Ship shaft power measurement method based on Monte Carlo Kalman filtering

Abstract

The invention provides a ship shaft power measurement method based on Monte Carlo Kalman filtering. The method comprises the specific process: abstracting a physical model of a shaft system according to the working principle of the shaft system, building a state equation and a measurement equation, and employing Monte Carlo Kalman filtering. The method comprises the following steps: firstly, simulating a random point set of state torque by adopting Monte Carlo according to a state estimation value and covariance at a previous moment, carrying out nonlinear transformation on the random point set according to a state equation, and calculating a state prediction value at the moment; secondly, simulating a random point set for the measured value of the rotating speed by adopting Monte Carlo, and fusing and calculating a predicted value of the shaft power according to a measurement equation; and finally, performing Kalman estimation on a torque state estimation value at the moment, and calculating the ship shaft power. Aiming at the defects of contact type and non-contact ship shaft power measurement, the invention aims to adopt a Monte Carlo Kalman filtering algorithm to carry out fusion filtering and noise covariance estimation on acquired data on the premise of not increasing hardware, so that the measurement precision is improved, and the purpose of monitoring the shaft power on line is achieved.

Description

technical field [0001] The invention relates to the field of ship shaft power measurement, and more particularly, to a method for measuring ship shaft power based on Monte Carlo Kalman filtering. Background technique [0002] According to application requirements, ship shaft power is divided into short-term detection and online monitoring. Short-term detection provides the most important performance parameters for the first voyage test after launching a new ship or after repairing a ship. On-line monitoring of the shaft power between the ship-engine-propeller is a key parameter to evaluate the coordination efficiency of the ship under different working conditions, and it is of great significance to improve the efficiency of the ship power system; Monitoring and fault diagnosis provide auxiliary parameters, which is of great significance to improve the reliability and safety of the ship power system; through real-time online monitoring of parameters such as shaft power, torqu...

AI Technical Summary

Problems solved by technology

When the random sample is high enough, the Monte Carlo Kalman filter can achieve arbitrary precision, but the disadvantage is that the amount of calculation is large, and in the shaft power measurement system, the torque and speed signals are collected by the acquisition card to the PC, and the PC Analysis and processing of torque and rotational speed signals and calculation of shaft power

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