Breeze-activated wind speed sensor with ultra-low friction resistance for self-powered gale disaster warning

The early warning and monitoring of gale disasters are very important for the safety of people’s lives and properties. Triboelectric nanogenerators(TENGs) are popular for wind speed sensors due to their self-powered property. However, a TENG cannot easily work at low wind speeds due to the limitation of the high frictional resistance structure. In this paper, a TENG-based breezeactivated wind speed sensor(BAWS) with an ultra-low frictional resistance is proposed. The key drive unit of the BAWS is a Savonius-like vertical axis wind turbine, which is fabricated by arrayed airfoil profile blades with excellent flow field characteristics. Here a wind turbine plays dual roles in driving the electromagnetic generator below it to supply energy and lead the TENG above it to sense the wind force. Compared to a classical turbine with a wind cup, the designed turbine has a low resistance torque. The synergistic effect of the drive unit with low-resistance and triboelectric materials with low viscosity allows the BAWS to be activated even at a wind speed of 2.9 m/s. The sensitivities of the voltage frequency and current amplitude of the TENG are used to reflect the electrical property of the BAWS. The measured values are 0.291 Hz/(m·s-1) and 0.221 μA/(m·s-1),which reflects the good sensitivity of the BAWS. Moreover, the linearity of the BAWS reaches up to 0.991, which shows an accurate output for the wind speed. In addition, the device is equipped with a combined electromagnetic-solar unit as the sole power source to meet the sensor’s all-weather operation requirements. This work expands the application prospects of selfpowered sensing technology in the field of disaster warning.

Design and Realization of Cold Disaster Early Warning System for Subtropics Aquaculture

By analyzing the subtropics aquaculture present situation,the necessity of the construction of cold disaster early warning system for subtropics aquaculture,the research goal and the duty were expounded. The system structure and the frame were introduced in detail. Several key questions and their solutions of the cold disaster early warning system for subtropics aquaculture were put forward.

Natural disaster warning system for safe operation of a high-speed railway

In this paper,the least square support vector machine(LSSVM)is used to study the safety of a high-speed railway.According to the principle of LSSVM regression prediction,the parameters of the LSSVM are optimized to model the natural disaster early warning of safe operation of a high-speed railway,and the management measures and methods of high-speed railway safety operation under natural disasters are given.The relevant statistical data of China’s high-speed railway are used for training and verification.The experimental results show that the LSSVM can well reflect the nonlinear relationship between the accident rate and the influencing factors,with high simulation accuracy and strong generalization ability,and can effectively predict the natural disasters in the safe operation of a high-speed railway.Moreover,the early warning system can improve the ability of safety operation evaluation and early warning of high-speed railway under natural disasters,realize the development goals of high-speed railway(safety,speed,economic,low-carbon and environmental protection)and provide a theoretical basis and technical support for improving the safety of a high-speed railway.

Development and Application of Meteorological Disaster Monitoring and Early Warning Platform for Characteristic Agriculture in Huzhou City Based on GIS

Based on the needs of characteristic agricultural production for meteorological services in Huzhou City,we use C# programming language to develop the meteorological disaster monitoring and early warning platform for characteristic agriculture in Huzhou City. This platform integrates the functions of meteorological and agricultural information monitoring,disaster identification and early warning,fine weather forecast product display,and data query and management,which effectively enhances the capacity of meteorological disaster monitoring and early warning for characteristic agriculture in Huzhou City,and provides strong technical support for the meteorological and agricultural departments in the agricultural meteorological services.

Cluster analysis of the domain of microseismic event attributes for fl oor water inrush warning in the working face

Differences are found in the attributes of microseismic events caused by coal seam rupture,underground structure activation,and groundwater movement in coal mine production.Based on these differences,accurate classification and analysis of microseismic events are important for the water inrush warning of the coal mine working facefloor.Cluster analysis,which classifies samples according to data similarity,has remarkable advantages in nonlinear classification.A water inrush early warning method for coal minefloors is proposed in this paper.First,the short time average over long time average(STA/LTA)method is used to identify effective events from continuous microseismic records to realize the identification of microseismic events in coal mines.Then,ten attributes of microseismic events are extracted,and cluster analysis is conducted in the attribute domain to realize unsupervised classification of microseismic events.Clustering results of synthetic andfield data demonstrate the effectiveness of the proposed method.The analysis offield data clustering results shows that thefirst kind of events with time change rules is of considerable importance to the early warning of water inrush from the coal mine working facefloor.

Developments and prospects of microseismic monitoring technology in underground metal mines in China

Microseismic monitoring technology has become an important technique to assess stability of rock mass in metal mines.Due to the special characteristics of underground metal mines in China,including the high tectonic stress,irregular shape and existence of ore body,and complex mining methods,the application of microseismic technology is more diverse in China compared to other countries,and is more challenging than in other underground structures such as tunnels,hydropower stations and coal mines.Apart from assessing rock mass stability and ground pressure hazards induced by mining process,blasting,water inrush and large scale goaf,microseismic technology is also used to monitor illegal mining,and track personnel location during rescue work.Moreover,microseismic data have been used to optimize mining parameters in some metal mines.The technology is increasingly used to investigate cracking mechanism in the design of rock mass supports.In this paper,the application,research development and related achievements of microseismic technology in underground metal mines in China are summarized.By considering underground mines from the perspective of informatization,automation and intelligentization,future studies should focus on intelligent microseismic data processing method,e.g.,signal identification of microseismic and precise location algorithm,and on the research and development of microseismic equipment.In addition,integrated monitoring and collaborative analysis for rock mass response caused by mining disturbance will have good prospects for future development.

Natural Disasters Warning for Enterprises Through Fuzzy Keywords Search

With the ever-increasing number of natural disasters warning documents in document databases, the document database is becoming an economic and efficient way for enterprise staffs to learn and understand the contents of the natural disasters warning through searching for necessary text documents. Generally, the document database can recommend a mass of documents to the enterprise staffs through analyzing the enterprise staff's precisely typed keywords. In fact, these recommended documents place a heavy burden on the enterprise staffs to learn and select as the enterprise staffs have little background knowledge about the contents of the natural disasters warning. Thus, the enterprise staffs fail to retrieve and select appropriate documents to achieve their desired goals.Considering the above drawbacks, in this paper, we propose a fuzzy keywords-driven Natural Disasters Warning Documents retrieval approach(named NDWDkeyword). Through the text description mining of documents and the fuzzy keywords searching technology, the retrieval approach can precisely capture the enterprise staffs' target requirements and then return necessary documents to the enterprise staffs. Finally, a case study is run to explain our retrieval approach step by step and demonstrate the effectiveness and feasibility of our proposal.