Abstract: Metallic mesh is a transparent electromagnetic shielding film with a fine metal line structure. However, it can develop defects in the production preparation or in actual use that affect the optoelectronic performance. The development of in situ non-destructive testing (NDT) devices for metallic mesh requires long working distances, reflective optical path design, and miniaturization. To address the limitations of existing smartphone microscopes, which feature short working distances and inadequate transmission imaging for industrial in situ inspection, we propose a novel long-working-distance reflective smartphone microscopy (LD-RSM) system. LD-RSM comprises a 4f optical imaging system with external optical components and a smartphone. This system uses a beam splitter to achieve reflective imaging with the illumination system and imaging system on the same side of the sample. It achieves an optical resolution of 4.92?m and a working distance of up to 22.23 mm. Additionally, we introduce dual-prior weighted robust principal component analysis (DW-RPCA) for defect detection. This approach leverages spectral filter fusion and the Hough transform to model different defect types, which enhances the accuracy and effeciency of defect identification. Coupled with a double-threshold segmentation approach, the DW-RPCA method achieves a pixel-level defect detection accuracy (f-value) of 0.856 and 0.848 in square and circular metallic mesh databases, respectively. Our work exhibits strong potential for growth in the field of in situ on-line inspection of industrial products.