Multi–physical-field characteristics modeling and structure optimization for kW-level ultra-high-speed PM motors with integrated support system

In the aerospace industry,the low-mass ultra-high-speed flywheel system play a critical role.In this paper,a kW-level Ultra-High Speed Permanent Magnet Synchronous Motor(UHSPMSM)as the core component of flywheel system is proposed and analyzed with consideration of multiple physical fields,including electromagnetic characteristics,mechanical strength and rotor dynamics.The integrated support structure is put forward to improve rotation accuracy and operation stability of the UHSPMSM.Further,influence of the integrated support structure on critical speed is explored,and the key parameters such as support position and support stiffness are designed.Moreover,the rotor strength is analyzed by analytical model developed of rotor stress that can deal with multiple boundary types.Material and thickness of the sleeve are optimized,and range of interference value is accurately limited based on four extreme operating conditions.The 3-D Finite Element Model(FEM)is used to validate the strength characteristics and stress distribu-tion of rotor.A 1.5 kW-150000 r/min UHSPMSM with integrated support system is manufactured and tested.The feasibility of UHSPMSM proposed and the accuracy of analysis method are verified through electromagnetic,temperature rise and vibration characteristics test.The machine prototype realizes the load operation at rated speed and the multi-physical-field characteristics achieve the design specification.

Location and allocation problem for spare parts depots on integrated logistics support

In equipment integrated logistics support(ILS), the supply capability of spare parts is a significant factor. There are lots of depots in the traditional support system, which makes too many redundant spare parts and causes high cost of support. Meanwhile,the inconsistency among depots makes it difficult to manage spare parts. With the development of information technology and transportation, the supply network has become more efficient. In order to further improve the efficiency of supply-support work and the availability of the equipment system, building a system of one centralized depot with multiple depots becomes an appropriate way.In this case, location selection of the depots including centralized depots and multiple depots becomes a top priority in the support system. This paper will focus on the location selection problem of centralized depots considering ILS factors. Unlike the common location selection problem, depots in ILS require a higher service level. Therefore, it becomes desperately necessary to take the high requirement of the mission into account while determining location of depots. Based on this, we raise an optimal depot location model. First, the expected transportation cost is calculated.Next, factors in ILS such as response time, availability and fill rate are analyzed for evaluating positions of open depots. Then, an optimization model of depot location is developed with the minimum expected cost of transportation as objective and ILS factors as constraints. Finally, a numerical case is studied to prove the validity of the model by using the genetic algorithm. Results show that depot location obtained by this model can guarantee the effectiveness and capability of ILS well.

An Integrated Information Retrieval Support System for Campus Network

This paper presents a new integrated information retrieval support system （IIRSS） which can help Web search engines retrieve cross-lingual information from hereto geneous resources stored in multi-databases in Intranet. The IIRSS, with a three-layer architecture, can cooperate with other application servers running in Intranet. By using intelligent agents to collect information and to create indexes on the-fly, using an access control strategy to confine a user to browsing those accessible documents for him/her through a single portal, and using a new cross-lingual translation tool to help the search engine retrieve documents, the new system provides controllable information access with different authorizations, personalized services, and real-time information retrieval.

An anomaly detection method for spacecraft solar arrays based on the ILS-SVM model

Solar arrays are important and indispensable parts of spacecraft and provide energy support for spacecraft to operate in orbit and complete on-orbit missions.When a spacecraft is in orbit,because the solar array is exposed to the harsh space environment,with increasing working time,the performance of its internal electronic components gradually degrade until abnormal damage occurs.This damage makes solar array power generation unable to fully meet the energy demand of a spacecraft.Therefore,timely and accurate detection of solar array anomalies is of great significance for the on-orbit operation and maintenance management of spacecraft.In this paper,we propose an anomaly detection method for spacecraft solar arrays based on the integrated least squares support vector machine(ILS-SVM)model:it selects correlated telemetry data from spacecraft solar arrays to form a training set and extracts n groups of training subsets from this set,then gets n corresponding least squares support vector machine(LS-SVM)submodels by training on these training subsets,respectively;after that,the ILS-SVM model is obtained by integrating these submodels through a weighting operation to increase the prediction accuracy and so on;finally,based on the obtained ILS-SVM model,a parameterfree and unsupervised anomaly determination method is proposed to detect the health status of solar arrays.We use the telemetry data set from a satellite in orbit to carry out experimental verification and find that the proposed method can diagnose solar array anomalies in time and can capture the signs before a solar array anomaly occurs,which reflects the applicability of the method.

Using Linked Data in a heterogeneous Sensor Web: challenges, experiments and lessons learned

Abundant sensor data are now available online from a wealth of sources,which greatly enhance research efforts on the Digital Earth.The combination of distributed sensor networks and expanding citizen-sensing capabilities provides a more synchronized image of earth’s social and physical landscapes.However,it remains difficult for researchers to use such heterogeneous Sensor Webs for scientific applications since data are published by following different standards and protocols and are in arbitrary formats.In this paper,we investigate the core challenges faced when consuming multiple sources for environmental applications using the Linked Data approach.We design and implement a system to achieve better data interoperability and integration by republishing real-world data into linked geo-sensor data.Our contributions include presenting:(1)best practices of re-using and matching the W3C Semantic Sensor Network(SSN)ontology and other popular ontologies for heterogeneous data modeling in the water resources application domain,(2)a newly developed spatial analysis tool for creating links,and(3)a set of RESTful OGC Sensor Observation Service(SOS)like Linked Data APIs.Our results show how a Linked Sensor Web can be built and used within the integrated water resource decision support application domain.