Deep Learning-Based Diagnosing Structural Behavior in Dam Safety Monitoring System

Collecting a myriad of prototype data through various types of monitoring sensors plays a virtual important role in many aspects of dam safety such as real-time grasp of safety state, exposure of hidden dangers, and inspection design and construction. However, the current methods of prediction are weak in the long-term sequence of nodes with missing and abnormal error value. Moreover, the limitation caused by the apparatus, environmental factors, and network transmission can lead to the deviation and inconsistency of diagnosis and evaluation of local region. In this paper, we consider the correlation of data on nodes in the entire monitoring network. To avoid the deviation caused by noise and missing value in the single-node data sequence, we calculate the correlation between the multiple sequences. A single-node assessment model based on multiple relevant sequence (SAM) is proposed to improve the accuracy of single node assessment. Given the different nodes of a local region have varying impacts on the evaluation results, a local region evaluation algorithm based on node credibility (LREA) is presented to model the credibility of nodes in order to alleviate inconsistent evaluation results in the local region of dam. LREA can assess the dam’s operation state by considering the variations in credibility and multiple nodes coordination. The experimental results illustrate the LREA can reveal the trends of the monitoring values change in a timely and accurate way, which can elevate the accuracy of evaluation results of dam safety

A stick-slip/inchworm hybrid rotary piezo motor based on a symmetric triangular driving mechanism

A stick-slip/inchworm hybrid rotary piezomotor based on a symmetric triangular driving mechanism, which can simultaneously achieve the benefits of both stick-slip and inchworm motors, was reported in this letter. It is based on the principle of stick-slip motors, and, inspired by the clamping-releasing actions from inchworm motors, it employs a symmetric triangular driving mechanism to generate a clamping action during the stick phase and a releasing action during the slip phase. Compared with stick-slip motors, it involves a clamping action during the stick phase and a releasing action during the slip phase, thus resulting in a larger driving force. Compared with inchworm motors, which require active control and coordination of clamping/releasing modules with feeding modules, it involves the control and operation of only one feeding piezoactuator without any actively controlled clamping/releasing module. Therefore, the control is easier, and a much larger operation frequency and driving speed can be achieved. Under the sawtooth waveform voltage of 90 V at 2600 Hz with a self-holding torque of 4 N m, the prototype achieved a no-load speed higher than 0.6 rad/s, a load torque capacity larger than 1.8 N m, and a weight carrying capacity more than 100 kg for both clockwise and anticlockwise directions. Compared with load torque capacity and weight carrying capacity in the reported stick-slip and inchworm rotary piezomotors, the current levels in terms of the same driving speed have been improved over 60 times and 12 times, respectively, in the proposed hybrid motor