The Axis calculation process is complicated, it is involving the measurement data of upper lead, lower lead, water lead, and other parts, which need the dimensions of upper lead to lower lead, upper lead to water lead, thrust head diameter, and so on. Axis adjustment central axis of the net total swing and maximum net total swing degrees is an important parameter of axis adjustment calculation, so the degree of the axis of the hydroelectric generating set net total swing and prediction as well as to the axis of maximum net total swing adjustment bearing search, to guarantee the safety of the hydro-generator unit and reduce economic loss of the hydro-power station is of great significance 5.The calculation of net total swing and relative swing in axis adjustment of the hydro-generator unit is still mainly by manual calculation. The quality of the unit axis comprehensively reflects the quality of installation and maintenance 4. Overhaul of the unit must also go through axis adjustment inspection. In practical engineering, axis adjustment is the most important work in the later period of unit installation. State of the reliable measurement of the trend of hydroelectric generating set axis for unit security, it promotes the power system stability of great significance 3. Hydro-generator unit (HGU) is a part of the key equipment of hydro-power station 1, 2. This method greatly improves the efficiency of azimuth search for axis adjustment. Simulation examples show that the proposed method can significantly improve accuracy of axis adjustment. This method solves the problem that GM(1, 1) can only be predicted by monotone sequence in the past and the problem that the search algorithm is easy to fall into local optimum, effectively improves the calculation efficiency of axis and shorts the search time. Then, the advanced flamingo search algorithm is used to search the maximum value of the sine function of the net total pendulum of the axis, and the axis adjustment orientation is obtained. It uses e 1 and e 2 factor transformation to establish an improved axis net total swing gray prediction model. First of all, it proposes a sequence acceleration translation and mean value transformation method, which is used to pre-process the axis net total swing sequence that exhibits oscillating fluctuations. This paper proposes a new method for axis adjustment of hydro-generator unit based on an improved grey prediction model and swarms intelligence optimization neural network. Therefore, to adopt effective axis adjustment technology to eliminate faults. The power quality and efficiency of the hydro-power station depend on the stable operation of the hydro-generator unit, which needs to continue to operate and it is prone to axis failure.
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