The invention relates to the field of wind power, in particular to a wind generating set blade abnormal recognition method. The wind generating set blade abnormal recognition method is used for monitoring the operation state of a wind generating set, operation parameter data of the wind generating set are obtained at first and at least comprise the Y-direction acceleration value, then, abnormal detection data are determined based on the operation parameter data, abnormal detection data sections where the abnormal detection data occur continuously are determined, the total frequency of the abnormal detection data sections is counted, if the total frequency is larger than or equal to the preset abnormal frequency threshold value, it is judged that a wind generating set blade is abnormal, andif not, the blade is not judged to be abnormal. Due to the fact that the performance of the blade is reduced due to cracking and other issues of the blade, the Y-direction acceleration value in the fan operating process can be abnormal, if the abnormal data frequently occur within a certain time continuously, it explains that the blade is abnormal, blade abnormity can be monitored in time when happening, and the blade abnormal recognition timeliness and accuracy are improved.