Multi-mode industrial soft sensor method based on mixture Laplace variational auto-encoder

The industrially collected process data usually exhibit non-Gaussian and multi-mode characteristics. Due to sensor failures, irregular disturbances, and transmission problems, there are unavoidable outliers that make the data exhibit heavy-tailed characteristics. To this end, a variational auto-encoder regression method based on the mixture...

A gridded air quality forecast through fusing site-available machine learning predictions from RFSML v1.0 and chemical transport model results from GEOS-Chem v13.1.0 using the ensemble Kalman filter

Statistical methods, particularly machine learning models, have gained significant popularity in air quality predictions. These prediction models are commonly trained using the historical measurement datasets independently collected at the environmental monitoring stations and their operational forecasts in advance using inputs of the real-time...

A Multi-Task Learning Based Runoff Forecasting Model for Multi-Scale Chaotic Hydrological Time Series

Accurately predicting runoff is crucial for managing water resources, preventing and mitigating floods, scheduling hydropower plant operations, and protecting the environment. The hydrological dynamic composite system that forms runoff is complex and random, and seemingly random behavior may be caused by nonlinear variables in a simple...

4DEnVar-based inversion system for ammonia emission estimation in China through assimilating IASI ammonia retrievals

Atmospheric ammonia has been hazardous to the environment and human health for decades. Current inventories are usually constructed in a bottom-up manner and subject to uncertainties and incapable of reproducing the spatiotemporal characteristics of ammonia emission. Satellite measurements, for example, Infrared Atmospheric Sounder...

Inverse modeling of the 2021 spring super dust storms in East Asia

Last spring, super dust storms reappeared in East Asia after being absent for one and a half decades. The event caused enormous losses in both Mongolia and China. Accurate simulation of such super sandstorms is valuable for the quantification of health damage, aviation risks, and profound impacts on the Earth system, but also to reveal the...

Application of YOLOv4 Algorithm for Foreign Object Detection on a Belt Conveyor in a Low-Illumination Environment

The most common failures of belt conveyors are runout, coal piles and longitudinal tears. The detection methods for longitudinal tearing are currently not particularly effective. A key study area for minimizing longitudinal belt tears with the advancement of machine learning is how to use machine vision technology to detect foreign items on...

Effects of the pre-absorption of superabsorbent polymers and the water-cement ratio of paste on the adsorption-desorption of superabsorbent polymers: an NMR study

As an internal curing material, superabsorbent polymers (SAPs) can effectively reduce the risk of volume shrinkage of cement-based materials. By preparing the cement paste mixed with SAPs, the amount of pre-absorbed water and the water-cement ratio of paste on the water absorption-release behavior in the fresh cement paste were studied by using...

Characteristics of fly ash blended mortars under ammonium chloride solution leaching

Characteristics of fly ash(FA) blended mortars (50%, 70% and 90%) at different curing ages (28 days and 180 days) under ammonium chloride solution(ACS) leaching were investigated. Mass loss under leaching, initial CaO content, Ca(OH)2 content(CH), content of chemical bonded water, and hydration degree of blended pastes were tested by XRF and DSC...

The dead line for oil and gas and implication for fossil resource prediction

Fossil fuel resources are invaluable to economic growth and social development. Understanding the formation and distribution of fossil fuel resources is critical for the search and exploration of them. Until now, the vertical distribution depth of fossil fuel resources has not been confirmed due to different understandings of their origins...

Research on Bearing Fault Diagnosis Method Based on Filter Features of MOMLMEDA and LSTM

As the supporting unit of rotating machinery, bearing can ensure efficient operation of the equipment. Therefore, it is very important to monitor the status of bearings accurately. A bearing fault diagnosis mothed based on Multipoint Optimal Minimum Local Mean Entropy Deconvolution Adjusted (MOMLMEDA) and Long Short-Term Memory (LSTM) is...

Research of planetary gear fault diagnosis based on permutation entropy of CEEMDAN and ANFIS

For planetary gear has the characteristics of small volume, light weight and large transmission ratio, it is widely used in high speed and high power mechanical system. Poor working conditions result in frequent failures of planetary gear. A method is proposed for diagnosing faults in planetary gear based on permutation entropy of Complete...

Planetary gear fault diagnosis via feature image extraction based on multi central frequencies and vibration signal frequency spectrum

Poor working environment leads to frequent failures of planetary gear trains. However, complex structure and variable transmission make the vibration signal strongly non-linear and non-stationary, which brings big problems to fault diagnosis. A method of planetary gear fault diagnosis via feature image extraction based on multi central...

Copper adparticle enabled selective electrosynthesis of n-propanol

The electrochemical reduction of carbon monoxide is a promising approach for the renewable production of carbon-based fuels and chemicals. Copper shows activity toward multi-carbon products from CO reduction, with reaction selectivity favoring two-carbon products; however, efficient conversion of CO to higher carbon products such as n...

Binaural Sound Localization Based on Reverberation Weighting and Generalized Parametric Mapping

Binaural sound source localization is an important technique for speech enhancement, video conferencing, and human-robot interaction, etc. However, in realistic scenarios, the reverberation and environmental noise would degrade the precision of sound direction estimation. Therefore, reliable sound localization is essential to practical...

Research on conditional characteristics vision real-time detection system for conveyor belt longitudinal tear

Conveyor belt longitudinal tear is one of the most serious problems in coal mining. Existing systems cannot realise lossless and real-time detection for longitudinal tear of conveyor belt. Currently, visual detecting systems are proposed by many researchers and are becoming the future trend. A visual recognition system based on using laser...