Fault diagnosis is the process of tracing a fault by means of its symptoms, applying knowledge, and analyzing test results. Accurate diagnosis of faults in complex engineering systems requires acquiring the information through sensors, processing the information using advanced signal processing algorithms, and extracting required features for efficient classification or identification of faults. Identification of faults and subsequent remedial action can increase productivity and reduce maintenance costs in various industrial applications. Machine learning methods involving feature extraction, feature selection, and classification of faults offer a systematic approach to fault diagnosis and can be used in automated or unmanned environments. These are increasingly used in industrial sectors, such as manufacturing, automotive, marine, and aerospace, to maximize equipment uptime and minimize maintenance and operating costs.