Reliable condition monitoring is needed for water-handling machinery used in mining, where abrasive media, humidity and variable loading can accelerate pump and bearing degradation. This study investigates the Teager–Kaiser energy operator (TKEO) as a complementary diagnostic tool for pump-bearing vibration analysis, with emphasis on water-lubricated plain bearings used in mining applications. Four synthetic signal models—normal operation, unbalance, localised surface defects and hydrodynamic instability—were analysed using time-domain statistics, Fast Fourier Transform (FFT) spectra and the three-sample discrete TKEO. A controlled laboratory proof-of-concept complemented the simulations by comparing displacement and acceleration records from three imposed bearing configurations (A–C) at a constant shaft speed of 25 Hz. The configurations were produced by rotating the bearing and thereby changing the location of the lubrication gap; they were not independently validated as stable, transient, or unstable dynamic states. Conventional RMS and FFT measures captured overall vibration levels and rotational harmonics. The TKEO-derived indicators also changed across the imposed configurations, but their numerical ratios are not directly comparable with conventional RMS because the two quantities have different amplitude scaling. Accordingly, the observed configuration-dependent changes are reported as descriptive proof-of-concept results and do not establish greater diagnostic sensitivity, statistical superiority, classification performance, or field validity. The specific contribution of this proof-of-concept is an application-focused comparison of conventional and TKEO-derived descriptors for displacement and acceleration records from a water-lubricated plain bearing under imposed Configurations A–C. The four synthetic signals are used only to illustrate the response of the processing methods to selected signal constructions and are not treated as validation or physical counterparts of the experimental configurations.