为了定量评价在线图像可视铁谱( OLVF)成像系统的像面照度均匀性，建立了一种像面照度模型。以像方参数及放大倍率表征物方视场，将物方视场区域离散化，采用朗伯余弦理论建立入瞳模式的像面照度模型，实现了像面照度的计算与均匀性评价。利用Matlab进行了物面照度仿真分析，确定了OLVF成像系统环形阵列光源的发光二极管(LED)数量，基于像面照度分析确定了最佳成像焦距和放大倍率。计算了油腔通油情况下成像系统中的光能量损耗以及磨粒沉积面的照度分布，建立了油液吸光系数与CCD像面轴上像点照度的关系。结果显示: LED发光强度已知时，仿真计算的像面不均匀度约为5.60%，实际测试的像面不均匀度为8%~9%，满足不均匀度≤10%的要求。开展了磨粒铁谱图像采集实验，结果表明: 图像中磨粒清晰可辨，便于图像分割与视觉特征提取。提出的模型可定量描述OLVF成像系统的像面照度，可作为优化系统结构，提高系统成像性能的依据。

To evaluate quantitatively the uniformity of image illumination for an On-line Visual Ferrograph (OLVF)imaging system, a new mathematical model of image illumination was presented. The view field of an object space was represented by image space parameters and optical magnification, then it was discretized into a micro area. By taking Lambert-cosine law as reference, the image illumination model based on the aperture of entrance pupil was established, the image illumination distribution was calculated reliably and the uniformity of image illumination was evaluated successfully. On the basis of Matlab simulation analysis, the number of single Light Emission Diodes(LEDs) in the circular ring array source of the OLVF imaging system was obtained and the optimized values of focal length and optical magnification were determined. The light loss of imaging system and the illumination distribution of wear debris deposition region were analyzed and calculated under the condition of the oil cavity filled with lubricant oil. The relationship between the absorptivity of lubricant oil and the peak value of CCD image illumination was investigated. The experimental results show when the luminous intensity of LED arrays is known, the imaging plane illumination non-uniformity is more than 5.60% by simulating calculation and that is from 8% to 9% by a practical test, which satisfies the demand by indicator less than 10%. Finally, this imaging system was practically used to capture the reflected ferrograph. The results show that the characteristics of wear debris has been clearly distinguished from the reflected ferrograph, and it is favorable to the ferrograph segmentation and image extraction. It concludes that the proposed model evaluates quantitatively the uniformity of image illumination, optimizes systematical structure and improves the imaging performance of the system.