Aerial display equipment fault detection method based on convolutional neural network and monitoring device

Abstract

The invention discloses an aerial display equipment fault detection method based on a convolutional neural network and a monitoring device, and the method comprises the following steps: 1, collectingan interface of aerial display equipment, and carrying out the pre-classification of a display interface; 2, designing a semantic comprehension model, constructing a convolutional neural network, andcarrying out semantic comprehension on a display interface of the aerial display equipment; 3, classifying the interfaces under the abnormal condition; 4, performing semantic understanding on the normally displayed aerial display interface, and detecting whether a fault occurs or not; 5, analyzing symbols and icons which cannot be understood; 6, sending the fault detection picture in combination with semantic comprehension information to a convolutional neural network for feature extraction and training; 7, optimizing and compressing the CNN fault classifier, and implanting the CNN fault classifier into SOM-RK3399 embedded equipment to obtain an aerial display monitoring device; and 8, enabling the monitoring device to collect an output signal of the aerial display device, form a display picture, send the display picture to the CNN processing module, and detect whether the aerial display device is in a normal working state.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a fault detection method and a monitoring device for aerial display equipment based on a convolutional neural network. Background technique [0002] With the increasing demand for air travel and the gradual improvement of travel standards, more and more airports have begun to implement "paperless" travel. Full-process self-service; in addition, the terminal display system is responsible for providing passengers with comprehensive information guidance, which is used to provide passengers with flight information, announcement information, service information, etc. The increase of aerial display equipment is also accompanied by problems such as display equipment failure. The failure of the aerial display equipment not only directly affects the timeliness and accuracy of the information provided by the aerial display system, but also brings great inconvenience t...

AI Technical Summary

Problems solved by technology

[0003] Traditional aerial display equipment fault detection mostly adopts manual inspection, but manual inspection has disadvantages such as low inspection frequency, poor inspection effect, and high labor cost.

Due to limited technology, in the past, the intelligent detection of the faults of aerial display equipment relied on the establishment of a standard database, the content was updated slowly, and the maintenance cost was high; the feature point comparison technology was used to compare the standard aerial display pictures and the aerial display pictures to be tested in the database. Comparison to detect the status of the display screen, this detection method cannot adapt to the growing demand and diverse display interface use cases

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