Plant-wide oscillations generated in a single unit can negatively affect the overall control performance of the process; thus, it is necessary to detect them and diagnose their root cause. However, the interference of noise and the need for oscillation propagation routes pose more challenges for process engineers. In this paper, the concept spectral transfer entropy is proposed and its connection to the spectral Granger causality is derived. Moreover, an information transfer method incorporating spectral envelope algorithm and spectral transfer entropy is applied to provide new diagnostic guidance, whose feasibility and effectiveness have been demonstrated by both simulated and industrial case studies. Compared with current methods, the new procedure enjoys the following advantages: (a) performing oscillation detection and diagnosis within a targeted frequency range and mitigating the effects of measurement noise outside the bandwidth; (b) provides an nominal causal map reflecting the oscillation propagation pattern. The root cause obtained by the method in the industrial case is further validated by a wavelet power spectrum.