To address the difficulty in accurately quantifying the fault degree of harmonic reducers and the inability to perform same-scale quantitative analysis for different fault locations, a same-scale quantitative assessment method is proposed for multiple states of harmonic reducer based on improved deep residual network (ResNet) and multi-kernel support vector data description (MKSVDD). First, a new same-scale quantitative assessment framework for multiple states of harmonic reducer is proposed, and continuous wavelet transform is applied to acoustic emission signals sensitive to weak faults to construct a two-dimensional time-frequency image dataset. Then, a convolutionalattention module is used to improve ResNet in order to fully extract the deep features of the two-dimensional time-frequency images. Furthermore, a multi-kernel function is introduced to enhance the support vector data description, and an MKSVDD health state assessment model is constructed based on the deep features of the harmonic reducer in the normal state. Next, the distance between the features of different fault degrees and the center of the hypersphere under the normal condition is calculated to construct the assessment indicators, and the quantitative assessment curve is obtained by fitting these indicators. In addition, based on the structure of the harmonic reducer and the propagation mechanism of acoustic emission signals, a relative distance compensation scheme is proposed to construct the multi-state assessment indicator, thereby achieving quantitative assessment of different health states for harmonic reducer under a unified scale. Through the establishment of a harmonic reducer test bench and multiple comparative experiments on data with unknown fault degrees, the results show that the features extracted by the improved deep residual network are more compact. The proposed method enables same-scale quantitative assessment of different fault locations, with an assessment error not exceeding 3.2%, effectively completing the same-scale quantitative assessment of harmonic reducer in multiple states.