Non-contact leakage detection device and method for lead-acid battery based on machine learning

Abstract

The invention discloses a non-contact liquid leakage detection device and method for a lead-acid storage battery based on machine learning, which belongs to the field of battery detection. The device includes a frame, and an image processor installed on the frame is connected with an infrared camera, a vertical rotation motor and a horizontal rotation motor, and controls their operation. The method includes the following steps: 1) adjusting the angle of the infrared camera on the rack to align with the lead-acid battery; 2) controlling the infrared camera to collect multiple images through an image processor; Denoising; 4) Identify the leaking area in the image in step 3); 5) Mark the leaking area in step 4). The invention adopts a non-contact method to detect liquid leakage, and the detection speed is fast, stable and efficient; the invention adopts machine learning logic regression and linear regression algorithms to judge the leakage state and identify the leakage area, and the recognition rate is high; the invention has low cost and is easy to install. The construction is simple and the application range is wide.

Description

technical field [0001] The invention relates to the field of battery detection, in particular to a non-contact leakage detection method for lead-acid storage batteries based on machine learning. Background technique [0002] With the development of society and the advancement of science and technology, reserve power has become a very important part of daily life and production. Reserve power can be divided into button batteries, dry batteries, lithium batteries, lead-acid batteries, etc. according to the capacity from small to large. Button batteries Commonly used in small electronic mechanical equipment, such as electronic watches, dry batteries are often used in small old electronic equipment, such as radios, electronic toys, etc., lithium batteries are often used in small mobile electronic equipment, such as mobile phones, laptops, etc., lead-acid batteries are often used in small portable Mobile electric equipment and large non-movable equipment, such as electric vehicle...

AI Technical Summary

Problems solved by technology

[0006] Aiming at the above-mentioned technical problems existing in the prior art, the present invention provides a technical solution of a non-contact leakage detection method for lead-acid batteries based on machine learning, which solves the problem that lead-acid batteries cannot be used as backup power sources for non-contact automatic Detect the problem of liquid leakage, and realize the non-contact automatic detection of liquid leakage of lead-acid batteries. It is applicable to a wide range of scenarios and easy to install.

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