4results about How to "Eliminate uncertainty" patented technology

The invention relates to a tunnel secondary lining concrete filling state real-time monitoring system which is characterized in that a secondary lining cavity is defined by a secondary lining template in a tunnel, the system comprises a sensor array located in the secondary lining cavity, the sensor array comprises a plurality of rows of optoelectronic switches distributed in the extending direction of the tunnel, and the optoelectronic switches in the same row are distributed in the circumferential direction of the tunnel; the signal processing and acquisition unit is responsible for supplying power to the photoelectric switch and converting the received signal of the photoelectric switch into a signal displayed by a display; and the data processing and displaying unit is responsible for displaying the signals transmitted by the signal processing and collecting unit on a reality device. The invention aims to provide the tunnel secondary lining concrete filling state real-time monitoring system capable of acquiring the cavity in real time, and the problem that the existing cavity can only be acquired afterwards is solved.

The invention provides an abnormal event root cause positioning method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring time sequence monitoring data of a target business index; performing anomaly detection based on the time sequence monitoring data to determine a time window of an abnormal event; obtaining multi-dimensional business feature data corresponding to the time window; performing causal analysis on the multi-dimensional business feature data to screen a candidate dimension subset having potential causal association with the abnormal event from a plurality of dimensions; performing contribution degree analysis on dimensions in the candidate dimension subset to quantify contribution values of the dimensions to the abnormal event of the target business index in the time window; and determining a core root cause dimension causing the abnormal event according to the contribution value. Therefore, the root cause positioning efficiency and the result reliability are improved.

The application provides a bidirectional fault detection method, system, device and readable storage medium, the method comprises the following steps: determining whether the received message is a BFD control message based on the access control list rule issued by the central processor; if the received message is a BFD control message, the BFD control message is sent to the hardware operation management maintenance engine, and the BFD session information corresponding to the BFD control message is acquired based on the hardware operation management maintenance engine to detect the connectivity of the BFD control message; if the received message is not a BFD control message, the received message is sent to the central processor. Compared with the prior art, the application avoids excessive consumption of CPU resources caused by the increase in the number of BFD sessions or the shortening of the detection period. On the other hand, the hardware processing of the BFD service eliminates the uncertainty factors on the software processing path, can realize better timing accuracy, and improves the reliability of detection and the network convergence speed.

This invention discloses a multi-degree-of-freedom control system based on surface micro-electrical signals, comprising: an electromyography (EMG) signal acquisition module for acquiring surface EMG signals; a signal preprocessing module for preprocessing the acquired EMG signals; a feature extraction module for calculating the optimal parameters of multi-scale permutation entropy using a particle swarm optimization algorithm for the preprocessed signals; and based on the optimal parameters, performing multi-scale permutation entropy feature extraction on the preprocessed EMG signals to obtain feature data of the EMG signals; a signal classification module for classifying the EMG signals according to the feature dataset; and a feature matching module for matching the classified signals with preset actions. This invention solves the problem of limited application scenarios and efficiency of existing surface EMG signal-controlled robotic arms, which is caused by the low degree of freedom of the robotic arm.