CN117572897A - Port operation abnormity diagnosis and analysis system and method based on unmanned integrated card - Google Patents

Port operation abnormity diagnosis and analysis system and method based on unmanned integrated card Download PDF

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Publication number
CN117572897A
CN117572897A CN202311326904.9A CN202311326904A CN117572897A CN 117572897 A CN117572897 A CN 117572897A CN 202311326904 A CN202311326904 A CN 202311326904A CN 117572897 A CN117572897 A CN 117572897A
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data
card
unmanned
analysis
time
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周文博
骆嫚
赵威
黄衍
邓瑶
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Dongfeng Yuexiang Technology Co Ltd
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Dongfeng Yuexiang Technology Co Ltd
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    • 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
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0208—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the configuration of the monitoring system
    • G05B23/0213—Modular or universal configuration of the monitoring system, e.g. monitoring system having modules that may be combined to build monitoring program; monitoring system that can be applied to legacy systems; adaptable monitoring system; using different communication protocols
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
    • G06F11/0703—Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation
    • G06F11/0706—Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation the processing taking place on a specific hardware platform or in a specific software environment
    • G06F11/0736—Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation the processing taking place on a specific hardware platform or in a specific software environment in functional embedded systems, i.e. in a data processing system designed as a combination of hardware and software dedicated to performing a certain function
    • G06F11/0739—Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation the processing taking place on a specific hardware platform or in a specific software environment in functional embedded systems, i.e. in a data processing system designed as a combination of hardware and software dedicated to performing a certain function in a data processing system embedded in automotive or aircraft systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
    • G06F11/0703—Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation
    • G06F11/079—Root cause analysis, i.e. error or fault diagnosis
    • 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
    • G05B2219/24—Pc safety
    • G05B2219/24065—Real time diagnostics

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Quality & Reliability (AREA)
  • General Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Health & Medical Sciences (AREA)
  • Biomedical Technology (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The invention provides a harbour operation abnormity diagnosis and analysis system and method based on an unmanned integrated card, wherein the system comprises a data embedding point reporting unit, a data embedding point analysis unit and a harbour machine equipment, wherein the data embedding point analysis unit is used for reporting embedding point data in automatic driving software, a dispatching system and the harbour machine equipment; the data acquisition and receiving unit is used for receiving buried point data of automatic driving software, a dispatching system and port machine equipment through a network; the real-time data storage unit is used for storing the automatic driving software, the dispatching system and the buried point data of the port machine equipment and forming a message queue; the data processing unit is used for storing buried data in a storage manner according to the message queue and carrying out anomaly identification on unmanned set card ad data; and the fusion analysis unit is used for carrying out fusion analysis on the data processing result according to a preset abnormality detection rule and a time-consuming index threshold value, and writing the analysis result into a database for visual presentation. The technical scheme helps operation developers to master and know time-consuming abnormal links and reasons of operation, and enables the automatic driving operation developers to rapidly locate and solve problems, so that unmanned card collecting operation efficiency is improved.

Description

Port operation abnormity diagnosis and analysis system and method based on unmanned integrated card
Technical Field
The application relates to the technical field of unmanned integrated cards, in particular to a port operation abnormity diagnosis and analysis system and method applied to an unmanned integrated card.
Background
Along with the development of globalization economy, each port is developed towards specialized and automatic directions, so that a port operation analysis system is required to be applied to collect and process data, the data is processed and calculated, special index analysis is carried out according to an analysis subject, and data visualization is carried out through report tools such as BI, so that the special report index output of each link of the port is realized, and operators are helped to know the overall operation condition of the port. However, since the port operation analysis system used at present is mainly used for data analysis scenes of transportation in the manned integrated card field, and the main analysis contents are indexes such as rail bridge crane energy consumption, yard illumination energy consumption, manned integrated card trailer efficiency, etc., the system cannot be applied to various abnormal time-consuming links and unstable factors in the unmanned integrated card operation process, and the port operation analysis system is mainly used for carrying out statistics and display by collecting state data of various devices, and cannot automatically identify and give automatic reason diagnosis to various abnormal time-consuming links in the unmanned integrated card operation process, so that operation management staff can only know that the system is abnormal, but the system cannot learn the abnormality and the reason.
Disclosure of Invention
In view of the above, the invention provides a port operation abnormality diagnosis analysis system and method applied to an unmanned set card, so as to solve the technical problems in the prior art that analysis, cause diagnosis and the like cannot be performed on abnormal time-consuming links of the unmanned set card in the operation process.
A port operation anomaly diagnostic analysis system for an unmanned header card, the system comprising: the data embedding point reporting unit is used for carrying out data embedding points on automatic driving software, a dispatching system and port machine equipment to report embedding point data; the data acquisition and receiving unit is used for receiving buried point data of automatic driving software, a dispatching system and port machine equipment through a network; the real-time data storage unit is used for storing the automatic driving software, the dispatching system and the buried point data of the port machine equipment and forming a message queue; the data processing unit is used for storing buried data in a storage manner according to the message queue and carrying out anomaly identification on unmanned set card ad data; and the fusion analysis unit is used for carrying out fusion analysis on the data processing result according to a preset abnormality detection rule and a time-consuming index threshold value, and writing the analysis result into a database for visual presentation.
Further, the system further comprises: the back-end service unit is used for configuring thresholds of time-consuming indexes of each operation flow link of the vehicle and algorithm rules, abnormality reasons and solutions of common abnormal time-consuming behaviors in the operation process of the vehicle before diagnosis and analysis.
Further, the operation flow link includes: the dispatching system receives loading and unloading task signals, the task flow is split, the dispatching system is used for planning a path, a card collecting running instruction is issued, a card collecting starts running, a card collecting arrives at a quay bridge, a card collecting starts aligning, a card collecting finishes, a card collecting starts to pack, a card collecting finishes packing, a card collecting starts running, a card collecting arrives at a storage yard, a card collecting starts aligning, a card collecting finishes, a card collecting starts to unload, a card collecting unloads a box and finishes, and the operation task is finished.
Further, the threshold value of the time consumption index of each operation flow link of the vehicle is 120% of the actual time consumption of each link.
Further, the system further comprises: and the display unit is used for performing visual presentation through the front end BI or the display screen.
Further, the data embedded point reporting unit reports embedded point data according to a periodic reporting or event triggering mode.
Further, the data embedded point reporting unit is further configured to upload the current event and the time data and the state data associated with the event when the state changes during the process of scheduling the vehicle operation by the scheduling system.
Furthermore, the data embedded point reporting unit is further used for reporting the automatic driving perception software data, the control software data, the planning software data and the positioning software data of the vehicle in a periodic mode in the running process of the vehicle.
Further, the data processing unit includes: the scheduling system buried point signal processing module is used for storing buried point data in a warehouse through receiving the buried point data in the vehicle operation process and calculating the time consumption of each link; the unmanned integrated card ad data processing module is used for identifying, diagnosing reasons and counting time consumption of abnormal events of the vehicle in the running process, and analyzing and counting abnormal behaviors of the vehicle in the running process and timely consuming the time.
The application provides a port operation abnormity diagnosis and analysis method applied to an unmanned collection card, which comprises the following steps: carrying out data embedding on automatic driving software, a dispatching system and port machine equipment to report embedded point data; receiving buried point data of automatic driving software, a dispatching system and port machine equipment through a network; storing embedded point data of automatic driving software, a dispatching system and port machine equipment, and forming a message queue; storing buried data in a storage manner, and carrying out anomaly identification on unmanned set card ad data; and carrying out fusion analysis on the data processing result according to a preset abnormality detection rule and a time-consuming index threshold value, and writing the analysis result into a database for visual presentation.
The invention provides a harbour operation abnormity diagnosis analysis system and method based on an unmanned integrated card, which are mainly used for solving the technical problems that the abnormal time-consuming links of the unmanned integrated card in the operation process cannot be analyzed and the reasons cannot be diagnosed in the prior art. According to the technical scheme, abnormal time consumption of the unmanned integrated circuit card in the operation process can be analyzed, and the reason analysis is carried out, so that operation developers are helped to quickly solve and locate relevant factors affecting operation, abnormal links and reasons of the time consumption of the operation are mastered, the operation developers can quickly locate and solve problems, and the operation efficiency of the unmanned integrated circuit card is improved.
Drawings
Fig. 1 is a schematic flow chart of a port operation abnormality diagnosis and analysis method applied to an unmanned integrated card;
fig. 2 is a schematic diagram of a port operation anomaly diagnosis and analysis system applied to an unmanned header card;
FIG. 3 is a schematic flow chart of another method for diagnosing and analyzing port operation anomalies applied to an unmanned integrated card;
FIGS. 4-6 are schematic flow diagrams of detecting and diagnosing an abnormal event by the data processing unit provided in the present application;
FIG. 7 is a schematic flow chart of the fusion analysis unit for performing operation diagnosis fusion analysis;
FIG. 8 is a schematic diagram of reporting buried point data on vehicle autopilot software provided by the present application;
fig. 9 is a schematic diagram of reporting buried point data on a scheduling system provided in the present application.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but 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.
Embodiment one:
the application provides a harbour operation abnormity diagnosis and analysis system and method based on an unmanned integrated card. As shown in fig. 1, the specific operation steps of the system are as follows.
S1: the data embedding point reporting unit is used for carrying out data embedding point on automatic driving software, a dispatching system and port machine equipment so as to report embedding point data;
s2: the data acquisition receiving unit receives buried point data of the automatic driving software, the dispatching system and the port machine equipment through a network;
s3: the real-time data storage unit stores the automatic driving software, the dispatching system and the buried point data of the port machine equipment and forms a message queue;
s4: the data processing unit performs storage of buried data according to the message queue, and performs anomaly identification on unmanned set card ad data;
s5: and the fusion analysis unit performs fusion analysis on the data processing result according to a preset abnormality detection rule and a time-consuming index threshold value, and writes the analysis result into a database for visual presentation.
According to the technical scheme, the data are buried at the automatic driving software, the dispatching system, the port machine equipment and the like, the buried data are stored by the data processing unit, the abnormality is identified, the time-consuming behavior and the reason are analyzed and associated by the final fusion analysis unit, and the analysis result is written into the database for visual presentation. The technical scheme can help operation developers to master and know time-consuming abnormal links and reasons of unmanned integrated circuit card operation, and can rapidly locate and solve problems, so that unmanned integrated circuit card operation efficiency is improved.
Embodiment two:
the application provides a harbour operation abnormity diagnosis and analysis system and method based on an unmanned integrated card, wherein the system comprises a data embedded point reporting unit, a data acquisition and receiving unit, a real-time data storage unit, a data processing unit, a fusion analysis unit, a back-end service unit and a display unit, as shown in fig. 2. The specific operation steps of the system are as follows, as shown in fig. 3.
S0: before diagnosis and analysis, the back-end service unit configures thresholds of time-consuming indexes of each operation flow link of the vehicle, and configures algorithm rules, abnormal reasons and solutions of common abnormal time-consuming behaviors in the operation process of the vehicle;
the vehicle that said in this application is unmanned collection card, and unmanned collection card refers to unmanned container truck, can be used to areas such as harbour, garden, mine, solves commodity circulation and the freight transportation in the limit scope. Each operation flow link of the unmanned integrated card comprises: the dispatching system receives loading and unloading task signals, split task flows, planning a dispatching system path, issuing a card collecting running instruction, starting running the card collecting, arriving at a quay bridge, starting aligning the card collecting, finishing aligning the card collecting, starting boxing the card collecting, finishing boxing the card collecting, starting running the card collecting, arriving at a storage yard, starting boxing the card collecting, finishing boxing the card collecting and finishing the operation task.
Before the technical scheme is implemented, the time-consuming index threshold value of each operation flow link is required to be configured through the back-end service unit. In general, the threshold value of the time consumption index of each operation flow link is set to be 120% of the actual time consumption of each link, and if the threshold value is exceeded, the abnormality is determined. For example, 100 seconds are actually taken for the unmanned set card to start aligning the operation flow link, and the unmanned set card is currently performing the operation flow link, but 121 seconds are taken, so that it can be determined that the unmanned set card is abnormal in the link and needs to be processed.
The link time elapsed time in the above refers to the average elapsed time. Because each link of the vehicle in the operation process is fixed, the method mainly comprises links of receiving tasks, issuing instructions, driving the vehicle to a destination, loading and unloading operations and the like, and operators count the normal actual time consumption of a plurality of operations, so that the average time consumption of each link is analyzed and analyzed.
The back-end service unit also needs to configure algorithm rules, exception reasons and solutions. The algorithm specification mainly includes detection rules and diagnostic rules for use by the subsequent data processing unit.
S1: the data embedding point reporting unit is used for carrying out data embedding point on automatic driving software, a dispatching system and port machine equipment so as to report embedding point data;
s2: the data acquisition receiving unit receives buried point data of the automatic driving software, the dispatching system and the port machine equipment through a network;
s3: the real-time data storage unit stores the automatic driving software, the dispatching system and the buried point data of the port machine equipment and forms a message queue;
s4: the data processing unit performs storage of buried data according to the message queue, and performs anomaly identification on unmanned set card ad data;
s5: the fusion analysis unit performs fusion analysis on the data processing results according to a preset abnormality detection rule and a time-consuming index threshold value, and writes the analysis results into a database for visual presentation;
s6: the display unit performs visual presentation through the front end BI or the display screen.
According to the technical scheme, the data are buried at the automatic driving software, the dispatching system, the port machine equipment and the like, the buried data are stored by the data processing unit, the abnormality is identified, the time-consuming behavior and the reason are analyzed and associated by the final fusion analysis unit, and the analysis result is written into the database for visual presentation. The technical scheme can help operation developers to master and know time-consuming abnormal links and reasons of unmanned integrated circuit card operation, and can rapidly locate and solve problems, so that unmanned integrated circuit card operation efficiency is improved.
Embodiment III:
the application provides a harbour operation abnormity diagnosis and analysis system and method based on an unmanned integrated card. As shown in fig. 1, the specific operation steps of the system are as follows.
S1: the data embedding point reporting unit is used for carrying out data embedding point on automatic driving software, a dispatching system and port machine equipment so as to report embedding point data;
the port machine equipment refers to various lifting equipment and loading and unloading machinery used in port and wharf facilities and is used for operations such as loading and unloading, stacking and transporting cargoes; a dispatch system refers to a software system for managing and distributing vehicles for transportation operations.
The reported buried data in this step includes: as shown in fig. 8, in the unmanned integrated card operation process, vehicle automatic driving perception software data, control software data, planning software data and positioning software data are reported in a periodic manner; as shown in fig. 9, in the process of scheduling the vehicle operation by the scheduling system, when the state changes, uploading the current event and the time data and the state data associated with the event; and reporting the operation data of the bridge crane and the field crane in the operation process of the port machine equipment. The data embedded point reporting unit generally reports to the data acquisition receiving unit in a periodic reporting or event triggering mode, wherein the data acquisition receiving unit is generally a data acquisition gateway.
S2: the data acquisition receiving unit receives buried point data of the automatic driving software, the dispatching system and the port machine equipment through a network;
s3: the real-time data storage unit stores the automatic driving software, the dispatching system and the buried point data of the port machine equipment and forms a message queue;
s4: the data processing unit performs storage of buried data according to the message queue, and performs anomaly identification on unmanned set card ad data;
s5: and the fusion analysis unit performs fusion analysis on the data processing result according to a preset abnormality detection rule and a time-consuming index threshold value, and writes the analysis result into a database for visual presentation.
According to the technical scheme, the data are buried at the automatic driving software, the dispatching system, the port machine equipment and the like, the buried data are stored by the data processing unit, the abnormality is identified, the time-consuming behavior and the reason are analyzed and associated by the final fusion analysis unit, and the analysis result is written into the database for visual presentation. The technical scheme can help operation developers to master and know time-consuming abnormal links and reasons of unmanned integrated circuit card operation, and can rapidly locate and solve problems, so that unmanned integrated circuit card operation efficiency is improved.
Embodiment four:
the application provides a harbour operation abnormity diagnosis and analysis system and method based on an unmanned integrated card. As shown in fig. 1, the specific operation steps of the system are as follows.
S1: the data embedding point reporting unit is used for carrying out data embedding point on automatic driving software, a dispatching system and port machine equipment so as to report embedding point data;
s2: the data acquisition receiving unit receives buried point data of the automatic driving software, the dispatching system and the port machine equipment through a network;
s3: the real-time data storage unit stores the automatic driving software, the dispatching system and the buried point data of the port machine equipment and forms a message queue;
s4: the data processing unit performs storage of buried data according to the message queue, and performs anomaly identification on unmanned set card ad data;
the data processing unit mainly comprises a scheduling system embedded point signal processing module and an unmanned set card ad data processing module. The scheduling system embedded point signal processing module is used for storing embedded point data in a warehouse through receiving the embedded point data in the vehicle operation process and calculating the time consumption of each link; the unmanned integrated card ad data processing module is used for identifying, diagnosing reasons and counting time consumption of abnormal events of the vehicle in the running process, and analyzing and counting abnormal behaviors of the vehicle in the running process and timely consuming the time. The embedded point signal processing module of the dispatching system mainly refers to an embedded point signal processing engine of the dispatching system, and the unmanned set card ad data processing module mainly refers to an ad data processing engine.
As shown in fig. 4-6, abnormal events in the vehicle during operation include sudden stop, job waiting, congestion, etc. The data processing unit needs to identify the situations, for example, according to the output data of the central control module in the ad data and preset detection rules and diagnosis rules, detecting and diagnosing various abnormal situations of the unmanned vehicle caused by factors such as environment, software, a vehicle collecting chassis and the like in the driving process, wherein the abnormal situations are caused by the sudden stop and the stagnation of the vehicle; for another example, the data processing unit identifies the situation that the vehicle waits at the port machine equipment all the time due to the reasons of port machine faults, human factors and the like in the process of loading and unloading operation of the unmanned integrated card by judging the data fusion analysis of the running state, the operation area, the port machine state and the like of the vehicle, records the abnormal reasons, and facilitates the follow-up tracing and the overall analysis; for example, the vehicles cannot normally run due to the fact that multiple vehicles possibly jam at an intersection and the like in the running process of the collector card, the data quantity unit judges whether the end vehicles jam or not through preset detection rules and the combination of ad data, judges whether the dispatching system sends dispatching information and the like for effectively eliminating jam or not through preset diagnosis rules to judge whether the dispatching system is caused by improper dispatching of the vehicles, records jam time and facilitates the follow-up examination of a problem module and the diagnosis of operation efficiency.
The ad data (Auto Driving Data, autopilot data) is result data which is output by each module of the autopilot software in the operation process, such as sensing, planning, controlling, positioning and the like. The unmanned set card ad data is the automatic driving data of the unmanned set card. The preset detection rules and the diagnosis rules are all set by the back-end service unit.
S5: and the fusion analysis unit performs fusion analysis on the data processing result according to a preset abnormality detection rule and a time-consuming index threshold value, and writes the analysis result into a database for visual presentation.
The abnormality detection rule and the abnormality time-consuming threshold are set in advance by the back-end service unit before performing the job abnormality diagnostic analysis. As shown in fig. 7, the fusion analysis herein mainly refers to performing anomaly detection by using the unmanned set card ad data and the buried data of the anomaly identified in step S4, if a related time-consuming anomaly occurs in the operation process, extracting an anomaly type, an anomaly time-consuming cause and a time-consuming source system by using the task name, time and vehicle number to correlate and schedule the buried data processing result, and outputting the correlated result. If the time consumption of the vehicle is abnormal, the abnormal event, the abnormal reason, the time consumption and the like in the running process of the vehicle are found out and recorded through the output result of the ad data processing engine associated with the information such as the vehicle number, the task name, the time and the like. And finally, the diagnosis fusion analysis engine correlates the abnormal time-consuming links in each operation flow with the vehicle ad data processing result and the scheduling buried point signal processing result to obtain the time-consuming and abnormal time-consuming links, the source system, the time-consuming reasons and the like of the operation flow, so that operation developers can conveniently find problem blocking points, comprehensively analyze problem sources affecting the operation efficiency, and assist on-site personnel to solve the problems, thereby improving the overall operation efficiency. The fusion analysis unit is mainly referred to as a job diagnosis analysis engine.
According to the technical scheme, the data are buried at the automatic driving software, the dispatching system, the port machine equipment and the like, the buried data are stored by the data processing unit, the abnormality is identified, the time-consuming behavior and the reason are analyzed and associated by the final fusion analysis unit, and the analysis result is written into the database for visual presentation. Unmanned integrated circuit is in unmanned operation entirely, and the efficiency in the operation in-process depends on a plurality of factors such as port machine, vehicle chassis stability, autopilot software, and current integrated circuit can appear various unusual circumstances in the operation in-process, leads to whole operation comparatively consuming time, influences whole operating efficiency, if through the time consuming condition of manual monitoring every platform truck, can cause a large amount of manpower resources to consume. Therefore, the method is very important for identifying and diagnosing abnormal time consumption of the vehicle in various operation processes, time-consuming links and problem reasons in the operation process can be automatically analyzed through a platform means, operation developers can be helped to quickly find time-consuming reasons and time-consuming modules in the operation process, the problems can be targeted and positioned, the integrated card is helped to improve the overall operation efficiency, the operation income is increased, and the labor input cost of development and operation is reduced. The technical scheme can help operation developers to master and know time-consuming abnormal links and reasons of unmanned integrated circuit card operation, and can rapidly locate and solve problems, so that unmanned integrated circuit card operation efficiency is improved.
In summary, the embodiment of the invention provides a port operation abnormality diagnosis analysis system and method applied to an unmanned set card, which are used for solving the technical problem that the operation abnormality diagnosis analysis cannot be performed on the unmanned set card in the prior art. According to the technical scheme, buried point data can be collected, processed and analyzed, and the data is visually displayed, so that operation manager can timely grasp operation abnormal conditions, quickly locate and solve problems, and further unmanned integrated card operation efficiency is provided.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather to enable any modification, equivalent replacement, improvement or the like to be made within the spirit and principles of the invention.

Claims (10)

1. A port operation anomaly diagnostic analysis system for an unmanned header card, the system comprising:
the data embedding point reporting unit is used for carrying out data embedding points on automatic driving software, a dispatching system and port machine equipment to report embedding point data;
the data acquisition and receiving unit is used for receiving buried point data of automatic driving software, a dispatching system and port machine equipment through a network;
the real-time data storage unit is used for storing the automatic driving software, the dispatching system and the buried point data of the port machine equipment and forming a message queue;
the data processing unit is used for storing buried data in a storage manner according to the message queue and carrying out anomaly identification on unmanned set card ad data;
and the fusion analysis unit is used for carrying out fusion analysis on the data processing result according to a preset abnormality detection rule and a time-consuming index threshold value, and writing the analysis result into a database for visual presentation.
2. The unmanned header card-based port operation anomaly diagnostic analysis system of claim 1, further comprising:
the back-end service unit is used for configuring thresholds of time-consuming indexes of each operation flow link of the vehicle and algorithm rules, abnormality reasons and solutions of common abnormal time-consuming behaviors in the operation process of the vehicle before diagnosis and analysis.
3. The system for diagnosing and analyzing port operation abnormality based on unmanned set card according to claim 2, wherein the operation procedure links include: the dispatching system receives loading and unloading task signals, the task flow is split, the dispatching system is used for planning a path, a card collecting running instruction is issued, a card collecting starts running, a card collecting arrives at a quay bridge, a card collecting starts aligning, a card collecting finishes, a card collecting starts to pack, a card collecting finishes packing, a card collecting starts running, a card collecting arrives at a storage yard, a card collecting starts aligning, a card collecting finishes, a card collecting starts to unload, a card collecting unloads a box and finishes, and the operation task is finished.
4. The harbour operation abnormity diagnosis and analysis system based on the unmanned integrated card as claimed in claim 2, wherein the threshold value of the time consumption index of each operation flow link of the vehicle is 120% of the actual time consumption of each link.
5. The unmanned header card-based port operation anomaly diagnostic analysis system of claim 1, further comprising:
and the display unit is used for performing visual presentation through the front end BI or the display screen.
6. The port operation anomaly diagnostic analysis system based on the unmanned integrated card according to claim 1, wherein the data embedded point reporting unit reports embedded point data according to a periodic reporting or event triggering mode.
7. The system for diagnosing and analyzing port operation anomalies based on unmanned set card as recited in claim 1, wherein the data embedded point reporting unit is further configured to upload the current event and the time data and the state data associated with the event when the state changes during the operation of the dispatching system dispatching the vehicle.
8. The port operation anomaly diagnostic analysis system based on the unmanned integrated card according to claim 1, wherein the data embedded point reporting unit is further used for reporting the automatic driving perception software data, the control software data, the planning software data and the positioning software data of the vehicle in a periodic manner during the running process of the vehicle.
9. The port work abnormality diagnosis and analysis system applied to an unmanned header card according to claim 1, wherein the data processing unit comprises:
the scheduling system buried point signal processing module is used for storing buried point data in a warehouse through receiving the buried point data in the vehicle operation process and calculating the time consumption of each link;
the unmanned integrated card ad data processing module is used for identifying, diagnosing reasons and counting time consumption of abnormal events of the vehicle in the running process, and analyzing and counting abnormal behaviors of the vehicle in the running process and timely consuming the time.
10. The port operation abnormity diagnosis and analysis method applied to the unmanned integrated card is characterized by comprising the following steps of:
carrying out data embedding on automatic driving software, a dispatching system and port machine equipment to report embedded point data;
receiving buried point data of automatic driving software, a dispatching system and port machine equipment through a network;
storing embedded point data of automatic driving software, a dispatching system and port machine equipment, and forming a message queue;
storing buried data in a storage manner, and carrying out anomaly identification on unmanned set card ad data;
and carrying out fusion analysis on the data processing result according to a preset abnormality detection rule and a time-consuming index threshold value, and writing the analysis result into a database for visual presentation.
CN202311326904.9A 2023-10-13 2023-10-13 Port operation abnormity diagnosis and analysis system and method based on unmanned integrated card Pending CN117572897A (en)

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