Wavelet Transform is a time-frequency representation of the input signal. Realization of wavelet transform on field-programmable gate array (FPGA) device for the detection of power system disturbances is proposed in this thesis. This approach provides an integral signal-processing paradigm, where its embedded wavelet basis serves as a window function to monitor the signal variations very efficiently. By using this technique, the time information and frequency information can be unified as a visualization scheme, facilitating the supervision of electrical power signals. To improve its computation performance, the proposed method starts with the software simulation of wavelet transform in order to formulate the mathematical model. This is followed by the circuit synthesis and timing analysis for the validation of the designated circuit. Then, the designated portfolio is programmed into the FPGA chip through the download cable. And the completed prototype is tested through softwaregenerated signals, in which test scenarios covering several kinds of electrical power quality disturbances are examined thoroughly.