Xi'an Jiaotong University

Junyi Cao

Shuo Wang

Jing Liu

Yaguo Lei

Tonghai Wu

Miao Wan

A method and system of enhancing online reflected light ferrograph images. The method includes: based on contour markers of wear particles in the online reflected light ferrograph image, performing concatenate fusion on the SqueezeNet-Unet-based wear particle position prediction network and the ResNeXt-CycleGAN image transformation network to construct an online reflected light ferrograph image enhancement model; determining loss function of the position prediction network; combining SSIM and L1 losses to optimize cycle-consistency loss function of the ResNeXt-CycleGAN image transformation network; designing overall loss function of the ferrograph image enhancement model by weighted fusion; and optimizing the ferrograph image enhancement model with the overall loss function as optimization object successively using a training sample set consisting of an original online reflected light ferrograph image and a traditional algorithm-enhanced online reflected light ferrograph image and a training sample set consisting of the original image and an offline reflected light ferrograph image.

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Xi'an, China

Junyi Cao