公开(公告)号：US12158457B2

公开(公告)日：2024-12-03

申请号：US17794767

申请日：2020-07-18

Applicant: East China University of Science and Technology

Inventor： Zejian Wang ,  Daqi Gao ,  Xiaoqin Zhang ,  Bo Li ,  Fang Cai ,  Jianhua Li ,  Mingjian Cheng

IPC: G01N30/88 ,  G01N1/24 ,  G01N33/00 ,  G06N3/045

Abstract: A method for online detecting and analyzing multiple state parameters in fermentation and malodorous pollution processes by using an electronic nose instrument of gas sensitivity and gas chromatography, where the electronic nose instrument includes a gas sensor array module, a capillary gas chromatographic column module, a gas auto-sampling module, a computer control and analysis module and an auxiliary gas source, which is configured to perform cyclically long-term online detection and intelligent analysis of a plurality of bio-fermentation processes or a plurality of malodorous pollution processes.

公开(公告)号：US20230141978A1

公开(公告)日：2023-05-11

申请号：US17794801

申请日：2020-07-18

Applicant: East China University of Science and Technology

Inventor： Zejian Wang ,  Daqi Gao ,  Bo Li ,  Xiaoqin Zhang ,  Fang Cai ,  Jianhua Li ,  Mingjian Cheng

IPC: G01N30/88 ,  G01N33/00 ,  G06N3/045

CPC classification number: G01N30/88 ,  G01N33/0032 ,  G01N33/0034 ,  G01N33/0062 ,  G06N3/045 ,  G01N2030/8804 ,  G01N2030/8809

Abstract: Provided is a method for multi-information fusion of gas sensitivity and chromatography and on-site detection and analysis of flavor substances using an electronic nose instrument. The electronic nose instrument includes a gas sensor array module (I), a capillary gas chromatographic column module (II), an automatic headspace sampling module (III), a computer control and data analysis module (IV), an automatic lifter (V) for headspace sampling, a large-volume headspace vapor generation device (VI) and two auxiliary gas sources (VII-1, VII-2). The electronic nose instrument detects a large number of odorous samples to establish a big odor data. On this basis, the normalization fusion preprocessing is done, and the cascade machine learning model realizes both an on-site recognition of many foods, condiments, fragrances and flavors, and petroleum waxes and a real-time quantitative prediction of their odor quality grades and many key component concentrations.

公开(公告)号：US12259374B2

公开(公告)日：2025-03-25

申请号：US17794801

申请日：2020-07-18

Applicant: East China University of Science and Technology

Inventor： Zejian Wang ,  Daqi Gao ,  Bo Li ,  Xiaoqin Zhang ,  Fang Cai ,  Jianhua Li ,  Mingjian Cheng

IPC: G01N30/88 ,  G01N33/00 ,  G06N3/045

Abstract: Provided is a method for multi-information fusion of gas sensitivity and chromatography and on-site detection and analysis of flavor substances using an electronic nose instrument. The electronic nose instrument includes a gas sensor array module (I), a capillary gas chromatographic column module (II), an automatic headspace sampling module (III), a computer control and data analysis module (IV), an automatic lifter (V) for headspace sampling, a large-volume headspace vapor generation device (VI) and two auxiliary gas sources (VII-1, VII-2). In the gas sampling period of T0-300-600 s, the gas sensor array module and the gas chromatography module have different flow rates, volumes and staring sampling time points of gas sampling, but have synchronous selection and analysis time points of multiple sensitive information. The electronic nose instrument obtains a 69-dimensional combined pattern, including steady-state response peak values, corresponding peak time points as well as under-curve areas, through each on-site real-time detection to a tested sample. The electronic nose instrument detects a large number of odorous samples to establish a big odor data. On this basis, the normalization fusion preprocessing is done, and the cascade machine learning model realizes both an on-site recognition of many foods, condiments, fragrances and flavors, and petroleum waxes and a real-time quantitative prediction of their odor quality grades and many key component concentrations.

公开(公告)号：US20230152287A1

公开(公告)日：2023-05-18

申请号：US17794767

申请日：2020-07-18

Applicant: East China University of Science and Technology

Inventor： Zejian Wang ,  Daqi Gao ,  Xiaoqin Zhang ,  Bo Li ,  Fang Cai ,  Jianhua Li ,  Mingjian Cheng

IPC: G01N30/88 ,  G01N33/00 ,  G06N3/045 ,  G01N1/24

CPC classification number: G01N30/88 ,  G01N33/00 ,  G06N3/045 ,  G01N1/24

Abstract: Provided is an electronic nose instrument based on gas sensitivity and gas chromatography and an online analysis method of multiple state parameters of fermentation and malodorous pollutant processes. The main constituent units of the instrument include a gas sensor array module, a capillary gas chromatographic column module, an automatic gas sampling module, and a computer control and analysis module. A single gas sampling period is T0=300-600s. Not only are two flow rates and two accumulative volumes of gas sampling unequal to each other, but also two starting time points are not synchronized to each other, between the gas sensor array module and the gas chromatography module. 3 pieces of sensitive information, i.e., a steady-state peak value, a corresponding peak time value and an area under a whole curve, are selected from a response curve of a single gas sensor with a 60s duration by the computer control and analysis module, or 48 pieces of gas sensitive information in total, and 21 pieces of sensitive information, i.e., 10 maximum peak values, 10 corresponding retention time values, and 1 area under the whole chromatographic curve, are selected from a semi-separation chromatogram with a duration T0−10 s. Furthermore, the cyclical online identification and intensity and quantitative estimation of multiple indices of odors for five fermentation or malodorous pollution processes with a maximum cyclical gas sampling period T=5T0 are realized by a modular deep convolutional neural network model according to a 69-dimensional normalized fused real-time sensitive pattern and an existing big odor data.