How do you locate a fault on a transmission line?
In practical electricity, people use the trial and error method to detect the fault location (Line to line fault / line to ground fault) of a transmission line. They feed supply at the single end at a time by dividing that transmission line into two parts and check the fault up to that section.
Is support vector machine good for classification?
“Support Vector Machine” (SVM) is a supervised machine learning algorithm that can be used for both classification or regression challenges. However, it is mostly used in classification problems. The SVM classifier is a frontier that best segregates the two classes (hyper-plane/ line).
What kinds of problems are support vector machine models good for?
SVM or Support Vector Machine is a linear model for classification and regression problems. It can solve linear and non-linear problems and work well for many practical problems. The idea of SVM is simple: The algorithm creates a line or a hyperplane which separates the data into classes.
How do you find fault location?
To locate a fault in the cable, the cable must first be tested for faults. Cable testing is therefore usually performed first in cable fault location. During the cable test, flash-overs are generated at the weak points in the cable, which can then be localised.
What measurements are used to identify a fault in a coax line?
Introduction. Distance-to-Fault (DTF) measurements, typically expressed in units of reflection coefficient, return loss, or VSWR as a function of distance, are used to find common faults in coaxial cables and connectors (Table 1).
How is the support vector machine used for binary classification?
You can use a support vector machine (SVM) when your data has exactly two classes. An SVM classifies data by finding the best hyperplane that separates all data points of one class from those of the other class. The best hyperplane for an SVM means the one with the largest margin between the two classes.
How can you use a support vector machine for classification?
SVM is a supervised machine learning algorithm which can be used for classification or regression problems. It uses a technique called the kernel trick to transform your data and then based on these transformations it finds an optimal boundary between the possible outputs.
How are the support vector machine useful for categories the data?
A support vector machine allows you to classify data that’s linearly separable. If it isn’t linearly separable, you can use the kernel trick to make it work. However, for text classification it’s better to just stick to a linear kernel.
Which method is used for locating cable faults?
To find the location of cable fault using the thumping method, a thumper is set to thump repeatedly and then walking along the cable route to hear the thumping sound. The higher the dc voltage applied, the louder will be the resulting thump. This method is useful for relatively shorter cables.