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Process monitoring plays a vital role in order to sustain optimal operation and maintenance of the plant in process industry. As an essential stage in process monitoring, datadriven fault detection and diagnosis techniques have evolved quickly owing to the prosperity of multivariate feature extraction methods. In addition to the application of basic feature extraction methods, hybrid algorithms combining...
A visibility-culling-based geometric rendering algorithm is proposed in this paper so as to visualize large-scale particle data efficiently. In the algorithm, the particles are culled based on their visibility at two granularities. All data patches beyond the OpenGL view frustum are firstly thrown away as a coarse culling. And then, the remaining particles will be judged their visibility based on...
Finding the unknown laws of sciences among data is one of the most essential goals in modern scientific discoveries. Visualization can be a useful tool for domain scientists to understand data if these data can be interactive rendered. But interactive rendering and exploring of these massive, complex data sets has been identified as one of the major challenges in current scientific visualization field...
The scale of some datasets generated by simulations on tens of thousands of cores are gigabyte or larger per output step. It is imperative that efficient coupling of these simulations and parallel visualization. Therefore, a patch-based parallel I/O strategy has been designed and implemented in JASMIN. These programs reconstructed or developed on JASMIN can write plotting data in many files. These...
Nowadays benefiting from the powerful computational capacity of the high performance computers, simulation of filamentation in laser plasma interaction(LPI) produces more than terabyte data, which makes traditional visualization ways inefficient and moreover, incapable of discovering more interior information. An analysis method based on signal processing and clustering technique proposed in the paper...
The distributed-memory parallel computer has become the most popular platform for the parallel acceleration of numerical simulations in scientific computing area. However, complex system characteristics and large-scale time-varying data produced on such environment present tremendous challenges for convenient data analyzing. A visualization system framework is introduced in this paper, which can be...
In this letter, a new method for nonlinear behavioral modeling of high-speed I/O drivers is presented, combining neural networks with driver specific circuit knowledge. In the proposed technique, the circuit knowledge of the driver is exploited to preserve the physical property of the driver. In addition, several neural network sub-models are incorporated into the overall model structure to effectively...
Operation temperature of a molten carbonate fuel cell stack should be controlled within a special range in order to improve availability and performance of fuel cells. In this paper, a predictive control algorithm based on the Takagi-Sugeno fuzzy model is developed for the temperature of a molten carbonate fuel cell stack. Based on the future outputs predicted by a Takagi-Sugeno fuzzy model, a discrete...
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