force (N)   Name of setting
  ----- ---------------------- ------------------ ------------------ -----------------
    0            1500                 0.7                1000          N15\_M07\_F10
    1            900                  0.7                1000          N09\_M07\_F10
    2            1500                 0.1                1000          N15\_M01\_F10
    3            1500                 0.7                400           N15\_M07\_F04

  : Four working conditions of PU datasets

In this paper, since using all the data will cause huge computational time, we only use the data collected from real damaged bearings ( including KA04, KA15, KA16, KA22, KA30, KB23, KB24, KB27, KI14, KI16, KI17, KI18, and KI22) under the working condition N15\_M07\_F10 to carry out the performance verification. It is worth mentioning that since KI04 is the same as KI14 completely shown in Table \[Tab\_3\], we delete KI04 and the total number of classes is thirteen. Besides, only vibration signals are used for testing the models.

UoC Gear Fault Dataset
----------------------

UoC gear fault datasets were provided by the University of Connecticut [@UoC], and UoC datasets were collected at 20 kHz. In this dataset, nine different gear conditions were introduced to the pinions on the input shaft, including healthy condition, missing tooth, root crack, spalling, and chipping tip with 5 different levels of severity. All the collected datasets are used and classified into nine categories (one health state and eight fault 