Drone Inspection of Port Machinery for Blind-Spot Defect Detection

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Solution Overview

Problem

Current manual inspection methods for port machinery are inefficient, pose high safety risks, and have blind spots due to the large size and corrosive environment of port machinery, making it difficult for inspectors to access and photograph all areas effectively.

Innovation Solution

An inspection technology utilizing drones equipped with ground locators, a ground monitoring and processing device, and a data management and evaluation device that automatically plans and executes inspection routes, performs aerial photography, and analyzes structural defects, providing comprehensive evaluation results.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual inspection methods are used, then inspectors can directly observe and evaluate structural defects, but inspectors face high safety risks and cannot access all areas due to the large size and corrosive environment of port machinery

Engineering Contradiction:
Improveinspection safetyVSAvoidaccessibility to inspection areas
Core Design Contradiction:
ReliabilityVSEase of operation

Solution Approach 1:

The patent introduces drones as intermediary inspection devices that can access hazardous and hard-to-reach areas without exposing human inspectors to safety risks. The drones carry cameras and sensors to capture images and data from all inspection areas, including corrosive environments and high locations, thereby resolving the contradiction between inspection safety and accessibility.

Inventive Principle:
Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent replaces the mechanical system of human inspectors physically climbing and accessing port machinery with an automated drone system equipped with imaging and sensing devices. This substitution eliminates the safety risks associated with manual inspection while maintaining comprehensive inspection coverage through automated navigation and data collection.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If manual inspection methods are used, then inspectors can take pictures and draft evaluation reports, but the detection cycle is long and detection results have many blind spots

Engineering Contradiction:
Improveinspection efficiencyVSAvoiddetection coverage
Core Design Contradiction:
ProductivityVSMeasurement precision

Solution Approach 1:

The patent implements continuous automated inspection through drones that can continuously capture images and data along pre-planned routes without interruption. The system processes images in real-time and generates evaluation reports automatically, eliminating the discontinuous nature of manual inspection and reducing detection cycles while ensuring comprehensive coverage without blind spots.

Inventive Principle:
Principle #20Continuity of useful action

Solution Approach 2:

The patent enables the inspection system to perform self-service through automated route planning, autonomous drone navigation, automatic image processing, and automated report generation. The system independently completes the entire inspection workflow without continuous human intervention, thereby improving inspection efficiency and eliminating detection blind spots through systematic automated procedures.

Inventive Principle:
Principle #25Self-service

3Measurement precision

If manual inspection methods are used, then inspectors can evaluate structural health, but the process is inefficient and has long detection cycles

Engineering Contradiction:
Improvestructural defect identification accuracyVSAvoiddetection cycle time
Core Design Contradiction:
Measurement precisionVSLoss of time

Solution Approach 1:

The patent applies preliminary action by pre-planning inspection routes, pre-positioning drones, and pre-processing images using automated algorithms before final evaluation. The system prepares inspection paths in advance, automatically navigates drones along these paths, and pre-processes captured images to identify potential defects, thereby reducing the overall detection cycle time while maintaining high accuracy in structural defect identification.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The patent implements feedback mechanisms where inspection results are automatically analyzed and fed back into the system for continuous improvement. The automated image processing algorithms provide real-time feedback on detected defects, and the system uses this feedback to refine its inspection processes and improve detection accuracy while reducing the time required for manual evaluation cycles.

Inventive Principle:
Principle #23Feedback

Data Source

PatentEP3680648B1Port machinery inspection device and inspection method
Publication Date: 2023.07.19 SHANGHAI ZHENHUA HEAVY IND
  • EP3680648B1 patent drawingFigure 1
  • EP3680648B1 patent drawingFigure 2
  • EP3680648B1 patent drawingFigure 3

AI summary

The present invention discloses an inspection apparatus for port machinery, which includes: a group of drones (101), a group of ground locators (102), a ground monitoring and processing device (103), and a data management and evaluation device (104). The drones conduct inspections of a port machinery to obtain images of the port machinery. The ground locator locates the three-dimensional position of the drone. The ground monitoring and processing device communicates with the drone and the ground locator. The ground monitoring and processing device (103) controls the flight of the drone, receives the images acquired by the drone, and monitors the status of the drone. The data management and evaluation device (104) communicates with the ground monitoring and processing device (103). The data management and evaluation device (104) stores the basic data of the port machinery. The data management and evaluation device receives the images from the ground monitoring and processing device, performs disease identification and disease analysis according to the images and generates evaluation results based on the disease identification and disease analysis.