This article discusses about how the variables affect the safety practice level of employees in a manufacturing organization. Brief gap analysis study is made between existing standard in calculating safety practice l...
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ISBN:
(纸本)9781479978496
This article discusses about how the variables affect the safety practice level of employees in a manufacturing organization. Brief gap analysis study is made between existing standard in calculating safety practice level index of the organization, and the proposed model of safety index. Left out variable in existing standard is added in proposed model of calculation of safety practice index. A new model is proposed to calculate safety practice level for manufacturing organization considering the expert opinion in manufacturing organization. fuzzylogic technique is used to calculate safety practice attributes and indexed variables which affect the safety level is approached through weighted scale method. fuzzyalgorithm model helps the users to calculate dependent variable much faster than other techniques. Considering the complexity, which is involved in independent variables affecting safety practice level of organization, fuzzy technique gives easier calculation process. The paper discusses variables which were stipulated to safety standards taken in to consideration. With the usage of fuzzylogic technique affecting variable's magnitude is calculated and improvement actions are taken accordingly. Research scope is limited to that stipulated company standard.
This study presents an objective verification of different icing algorithms for two periods from 5December 2012 to 17April 2013 and from 9October to 11December 2013. The predicted icing potential and severity are eval...
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This study presents an objective verification of different icing algorithms for two periods from 5December 2012 to 17April 2013 and from 9October to 11December 2013. The predicted icing potential and severity are evaluated against pilot reports of aircraft icing below 23000feet over Eastern United States. The icing algorithms are applied to the deterministic forecasts of European Centre for Medium-Range Weather Forecasts (ECMWF). Two of these algorithms are based only on forecasts of temperature (T) and relative humidity (RH), but the first uses fixed thresholds and the second uses a fuzzylogic approach. Although the second algorithm detects less icing events, it is more efficient with respect to the warning area, i.e. it forecasts icing over a smaller percentage of the airspace than the first algorithm. The impact of adding information from cloud liquid water (CLW) content and/or vertical velocity in the fuzzylogic scheme is assessed. algorithms using T, CLW and vertical velocity as predictors are also tested. Most of the algorithms reveal a good performance in discriminating between icing and no-icing conditions, but are less skilful in forecasting the icing severity. The results also show that the use of CLW is essential to avoid issuing too many warnings. Moreover, the algorithm combining T, RH, CLW and vertical velocity attains the best performance. This algorithm, SFIPO, has been operational at the Portuguese Meteorological Watch Office since June 2013, and an example of a severe icing episode in February 2014 over mainland Portugal is presented.
In this paper a Sliding Mode Control scheme (SMC) applied to the Permanent Magnet Synchronous Motor (PMSM) speed control is designed and improved. A fuzzy logic algorithm is added to mitigate chattering caused by disc...
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In this paper a Sliding Mode Control scheme (SMC) applied to the Permanent Magnet Synchronous Motor (PMSM) speed control is designed and improved. A fuzzy logic algorithm is added to mitigate chattering caused by discontinuous term in steady states, and to ensure good performances of the controller in transient states. The proposed fuzzy-SMC performance is tested in simulation and experimental results are obtained using eZdsp F28335.
Braking force distribution (BFD) for electrified vehicles for maximizing energy regeneration has been a challenging research topic, due to the complex operating conditions and tradeoff among different vehicle performa...
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ISBN:
(纸本)9781509001934
Braking force distribution (BFD) for electrified vehicles for maximizing energy regeneration has been a challenging research topic, due to the complex operating conditions and tradeoff among different vehicle performance measures. It is known that the level of tire-road friction has a significant impact on the braking force boundaries that define the locking conditions of front and rear wheels. However, conventional BFD strategies for electrified vehicles have not taken full advantage of tire-road friction and generally preferred conservative algorithms. These suggest a potential for exploiting tire-road friction estimation for BFD so as to enhance energy regeneration of electrified vehicles while retaining vehicle stability. This study tackles this challenge by proposing a tire-road-friction-estimation-based BFD for all-wheel-drive (AWD) electrified vehicles with a single electric motor. The specific topology considered in this study is a plug-in hybrid electric vehicle that is powered by an internal combustion engine and a single electric machine. The AWD capacity is provided by a propeller differential shaft connecting the front and rear axles, which imposes a constraint on the ratio of front/rear regenerative brake forces, which is always equal on both axles for the vehicle topology considered here. For the proposed BFD strategy, a fuzzy-logic based tire-road friction estimation algorithm is developed, which uses the longitudinal wheel slip estimated from sensor measurements of vehicle acceleration and wheel speeds. The tire-road friction estimation algorithm is accordingly integrated within the braking controller for front and rear braking force generation and allocation. Simulation analyses are conducted, and the results and discussions demonstrate the effectiveness of the proposed tire-road friction estimation algorithm, and that the tire-road friction estimation-oriented BFD strategy can help to improve the braking energy recovery.
A fuzzy-logic based methodology is proposed and evaluated for energy management in off-grid installations with photovoltaic panels as the source of energy and a limited storage capacity in batteries. The decision on t...
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A fuzzy-logic based methodology is proposed and evaluated for energy management in off-grid installations with photovoltaic panels as the source of energy and a limited storage capacity in batteries. The decision on the connection or disconnection of components is based on fuzzy rules on the basis of the Photovoltaic Panel Generation measurement, the measured power required by the load, and the estimation of the stored energy in the batteries (this last is obtained from the estimation of the Depth-of-Discharge). The algorithm aims to ensure the system's autonomy by controlling the switches linking the system components with respect to a multi-objective management criterion developed from the requirements (supply of the load, protection of the battery, etc.). Detailed tests of the proposed system are carried out using data (irradiation, temperature, power consumption, etc.) measured in a household at the target area at several days of the year. The results demonstrate that the proposed approach achieves the objectives of system autonomy, battery protection and power supply stability. Compared with a basic algorithm, the proposed algorithm is not sensitive to sudden changes in atmospheric parameters and avoids overcharging the battery. (C) 2013 Elsevier Ltd. All rights reserved.
The freezing of gait (FOG) is a common and highly distressing motor symptom of patients with Parkinson's Disease (PD). Effective management of FOG is difficult given its episodic nature, heterogeneous manifestatio...
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ISBN:
(纸本)9781479922802
The freezing of gait (FOG) is a common and highly distressing motor symptom of patients with Parkinson's Disease (PD). Effective management of FOG is difficult given its episodic nature, heterogeneous manifestation and limited responsiveness to drug treatment. Clinicians found alternative approaches, such as rhythmic cueing. We built a smartphone-based architecture in agreement with acceptability and usability requirements which is able to gather data and information useful to detect FOG. In this work fusing together the information of freeze index, energy, cadency variation and the ratio of the derivative of the energy a novel fuzzylogic based algorithm is developed. Performances of the fuzzyalgorithm are compared with two other algorithms showing its capability to reduce false negative detection thus improving sensitivity and specificity.
In the present study, Grey based fuzzyalgorithm was used for the optimization of complex multiple performance characteristics of the ball burnishing process. Experiments have been planned according to Taguchi's L...
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In the present study, Grey based fuzzyalgorithm was used for the optimization of complex multiple performance characteristics of the ball burnishing process. Experiments have been planned according to Taguchi's L-16 orthogonal design matrix. Burnishing force, number of passes, feed rate and burnishing speed were selected as input parameters, whereas surface roughness and microhardness were selected as output responses. Using Grey relation analysis (GRA), Grey relational coefficient (GRC) and Grey relation grade (GRG) were obtained. Then, Grey-based fuzzyalgorithm was applied to obtain Grey fuzzy reasoning grade (GFRG). Analysis of variance (ANOVA) was carried out to find the significance and contribution of parameters on multiple performance characteristics. Finally, a confirmation test was applied at the optimum level of GFRG to validate the results. The results also show the feasibility of the Grey-based fuzzyalgorithm for continuous improvement in product quality in complex manufacturing processes.
The Unit Commitment Problem is to determine a minimal cost turn-on and turn-off schedule of a set of electrical power generating units to meet a load demand while satisfying a set of operational constraints. The produ...
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ISBN:
(纸本)9788184244397
The Unit Commitment Problem is to determine a minimal cost turn-on and turn-off schedule of a set of electrical power generating units to meet a load demand while satisfying a set of operational constraints. The production cost includes fuel, startup, shutdown, and no-load costs. Some of the operational constraints that must be taken into account include,[2] 1. The total power generated must meet the load demand plus system losses. 2. There must be enough spinning reserve to cover any shortfalls in generation. 3. The loading of each unit must be within its minimum and maximum allowable rating. 4. The minimum up and down times of each unit must be observed. The unit commitment is aimed at devising a proper generator commitment schedule for a power system over a period of one day to one week. The main objective of unit commitment is to minimize the total production cost over the study period & to satisfy the constraints imposed on the system such as power generation-load balance, spinning reserve, operating constraints, minimum up time & minimum down time, etc. Several conventional methods are available to solve the unit commitment problem. But all these methods need the exact mathematical model of the system & there may be a chance of getting stuck at the local optimum. This paper describes the application of fuzzy logic algorithm for determining short term commitment of thermal units in electrical power generation. The results obtained from fuzzylogic based approach are compared with the priority list method solution to unit commitment problem. The comparison fuzzylogic based approach are powerful tools for solving such highly non-linear, multi constrained optimization problems in electrical power systems.
The main goal of this research is to identify the system parameters of the dynamics of Rotor/Active Magnetic Bearing (Rotor/AMB) system employed in turbo molecular pumps (TMPs). The identification approach adopted in ...
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The main goal of this research is to identify the system parameters of the dynamics of Rotor/Active Magnetic Bearing (Rotor/AMB) system employed in turbo molecular pumps (TMPs). The identification approach adopted in this work is based on experimental analysis and the application of fuzzylogic Adaptive Control-Extended Kalman Filter (FLAC-EKF). The estimation error for either system state or system parameters can be gradually converged to zero via self-tuning of the design parameters of FLAC-EKF. The proposed algorithm has been verified by numerical simulations and intensive experiments. It is concluded that the FLAC-EKF can exhibit satisfactory performance in terms of estimation accuracy on the system parameters even under contamination of a certain degree of process disturbance and sensor noise. (C) 2014 Elsevier Ltd. All rights reserved.
A fuzzy anti-windup (AW) compensator is proposed and applied to the embedded cylindrical-array magnetic actuator (ECAMA) to ensure the superior performance of spindle position regulation for milling machines under act...
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A fuzzy anti-windup (AW) compensator is proposed and applied to the embedded cylindrical-array magnetic actuator (ECAMA) to ensure the superior performance of spindle position regulation for milling machines under actuator saturation. Since ECAMA is a type of active magnetic bearing (AMB), the supplied coil current and the induced magnetic force are both limited by the maximum current and power output of the AMB and the associated amplifier. Once the magnetic actuator is saturated, the required control input cannot be realized by ECAMA and may lead to drastic tremble of spindle position. In this work, an AW compensator, based on fuzzy logic algorithm, is therefore proposed to rectify the control input to ECAMA. By employing commercial software MATLAB/Simulink and signal processing interface, Module DS1104 by dSPACE, the efficacy of the fuzzy AW compensation is practically verified by intensive experiments.
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