An Intelligent Fault Diagnosis Method for Street Lamps

Abstract

The invention discloses a street lamp intelligent fault diagnosis method. A narrow band Internet of Things (IoT) module embedded with an illuminance sensor is installed at a light source of each street lamp, and each narrow band IoT module is numbered. Each illuminance sensor measures the illuminance at the corresponding narrow band IoT module, and uploads the collected illuminance data to a server to construct an illuminance database. A normal illuminance data set is selected from the illuminance database as a training data set, and a machine learning method is used for pattern learning of an illuminance sequence to construct a street lamp turn-on model. On the basis of the street lamp turn-on model, the real-time illuminance sampling data sequence is processed to realize the fault diagnosis and fault type diagnosis of a single street lamp and a lamp group. Also, the machine learning method is used for updating the street lamp turn-on model. According to the invention, the faults of the single lamp and the lamp group can be automatically detected in time without breaking the line, the fault types can be determined and fed back to working staff, and the intelligent diagnosis of the street lamp faults is realized.

Description

technical field [0001] The invention relates to a fault diagnosis method, in particular to an intelligent fault diagnosis method for street lamps. It belongs to the field of intelligent lighting technology. Background technique [0002] With the development of the economy and the continuous improvement of public infrastructure, street lights, as an important public infrastructure, are increasingly playing an indispensable role in people's lives. However, due to natural or man-made factors, urban street lamps often have failures such as lamp damage and line damage. If these failures cannot be found and repaired in time, it will bring great inconvenience to people's lives, and will also increase the frequency of traffic accidents. [0003] The existing street lamp fault diagnosis method has the following problems: [0004] (1) The existing non-informationized street lamp fault diagnosis method is mainly based on current or voltage, which needs to break the existing line and...

AI Technical Summary

Problems solved by technology

[0004] (1) The existing non-informationized street lamp fault diagnosis method is mainly based on current or voltage, which needs to be broken and reconstructed on existing lines, and cannot identify the situation where the luminous flux of the lamp is attenuated but not completely damaged

In addition, the diagnosis is mainly for a single street light, and it cannot diagnose the failure of the light group caused by the local route.

[0005] (2) Existing information-based street lamp management systems, such as "A Smart Street Light System for the Internet of Things (Application Number: 201610041523.X)" need to use a single-lamp control box, which still needs to be modified on the basis of the original circuit. Moreover, many devices are used and the structure is complex, which makes the cost relatively high

In addition, it can only realize street lamp information collection based on the Internet of Things, and does not give a specific method to use illuminance data to diagnose street lamp faults

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