2results about How to "Suitable for detection" patented technology

The application discloses a time-frequency cooperative power equipment anomaly detection method, relates to the power equipment detection field, and aims at the problem of lacking representation ability in the prior art. A time-frequency cooperative anomaly detection model is established by constructing a time domain local branch and a frequency domain global branch, and the time-frequency cooperative anomaly detection model is used for anomaly detection on a time sequence of power equipment, the time sequence being a sequence formed by monitoring data of the power equipment arranged in time sequence and used for representing the equipment operation state. The time domain local branch is used for extracting local fluctuation features and short-term dependence features in the time sequence. The frequency domain global branch is used for extracting periodic change features and global frequency features in the time sequence. The method has the advantages that the time domain branch and the frequency domain branch are constructed, local change information and global periodic information in the equipment operation time sequence are cooperatively modeled, the equipment operation state is more fully represented, and the accuracy and stability of anomaly detection are improved.

The application provides a blanking hole clogging detection system based on infrared thermal imaging. The blanking hole is adjacent to the end of a material conveying belt. The thermal imaging device of the infrared image acquisition unit comprises a long-wave infrared detector arranged at the blanking hole through a mounting bracket. The long-wave infrared detector can obtain a continuous infrared image sequence in a high-concentration dust environment. The field angle of the long-wave infrared detector is adjusted to cover the entire blanking hole area, so that an abnormal heat area formed when the blanking hole is clogged enters the imaging range completely. When the detection system is working, the intelligent computing unit analyzes the infrared thermal image sequence, analyzes the spatial distribution characteristics and time evolution characteristics of the temperature field, and determines whether the blanking hole is clogged by using a multi-feature fusion diagnosis model. The application can accurately and continuously collect and continuously monitor the infrared light data at the blanking hole in a high-dust-concentration environment and under the condition that the infrared light characteristics of different materials of the conveying belt are seriously different, and determine whether the blanking hole is clogged abnormally.