Biomass carbon content measurement and modeling method based on infrared spectrum principal component and neural network

• Main Authors: HU XIAOYING, WANG XIAOQIANG, ZHANG XUMING, ZHENG ZONGMING, ZHU HENG, ZHANG JUNJIAO, XUE JUNJIE, ZHAO YING, DONG CHANGQING
• Format: Patent
• Language: Chinese; English
• Published: 28.05.2021
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; ELECTRIC DIGITAL DATA PROCESSING; INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES; MEASURING; PHYSICS; TESTING

The invention discloses a biomass carbon content measurement and modeling method based on an infrared spectrum principal component and a neural network. The biomass carbon content measurement and modeling method mainly comprises the following steps: (1) acquiring and preprocessing biomass infrared spectrum data; (2) recording environment state parameters during acquisition of the infrared spectrum data; (3) measuring carbon content measurement value data of the biomass sample according to national or industrial standards; (4) carrying out correlation calculation on the infrared spectrum data and the carbon content measurement value in pairs; (5) carrying out dimension reduction on the data by adopting a principal component analysis method; (6) establishing a neural network model by taking the principal component data and the environmental state parameters as input and the carbon content measurement value as output, and training by using the training set until the error is less than 0.1%; and (7) inputting ver