3results about How to "Excellent decomposability" patented technology

According to the aerosol generating product capable of being rapidly degraded and the preparation method of the aerosol generating product, a biodegradable fuming section, a biodegradable supporting section, a biodegradable cooling section and a biodegradable filtering section are formed by designing and matching specific biodegradable materials for four functional sections of the aerosol generating product respectively; the whole section of the aerosol generating product is completely biodegradable; the whole aerosol generating product can be effectively decomposed by microorganisms under the natural environment or industrial compost condition after being used, and is finally converted into carbon dioxide, water and biomass, so that the problem of persistent plastic pollution caused by cigarette waste is completely eradicated from the source, and the minimum influence of the whole life cycle of the product on the environment is realized; the global trend of circular economy and sustainable development is positively responded.

According to the building energy consumption prediction method and system based on multi-frequency characteristic decomposition and double-branch modeling provided by the invention, a complete ensemble empirical mode decomposition (CEEMDAN) adaptive noise algorithm is introduced to perform multi-scale decomposition on a building energy consumption signal, so that the decomposability and the signal stability of an original energy consumption sequence are greatly improved. The CEEMDAN decomposition mechanism ensures that different frequency components are effectively distinguished before modeling, and the problems of mode aliasing and feature distortion caused by direct modeling of non-stationary signals are avoided. And through an adaptive grouping strategy based on variance entropy, the decomposed signals are automatically classified and reconstructed, so that high-frequency disturbance and low-frequency trend can be modeled in a targeted manner, and the feature expression ability and generalization performance of the model are further improved.

This invention relates to the field of dynamic disturbance measurement technology, specifically to a method and apparatus for measuring vertical dynamic disturbance of high-speed railway bridges. The method involves taking a subsequence at each sampling moment in the vertical displacement time series at a key section of the bridge, using a sliding window centered on that moment, and identifying local extreme points. The extreme point density and amplitude dispersion are determined based on these local extreme points. The extreme point density and amplitude dispersion are processed to obtain normalized distortion. An adaptive threshold is constructed based on the normalized distortion. The sequence or the unprocessed residual components from the previous decomposition are used as the signal to be decomposed, and iterative sieving is performed to extract intrinsic mode functions (EMFs). Each sieving iteration calculates the local deviation. If the local deviation is less than the adaptive threshold and meets preset constraints, the iteration terminates and the EMF is output. The obtained EMFs are used to reconstruct the signal, resulting in the vertical dynamic disturbance waveform, thereby improving the accuracy of vertical dynamic disturbance measurement.