首先针对基于多元统计技术的间歇过程统计建模、在线监测、故障诊断及质量预测等热点问题进行了论述, 回顾了各类方法的发展, 并分析了各自的优缺点. 接下来重点针对间歇工业过程多时段及时段过渡特性, 详细介绍了基于时段的统计分析策略, 分析了各时段的潜在过程行为及其对产品质量的影响与作用关系, 探讨了该思想方法的本质依据, 揭示了其研究价值和重要意义. 最后从解决实际问题的角度出发, 发掘了其存在的潜在问题及今后的研究前景与发展空间. 基于时段的间歇过程多元统计分析是一个既有理论意义又有较高实际应用价值的研究课题, 必将有利于后续的过程监测、故障诊断及质量改进.
The paper first presents a comprehensive description of some hot problems in statistical modeling, online monitoring, and quality prediction for batch process based on multivariate statistical techniques, including the development of various solutions and their advantages and disadvantages. Then, phase-based statistical analysis strategies are addressed with a focus on the multiplicity of operation phase and phase transition behaviors. This part analyzes the phase-based process characteristics and their effects on product quality, discusses the inherent basis, and reveals their significance. Finally, from the viewpoint of solving practical problems, the existing problems are explored and their prospective development is discussed. Phase-based statistical analysis for batch processes is important in both theory meaning and application, which will benefit further process monitoring, fault diagnosis and quality prediction.