A Fault Diagnosis Scheme for Gearbox Based on Improved Entropy and Optimized Regularized Extreme Learning Machine

The performance of a gearbox is sensitive to failures, especially in the long-term high speed and heavy load field. However, the multi-fault diagnosis in gearboxes is a challenging problem because of the complex and non-stationary measured signal. To obtain fault information more fully and improve the accuracy of gearbox fault diagnosis, this paper proposes a feature extraction method, hierarchical refined composite multiscale fluctuation dispersion entropy (HRCMFDE) to extract the fault features of rolling bearing and the gear vibration signals at different layers and scales. On this basis, a novel fault diagnosis scheme for the gearbox based on HRCMFDE, ReliefF and grey wolf optimizer regularized extreme learning machine is proposed. Firstly, HRCMFDE is employed to extract the original features, the multi-frequency time information can be evaluated simultaneously, and the fault feature information can be extracted more fully. After that, ReliefF is used to screen the sensitive features from the high-dimensional fault features. Finally, the sensitive features are inputted into the optimized regularized extreme learning machine to identify the fault states of the gearbox. Through three different types of gearbox experiments, the experimental results confirm that the proposed method has better diagnostic performance and generalization, which can effectively and accurately identify the different fault categories of the gearbox and outperforms other contrastive methods.</p

Fault Diagnosis Method of Intelligent Substation Protection System Based on Gradient Boosting Decision Tree

In order to improve the efficiency of the devices’ fault diagnosis of the protection systems of intelligent substation, a fault diagnosis method based on a gradient boosting decision tree (GBDT) was proposed. Using the integrated alarm information, the device self-checking information, the link information of generic object-oriented substation event (GOOSE) and sampled value (SV) and the sampling value information generated during the fault of the protection system, the fault feature information set is constructed. According to different fault characteristics, the protection system faults are classified into simple faults and complex faults to improve the diagnosis efficiency. Using GBDT training rules, a fault diagnosis model of protection system based on GBDT is established and fault diagnosis steps are given. This study takes a 110 kV intelligent substation in southern China as an example, to verify the effectiveness and accuracy of the proposed fault diagnosis method, and compared it with the existing methods in terms of the accuracy. The diagnostic accuracy in the case of false alarms and the case of multiple faults are verified. The results show that the method can meet the practical engineering application

Data collected in an integrated ecological survey of rotifer communities and corresponding environmental variables in the highly polluted Haihe River Basin, China

Here we presented two datasets (biological and environmental datasets) collected in a comprehensive large geographical scale (approximately 1.1×105 km2) survey of rivers/streams in the Haihe River Basin (HRB), which has become the most polluted river basin in past two decades in China. The survey selected a total of 94 representative sampling sites in the plain region of HRB, where environmental pollution is more severe than the mountain region. The biological dataset contains the information on the identified rotifer species and their abundance, while the environmental dataset provides the measured environmental variables at each sampling site. Based on this ecological survey, we identified a total of 91 rotifer species and their abundance, as well as abundance of two crucial taxonomic groups on rotifers’ food webs (i.e., protozoans and crustaceans), and also presented seven environmental variables, particularly those associated with nitrogen and phosphorus pollution. Keywords: Environmental pollution, Nitrogen, Phosphorus, Rotifer, Strea

A Wide-Area Measurement System-Based Load Encroachment Identification Method Applicable to Power Systems with High Wind Power Penetration

One of the main factors in triggering cascading outages is the unexpected tripping of backup protection caused by load encroachment (LE). Hence, LE should be identified quickly to avoid unexpected tripping. This paper proposes a fast LE identification method based on the wide-area measurement system (WAMS), applicable to transmission grids with high wind power penetration. Firstly, based on the improved shortest path algorithm, the method searches for critical lines greatly affected by the LE to determine the collected range of wide-area information. Then, by analyzing the hidden dangers of the existing calculation method for the active power estimation value (APEV) in the power system with wind farms, a fast calculation method of the APEV based on the WAMS is proposed to ensure that the existing LE identification criterion is still applicable in the high-penetration system of wind power. Finally, based on the PSASP platform, the wind farm model is integrated into the IEEE 39-bus New England system for simulation. The simulation results show that the method proposed in this paper can quickly search for the critical line set (CLS) and accurately identify the LE under high wind power penetration, effectively avoiding the unexpected tripping of backup protection and preventing cascading outages

State Evaluation and Fault Prediction of Protection System Equipment Based on Digital Twin Technology

Digital twin technology aims to build a map of physical entities in virtual space, and simulate the real-time state and dynamic characteristics of physical devices through bi-directional interactive data flow. In order to guarantee the safe and stable operation of protection system equipment in intelligent substations and improve the efficiency of protection system operation and condition maintenance, this paper proposes a protection system state evaluation and fault prediction method based on digital twin technology. The architecture, application and operation control mode of digital twin technology in a real-time state analysis of a protection system are studied. The state evaluation model based on matter-element extension and the fault prediction model based on clustering algorithm are constructed. By analyzing the historical data of an intelligent station protection system in actual operation, a database that can be updated and corrected in real time is constructed. The effectiveness and accuracy of the state evaluation and fault prediction method are verified with actual cases, which can provide technical support for the operation and maintenance of the protection system

Research of the technology based on fiber bragg grating for measurement of temperature rise of electrical appliances

Conference Name:2012 International Meeting on Opto-Electronics Engineering and Materials Research, OEMR 2012. Conference Address: Shenyang, Liaoning, China. Time:July 27, 2012 - July 29, 2012.A new method of using fiber Bragg gratings as the sensing elements in the measurement of temperature rises of electrical appliances is proposed in this paper. Comparing with the conventional measurement method with thermocouples, the new method can overcome problems such as electromagnetic interference, hazard of electrical leakage, etc. The characteristics and key components employed in the measuring system are analyzed and discussed. The experimental results show that the temperature rises of electrical appliances under test can be obtained quickly and accurately with the specifically designed sensors made by optical fiber Bragg gratings. 漏 (2012) Trans Tech Publications, Switzerland

Controlled Shape Memory Behavior of a Smectic Main-Chain Liquid Crystalline Elastomer

A smectic main-chain liquid crystalline elastomer (LCE), with controlled shape memory behavior, is synthesized by polymerizing a biphenyl-based epoxy monomer with an aliphatic carboxylic acid curing agent. Microstructures of the LCEs, including their liquid crystallinity and cross-linking density, are modified by adjusting the stoichiometric ratio of the reactants to tailor the thermomechanical properties and shape memory behavior of the material. Thermal and liquid crystalline properties of the LCEs, characterized using differential scanning calorimetry and dynamic mechanical analysis, and structural analysis, performed using small-angle and wide-angle X-ray scattering, show that liquid crystallinity, cross-linking density, and network rigidity are strongly affected by the stoichiometry of the curing reaction. With appropriate structural modifications it is possible to tune the thermal, dynamic mechanical, and thermomechanical properties as well as the shape memory and thermal degradation behavior of LCEs

Quasi-free-standing epitaxial graphene on SiC (0001) by fluorine intercalation from a molecular source

10.1021/nn202910tACS Nano597662-766