounted control module: and executing movement control of the garbage truck according to the control management data, connecting the truck body of the garbage truck with the truck body according to the truck body reversing connection path, and carrying out overweight, compression management and leakage monitoring on the garbage truck based on the working monitoring data.

2. The vehicle-mounted mechanism controller of the non-floor-standing garbage truck according to claim 1, wherein the data acquisition module comprises a road surface unit, a traveling unit, a working unit and a box unit;

the road surface unit acquires road surface basic data;

The running unit acquires the running basic data and the running unit acquires the running basic data;

The driving basic data is acquired, and the method concretely comprises the following steps:

The working unit acquires working monitoring data;

the working monitoring data are acquired as follows:

the box body unit acquires box body basic data;

the basic data of the box body are acquired, and the method specifically comprises the following steps:

Acquiring box position data through a second position sensor;

acquiring real-time position data of the obstacle through a laser radar;

3. The vehicle-mounted mechanism controller of the non-floor-standing garbage truck according to claim 2, wherein the road surface unit acquires road surface basic data, specifically as follows:

Acquiring road image data of a non-floor garbage truck through a first high-definition camera;

Judging the obstacle in front of the road according to the road image data;

4. The vehicle-mounted mechanism controller of the non-floor-standing garbage truck according to claim 1, wherein the data analysis module comprises a road surface analysis unit, a traveling analysis unit and a box analysis unit;

The driving analysis unit obtains a vehicle body stability reference value;

the box analysis unit acquires box analysis data;

the data stored in the database includes vehicle size data and turning radius;

The box analysis data is acquired, and the method is concretely as follows:

5. The vehicle-mounted mechanism controller of the non-floor-standing garbage truck according to claim 4, wherein the road surface analysis unit obtains the reference value of the obstacle blocking coefficient, specifically as follows:

6. The vehicle-mounted mechanism controller of the non-floor-standing garbage truck according to claim 1, wherein the data processing module processes basic control data and control analysis data, specifically as follows:

the path planning unit performs moving path planning, specifically as follows:

the data stored in the database comprises a vehicle body width value, a vehicle body stability critical reference value, a district road design width value and an obstacle blocking critical coefficient reference value; ;

comparing the vehicle body width value with the minimum road width value;

7. The vehicle-mounted mechanism controller of a non-floor-standing garbage truck according to claim 1, wherein the vehicle-mounted control module comprises a pass-through control unit, a tank mounting unit, a work monitoring unit and a leakage monitoring unit;

Acquiring road trafficability grading data;

The box body mounting unit comprises a weight sensor;

acquiring the rated load capacity of the box body through a database;

The leakage monitoring unit is used for carrying out leakage monitoring on the garbage truck box body.

8. The vehicle-mounted mechanism controller of a non-floor-standing garbage truck according to claim 7, wherein the leakage monitoring unit is configured to monitor leakage of a garbage truck box body, specifically as follows:

9. The vehicle-mounted mechanism controller of a non-floor-standing garbage truck according to claim 8, wherein the operation monitoring unit monitors operation safety according to operation monitoring data, specifically as follows:

10. A method for controlling a vehicle-mounted mechanism of a non-floor-standing garbage truck, which is applicable to the vehicle-mounted mechanism controller of the non-floor-standing garbage truck according to any one of claims 1 to 9, and is characterized in that the method comprises the following steps:

Step S1: collecting road image data of a non-floor garbage truck, and judging whether an obstacle exists or not; if an obstacle exists, measuring n groups of road characteristic points through a laser range finder to obtain a road average width value and a road minimum width value, and obtaining road surface basic data; meanwhile, collecting driving basic data, working monitoring data and box basic data, and combining the driving basic data, the working monitoring data and the box basic data with road surface basic data to obtain basic control data;

Step S2: analyzing the basic control data to obtain an obstacle blocking coefficient reference value, a vehicle body stability reference value and a box body reversing connection path, and defining the reference value, the vehicle body stability reference value and the box body reversing connection path as control analysis data;

Step S3: comprehensively processing basic control data and control analysis data, and planning a garbage truck moving path; based on the obtained minimum width value and control analysis data of the road, comparing the minimum width value and control analysis data with the width of the vehicle body, the stability standard and the road design parameters in the database, determining the trafficability classification of the road, and obtaining road trafficability classification data; defining the obtained garbage truck moving path and road trafficability grading data as control management data;

Step S4: and executing movement control of the garbage truck according to the control management data, connecting the truck body of the garbage truck with the truck body according to the truck body reversing connection path, and carrying out overweight, compression management and leakage monitoring on the garbage truck based on the working monitoring data.