The invention provides a blocking method for identifying abnormal rotation behaviors of pigs only based on three-axis attitude angles, and aims to realize early identification and
continuous monitoring of
nervous system related behaviors such as abnormal rotation of pigs. The method comprises the following steps: acquiring three-axis attitude angle data (a
yaw angle
Yaw, a
pitch angle
Pitch and a roll angle Roll) of a pig through a wearable terminal; preprocessing and basic stability correction are carried out; extracting the characteristics of directional fluctuation, continuous offset, reciprocating swing and the like in the attitude angle sequence; constructing a behavior trend in combination with a multi-scale time window; and judging an abnormal rotation behavior based on the rule model and outputting an identification result. A low-frequency continuous sampling mechanism is adopted, the
power consumption burden of high-frequency continuous sampling is avoided, the method does not depend on multi-mode signals such as acceleration, images and temperature, and only the three-axis attitude angle serves as the unique judgment basis. The method has the advantages of being simple in deployment, low in
power consumption and high in
blockade, is suitable for an intelligent
recognition system in a large-scale breeding scene, and can effectively improve the early warning capability of the neural abnormal behaviors of the pigs.