Linear and nonlinear relationships may exist simultaneously across process variables and quality variables. If only the linear model is established, the nonlinear structure may be neglected. If only the nonlinear model is constructed, the model accuracy and monitoring performance may be degraded. Thus, the quality monitoring method considering both linear and nonlinear relationships needs to be presented. In this paper, a serial ridge regression (SRR) method is proposed for quality monitoring in the linear-nonlinear-coexistence process. Firstly, linear features are extracted to construct the linear-quality-feature subspace, and the remaining information constitutes the complementary feature subspace. Then, the nonlinear-quality-features are further extracted from the complementary feature subspace via kernel-based strategy. Thereafter, in order to obtain more direct and clear monitoring results, the quality monitoring index is developed based on Bayesian inference. Case studies in a numerical simulation, continuous stirred tank reactor (CSTR) process and TE process demonstrate that the SRR-based method significantly outperforms partial least squares (PLS), ridge regression (RR) and kernel ridge regression (KRR)-based methods, in terms of higher fault detection rates, lower false alarm rates and better fault sensitivity. It helps the operator to detect faults earlier and avoid unnecessary downtime and maintenance.

线性和非线性关系可能同时存在于过程变量和质量变量之间。如果仅建立线性模型，则可以忽略非线性结构。如果仅构建非线性模型，则模型的准确性和监视性能可能会降低。因此，需要提出同时考虑线性和非线性关系的质量监测方法。针对线性-非线性共存过程中的质量监控问题，提出了一种基于序列岭回归（SRR）的质量监测方法。首先，提取线性特征以构建线性质量特征子空间，剩余信息构成互补特征子空间。然后，通过基于核的策略进一步从互补特征子空间中提取非线性质量特征。之后，为了获得更直接，更清晰的监测结果，基于贝叶斯推论建立了质量监测指标。在数值模拟，连续搅拌釜反应器（CSTR）和TE过程中进行的案例研究表明，基于SRR的方法明显优于基于偏最小二乘（PLS），岭回归（RR）和核仁回归（KRR）的方法，在更高的故障检测率，更低的误报率和更好的故障敏感性方面。它有助于操作员及早发现故障，避免不必要的停机和维护。连续搅拌釜反应器（CSTR）工艺和TE工艺表明，基于SRR的方法在故障检出率更高的方面明显胜过基于偏最小二乘（PLS），岭回归（RR）和核仁回归（KRR）的方法。 ，更低的误报率和更好的故障敏感性。它有助于操作员及早发现故障，避免不必要的停机和维护。连续搅拌釜反应器（CSTR）工艺和TE工艺表明，基于SRR的方法在故障检出率更高的方面明显优于基于偏最小二乘（PLS），岭回归（RR）和核仁回归（KRR）的方法。 ，降低误报率，并提高故障敏感性。它有助于操作员及早发现故障，避免不必要的停机和维护。