Industrial signal processing is the application of signal processing theories, algorithms, and systems to analyze, interpret, and extract meaningful information from data originating within industrial environments. This research field and methodological approach investigates signals generated by sensors, machines, and processes in sectors such as manufacturing, energy, automation, and infrastructure, addressing specific challenges like noise contamination, real-time constraints, and the need for robust fault detection and diagnosis. Its significance lies in providing the analytical foundation for advanced industrial monitoring, control, predictive maintenance, and optimization, thereby improving operational performance, reliability, safety, and product quality.