Random drift error is one of the important factors of MEMS (micro-electro-mechanical-system) sensor output error. Identifying and compensating sensor output error is an important means to improve sensor accuracy. In order to reduce the impact of white noise on neural network modeling, the ensemble empirical mode decomposition (EEMD) method was used to separate white noise from the original signal. The drift signal after noise removal is modeled by GRNN (general regression neural network). In order to achieve a better modeling effect, cross-validation and parameter optimization algorithms were designed to obtain the optimal GRNN model. The algorithm is used to model and compensate errors for the generated random drift signal. The results show that the mean value of original signal decreases from 0.1130 m/s² to −1.2646 × 10⁻⁷ m/s², while the variance decreases from 0.0133 m/s² to 1.0975 × 10⁻⁵ m/s². In addition, the displacement test was carried out by MEMS acceleration sensor. Experimental results show that the displacement measurement accuracy is improved from 95.64% to 98.00% by compensating the output error of MEMS sensor. By comparing the GA-BP (genetic algorithm-back propagation) neural network and the polynomial fitting method, the EEMD-GRNN method proposed in this paper can effectively identify and compensate for complex nonlinear drift signals.

Limited by some engineering occasions and displacement sensors, it is usually difficult to measure the distance of moving objects directly. However, the acceleration of the moving object is usually easy to measure, so the distance of the moving object can be easily obtained through the acceleration integral. To solve this problem, a distance measurement system based on the micro-electro-mechanical system accelerometer is designed. The hardware structure of the system includes the data measurement module, data acquisition module, and data processing module. Thanks to the excellent characteristics of the sensor, the system can be used in a small space, overload impact, and other harsh environments. In this paper, a time domain algorithm based on acceleration integration is proposed. The algorithm not only has no loss of sampling points but also has cubic algebraic accuracy. The fixed output error caused by the installation position of the sensor is analyzed. The analysis shows that the error will lead to a serious trend error. For this problem, an algorithm for removing the trend term error is given. Aiming at the random zero drift of the sensor, the Kalman filter algorithm is used to reduce noise. The distance measurement experiment is carried out on the horizontal slide rail, and the calculation results show that the average measurement accuracy of this distance measurement system can reach 97.89%. The experimental results show the feasibility of the system and the validity of the data processing algorithm. The accuracy of the distance measurement system can meet most of the engineering needs, so it has important significance in the field of engineering distance measurement.

The muzzle velocity of the projectile is one of the important parameters for flight control of the projectile. In order to further improve The stability and precision of the measurement of the muzzle velocity of the projectile, the relative theory of velocity measurement was studied and a new experimental method was put forward. Analysis shows that timers starts or stops timing at the zero point of the voltage signal can improve the velocity measurement accuracy. In order to solve the problem, a signal processing module is designed. The signal processing module can convert the induced voltage signal into a square wave signal. Then the DSP(Digital Signal Processor) can capture the falling edge of the square wave signal and generate interrupt timing. Thus, the timer can be accurately timed at the zero point of the induced voltage signal.In addition, the relevant theories and analysis methods of velocity measurement were established in the article.The induced voltage distribution on the axis of the excitation coil was modeled and simulated.The velocity measurement experiments are carried out by using the proposed method and the traditional pulse induction method.The comparison of experimental results shows that the test method used in this paper has a higher measurement accuracy and the relative error can be controlled within 1%.In this paper, there are some innovations in the theory of speed measurement and the experimental method of timer timing at zero induced voltage.The measurement method is of great significance in the field of velocity measurement.

An economical and effective method to measure displacement is to integrate the acceleration signal. Because of the zero drift in the acceleration sensor, there will be a trend term in the process of acceleration secondary integration, which will cause some errors in displacement measurement. In this paper, several methods of acceleration signal processing with zero drift are given, and the advantages and disadvantages of these methods as well as the applicable occasions are analysed, which have important reference value for selecting reasonable methods in dealing with engineering problems.

The ability of the projectile to strike accurately in the air depends on the accurate measurement of its flight distance. Due to the influence of the external environment, it is very difficult to measure the distance of high-speed projectiles in real time with ranging equipment such as radar and laser. Based on this, a real-time measurement model of the horizontal flight distance of the projectile was designed, which combines trajectory equation and discrete acceleration. First, the angle of inclination of the projectile at each position was calculated according to the six-degree-of-freedom rigid outer trajectory model. Then, two kinds of distance measurement models based on discrete acceleration integration were introduced, and the accuracy simulation was carried out. Simulation results show that the Simpson integral method is more accurate. The flight arc length of the projectile was calculated by the Simpson integral method. Finally, the horizontal flight distance of the projectile was obtained by combining the flight arc length and inclination angle of the projectile. Finally, the flight distance measurement model was simulated, and the simulation results show that the model has high accuracy. The simulation results show that the horizontal flight distance of the projectile can be measured by the trajectory equation and discrete acceleration according to the set conditions. This method can be used to measure the distance of the projectile by carrying the sensor and is less affected by the external environment. It can provide a theoretical basis and reference for the measurement of the horizontal distance of the projectile.