CN112631191A - Method for realizing radar type convergence branch intelligent alarm - Google Patents
Method for realizing radar type convergence branch intelligent alarm Download PDFInfo
- Publication number
- CN112631191A CN112631191A CN202110252627.6A CN202110252627A CN112631191A CN 112631191 A CN112631191 A CN 112631191A CN 202110252627 A CN202110252627 A CN 202110252627A CN 112631191 A CN112631191 A CN 112631191A
- Authority
- CN
- China
- Prior art keywords
- conveying channel
- branch
- alarm
- radar
- main conveying
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
- G05B19/042—Programme control other than numerical control, i.e. in sequence controllers or logic controllers using digital processors
- G05B19/0423—Input/output
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
- B65G43/00—Control devices, e.g. for safety, warning or fault-correcting
- B65G43/08—Control devices operated by article or material being fed, conveyed or discharged
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
- B65G47/00—Article or material-handling devices associated with conveyors; Methods employing such devices
- B65G47/52—Devices for transferring articles or materials between conveyors i.e. discharging or feeding devices
- B65G47/68—Devices for transferring articles or materials between conveyors i.e. discharging or feeding devices adapted to receive articles arriving in one layer from one conveyor lane and to transfer them in individual layers to more than one conveyor lane or to one broader conveyor lane, or vice versa, e.g. combining the flows of articles conveyed by more than one conveyor
- B65G47/70—Devices for transferring articles or materials between conveyors i.e. discharging or feeding devices adapted to receive articles arriving in one layer from one conveyor lane and to transfer them in individual layers to more than one conveyor lane or to one broader conveyor lane, or vice versa, e.g. combining the flows of articles conveyed by more than one conveyor with precedence controls among incoming article flows
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
- G01S13/06—Systems determining position data of a target
- G01S13/08—Systems for measuring distance only
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
- G01S13/50—Systems of measurement based on relative movement of target
- G01S13/58—Velocity or trajectory determination systems; Sense-of-movement determination systems
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
- B65G2203/00—Indexing code relating to control or detection of the articles or the load carriers during conveying
- B65G2203/02—Control or detection
- B65G2203/0208—Control or detection relating to the transported articles
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
- B65G2203/00—Indexing code relating to control or detection of the articles or the load carriers during conveying
- B65G2203/02—Control or detection
- B65G2203/0208—Control or detection relating to the transported articles
- B65G2203/025—Speed of the article
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
- B65G2203/00—Indexing code relating to control or detection of the articles or the load carriers during conveying
- B65G2203/04—Detection means
- B65G2203/042—Sensors
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/20—Pc systems
- G05B2219/25—Pc structure of the system
- G05B2219/25257—Microcontroller
Abstract
The invention provides a method for realizing radar type convergence branch intelligent alarm, which comprises four steps of observation point setting, system networking, alarm setting, convergence alarm and the like. On one hand, the system has simple structure and good universality, can effectively meet the requirements of monitoring and safety alarming on the position of the confluence node under different media, equipment and environments, prevents the collision and mixing condition among all conveying media during confluence operation, and improves the safety of medium conveying; on the other hand, when monitoring and alarming operation is carried to the confluence node medium, the data processing capacity is strong, the operation automation and the intelligent degree are high, the working efficiency and the precision of the operation control and the alarming operation of the confluence position device can be effectively improved, and the cost and the difficulty of the operation of the system can be effectively reduced.
Description
Technical Field
The invention relates to a method for realizing radar type convergence branch intelligent alarm, belonging to the technical field of security monitoring and electromechanical technology.
Background
At present, in the fields of industrial and agricultural production, transportation and the like, confluence operation is often required to be carried out on materials, equipment or vehicles on two or more conveying devices, roads and air lines so as to meet the operation requirements of the transportation, material transportation and the like, but in actual work, no effective equipment or method for accurately monitoring the operation state of confluence points exists at present, the equipment or method is often required to be controlled on site by drivers and operators of mechanical equipment, although the requirements of multi-path confluence operation can be met, the control precision and the control flexibility are relatively poor during the confluence operation, the control precision of the material confluence mixing proportion is very easy to cause, the materials in all confluence directions are very easy to collide to damage or cause accidents during the confluence operation, and the phenomena of blockage and the like are very easy to be caused due to unreasonable arrangement of the passing sequence among the materials in all backflow directions and the transportation, thereby seriously affecting the reliability and safety of the confluence operation.
In view of the above problem, there is a need to develop a monitoring and protection system and a corresponding management method to meet the needs of actual work.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a method for realizing radar type convergence branch intelligent alarm, which overcomes the defects in the production of the existing similar products and meets the requirements of actual use.
In order to achieve the purpose, the invention provides the following technical scheme:
a radar type convergence branch intelligent alarm implementation method comprises the following steps:
s1, setting observation points, namely, firstly, carrying out layout detection on the conveying system, detecting a main conveying channel, a branch conveying channel, a main conveying channel and a branch conveying channel converging position, then setting the main conveying channel and the branch conveying channel converging position as the observation points, and then setting parameters of the observation points, the number of the observation points in the conveying direction of the main conveying channel and the distance between every two adjacent observation points, namely, finishing the setting of the observation points;
s2, networking the system, after the step S1 is completed, firstly setting an alarm server, then measuring the intersection point position of the main conveying channel and the branch conveying channel at the position of an observation point to be alarmed and the included angle between the main conveying channel and the branch conveying channel, and on one hand respectively setting alarm observation radars at the inflow end and the outflow end of the main conveying channel corresponding to the observation point along the axial direction of the main conveying channel; on the other hand, alarm observation radars are respectively arranged at the inflow end and the outflow end of the branch conveying channel corresponding to the observation point along the axial direction of each branch conveying channel, then the included angle of 0-60 degrees is formed between the axial line of the alarm observation radar arranged in the main conveying channel and the branch conveying channel and the axial line of the main conveying channel and the branch conveying channel where the alarm observation radar is arranged, the alarm observation radars are mutually connected in parallel, and finally the alarm observation radars are respectively connected with an alarm server through a communication network to complete system networking;
s3, alarm setting, after completing the operation of the step S2, firstly inputting and constructing a nested framework BP neural network system adopting a C/S structure and a B/S structure, and an LSTM-based intelligent prediction system and a deep learning neural network system which run cooperatively with the BP neural network system into an alarm server, then setting the working mode of each alarm observation radar on-off machine, setting a main conveying channel and the maximum limit flow of a branch conveying channel, setting the main conveying channel and the minimum limit distance between two adjacent media in the branch conveying channel, setting the maximum and minimum limit flow rates of the main conveying channel and the branch conveying channel, and setting the minimum relative speed difference of the intersection of the media in the same batch of the main conveying channel and the branch conveying channel on the one hand through the nested framework BP neural network system, and completing alarm detection setting; on the other hand, an alarm analysis deep learning analysis system is set;
s4, after finishing the operation of S3, the confluence alarm firstly detects the medium parameters of the main conveying channel and the branch conveying channel at the position of the observation point through the alarm observation radar at the inflow end position of the main conveying channel and the branch conveying channel, and the BP neural network system carries out operation according to the detection data, on one hand, the medium traffic volume and the traffic speed in the main conveying channel and the branch conveying channel are judged, setting the medium conveying priority in the main conveying channel and the branch conveying channel according to the medium passing amount and the passing speed, analyzing and calculating the collision rate of passing media in the main conveying channel and the branch conveying channel, and simultaneously alarms through the alarm observation radar and the alarm server when the collision condition exists, meanwhile, the passing speeds of corresponding media in the main conveying channel and the branch conveying channel are set, so that the collision condition is avoided; and on the other hand, an LSTM-based intelligent prediction system and a deep learning neural network system which drive the BP neural network system to cooperatively operate are operated, background simulation and learning are carried out on the data analysis operation process of the main conveying channel and the branch conveying channel, medium operation control strategies of the main conveying channel and the branch conveying channel under the same parameters are generated, the medium operation control strategies under various parameters are stored in an alarm server for standby, and when the parameters of subsequent passing media in the main conveying channel and the branch conveying channel are consistent with the operation control strategies, an alarm is directly carried out according to the operation control strategies and the media in the main conveying channel and the branch conveying channel are guided to operate.
Further, in the step S2, the direction of the warning observation radar axis is opposite to the conveying direction of the main conveying path and the branch conveying path.
Further, the step S2, the warning observation radar includes a bearing base, a guide arm, a detection head, a distance measuring radar, a speed measuring radar, a monitoring camera, an auxiliary illuminating lamp, a driving circuit, and an intelligent communication gateway, wherein the rear end face of the guide arm is connected to the bearing base through a turntable mechanism, and is connected to an external positioning mechanism through the bearing base, and the axis of the guide arm forms an included angle of 0-135 ° with the axis of the main conveying passage and the branch conveying passage, the front end face of the guide arm is hinged to the detection head through the turntable mechanism, the detection head is of a sealed cavity structure and is located above the main conveying passage and the branch conveying passage, the distance measuring radar, the speed measuring radar, the monitoring camera, and the auxiliary illuminating lamp are embedded in the front end face of the detection head, and the optical axes of the distance measuring radar, the speed measuring radar, the monitoring camera, and the auxiliary illuminating lamp are distributed in parallel to each other, The speed measuring radar, the monitoring camera, the auxiliary lighting lamp optical axis and the main conveying channel and the branch conveying channel axis are included angles of 0-135 degrees, the driving circuit is embedded in the detection head and is electrically connected with the guide arm, the distance measuring radar, the speed measuring radar, the monitoring camera, the auxiliary lighting lamp, the intelligent communication gateway and the rotary table mechanism respectively, the intelligent communication gateway is connected with the outer surface of the bearing base, and the intelligent communication gateway is connected with the alarm server through a communication network.
Furthermore, the guide arm is a 3-6 degree-of-freedom electric mechanical arm; the rotary table mechanism is any one of a three-dimensional rotary table and a three-dimensional displacement table, and an angle sensor is additionally arranged on the rotary table mechanism; the upper end face of the detection head is additionally provided with an inclination angle sensor, and the angle sensor and the inclination angle sensor are electrically connected with the driving circuit.
Furthermore, the driving circuit is a central data processing circuit based on an FPGA chip and a GPU chip, and the driving circuit is additionally provided with an auxiliary driving battery, an acceleration operation circuit based on PID, a data communication bus circuit, an MOS driving circuit, a crystal oscillator clock circuit, a data cache circuit and an I/O communication port circuit, wherein the central data processing circuit is electrically connected with the acceleration operation circuit based on PID, the MOS driving circuit, the crystal oscillator clock circuit, the data cache circuit and the I/O port circuit through the data communication bus circuit, and the MOS driving circuit and the I/O port circuit are electrically connected with the auxiliary driving battery and a serial port communication terminal.
Further, in the step S2, the alarm server is a server based on cloud computing, and the alarm server establishes a data connection with an external third-party data platform through a data communication network.
Further, in the step S4, when setting the passing speeds of the respective media in the main conveying path and the branch conveying path, and adjusting the conveying amounts of the media in the main conveying path and the branch conveying path, an adjustment reference amount determination criterion is additionally set, and the adjustment reference amount determination criterion specifically includes:
1. regulating the medium conveying amount in the branch conveying channel by taking the mixing ratio of the conveying media in the main conveying channel and the branch conveying channel as a regulating basis and taking the medium conveying amount of the main conveying channel as a reference;
2. the passing speed of the conveying medium in the main conveying channel and the branch conveying channel is used as the adjusting basis, and the medium entering the observation point has high input speed and preferentially passes through the observation point;
3. the medium passing amount in the observation point is large and the medium passing amount in the observation point preferentially passes by taking the passing amounts of the conveying media in the main conveying channel and the branch conveying channel as the adjusting basis.
Furthermore, the main conveying channel and the branch conveying channel are any one of a conveying belt, a conveying pipe, a road and a route; the medium is any one of a vehicle, a liquid substance, a solid powdery substance and an electromechanical device.
On one hand, the system has simple structure and good universality, can effectively meet the requirements of monitoring and safety alarming on the position of the confluence node under different media, equipment and environments, prevents the collision and mixing condition among all conveying media during confluence operation, and improves the safety of medium conveying; on the other hand, when monitoring and alarming operation is carried to the confluence node medium, the data processing capacity is strong, the operation automation and the intelligent degree are high, the working efficiency and the precision of the operation control and the alarming operation of the confluence position device can be effectively improved, and the cost and the difficulty of the operation of the system can be effectively reduced.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a schematic diagram of a structure of an alarm observation radar;
FIG. 3 is a schematic diagram of a driving circuit;
FIG. 4 is a schematic diagram of the system of the present invention.
The reference numbers in the figures: bear base 1, guide arm 2, detection head 3, range radar 4, speed measuring radar 5, surveillance camera head 6, auxiliary lighting lamp 7, drive circuit 8, intelligent communication gateway 9, revolving stage mechanism 10, inclination sensor 12, angle sensor 13.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, a method for implementing radar type convergence branch intelligent alarm includes the following steps:
s1, setting observation points, namely, firstly, carrying out layout detection on the conveying system, detecting a main conveying channel, a branch conveying channel, a main conveying channel and a branch conveying channel converging position, then setting the main conveying channel and the branch conveying channel converging position as the observation points, and then setting parameters of the observation points, the number of the observation points in the conveying direction of the main conveying channel and the distance between every two adjacent observation points, namely, finishing the setting of the observation points;
s2, networking the system, after the step S1 is completed, firstly setting an alarm server, then measuring the intersection point position of the main conveying channel and the branch conveying channel at the position of an observation point to be alarmed and the included angle between the main conveying channel and the branch conveying channel, and on one hand respectively setting alarm observation radars at the inflow end and the outflow end of the main conveying channel corresponding to the observation point along the axial direction of the main conveying channel; on the other hand, alarm observation radars are respectively arranged at the inflow end and the outflow end of the branch conveying channel corresponding to the observation point along the axial direction of each branch conveying channel, then the included angle of 0-60 degrees is formed between the axial line of the alarm observation radar arranged in the main conveying channel and the branch conveying channel and the axial line of the main conveying channel and the branch conveying channel where the alarm observation radar is arranged, the alarm observation radars are mutually connected in parallel, and finally the alarm observation radars are respectively connected with an alarm server through a communication network to complete system networking;
s3, alarm setting, after completing the operation of the step S2, firstly inputting and constructing a nested framework BP neural network system adopting a C/S structure and a B/S structure, and an LSTM-based intelligent prediction system and a deep learning neural network system which run cooperatively with the BP neural network system into an alarm server, then setting the working mode of each alarm observation radar on-off machine, setting a main conveying channel and the maximum limit flow of a branch conveying channel, setting the main conveying channel and the minimum limit distance between two adjacent media in the branch conveying channel, setting the maximum and minimum limit flow rates of the main conveying channel and the branch conveying channel, and setting the minimum relative speed difference of the intersection of the media in the same batch of the main conveying channel and the branch conveying channel on the one hand through the nested framework BP neural network system, and completing alarm detection setting; on the other hand, an alarm analysis deep learning analysis system is set;
s4, after finishing the operation of S3, the confluence alarm firstly detects the medium parameters of the main conveying channel and the branch conveying channel at the position of the observation point through the alarm observation radar at the inflow end position of the main conveying channel and the branch conveying channel, and the BP neural network system carries out operation according to the detection data, on one hand, the medium traffic volume and the traffic speed in the main conveying channel and the branch conveying channel are judged, setting the medium conveying priority in the main conveying channel and the branch conveying channel according to the medium passing amount and the passing speed, analyzing and calculating the collision rate of passing media in the main conveying channel and the branch conveying channel, and simultaneously alarms through the alarm observation radar and the alarm server when the collision condition exists, meanwhile, the passing speeds of corresponding media in the main conveying channel and the branch conveying channel are set, so that the collision condition is avoided; and on the other hand, an LSTM-based intelligent prediction system and a deep learning neural network system which drive the BP neural network system to cooperatively operate are operated, background simulation and learning are carried out on the data analysis operation process of the main conveying channel and the branch conveying channel, medium operation control strategies of the main conveying channel and the branch conveying channel under the same parameters are generated, the medium operation control strategies under various parameters are stored in an alarm server for standby, and when the parameters of subsequent passing media in the main conveying channel and the branch conveying channel are consistent with the operation control strategies, an alarm is directly carried out according to the operation control strategies and the media in the main conveying channel and the branch conveying channel are guided to operate.
In this embodiment, in the step S2, the direction of the warning observation radar axis is opposite to the conveying direction of the main conveying path and the branch conveying path.
As shown in fig. 2-4, the warning observation radar in the step S2 includes a bearing base 1, a guiding arm 2, a detection head 3, a distance measuring radar 4, a speed measuring radar 5, a monitoring camera 6, an auxiliary illuminating lamp 7, a driving circuit 8, and an intelligent communication gateway 9, wherein the rear end face of the guiding arm 2 is connected with the bearing base 1 through a turntable mechanism 10, and is connected with an external positioning mechanism through the bearing base 1, the axial line of the guiding arm 2 forms an included angle of 0 ° to 135 ° with the axial line of the main conveying channel and the branch conveying channel, the front end face of the guiding arm 2 is hinged with the detection head 3 through the turntable mechanism 10, the detection head 3 is a closed cavity structure and is located above the main conveying channel and the branch conveying channel, the distance measuring radar 4, the speed measuring radar 5, the monitoring camera 6, and the auxiliary illuminating lamp 7 are all embedded in the front end face of the detection head 3, and the distance measuring radar 4, the speed, Monitoring camera 6, the mutual parallel distribution of 7 optical axes of auxiliary lighting lamp, and range radar 4, the radar 5 that tests the speed, monitoring camera 6, 7 optical axes of auxiliary lighting lamp are 0-135 contained angles with main transfer passage, branch road transfer passage axis, drive circuit 8 inlays in detector 3 to respectively with guiding arm 2, range radar 4, radar 5, monitoring camera 6, auxiliary lighting lamp 7, intelligent communication gateway 9 and 10 electrical connections of revolving stage mechanism, intelligent communication gateway 9 with bear 1 surface connection of base, and intelligent communication gateway 9 passes through communication network and reports to the police the server and establish data connection.
Wherein, the guide arm 2 is a 3-6 degree-of-freedom electric mechanical arm; the rotary table mechanism 10 is any one of a three-dimensional rotary table and a three-dimensional displacement table, and an angle sensor 13 is additionally arranged on the rotary table mechanism 10; the upper end surface of the detection head 3 is additionally provided with an inclination angle sensor 12, and the angle sensor 13 and the inclination angle sensor 12 are both electrically connected with the driving circuit 8.
It should be noted that the driving circuit 8 is a central data processing circuit based on an FPGA chip and a GPU chip, and the driving circuit 8 is further provided with an auxiliary driving battery, an acceleration operation circuit based on a PID, a data communication bus circuit, an MOS driving circuit, a crystal oscillator clock circuit, a data cache circuit, and an I/O communication port circuit, wherein the central data processing circuit is electrically connected to the acceleration operation circuit based on the PID, the MOS driving circuit, the crystal oscillator clock circuit, the data cache circuit, and the I/O port circuit through the data communication bus circuit, and the MOS driving circuit and the I/O port circuit are electrically connected to the auxiliary driving battery and the serial communication terminal.
In this embodiment, in the step S2, the alarm server is a server based on cloud computing, and the alarm server further establishes a data connection with an external third-party data platform through a data communication network.
In this embodiment, in the step S4, when setting the passing speeds of the corresponding media in the main conveying path and the branch conveying path, and adjusting the conveying amounts of the media in the main conveying path and the branch conveying path, an adjustment reference amount determination standard is further set, and the adjustment reference amount determination standard specifically includes:
1. regulating the medium conveying amount in the branch conveying channel by taking the mixing ratio of the conveying media in the main conveying channel and the branch conveying channel as a regulating basis and taking the medium conveying amount of the main conveying channel as a reference;
2. the passing speed of the conveying medium in the main conveying channel and the branch conveying channel is used as the adjusting basis, and the medium entering the observation point has high input speed and preferentially passes through the observation point;
3. the medium passing amount in the observation point is large and the medium passing amount in the observation point preferentially passes by taking the passing amounts of the conveying media in the main conveying channel and the branch conveying channel as the adjusting basis.
Furthermore, the main conveying channel and the branch conveying channel are any one of a conveying belt, a conveying pipe, a road and a route; the medium is any one of a vehicle, a liquid substance, a solid powdery substance and an electromechanical device.
On one hand, the system has simple structure and good universality, can effectively meet the requirements of monitoring and safety alarming on the position of the confluence node under different media, equipment and environments, prevents the collision and mixing condition among all conveying media during confluence operation, and improves the safety of medium conveying; on the other hand, when monitoring and alarming operation is carried to the confluence node medium, the data processing capacity is strong, the operation automation and the intelligent degree are high, the working efficiency and the precision of the operation control and the alarming operation of the confluence position device can be effectively improved, and the cost and the difficulty of the operation of the system can be effectively reduced.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (8)
1. A radar type convergence branch intelligent alarm implementation method is characterized in that: the method comprises the following steps:
s1, setting observation points, namely, firstly, carrying out layout detection on the conveying system, detecting a main conveying channel, a branch conveying channel, a main conveying channel and a branch conveying channel converging position, then setting the main conveying channel and the branch conveying channel converging position as the observation points, and then setting parameters of the observation points, the number of the observation points in the conveying direction of the main conveying channel and the distance between every two adjacent observation points, namely, finishing the setting of the observation points;
s2, networking the system, after the step S1 is completed, firstly setting an alarm server, then measuring the intersection point position of the main conveying channel and the branch conveying channel at the position of an observation point to be alarmed and the included angle between the main conveying channel and the branch conveying channel, and on one hand respectively setting alarm observation radars at the inflow end and the outflow end of the main conveying channel corresponding to the observation point along the axial direction of the main conveying channel; on the other hand, alarm observation radars are respectively arranged at the inflow end and the outflow end of the branch conveying channel corresponding to the observation point along the axial direction of each branch conveying channel, then the included angle of 0-60 degrees is formed between the axial line of the alarm observation radar arranged in the main conveying channel and the branch conveying channel and the axial line of the main conveying channel and the branch conveying channel where the alarm observation radar is arranged, the alarm observation radars are mutually connected in parallel, and finally the alarm observation radars are respectively connected with an alarm server through a communication network to complete system networking;
s3, alarm setting, after completing the operation of the step S2, firstly inputting and constructing a nested framework BP neural network system adopting a C/S structure and a B/S structure, and an LSTM-based intelligent prediction system and a deep learning neural network system which run cooperatively with the BP neural network system into an alarm server, then setting the working mode of each alarm observation radar on-off machine, setting a main conveying channel and the maximum limit flow of a branch conveying channel, setting the main conveying channel and the minimum limit distance between two adjacent media in the branch conveying channel, setting the maximum and minimum limit flow rates of the main conveying channel and the branch conveying channel, and setting the minimum relative speed difference of the intersection of the media in the same batch of the main conveying channel and the branch conveying channel on the one hand through the nested framework BP neural network system, and completing alarm detection setting; on the other hand, an alarm analysis deep learning analysis system is set;
s4, after finishing the operation of S3, the confluence alarm firstly detects the medium parameters of the main conveying channel and the branch conveying channel at the position of the observation point through the alarm observation radar at the inflow end position of the main conveying channel and the branch conveying channel, and the BP neural network system carries out operation according to the detection data, on one hand, the medium traffic volume and the traffic speed in the main conveying channel and the branch conveying channel are judged, setting the medium conveying priority in the main conveying channel and the branch conveying channel according to the medium passing amount and the passing speed, analyzing and calculating the collision rate of passing media in the main conveying channel and the branch conveying channel, and simultaneously alarms through the alarm observation radar and the alarm server when the collision condition exists, meanwhile, the passing speeds of corresponding media in the main conveying channel and the branch conveying channel are set, so that the collision condition is avoided; and on the other hand, an LSTM-based intelligent prediction system and a deep learning neural network system which drive the BP neural network system to cooperatively operate are operated, background simulation and learning are carried out on the data analysis operation process of the main conveying channel and the branch conveying channel, medium operation control strategies of the main conveying channel and the branch conveying channel under the same parameters are generated, the medium operation control strategies under various parameters are stored in an alarm server for standby, and when the parameters of subsequent passing media in the main conveying channel and the branch conveying channel are consistent with the operation control strategies, an alarm is directly carried out according to the operation control strategies and the media in the main conveying channel and the branch conveying channel are guided to operate.
2. The method for realizing radar type convergence branch intelligent alarm according to claim 1, wherein the method comprises the following steps: in step S2, the direction of the warning observation radar axis is opposite to the conveying direction of the main conveying path and the branch conveying path.
3. The method for realizing radar type convergence branch intelligent alarm according to claim 1, wherein the method comprises the following steps: s2 step in report an emergency and ask for help or increased vigilance observation radar including bearing base (1), guiding arm (2), detect head (3), range finding radar (4), speed measuring radar (5), surveillance camera head (6), auxiliary lighting lamp (7), drive circuit (8), intelligent communication gateway (9), wherein guiding arm (2) rear end face passes through revolving stage mechanism (10) and is connected with bearing base (1) to be connected with outside positioning mechanism through bearing base (1), and guiding arm (2) axis and main transfer passage, branch road transfer passage axis are 0 ~ 135 contained angle, guiding arm (2) preceding terminal surface passes through revolving stage mechanism (10) and articulates with detect head (3), detect head (3) are airtight cavity structure to be located main transfer passage, branch road transfer passage top, range finding radar (4), speed measuring radar (5), range finding radar (4), The monitoring camera (6) and the auxiliary illuminating lamp (7) are embedded on the front end surface of the detection head (3), and the optical axes of the distance measuring radar (4), the speed measuring radar (5), the monitoring camera (6) and the auxiliary illuminating lamp (7) are distributed in parallel, and the optical axes of the distance measuring radar (4), the speed measuring radar (5), the monitoring camera (6) and the auxiliary illuminating lamp (7) form 0-135 degree included angles with the axes of the main conveying channel and the branch conveying channel, the driving circuit (8) is embedded in the detection head (3), and are respectively electrically connected with the guide arm (2), the distance measuring radar (4), the speed measuring radar (5), the monitoring camera (6), the auxiliary illuminating lamp (7), the intelligent communication gateway (9) and the turntable mechanism (10), the intelligent communication gateway (9) is connected with the outer surface of the bearing base (1), and the intelligent communication gateway (9) establishes data connection with the alarm server through a communication network.
4. The method for realizing intelligent alarm of radar type convergence branch according to claim 3, wherein: the guide arm (2) is a 3-6 degree-of-freedom electric mechanical arm; the rotary table mechanism (10) is any one of a three-dimensional rotary table and a three-dimensional displacement table, and an angle sensor (13) is additionally arranged on the rotary table mechanism (10); the upper end face of the detection head (3) is additionally provided with an inclination angle sensor (12), and the angle sensor (13) and the inclination angle sensor (12) are electrically connected with the driving circuit (8).
5. The method for realizing intelligent alarm of radar type convergence branch according to claim 3, wherein: the driving circuit (8) is a central data processing circuit based on an FPGA chip and a GPU chip, and the driving circuit (8) is additionally provided with an auxiliary driving battery, an acceleration operation circuit based on PID, a data communication bus circuit, an MOS driving circuit, a crystal oscillator clock circuit, a data cache circuit and an I/O communication port circuit, wherein the central data processing circuit is respectively and electrically connected with the acceleration operation circuit based on PID, the MOS driving circuit, the crystal oscillator clock circuit, the data cache circuit and the I/O port circuit through the data communication bus circuit, and the MOS driving circuit and the I/O port circuit are both electrically connected with the auxiliary driving battery and a serial port communication terminal.
6. The method for realizing radar type convergence branch intelligent alarm according to claim 1, wherein the method comprises the following steps: in the step S2, the alarm server is a server based on cloud computing, and the alarm server further establishes a data connection with an external third-party data platform through a data communication network.
7. The method for realizing radar type convergence branch intelligent alarm according to claim 1, wherein the method comprises the following steps: in the step S4, when setting the passing speeds of the respective media in the main conveying path and the branch conveying path, and adjusting the conveying amounts of the media in the main conveying path and the branch conveying path, additionally setting an adjustment reference amount determination standard, where the adjustment reference amount determination standard specifically is:
1. regulating the medium conveying amount in the branch conveying channel by taking the mixing ratio of the conveying media in the main conveying channel and the branch conveying channel as a regulating basis and taking the medium conveying amount of the main conveying channel as a reference;
2. the passing speed of the conveying medium in the main conveying channel and the branch conveying channel is used as the adjusting basis, and the medium entering the observation point has high input speed and preferentially passes through the observation point;
3. the medium passing amount in the observation point is large and the medium passing amount in the observation point preferentially passes by taking the passing amounts of the conveying media in the main conveying channel and the branch conveying channel as the adjusting basis.
8. The method for realizing radar type convergence branch intelligent alarm according to claim 1, wherein the method comprises the following steps: the main conveying channel and the branch conveying channel are any one of a conveying belt, a conveying pipe, a road and a route; the medium is any one of a vehicle, a liquid substance, a solid powdery substance and an electromechanical device.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110252627.6A CN112631191B (en) | 2021-03-09 | 2021-03-09 | Method for realizing radar type convergence branch intelligent alarm |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110252627.6A CN112631191B (en) | 2021-03-09 | 2021-03-09 | Method for realizing radar type convergence branch intelligent alarm |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112631191A true CN112631191A (en) | 2021-04-09 |
| CN112631191B CN112631191B (en) | 2021-05-07 |
Family
ID=75297790
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110252627.6A Active CN112631191B (en) | 2021-03-09 | 2021-03-09 | Method for realizing radar type convergence branch intelligent alarm |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112631191B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112987628A (en) * | 2021-05-12 | 2021-06-18 | 南京斯酷环境科技有限公司 | Comprehensive monitoring backbone network interface communication module and monitoring method thereof |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| RU2111505C1 (en) * | 1988-01-18 | 1998-05-20 | Альберто Паолетти Паоло | Radiolocation system preventing collision of transport means |
| CN102322002A (en) * | 2011-05-30 | 2012-01-18 | 戴小文 | Continue and operation anti-collision early warning control device from the wheel movement special equipment |
| CN202783898U (en) * | 2012-03-23 | 2013-03-13 | 南京中钞长城金融设备有限公司 | Bank note pack converging and storing and conveying apparatus |
| CN105278443A (en) * | 2015-10-27 | 2016-01-27 | 天时海洋工程及石油装备研究院（青岛）有限公司 | Drilling device region anti-collision control method and control system |
| KR101604171B1 (en) * | 2013-11-08 | 2016-03-16 | 강원대학교산학협력단 | SOM type doppler radar using filter of resonator and antenna |
| CN207774646U (en) * | 2018-01-19 | 2018-08-28 | 日照港股份有限公司第二港务分公司 | Ship unloaders walking anti-collision monitoring device based on radar |
| CN108499882A (en) * | 2018-02-01 | 2018-09-07 | 南华大学 | Method for sorting is wrapped up in address error correction based on time difference principle |
| CN109910258A (en) * | 2019-03-15 | 2019-06-21 | 新安天玉有机硅有限公司 | Adhesive tape squeezes out packaging production equipment and its production method |
-
2021
- 2021-03-09 CN CN202110252627.6A patent/CN112631191B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| RU2111505C1 (en) * | 1988-01-18 | 1998-05-20 | Альберто Паолетти Паоло | Radiolocation system preventing collision of transport means |
| CN102322002A (en) * | 2011-05-30 | 2012-01-18 | 戴小文 | Continue and operation anti-collision early warning control device from the wheel movement special equipment |
| CN202783898U (en) * | 2012-03-23 | 2013-03-13 | 南京中钞长城金融设备有限公司 | Bank note pack converging and storing and conveying apparatus |
| KR101604171B1 (en) * | 2013-11-08 | 2016-03-16 | 강원대학교산학협력단 | SOM type doppler radar using filter of resonator and antenna |
| CN105278443A (en) * | 2015-10-27 | 2016-01-27 | 天时海洋工程及石油装备研究院（青岛）有限公司 | Drilling device region anti-collision control method and control system |
| CN207774646U (en) * | 2018-01-19 | 2018-08-28 | 日照港股份有限公司第二港务分公司 | Ship unloaders walking anti-collision monitoring device based on radar |
| CN108499882A (en) * | 2018-02-01 | 2018-09-07 | 南华大学 | Method for sorting is wrapped up in address error correction based on time difference principle |
| CN109910258A (en) * | 2019-03-15 | 2019-06-21 | 新安天玉有机硅有限公司 | Adhesive tape squeezes out packaging production equipment and its production method |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112987628A (en) * | 2021-05-12 | 2021-06-18 | 南京斯酷环境科技有限公司 | Comprehensive monitoring backbone network interface communication module and monitoring method thereof |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112631191B (en) | 2021-05-07 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112631191B (en) | Method for realizing radar type convergence branch intelligent alarm | |
| CN111210662A (en) | Intersection safety early warning system and method based on machine vision and DSRC | |
| CN102033237B (en) | Method and system for predicating collision possibility as well as anti-collision control method and system | |
| Wang et al. | Vehicle collision prediction at intersections based on comparison of minimal distance between vehicles and dynamic thresholds | |
| CN108590664B (en) | Multi-functional unattended intelligent tunnel digging change system based on trinocular vision identification technology | |
| CN104269070A (en) | Active vehicle safety pre-warning method and safety pre-warning system with same applied | |
| CN112509297B (en) | Intelligent monitoring method and device for preventing transmission line from being broken outside | |
| CN107543726A (en) | A kind of method of testing and device of unmanned vehicle Ride Control System manipulation precision | |
| CN110615368A (en) | Building construction tower crane anti-collision early warning system considering wind speed influence | |
| CN111882694A (en) | Machine room inspection method and device and robot | |
| CN112446543A (en) | Urban underground comprehensive pipe gallery risk management and control system and method based on neural network | |
| CN105372650A (en) | Unmanned plane flight track precision detection method and device | |
| Billones et al. | Microscopic road traffic scene analysis using computer vision and traffic flow modelling | |
| CN110244002B (en) | Atmospheric pollution source tracking method based on unmanned aerial vehicle system | |
| CN113358817B (en) | Gas source positioning device based on gas concentration gradient driving | |
| CN113204041B (en) | Electronic job ticket management and control system and method based on location service | |
| CN111332950B (en) | Anti-collision control device and method for cantilever crane | |
| CN108562909A (en) | A kind of industrial robot track detection device | |
| CN104063884A (en) | Image target recognition method based on combination of motion prediction and multi-template matching | |
| CN111137792A (en) | Three-dimensional anti-collision method and equipment for tower crane | |
| CN105484211A (en) | Safety monitoring and management system for gantry crane | |
| Talpur et al. | Smart Railway Track and Crossing Gate Security System Based on IoT | |
| Genders et al. | Smartphone construction safety awareness system: A cyber-physical system approach | |
| JP2019520648A (en) | Method, apparatus and system for detecting reverse running driver | |
| KR102470359B1 (en) | A system for providing environmental information using moble environmental information collector |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |