May 28 • Notes • 1194 Views • No Comments on POWER NETWORK RELIABILITY TERMS



A data logger (also data logger or data recorder) is an electronic device that records data over time or in relation to location either with a built in instrument or sensor or via external instruments and sensors. Not completely they are based on a digital processor (or computer). They are usually small, battery powered, portable, and generally equipped with a microprocessor, internal memory for the data storage and sensors. Some data loggers interface with a personal computer and utilize software to activate the data logger and view and analyze the collected data, while rest have a local interface device (keypad, LCD) and can be used as a stand-alone device.
Data loggers vary between general purpose types for a range of measurement applications to very specific devices for measuring in one environment or application type only. It is much common for general purpose types to be programmable; however, many of them remain as static machines with only a limited number or no changeable parameters. Data loggers have replaced chart recorder in many applications.
One of the primary benefits of using data loggers is the ability to automatically collect data on a 24-hour basis. On activation, data loggers are typically deployed and left unattended to measure and record information for the duration of the monitoring period. This permits for a comprehensive and accurate picture of the environmental conditions being monitored, such as the air temperature and the relative humidity.
The cost of data loggers has been declining over the years as technology improves and costs are reduced highly . Simple single channel data loggers cost as little as $25. More complicated loggers may costs hundreds or thousands of dollars.


The negative of phase difference between a sinusoidally varying quantity and a reference quantity which varies sinusoidally at the same frequency, when this mentioned phase difference is negative. Also known as angle of lag.

The angle by which a rotor blade is displaced about its own drag hinge. The angle is measured between the blade-span axis and a radial line taken across the rotor disc containing the drag hinge and the axis of rotation.

Feed forward control is best deployed in control systems design applications where the process or controlled variable behaviour is well understood. A well understood process is that one in which, first principal equations describing the process are known for the given application, and are correctly applied and adequately describe the process. It is also useful in designs where the process is not understood thoroughly, but the behaviour of this process can be measured and experience has shown that it is replicable under known operating conditions. Usually a mixture of both approaches is used. Following are some of its examples:

Example 1) the feed-forward speed regulation

Example 2) the Feed-forward tension control


Time Scales in the Climate System Foster [2007] focus on several statistical problems in the analysis of SES and show that the observed global temperature in fact does not behave like a first-order auto regressive (AR(1)) process. They also demonstrate that the method proposed by SES would result in a biased estimate of the time scale even for a perfect AR(1) process because of the limited length of the time series and the presence of a trend. From a physical point of view, the critical assumption made by SES is that the Earth has a single time scale which characterizes inter annual variability as well as the response to radioactive forcing imposed for decades to centuries. Given the large number of processes which affect temperature in the climate system and which operate on time scales of days to centuries, this seems to be a prior implausible. Inter annual variations in global temperature, which dominate the auto correlation estimate by SES are determined mostly by atmospheric processes and, e.g., patterns like ENSO, with typical time scales shorter than a few years, i.e., exchanges of heat between the upper ocean and space. They are also influenced by short-term variations in the radioactive forcing, e.g., by volcanic eruptions. The response time scale of global temperature to sustained radioactive forcing, on the other hand, has several components. The response of the atmosphere is fast (order years or less), the land and sea ice components react slower, and the long time scales of the response are dominated by the time it takes for the ocean to equilibrate with the forcing [e.g., Hansen et al., 1985]. While the ocean mixed layer reacts relatively quickly, both models and observations indicate that the typical time scales for diffusion and advection of heat and other tracers into the deep ocean are from decades to centuries . These time scales can be estimated from the distributions of temperature and salinity in the oceans themselves, as well as from measurements of how quickly the anthropogenic perturbations of heat, carbon dioxide and carbon isotopes.

These were some important power network reliability terms.

some expected questions and answers:



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