3results about How to "Realize automatic diagnosis" patented technology

The invention discloses an automatic cleaning and maintenance control method and system for water quality monitoring equipment and a medium, and belongs to the field of water quality monitoring. The method comprises the steps that pure water generated by a built-in pure water production assembly of equipment serves as a measurement anchor point, and whether sensors are normal or not is judged on the basis of comparison results of detection numerical values of the sensors in a pure water environment and a preset pure water threshold value; monitoring operation state parameters of the pure water production assembly, and dynamically adjusting and updating the pure water threshold value corresponding to each sensor; when the value of the sensor deviates from the threshold value, first-stage pure water flushing is executed; if not, second-stage maintenance is started according to the sensor type, the optical sensor performs optical path self-cleaning or backwashing, and the electrochemical sensor performs electrode cleaning; and detecting again after maintenance, and locking the sensor and generating a fault alarm if the sensor is still not recovered. Through dynamic threshold configuration, progressive maintenance and sensor adaptive cleaning, the problems of reference drift and deep pollution are solved, the data credibility is improved, and the operation and maintenance cost is reduced.

Embodiments of the present application provide a kind of fault detection method, device and equipment of mutual inductor and mutual inductor, it is related to power system technical field.The method comprises: obtaining the multiple sensor data that multiple sensors deployed in mutual inductor are collected in real time;According to the first feature information corresponding to multiple sensor data, determine the fault score of mutual inductor;Obtain the historical sensor data of mutual inductor, and according to multiple sensor data, historical sensor data and the equipment related information of mutual inductor, determine the dynamic fault threshold corresponding to mutual inductor;If according to fault score and dynamic fault threshold, it is determined that mutual inductor exists fault, then according to the second feature information corresponding to multiple sensor data, determine the fault type of mutual inductor.The method of the present application can comprehensively, accurately and efficiently realize the fault detection of mutual inductor, to help guarantee the stable operation of power system.

This invention discloses a method and system for video diagnosis of power system faults based on spatiotemporal semantic fusion, relating to the fields of power system fault detection, computer vision, and multimodal information fusion. The method involves acquiring fault videos and dividing them into multiple video sub-segments. For each video sub-segment, a CLIP image encoder is used to extract spatial feature vectors from each frame, resulting in a corresponding spatial feature sequence. This spatial feature sequence, after being embedded with positional information, is input into a temporal Transformer encoder. A self-attention mechanism is used to calculate the internal temporal relationships, and these are aggregated to obtain a sub-segment feature vector representing the dynamic features of that video sub-segment. Text describing the power system fault is collected, and a CLIP text encoder is used to extract text feature vectors for each fault text. Cross-modal similarity matching is performed between the sub-segment feature vectors and the text feature vectors, and the matching result with the highest similarity score is used as the fault diagnosis result. This invention has significant advantages for the identification of complex dynamic fault events.