Remote monitoring and maintenance system for wrapping robot

Abstract

The invention discloses a wrapping robot remote monitoring and maintenance system, which comprises a master control terminal, and the master control terminal is connected with an automatic operation and maintenance unit which manages and configures software and environment of a remote robot by using automatic operation and maintenance tools such as Ansible, Chef or Puppet, realizes automatic deployment, configuration management and software updating tasks, and realizes remote monitoring and maintenance of the wrapping robot. The stability and maintainability of the system are improved; the remote log and exception monitoring unit is integrated with an ELK Stack, namely, an Elasticsearch log management system, a Logstash log management system and a Kibana log management system; according to the design of the invention, by combining the Internet of Things technology, remote monitoring of the wrapping robot is realized, all real scene monitoring is realized by adopting a video stream mode, once faults or abnormities occur, rapid diagnosis and analysis can be realized, the maintenance cost can be reduced, and an efficient, stable and easy-to-maintain robot remote monitoring and maintenance system is constructed, so that the maintenance efficiency of the wrapping robot is improved. And the system has relatively high reliability and management efficiency, and makes up for the defect that the existing wrapping robot is insufficient in self-monitoring during use.

Description

Technical Field

[0001] The invention belongs to the technical field of wrapping robots, and in particular relates to a remote monitoring and maintenance system for wrapping robots. Background Art

[0002] With the development of domestic urbanization, underground cables have become one of the main forms of power transmission. However, the current cable joint failure rate is relatively high. The current cable joint construction method is time-consuming and complex, and it is impossible to reduce manual participation, which has a great impact on the laying efficiency. The wrapping robot can replace manual labor, realize the standardization of key technologies, ensure the accuracy of cable pre-processing dimensions, and improve the pre-processing quality of wrapping insulating tapes. In order to ensure the normal operation of the wrapping robot, real-time monitoring is required through a special remote monitoring and maintenance system.

[0003] At present, the systems used in wrapping robots are mainly focused on the operation process and operation result detection of cable joints, while the function of monitoring the operation status of the wrapping robots themselves is single, and they can only monitor basic quantities such as power, working speed, working time, etc. Not only can they not conduct in-depth detection of the actual status of the wrapping robots, but the detection results cannot be viewed remotely. There are major deficiencies in the unified management of wrapping robots, so there is room for improvement. Summary of the invention

[0004] The purpose of the present invention is to provide a remote monitoring and maintenance system for a wrapping robot, so as to solve the problem mentioned in the above background technology that the existing wrapping robots do not have the functions of in-depth detection of their own working status and remote unified management.

[0005] To achieve the above object, the present invention provides the following technical solution: a remote monitoring and maintenance system for a wrapping robot, comprising a main control terminal, to which is connected: Automated operation and maintenance units, which use automated operation and maintenance tools such as Ansible, Chef, or Puppet to manage and configure the software and environment of remote robots, implement automated deployment, configuration management, and software update tasks, and improve system stability and maintainability; Remote log and exception monitoring unit, integrated with ELK Stack (Elasticsearch, Logstash, Kibana) log management system, real-time monitoring and analysis of robot operation logs; and use Sentry or Rollbar to capture and analyze errors in exception monitoring; Remote control unit, used to remotely access and control the robot system. Using tools like ngrok, you can safely expose the local server in the intranet environment to facilitate remote debugging and access. Remote hardware control unit, used to manage and control IoT devices, integrates remote switches, sensor data collection and control, ensures that each component of the robot can be remotely operated and monitored, and can use remote IoT platforms such as AWS IoT and Azure IoT Hub; Real-time video stream monitoring unit, which uses WebRTC's video stream processing and display tools to integrate real-time video stream monitoring, and uses the OpenCV computer vision library to implement video stream processing and analysis, such as object detection, motion tracking and other functions; The alarm effect unit monitors and promptly responds to abnormal conditions in the wrapping process, implements an automated emergency response process, and ensures that the system recovers quickly or notifies relevant personnel when a failure or abnormal condition occurs.

[0006] As a preferred technical solution in the present invention, the real-time video stream monitoring unit includes: The high-precision comparison module extracts non-standard conditions in the wrapping process based on the data information in the video stream and compares them with the previously entered standard data; Video stream encoder, which provides efficient video encoding and decoding technologies, including H.264 and H.265 / HEVC, to ensure the transmission and processing of high-quality video streams under limited bandwidth; The data visualization feedback module displays the video stream monitoring data on the visualization device, so that the operation and maintenance personnel and security personnel can instantly view the analysis results and alarm information of the video stream; Distributed real-time processing module, used to process, analyze, and store data streams.

[0007] As a preferred technical solution in the present invention, the high-precision comparison module is connected to an Internet of Things module, which is used to automatically obtain the latest standard data of wrapping operations from the Internet and transmit it to the high-precision comparison module to ensure that the comparison method of the high-precision comparison module is in the latest standard.

[0008] As a preferred technical solution in the present invention, the high-precision comparison module includes: The computer vision algorithm submodule integrates computer vision technology through a deep learning model, where the deep learning model uses a neural network-based object detection and tracking algorithm to achieve object recognition, tracking, and comparative analysis in video streams; The object recognition and classification submodule uses object recognition technologies, such as YOLO and SSD, to identify specific objects or behaviors in the video stream and perform real-time classification and analysis.

[0009] As a preferred technical solution in the present invention, the distributed real-time processing module includes: The streaming data processing submodule uses Apache Kafka and Apache Flink streaming data processing platforms to support the processing and analysis of real-time data streams, ensuring low latency and high throughput; The distributed computing storage submodule is used to store and process video stream data in shards to cope with large-scale data volumes and complex analysis requirements.

[0010] As a preferred technical solution in the present invention, the automated operation and maintenance unit includes: Containerized management platform, used to achieve standardized packaging and deployment of applications, simplifying environment configuration and expansion management; The automated alarm module automatically generates alarms based on pre-set monitoring indicators and integrates alarm notifications into the communication platform so that the operation and maintenance team can respond and handle problems in a timely manner. Log collection and analysis module, set up automatic detection of log anomalies and errors, and notify relevant teams through the alert notification system; Automated testing validates modules, performs end-to-end testing and integration testing, and verifies application functionality and performance.

[0011] As a preferred technical solution in the present invention, the automatic operation and maintenance unit is automatically started when the main control terminal does not respond or cannot contact the wrapping robot.

[0012] As a preferred technical solution in the present invention, the containerized management platform uses Docker or Kubernetes, and the configuration management tools include Ansible, Chef, and Puppet.

[0013] As a preferred technical solution in the present invention, the computer vision algorithm submodule is composed of the following core components: Image acquisition, responsible for collecting image and video data and converting them into digital signals; Image preprocessing, responsible for preprocessing the collected image data to improve image quality and recognition rate; Feature extraction: extracting effective feature information from preprocessed image data for subsequent image recognition and classification; Image recognition, responsible for classifying and identifying the extracted feature information; Decision-making and judgment: Make decisions and judgments based on the recognition results to realize automatic analysis and processing of image data.

[0014] As a preferred technical solution in the present invention, the feature extraction in the computer vision algorithm submodule mainly adopts local binary pattern, directional gradient histogram and convolutional neural network algorithm.

[0015] Compared with the prior art, the present invention has the following beneficial effects: Through the design of the present invention, combined with the Internet of Things technology, remote monitoring of the wrapping robot is realized, and full real-scene monitoring is achieved by using video streaming. Once a fault or abnormality occurs, it can be quickly diagnosed and analyzed to reduce maintenance costs, and build an efficient, stable and easy-to-maintain robot remote monitoring and maintenance system. The system has high reliability and management efficiency, which makes up for the defect of insufficient self-monitoring of existing wrapping robots during use. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a system diagram of the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] See also Figure 1 The present invention provides a technical solution: a remote monitoring and maintenance system for a wrapping robot, comprising a main control terminal, to which is connected: Automated operation and maintenance units, which use automated operation and maintenance tools such as Ansible, Chef, or Puppet to manage and configure the software and environment of remote robots, implement automated deployment, configuration management, and software update tasks, and improve system stability and maintainability; Remote log and exception monitoring unit, integrated with ELK Stack (Elasticsearch, Logstash, Kibana) log management system, real-time monitoring and analysis of robot operation logs; and use Sentry or Rollbar to capture and analyze errors in exception monitoring; Remote control unit, used to remotely access and control the robot system. Using tools like ngrok, you can safely expose the local server in the intranet environment to facilitate remote debugging and access. Remote hardware control unit, used to manage and control IoT devices, integrates remote switches, sensor data collection and control, ensures that each component of the robot can be remotely operated and monitored, and can use remote IoT platforms such as AWS IoT and Azure IoT Hub; Real-time video stream monitoring unit, which uses WebRTC's video stream processing and display tools to integrate real-time video stream monitoring, and uses the OpenCV computer vision library to implement video stream processing and analysis, such as object detection, motion tracking and other functions; The alarm effect unit monitors and promptly responds to abnormal conditions in the wrapping process, implements an automated emergency response process, and ensures that the system recovers quickly or notifies relevant personnel when a failure or abnormal condition occurs.

[0019] In this embodiment, the real-time video stream monitoring unit includes: The high-precision comparison module extracts non-standard conditions in the wrapping process based on the data information in the video stream and compares them with the previously entered standard data; Video stream encoder, which provides efficient video encoding and decoding technologies, including H.264 and H.265 / HEVC, to ensure the transmission and processing of high-quality video streams under limited bandwidth; The data visualization feedback module displays the video stream monitoring data on the visualization device, so that the operation and maintenance personnel and security personnel can instantly view the analysis results and alarm information of the video stream; Distributed real-time processing module, used to process, analyze, and store data streams.

[0020] In this embodiment, the high-precision comparison module is connected to an Internet of Things module, which is used to automatically obtain the latest standard data of wrapping operations from the Internet and transmit it to the high-precision comparison module to ensure that the comparison method of the high-precision comparison module is in the latest standard.

[0021] In this embodiment, the high-precision comparison module includes: The computer vision algorithm submodule integrates computer vision technology through a deep learning model, where the deep learning model uses a neural network-based object detection and tracking algorithm to achieve object recognition, tracking, and comparative analysis in video streams; The object recognition and classification submodule uses object recognition technologies, such as YOLO and SSD, to identify specific objects or behaviors in the video stream and perform real-time classification and analysis.

[0022] In this embodiment, the distributed real-time processing module includes: The streaming data processing submodule uses Apache Kafka and Apache Flink streaming data processing platforms to support the processing and analysis of real-time data streams, ensuring low latency and high throughput; The distributed computing storage submodule is used to store and process video stream data in shards to cope with large-scale data volumes and complex analysis requirements.

[0023] In this embodiment, the automated operation and maintenance unit includes: Containerized management platform, used to achieve standardized packaging and deployment of applications, simplifying environment configuration and expansion management; The automated alarm module automatically generates alarms based on pre-set monitoring indicators and integrates alarm notifications into the communication platform so that the operation and maintenance team can respond and handle problems in a timely manner. Log collection and analysis module, set up automatic detection of log anomalies and errors, and notify relevant teams through the alert notification system; Automated testing validates modules, performs end-to-end testing and integration testing, and verifies application functionality and performance.

[0024] In this embodiment, the automatic operation and maintenance unit is automatically started when the main control terminal does not respond or cannot contact the wrapping robot.

[0025] In this embodiment, the container management platform uses Docker or Kubernetes, and the configuration management tools include Ansible, Chef, and Puppet.

[0026] As a preferred technical solution in the present invention, the computer vision algorithm submodule is composed of the following core components: Image acquisition is responsible for collecting image and video data and converting them into digital signals, including cameras, lenses, light source hardware equipment, and digital signal processing equipment such as acquisition cards and interface cards. The image acquisition module collects image or video data from external sensors or other sources into the computer; Image preprocessing is responsible for preprocessing the collected image data to improve image quality and recognition rate, including image enhancement, filtering, denoising, edge detection and other algorithms. The preprocessing module processes the collected images, including image enhancement, grayscale, morphological processing, etc., to better perform subsequent processing; Feature extraction: extracting effective feature information from preprocessed image data for subsequent image recognition and classification; Image recognition is responsible for classifying and identifying the extracted feature information, including support vector machine (SVM), artificial neural network (ANN), convolutional neural network (CNN) and other algorithms. The image recognition module is used to detect and identify target objects in images or videos, usually including homography matrix estimation, color analysis, edge detection and other algorithms; Decision-making and judgment, making decisions and judgments based on the recognition results to realize automatic analysis and processing of image data. Decision-making and judgment is the last hope in the machine vision system. It is mainly responsible for making decisions and judgments based on the recognition results to realize automatic analysis and processing of image data.

[0027] As a preferred technical solution in the present invention, the feature extraction in the computer vision algorithm submodule mainly adopts local binary pattern, directional gradient histogram and convolutional neural network algorithm.

[0028] Although embodiments of the present invention have been shown and described (see the above detailed description for details), it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. The remote monitoring and maintenance system of the wrapping robot includes a main control terminal, which is characterized by: The main control terminal is connected with: The automated operation and maintenance unit manages and configures the software and environment of the remote robot by using automated operation and maintenance tools to achieve automated deployment, configuration management, and software update tasks; Remote log and exception monitoring unit, integrated with ELK Stack log management system, real-time monitoring and analysis of robot operation logs; and use Sentry or Rollbar to capture and analyze errors in exception monitoring; Remote control unit for remote access and control of the robot system; Remote hardware control unit, used to manage and control IoT devices, integrates remote switches, sensor data collection and control, and ensures that various components of the robot can be remotely operated and monitored; Real-time video stream monitoring unit, which uses WebRTC's video stream processing and display tools to integrate real-time video stream monitoring, and uses the OpenCV computer vision library to process and analyze video streams; The alarm effect unit monitors and promptly responds to abnormal conditions in the wrapping process, implements an automated emergency response process, and ensures that the system recovers quickly or notifies relevant personnel when a failure or abnormal condition occurs.

2. The remote monitoring and maintenance system for a wrapping robot according to claim 1, characterized in that: The real-time video stream monitoring unit comprises: The high-precision comparison module extracts non-standard conditions in the wrapping process based on the data information in the video stream and compares them with the previously entered standard data; Video stream encoder, which provides efficient video encoding and decoding technology to ensure the transmission and processing of high-quality video streams under limited bandwidth; The data visualization feedback module displays the video stream monitoring data on the visualization device, so that the operation and maintenance personnel and security personnel can instantly view the analysis results and alarm information of the video stream; Distributed real-time processing module, used to process, analyze, and store data streams.

3. The remote monitoring and maintenance system for a wrapping robot according to claim 2 is characterized in that: The high-precision comparison module is connected to an Internet of Things module, which is used to automatically obtain the latest standard data of wrapping operations from the Internet and transmit it to the high-precision comparison module to ensure that the comparison method of the high-precision comparison module is in the latest standard.

4. The remote monitoring and maintenance system for a wrapping robot according to claim 3 is characterized in that: The high-precision comparison module includes: The computer vision algorithm submodule integrates computer vision technology through deep learning models to achieve target recognition, tracking, and comparative analysis in video streams; The object recognition and classification submodule uses object recognition technology to identify specific objects or behaviors in the video stream and perform real-time classification and analysis.

5. The remote monitoring and maintenance system for a wrapping robot according to claim 2, characterized in that: The distributed real-time processing module includes: The streaming data processing submodule uses a streaming data processing platform to support the processing and analysis of real-time data streams, ensuring low latency and high throughput; The distributed computing storage submodule is used to store and process video stream data in shards to cope with large-scale data volumes and complex analysis requirements.

6. The remote monitoring and maintenance system for a wrapping robot according to claim 1, characterized in that: The automated operation and maintenance unit comprises: Containerized management platform, used to achieve standardized packaging and deployment of applications, simplifying environment configuration and expansion management; The automated alarm module automatically generates alarms based on pre-set monitoring indicators and integrates alarm notifications into the communication platform so that the operation and maintenance team can respond and handle problems in a timely manner. Log collection and analysis module, set up automatic detection of log anomalies and errors, and notify relevant teams through the alert notification system; Automated testing validates modules, performs end-to-end testing and integration testing, and verifies application functionality and performance.

7. The remote monitoring and maintenance system for a wrapping robot according to claim 6, characterized in that: The automatic operation and maintenance unit is automatically started when the main control terminal does not respond or cannot contact the wrapping robot.

8. The remote monitoring and maintenance system for a wrapping robot according to claim 6, characterized in that: The containerized management platform uses Docker or Kubernetes, and the configuration management tools include Ansible, Chef, and Puppet.

9. The remote monitoring and maintenance system for a wrapping robot according to claim 4, characterized in that: The computer vision algorithm submodule consists of the following core components: Image acquisition, responsible for collecting image and video data and converting them into digital signals; Image preprocessing, responsible for preprocessing the collected image data to improve image quality and recognition rate; Feature extraction: extracting effective feature information from preprocessed image data for subsequent image recognition and classification; Image recognition, responsible for classifying and identifying the extracted feature information; Decision-making and judgment: Make decisions and judgments based on the recognition results to realize automatic analysis and processing of image data.

10. The remote monitoring and maintenance system for a wrapping robot according to claim 9, characterized in that: The feature extraction in the computer vision algorithm submodule mainly adopts local binary pattern, oriented gradient histogram and convolutional neural network algorithms.

Images