To improve the reliability and optimize the maintenance strategy of a large‐scale wind farm, a health condition assessment method of wind turbine generator system (WTGS) based on multiple turbines cooperation is presented in this paper. First, a health condition assessment framework is established by analyzing the existing monitoring characteristics of SCADA system. Second, to quantify the health condition of a WTGS, the concept of synthetic degradation factor is introduced and calculated using variable weight of assessment indices. Third, in order to acquire the health level of a WTGS effectively, based on the idea of multiple turbines cooperation, the health condition assessment model is proposed by utilizing the moving average method and quantile algorithm. Finally, by using SCADA monitoring data of a wind farm with 33 × 1.5 MW WTGSs including temperature, pressure, vibration, and so on; the processes of condition assessment are performed, and the effectiveness is also compared to a traditional assessment method with the fixed threshold. The results show that the condition assessment that utilizes the proposed method can acquire the change of health conditions and has a better coherence with real health conditions.
In this paper a model-based development method which is based on the OSEK/ASCET [1] [2] automotive embedded software development platform for the control of the mass air flow and the exhaust gas recirculation (EGR) by using the EGR valve and the intake throttle (TVA) was evaluated. Through the analysis of the diesel engine air system and the EGR system, based on a model driven development platform, a complete model of diesel engine EGR system was built. And in the end through the offline simulation and the bench test of the application software in accordance with set calibration parameters, the end result of the study concluded that the model-based development method of automotive software is more stable and efficient than the previous manual developing method.
This paper presents the window cleaning device carried by four-rotor aircraft. The cleaning device adopts the gear drive with the electromagnet; Considering the different shapes of the windows, it is designed there different replaceable cleaning disc; the control system can control the actions of the aircraft and cleaning disc. It meets the requirements of the low-mass, high reliability, high automation, good stability, easy operation to the widow cleaning device.
A dynamic modal of the milling of ball end milling is presented for the simulation and analyzing the influence of the milling parameters on milling in order to avoid the vibration. The milling cutter and constrains are simplified to be a system with the two modes of vibration, the modal is developed considering effective cutting area of the cutting edge and regenerative effect, which directly reflects the cutter-in and the cutter-out. The mode testing and identifying determine the equation coefficients. It is found that reducing the milling depth can improve the stability and avoid self-excited vibration milling when the depth less than the critical milling depth, the frequency of the milling system will change while changing the rotate speed of the spindle, the self-excited is prone to occur when the frequency is close to the natural frequency. The results of simulation are benefit of the milling and optimal design of the parallel machine tools.
The development of Operation &Maintenance Automation System of CSG EHV Power Transmission Company needs to integrate some automation systems being in use, in order to build effective connections among different data and business process. This paper introduced several system integration technologies, and analyzed the applicability of these technologies referring to the automation systems used in power Grid Company, and proposed system integration solutions for typical automation systems in details.
The paper introduces the key points of vibration diagnosis technology on-site operation, from the diagnosis, diagnostic object, working condition of equipment, equipment principle and correct data analysis etc., and giving analysis, to prevent the generation of error analysis, to prevent the acquisition signal distortion, improving the diagnosis efficiency and reliability.
Although the global wind energy industry has made considerable progress in recent years, wind turbines suffer from frequent failures since the systems are complicated and the working conditions are far from being satisfactory. For the wind turbines to function well, it is imperative to study the overall status of the wind turbine unit, evaluate the performance of the wind farm, apply intelligent operation and maintenance technology, and improve operation and maintenance strategies on an on-going basis, all of which are based on the operation data of the unit. This paper focuses on the evaluation and extension of the lifetime of wind turbines. Based on relevant knowledge and theories from previous studies, an evaluation method based on big data was designed to do the evaluation, and the results of which were verified by real cases. With the duration of catastrophic failures taken into account, the proposed life prediction algorithm was proved to be effective. If the bearing runs for 34 days, the actual remaining life of wind turbines is 0.2 days. The number predicted for LRM is 0.8 days and that predicted for ILRM is 0.31 days. Compared with LRM, the prediction for ILRM is much more accurate.
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