Although the quality inspection method of polycarboxylate superplasticizers (PCE) based on macroperformance is still widely used, it has the drawbacks of time-consuming and low precision. This study aims to develop a practicable alternative method for quality inspection of PCE. For this, spectra collection, feature extraction, and cluster analysis were performed up on the PCE samples to demonstrate the feasibility of the method. Also, a new similarity calculation method was introduced in this work. Results show that the solid PCE sample for spectrum collection can be prepared using the simple heating method. High-quality spectra can be rapidly collected by infrared spectrometer combined with ATR accessory. Meanwhile, the accuracy of classification and clustering is high, suggesting that the feature extraction method based on principal component analysis (PCA) is effective. In addition, compared with conventional similarity calculation methods of cosine angle and correlation coefficient, the new similarity calculation method achieves better classification results and better generalization ability. This work provides a method of quantitative analysis and rapid identification of PCE for the construction site.
Rapid Identification and Quantitative Analysis of Polycarboxylate Superplasticizers Using ATR-FTIR Spectroscopy Combined with Chemometric Methods
