5results about How to "Timely diagnosis" patented technology

A data transmission method for a handheld ultrasonic system and the handheld ultrasonic system, the method being applied to a mobile terminal deployed with the handheld ultrasonic system, the mobile terminal comprising a first near field communication module, the method comprising: in response to a first user operation, transmitting data to the handheld ultrasonic system through the first near field communication module, acquiring identification information of a target monitor from the target monitor comprising a second near field communication module; wherein the first user operation comprises the step that a user enables the mobile terminal to be close to the target monitor; and establishing communication connection with the target monitor based on the identification information of the target monitor, and transmitting ultrasonic image data to the target monitor based on the communication connection so as to project an ultrasonic image displayed on the mobile terminal to the target monitor for display. The method and the system can solve the problem that the screen of the mobile terminal is small and is difficult to meet the requirement of multi-user simultaneous viewing, and are simple in user operation and good in user experience.

The present disclosure relates to methods and systems for diagnosing a particulate filter sensor. Systems and methods are presented for diagnosing operation of a sensor of an exhaust system. In one example, the systems and methods can diagnose operation of the sensor while the engine is combusting air and fuel. Further, operation of the sensor can be diagnosed while the engine is not combusting air and fuel, such that vehicle occupants are not disturbed by the diagnosis.

The application relates to the technical field of power mode recognition, in particular to a power equipment fault detection method and system based on a deep learning network, which comprises the following steps: collecting and preprocessing multimodal data such as power time series and equipment images; monitoring the resource state of an edge node in real time, and adjusting the configuration parameters of a lightweight feature extraction model according to a preset rule; adopting a bidirectional cross-modal attention mechanism, calculating query, key and value representation and attention weight, dynamically weighting and fusing projection feature vectors of different modes, and generating a unified fault representation vector; calculating a fault probability by using the representation vector, and adaptively optimizing the parameters of a probability calculation model through online incremental learning; finally, calculating a task priority, and determining whether data is uploaded to a higher-level system for more detailed analysis according to the priority and a real-time resource state. The application can effectively improve the real-time performance, accuracy and adaptive capacity of edge-end power equipment fault detection.

The present application relates to the field of electric meter remote monitoring, more particularly, the present application relates to the electric meter remote fault diagnosis method and system based on internet of things, the method comprises: obtaining all historical fault sequences corresponding to each fault type; the period of each historical fault sequence is calculated and the probability of each period appearing, and based on the historical fault sequence corresponding to a single period, the template sequence of the period is generated; the real-time parameter time sequence of the electric meter is collected, the similarity of the real-time parameter time sequence and the template sequence of each period corresponding to the fault type is calculated, the calculated similarity is weighted and summed according to the probability of each period appearing, and the real-time fault probability of the fault type is obtained; when the real-time fault probability is greater than the preset fault threshold, the diagnosis result of the corresponding fault type of the electric meter is output. The present application can more comprehensively and accurately describe the complex evolution law of the fault, and realize the remote and timely diagnosis of the electric meter fault.

The invention provides EB (Epstein-Barr) virus nucleic acid detection primers, a probe and a kit, according to a target sequence of an EB virus gene, the sequences of the primers and the probe in an asymmetric primer ERA detection system are designed and screened, and the ratio of upstream and downstream primers and an amplification reaction system are optimized, so that the EB virus nucleic acid sequence can be specifically identified, and the EB virus nucleic acid detection kit has the advantages of high specificity and high sensitivity. Non-specific binding with other irrelevant nucleic acids is reduced, so that the detection specificity is improved; meanwhile, efficient amplification of EB virus nucleic acid is realized, and the EB virus nucleic acid can be accurately detected even under the condition that the content of the virus nucleic acid is extremely low, so that the detection sensitivity and the amplification efficiency are improved.