Abstract: As a critical energy source and chemical raw material in China, coal plays a vital role in economic development, making its rational exploitation and utilization highly significant. Currently, the coal industry is undergoing a crucial period of intelligent transformation, and the intelligentization of coal preparation plants represents a core step in shifting the sector from being “labor-driven” to “technology-driven.” Ash content, being one of the key indicators for evaluating coal product quality, requires real-time and accurate detection, which has become essential for achieving clean and efficient utilization of coal. The article outlines the principles and operational procedures of offline coal ash content detection technologies, represented by the slow ashing method and rapid ashing method. It points out that while these methods offer high accuracy, they suffer from limitations such as complex operations, long processing times, and the inability to provide real-time ash content data. Currently, they are primarily used to verify the accuracy of online detection methods. The article also introduces five types of online ash detection technologies based on γ-rays, X-rays, natural coal radioactivity, neutron activation, and laser techniques. It elaborates on the structural features, working conditions, and performance indicators of various online ash analyzers, with a focused comparative analysis of their advantages and disadvantages in practical applications. Analysis indicates that different online ash detection technologies vary in applicable scenarios, performance advantages, and limitations due to differences in their working principles. The selection of an appropriate method must comprehensively consider specific application contexts, coal characteristics, and costs. Finally, it is pointed out that the future development of coal ash detection technology should focus on intelligence, precision, and efficiency. Efforts should be made to enhance technical capabilities and support the coal industry by strengthening R&D to drive innovation, deeply integrating with intelligent coal preparation plant systems, establishing comprehensive technical standards and regulations, prioritizing safety and environmental protection, and fostering talent development. This article can provide valuable insights for coal enterprises and related researchers in selecting appropriate ash detection methods.