Multi-fault diagnosis for rolling element bearings based on intrinsic mode function screening and optimized least squares support vector machine

Multi-fault diagnosis of rolling element bearing is significant to avoid serious accidents and huge economic losses effectively. However, due to the vibration signal with the character of nonstationarity and nonlinearity, the detection, extraction and classification of the fault feature turn into a challenging task. This paper presents a novel method based on redundant second generation wavelet packet transform (RSGWPT), ensemble empirical mode decomposition (EEMD) and optimized least squares support vector machine (LSSVM) for fault diagnosis of rolling element bearings. Firstly, this method implements an analysis combining RSGWPT-EEMD to extract the crucial characteristics from the measured signal to identify the running state of rolling element bearings, the vibration signal is adaptively decomposed into a number of modified intrinsic mode functions (modified IMFs) by two step screening processes based on the energy ratio; secondly, the matrix is formed by different level modified IMFs and singular value decomposition (SVD) is used to decompose the matrix to obtain singular value as eigenvector; finally, singular values are input to LSSVM optimized by particle swarm optimization (PSO) in the feature space to specify the fault type. The effectiveness of the proposed multi-fault diagnosis technique is demonstrated by applying it to both simulated signals and practical bearing vibration signals under different conditions. The results show that the proposed method is effective for the condition monitoring and fault diagnosis of rolling element bearings

Spatiotemporal distribution and prediction of chlorophyll-a in Ulansuhai lake from an arid area of China

Lake Ulansuhai, a typical shallow lake in an arid area that is economically and ecologically important along the Yellow River, is currently eutrophic. Long-term (2010–2020) data on chlorophyll-a, nutrient, and environmental factors were obtained from three Lake Ulansuhai monitoring stations. The temporal and spatial distribution characteristics of Chl-a were analyzed. Additionally, a hybrid evolutionary algorithm was established to simulate and predict Chl-a, and sensitivity analysis revealed the interaction between environmental factors and eutrophication. The results indicated that (1) the seasonal variation of eutrophication showed an obvious trend of spring > summer > autumn > winter, and the concentration of Chl-a in the inlet was significantly higher than that in the outlet; (2) The inlet, center, and outlet of Ulansuhai Lake are satisfactorily affected by HEA in the best suited method. The fitting coefficients (R2) of the optimal models were 0.58, 0.59, and 0.62 for the three monitoring stations, and the root mean square errors (RMSE) were 3.89, 3.21, and 3.56, respectively; (3) under certain range and threshold conditions, Chl-a increased with the increase of permanganate index, water temperature, dissolved oxygen concentration, and ammonia nitrogen concentration, but decreased with the increase of water depth, Secchi disk depth, pH, and fluoride concentration. The results indicate that the HEA can simulate and predict the dynamics of Chl-a, and identify and quantify the relationships between eutrophication and the threshold data. The research results provide theoretical basis and technical support for the prediction and have great significance for the improvement of water quality and environmental protection in arid and semi-arid inland lakes

Introduction to Special Issue - In-depth study of air pollution sources and processes within Beijing and its surrounding region (APHH-2 Beijing)

Abstract. The Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-Beijing) programme is an international collaborative project focusing on understanding the sources, processes and health effects of air pollution in the Beijing megacity. APHH-Beijing brings together leading China and UK research groups, state-of-the-art infrastructure and air quality models to work on four research themes: (1) sources and emissions of air pollutants; (2) atmospheric processes affecting urban air pollution; (3) air pollution exposure and health impacts; and (4) interventions and solutions. Themes 1 and 2 are closely integrated and support Theme 3, while Themes 1-3 provide scientific data for Theme 4 to develop cost-effective air pollution mitigation solutions. This paper provides an introduction to (i) the rationale of the APHH-Beijing programme, and (ii) the measurement and modelling activities performed as part of it. In addition, this paper introduces the meteorology and air quality conditions during two joint intensive field campaigns - a core integration activity in APHH-Beijing. The coordinated campaigns provided observations of the atmospheric chemistry and physics at two sites: (i) the Institute of Atmospheric Physics in central Beijing, and (ii) Pinggu in rural Beijing during 10 November – 10 December 2016 (winter) and 21 May- 22 June 2017 (summer). The campaigns were complemented by numerical modelling and automatic air quality and low-cost sensor observations in the Beijing megacity. In summary, the paper provides background information on the APHH-Beijing programme, and sets the scene for more focussed papers addressing specific aspects, processes and effects of air pollution in Beijing

An interlaboratory comparison of aerosol inorganic ion measurements by ion chromatography : Implications for aerosol pH estimate

Water-soluble inorganic ions such as ammonium, nitrate and sulfate are major components of fine aerosols in the atmosphere and are widely used in the estimation of aerosol acidity. However, different experimental practices and instrumentation may lead to uncertainties in ion concentrations. Here, an intercomparison experiment was conducted in 10 different laboratories (labs) to investigate the consistency of inorganic ion concentrations and resultant aerosol acidity estimates using the same set of aerosol filter samples. The results mostly exhibited good agreement for major ions Cl-, SO2-4, NO-3, NHC4 and KC. However, F-, Mg2C and Ca2C were observed with more variations across the different labs. The Aerosol Chemical Speciation Monitor (ACSM) data of nonrefractory SO2-4, NO-3 and NHC4 generally correlated very well with the filter-analysis-based data in our study, but the absolute concentrations differ by up to 42 %. Cl-from the two methods are correlated, but the concentration differ by more than a factor of 3. The analyses of certified reference materials (CRMs) generally showed a good detection accuracy (DA) of all ions in all the labs, the majority of which ranged between 90 % and 110 %. The DA was also used to correct the ion concentrations to showcase the importance of using CRMs for calibration check and quality control. Better agreements were found for Cl-, SO2-4, NO-3, NHC4 and KC across the labs after their concentrations were corrected with DA; the coefficient of variation (CV) of Cl-, SO2-4, NO-3, NHC4 and KC decreased by 1.7 %, 3.4 %, 3.4 %, 1.2 % and 2.6 %, respectively, after DA correction. We found that the ratio of anion to cation equivalent concentrations (AE/CE) and ion balance (anions-cations) are not good indicators for aerosol acidity estimates, as the results in different labs did not agree well with each other. In situ aerosol pH calculated from the ISORROPIA II thermodynamic equilibrium model with measured ion and ammonia concentrations showed a similar trend and good agreement across the 10 labs. Our results indicate that although there are important uncertainties in aerosol ion concentration measurements, the estimated aerosol pH from the ISORROPIA II model is more consistent

Influence and optimization of mooring angle in multi-point mooring positioning system

[Objectives] In this paper, a method for calculating the static restoring force of a mooring system is proposed in order to optimize the mooring angle and meet the strength requirements of mooring lines. [Methods] Using this method, a study is conducted on the influence of the mooring angle on the static restoring force and heading of the platform, and the tension uniformity of all mooring lines. An improved Genetic Algorithm (GA) is used to optimize the mooring angle, and the accuracy of the algorithm is enhanced in two ways:the first is that it can generate the initial population artificially by analyzing the influence of three factors(value of static restoring force, sensitivity of static restoring force to interference direction, and tension uniformity of all mooring lines);the second is that it strengthens the local search ability by combining an adaptive algorithm. [Results] The results show that the improved genetic algorithm has a higher optimization accuracy. The optimized results are fed back to the tension model of the mooring system, and the breaking strength requirements of the mooring lines are appropriately reduced. [Conclusions] This research can provide valuable references for mooring layout design and the material selection of mooring lines

An Efficient Opportunistic Routing Protocol with Low Latency for Farm Wireless Sensor Networks

Wireless sensor networks (WSN) can accurately and timely obtain the production information of crops, and provide data basis for intelligent agriculture. The dynamic crop state and unstable climate environment make it difficult to predict the connectivity probability of wireless links. Therefore, this paper studies an energy-saving opportunity routing transmission strategy under the influence of dynamic link interaction. The protocol establishes an importance model based on algebraic connectivity to reduce the energy consumption of network key nodes. At the same time, based on the improved Bellman–Ford algorithm, a method of constructing candidate sets is studied. It converts the opportunistic routing transmission cost of farm WSN into anycast link cost and the remaining opportunistic path cost affected by energy consumption. The priority queue is used to determine the nodes participating in the iteration, thereby reducing the computational overhead. The protocol also designs a backoff strategy considering the current residual energy to select the only forwarding node and reduce the unnecessary packet copies in the transmission process. Simulation results show that the studied method is superior to the existing opportunistic routing schemes in terms of packet overhead, network lifetime, energy consumption, and packet delivery rate

An Efficient Opportunistic Routing Protocol with Low Latency for Farm Wireless Sensor Networks

Wireless sensor networks (WSN) can accurately and timely obtain the production information of crops, and provide data basis for intelligent agriculture. The dynamic crop state and unstable climate environment make it difficult to predict the connectivity probability of wireless links. Therefore, this paper studies an energy-saving opportunity routing transmission strategy under the influence of dynamic link interaction. The protocol establishes an importance model based on algebraic connectivity to reduce the energy consumption of network key nodes. At the same time, based on the improved Bellman–Ford algorithm, a method of constructing candidate sets is studied. It converts the opportunistic routing transmission cost of farm WSN into anycast link cost and the remaining opportunistic path cost affected by energy consumption. The priority queue is used to determine the nodes participating in the iteration, thereby reducing the computational overhead. The protocol also designs a backoff strategy considering the current residual energy to select the only forwarding node and reduce the unnecessary packet copies in the transmission process. Simulation results show that the studied method is superior to the existing opportunistic routing schemes in terms of packet overhead, network lifetime, energy consumption, and packet delivery rate

Fault-Tolerant Topology of Agricultural Wireless Sensor Networks Based on a Double Price Function

Wireless sensor networks (WSN) enable the acquisition of multisource environmental data and crop states in precision agriculture. However, the complex agricultural environment causes the WSN topology to change frequently and link connection probability is difficult to predict. In order to improve the utilization of network resources and balance the network energy consumption, this paper studies an agricultural fault-tolerant topology construction method based on the potential game and cut vertex detection. Considering the connectivity redundancy, node lifetime, and residual energy, a fault-tolerant topology algorithm for agricultural WSN based on a double price function is designed. The network is clustered according to the node location and residual energy to form a single-hop effective cluster. Based on the network cluster, the price function is constructed in order to reduce energy consumption and balance network energy efficiency. The initial transmit power set supporting inter-cluster communication is obtained by potential game theory. While preserving the game characteristics of topology, the redundant links are eliminated and the transmit power is adjusted by a cut vertex detection algorithm to realize the construction of a 2-connected cluster head network. Simulation results show that the network topology constructed by the studied algorithm can balance the energy consumption and prolong the network lifetime effectively

Fault-Tolerant Topology of Agricultural Wireless Sensor Networks Based on a Double Price Function

Wireless sensor networks (WSN) enable the acquisition of multisource environmental data and crop states in precision agriculture. However, the complex agricultural environment causes the WSN topology to change frequently and link connection probability is difficult to predict. In order to improve the utilization of network resources and balance the network energy consumption, this paper studies an agricultural fault-tolerant topology construction method based on the potential game and cut vertex detection. Considering the connectivity redundancy, node lifetime, and residual energy, a fault-tolerant topology algorithm for agricultural WSN based on a double price function is designed. The network is clustered according to the node location and residual energy to form a single-hop effective cluster. Based on the network cluster, the price function is constructed in order to reduce energy consumption and balance network energy efficiency. The initial transmit power set supporting inter-cluster communication is obtained by potential game theory. While preserving the game characteristics of topology, the redundant links are eliminated and the transmit power is adjusted by a cut vertex detection algorithm to realize the construction of a 2-connected cluster head network. Simulation results show that the network topology constructed by the studied algorithm can balance the energy consumption and prolong the network lifetime effectively

Testing Study of Different Flow Direction and Structure for Air-Cooled Proton Exchange Membrane Fuel Cell

The air-cooled proton exchange membrane fuel cell is widely used in unmanned aerial vehicle since its small size and high efficiency. The bipolar plate structure is an important factor affecting the performance of fuel cells. This article conducts experimental research on the impact of different channel structures on performance based on the annular bipolar plate designed by the team. A single air-cooled fuel cell with 50cm2 is used in the experiment to investigate the dynamic response under different current loading rates of 0–40 A. The test results show that the hydrogen and oxygen in different flow directions have a significant impact on the performance of the fuel cell, with a performance improvement of 8.1% by the hydrogen and oxygen in vertical and staggered flow directions for the enhancement of heat and mass transfer ability, and a decrease of about 3.5° compared with the hot spot temperature. In addition, this study further demonstrated the applicability of the annular bipolar plate structure, and verified the impact of different channels on cathode side and ridge shaped structure on performance, wind speed, temperature distribution, stability and mass power density, of which the performance of the fan channel/linear ridge is the best, which is about 8.5% higher than the output power of the worst fan channel/fan back. These test results provide basic data and technical support for the system design and application of air-cooled fuel cell of open cathode