34 research outputs found
Electrothermal combined optimization on notch in air-cooled high-speed permanent-magnet generator
A 30kVA, 96000rpm, air cooled high-speed permanent magnetic generator (HSPMG) is investigated in this paper. Considering effects on both the magnetic circuit and heat transfer paths comprehensively, the stator slot notch in this HSPMG is optimized. First, by using the time-stepping finite element method, the transient electromagnetic fields of HSPMG is numerically calculated, and the electromagnetic losses in different components are obtained. Then, after the determination of other mechanical losses in such a machine, a three-dimensional fluid-thermal coupling calculation model is established, and the working temperature distribution in the HSPMG is studied. Thus, the electromagnetic-fluid-thermal coupling analysis method on the HSPMG is proposed, by using which the influences of machine notch height on machine magnetic circuit and cooling air flowing path are investigated. Meanwhile, both the electromagnetic performance and the temperature distribution in HSPMG with different stator notch height are studied, and a series of analytical equations are deduced to describe the variations of machine performances with stator notch. By using the proposed unbalance relative weighting method, the notch height is optimized to enhance the performance of HSPMG. The obtained conclusions could provide reference for HSPMG electromagnetic calculation, cooling system design, and optimization design
Forest cover maps of China in 2010 from multiple approaches and data sources: PALSAR, Landsat, MODIS, FRA, and NFI
Turning Video Resource Management into Cloud Computing
Big data makes cloud computing more and more popular in various fields. Video resources are very useful and important to education, security monitoring, and so on. However, issues of their huge volumes, complex data types, inefficient processing performance, weak security, and long times for loading pose challenges in video resource management. The Hadoop Distributed File System (HDFS) is an open-source framework, which can provide cloud-based platforms and presents an opportunity for solving these problems. This paper presents video resource management architecture based on HDFS to provide a uniform framework and a five-layer model for standardizing the current various algorithms and applications. The architecture, basic model, and key algorithms are designed for turning video resources into a cloud computing environment. The design was tested by establishing a simulation system prototype
The application of improved association rules data mining algorithm Apriori in CRM
Based on Customer Relationship Management System of ShanHua Carpet Company, this paper introduces an improved Data Mining Association Rules Apriori Algorithm and its deployment to Shanhua group Cross-selling analysis. The deployment of the Apriori algorithm deletes lots of invalid business, reduces the records for the following scanning, which raises the efficiency of data mining. At the same time, with the deduction of the business, the scale of database will also decrease. Consequently, the scanning time will be saved and the processing efficiency will be enhanced
Phenology-Based Method for Mapping Tropical Evergreen Forests by Integrating of MODIS and Landsat Imagery
Updated extent, area, and spatial distribution of tropical evergreen forests from inventory data provides valuable knowledge for research of the carbon cycle, biodiversity, and ecosystem services in tropical regions. However, acquiring these data in mountainous regions requires labor-intensive, often cost-prohibitive field protocols. Here, we report about validated methods to rapidly identify the spatial distribution of tropical forests, and obtain accurate extent estimates using phenology-based procedures that integrate the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat imagery. Firstly, an analysis of temporal profiles of annual time-series MODIS Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Land Surface Water Index (LSWI) was developed to identify the key phenology phase for extraction of tropical evergreen forests in five typical lands cover types. Secondly, identification signatures of tropical evergreen forests were selected and their related thresholds were calculated based on Landsat NDVI, EVI, and LSWI extracted from ground true samples of different land cover types during the key phenology phase. Finally, a map of tropical evergreen forests was created by a pixel-based thresholding. The developed methods were tested in Xishuangbanna, China, and the results show: (1) Integration of Landsat and MODIS images performs well in extracting evergreen forests in tropical complex mountainous regions. The overall accuracy of the resulting map of the case study was 92%; (2) Annual time series of high-temporal-resolution remote sensing images (MODIS) can effectively be used for identification of the key phenology phase (between Julian Date 20 and 120) to extract tropical evergreen forested areas through analysis of NDVI, EVI, and LSWI of different land cover types; (3) NDVI and LSWI are two effective metrics (NDVI ≥ 0.670 and 0.447 ≥ LSWI ≥ 0.222) to depict evergreen forests from other land cover types during the key phenology phase in tropical complex mountainous regions. This method can make full use of the Landsat and MODIS archives as well as their advantages for tropical evergreen forests geospatial inventories, and is simple and easy to use. This method is suggested for use with other similar regions
The Mechanism of the Effect of Al2O3 Content on the Liquid Phase Fluidity of Iron Ore Fines
The sintering process is significantly important for the ironmaking in China because of the large amount of sinter consumed. Al2O3 is an important element determining the quality and quantity of sinter. However, different conclusions have been made regarding the effects of Al2O3 on the amount and fluidity of the liquid phase formed in the sinter phase. Therefore, it is necessary to examine the effects of Al2O3 content on the amount and fluidity of the liquid phase. The present work investigated the effects of different Al2O3 contents of iron ore fines on the liquid phase formation, mineral composition, and consolidation strength. The results showed that a small amount of Al2O3 increased the amount of calcium ferrite, making the liquid phase formation easier. As the Al2O3 content in iron ore fines increased, the liquidity index decreased continuously, while the fluidity and the consolidation strength of the sintered body were directly related to the content squared. The quality of the sinter is optimal when the Al2O3 content of the iron ore fines is about 2 wt % (the SiO2 content is 4 wt %)
Phenology-Based Method for Mapping Tropical Evergreen Forests by Integrating of MODIS and Landsat Imagery
The pruning phenological phase-based method for extracting tea plantations by field hyperspectral data and Landsat time series imagery
Tea plantations expansion has occurred in the major tea planting area of Yunnan province, China, however, it is a big challenge to extract and map the distribution of tea plantations due to their non-obvious phenological characteristics in the tropical and subtropical regions. Firstly, we demonstrated the pruning phenological phase of tea plantations by using field hyperspectral data. Secondly, we analyzed the optical features of typical land cover types from the available time series Landsat imagery with the Google Earth Engine (GEE) platform. We proposed a pixel and phenology- based approach to extract and map tea plantations distribution at the 30-m resolution of the historical time period of 2015 to 2019. The resultant map had high user/producer accuracies of 91.07% and 86.90%, respectively. Our study provides a promising new approach to extract and map tea plantations in complex tropical landscapes at fine spatial resolution by using only free historical Landsat imagery
The dynamics of tea plantation encroachment into forests and effect on forest landscape pattern during 1991–2021 through time series Landsat images
Tea plantations encroachment into forests has occurred in the major tea planting area of Yunnan province, China in the past decades. However, the dynamics of tea plantation encroachment into forests and the effect on forest landscape pattern is not clear. In this study, we proposed a method to evaluate the dynamic effects of tea plantation encroachment on forest landscape pattern change by using time series Landsat 5/7/8 data from 1991 to 2021 on the Google Earth Engine (GEE) platform. First, a pixel- and phenology-based algorithm was applied to generate tea plantations encroachment into forests maps for seven historical periods. Second, three indices including the tea plantations encroachment index (TPEI), the growth area of tea plantations encroachment into forests (GATEF), and the growth index of tea plantations encroachment into forests (GITEF) were used to quantify the tea plantations encroachment into forests of seven historical periods. Third, the effects of forests landscape pattern resulting from tea plantations encroachment were evaluated in class metrics and landscape metrics respectively. Our results show a total of 13,721 ha of GATEF from the early 1990s to the early 2020s. The GITEF increased from the early 1990s to the early 2010s and decreased from the early 2010s to the early 2020s in our study area. And the TPEI indicates that the edge encroachment mode dominated in our study period. Correlation analysis indicates that tea plantations encroachment level had significant correlation coefficients with landscape pattern indices (such as CONTAG (r = −0.91), ED (r = 0.95), DIVISION (r = 0.85), and SHEI (r = 0.86)), which indicates that the level of tea plantations encroachment affects significantly the forest landscape pattern. This study provides a promising approach to quantifying the effect of forest landscape pattern results from tea plantations encroachment
Mapping Deciduous Rubber Plantation Areas and Stand Ages with PALSAR and Landsat Images
Accurate and updated finer resolution maps of rubber plantations and stand ages are needed to understand and assess the impacts of rubber plantations on regional ecosystem processes. This study presented a simple method for mapping rubber plantation areas and their stand ages by integration of PALSAR 50-m mosaic images and multi-temporal Landsat TM/ETM+ images. The L-band PALSAR 50-m mosaic images were used to map forests (including both natural forests and rubber trees) and non-forests. For those PALSAR-based forest pixels, we analyzed the multi-temporal Landsat TM/ETM+ images from 2000 to 2009. We first studied phenological signatures of deciduous rubber plantations (defoliation and foliation) and natural forests through analysis of surface reflectance, Normal Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Land Surface Water Index (LSWI) and generated a map of rubber plantations in 2009. We then analyzed phenological signatures of rubber plantations with different stand ages and generated a map, in 2009, of rubber plantation stand ages (≤5, 6–10, >10 years-old) based on multi-temporal Landsat images. The resultant maps clearly illustrated how rubber plantations have expanded into the mountains in the study area over the years. The results in this study demonstrate the potential of integrating microwave (e.g., PALSAR) and optical remote sensing in the characterization of rubber plantations and their expansion over time