With the infrastructure construction project to the sea, the shipborne concrete batching plant has been widely used, but its compound movement of rising and sinking, horizontal rocking, horizontal and vertical under wave excitation will occur, which will lead to deviation of the metering system. Based on this, an error suppression algorithm of shipborne load cell based on periodic sliding average Kalman filtering is proposed. Firstly, the original data is processed by traditional Kalman filtering to eliminate random errors. Then, the spectrum analysis of the data is carried out by shorttime Fourier transform to obtain the frequency characteristics of periodic error. Finally, periodic errors in the system are eliminated by sliding window mean filtering. Through the sixdegreeoffreedom experimental platform, the movement of the ship in the presence of wave excitation is simulated and weighed by measuring and weighing through the threepoint scale, and the weighing data processed by different algorithms are recorded separately. The experimental results show that the maximum error of the original weighing data is 96%. The maximum error of the weighing data processed by the Kalman filter is 21%. In this paper, the maximum error of the weighing data processed by the algorithm is 03%, which can effectively eliminate the periodic error caused by periodic wave excitation and the random error generated by the sensor itself, and improve the measurement accuracy of the shipborne concrete batching plant.