The invention relates to the technical field of
food processing, and discloses an intelligent
cephalopod food
nutritional quality regulation and control method, which comprises the following steps: S1,
data acquisition and deployment: respectively arranging sensor combinations in a frying area, a
coating area, a conveying area and an environment monitoring point of a
cephalopod food coating and frying
production line; the method comprises the following steps: S1, generating a
processing variable
feature set and a quality
feature set, S3, screening key data, S4, generating regulation and
control parameters, and S5, performing real-time regulation and control. According to the method, multiple types of sensors are deployed in a key area of a
production line, data such as
oil temperature and
humidity are collected according to the frequency of 50 ms / time,
feature extraction, a
random forest and a BP neural network
coupling algorithm are combined, the nonlinear relation between
processing variables and quality and the dynamic relation between the material progress and a failure event are analyzed, and the
processing accuracy is improved. The problems that in traditional production, real-
time information is difficult to obtain, and the variable influence rule is unknown are solved, and comprehensive data support and scientific basis are provided for accurate regulation and control.