Fine-grained localization of the first (S1) and second (S2) heart sound sub-peaks is important for cardiac mechanics evaluation, yet challenging in wearable bone-conducted phonocardiogram (BC-PCG) signals. To localize five prominent sub-peaks using multi-modal signals, an improved one-dimensional Residual U-Net is proposed, featuring a sparsity-aware composite heatmap loss to address extreme feature sparsity. A post-processing pipeline using non-maximum suppression (NMS) and conditional random field (CRF) Viterbi decoding enforces physiological temporal constraints. Under leave-one-subject-out cross-validation (LOSOCV) on 12 subjects, the optimal PCG and electrocardiogram (ECG) configuration achieved an 86.57% macro-average F1-score and a 19.36 dB signal-to-noise ratio (SNR), effectively circumventing dynamic temporal misalignments introduced by photoplethysmogram (PPG) integration to ensure robust localization despite physiological intra-wave imbalances. This framework enhances BC-PCG interpretability and facilitates cardiovascular disease diagnostics.