Measurement and Control

According to the special condition expression of the aerial lithium-ion battery pack, a novel targeted equivalent model (Splice–Equivalent Circuit Model) is proposed and constructed. The Splice–Equivalent Circuit Model achieves the accurate mathematical expression of the special operating conditions and the working process for the lithium-ion battery pack, which is realized by using the equivalent simulation of different internal effects in the charging and discharging process of the battery pack. The theoretical study and analysis of the working principle is investigated to express the working characteristics of the aerial lithium-ion battery pack together with the experimental analysis. Then, the equivalent circuit model of the aerial lithium-ion battery pack is carried out on the composite construction methods. The experimental studies are carried out in order to identify the parameters of the improved Splice–Equivalent Circuit Model, obtaining respectable identification results of battery equivalent model parameters.

Estimation of vehicle speed by analysis of drive-by noise is a known technique. The methods used in this kind of practice generally estimate the velocity of the vehicle with respect to the microphone(s), so they rely on the relative motion of the vehicle to the microphone(s). There are also other methods that do not rely on this technique. For example, recent research has shown that there is a statistical correlation between vehicle speed and drive-by noise emissions spectra. This does not rely on the relative motion of the vehicle with respect to the microphone(s) so it inspires us to consider the possibility of predicting velocity of the vehicle using an on-board microphone. This has the potential for the development of a new kind of speed sensor. For this purpose we record sound signal from a vehicle under speed variation using an on-board microphone. Sound emissions from a vehicle are very complex, which is from the engine, the exhaust, the air conditioner, other mechanical parts, tires, and air resistance. These emissions carry both stationary and non-stationary information. We propose to make the analysis by wavelet packet analysis, rather than traditional time or frequency domain methods. Wavelet packet analysis, by providing arbitrary time-frequency resolution, enables analyzing signals of stationary and non-stationary nature. It has better time representation than Fourier analysis and better high-frequency resolution than Wavelet analysis. Subsignals from the wavelet packet analysis are analyzed further by Norm Entropy, Log Energy Entropy, and Energy. These features are evaluated by feeding them into a multilayer perceptron. Norm entropy achieves the best prediction with 97.89% average accuracy with 1.11 km/h mean absolute error which corresponds to 2.11% relative error. Time sensitivity is ±0.453 s and is open to improvement by varying the window width. The results indicate that, with further tests at other speed ranges, with other vehicles and under dynamic conditions, this method can be extended to the design of a new kind of vehicle speed sensor.

In industrial and medical laboratories, prior to initiating the daily test procedure, the accuracy of the system is observed by measuring the reference control values. Measurements and test results may be below or above the reference value. Hence, the control data is employed in order to ensure that the test scores lie in the targeted range values, and the results obtained from the control data are evaluated via computer-based analysis. The results of the analysis have significant importance for control and improvement of process. Furthermore, the data to be analyzed may be the test results of a product as well as the measurement outcomes obtained from a laboratory. In this study, an algorithm named as Adaptive Precision Point Algorithm is proposed to evaluate the control data and to increase the stability by reducing the loss. In this schema, the contribution to the reduction of the total systematic error was observed by calculating the target working point and the Adaptive Precision Point deviations. Measurement outputs, in other terms the data, are processed in Adaptive Precision Point Algorithm. The algorithm determines a new adaptive working point for the incoming data by doing the required computations for precision working point. Moreover, the deviation between adaptive working point and the specified working point, which is defined according to the standards and rules, is calculated. By this way, adaptive working point is being utilized throughout the reduction of systemic errors. According to the results of the research, Adaptive Precision Point Algorithm eliminates the systematic errors on a large scale. The suggested algorithm provides results within the accepted quality deviation limits so it does not form a negativity in the understanding of quality. It is also observed that the algorithm sets a positive correlation between the minimized test results and reduction of time and material usage. Furthermore, the research and the algorithm offer a cost-effective solution. Consequently, the contribution and significance of the proposed algorithm can be understood in a better way by considering that it does not only maintain the quality limits but it also minimizes the cost and time spent during the testing of thousands of laboratory samples.

This paper deals with the eddy current technique for nondestructive evaluation of the crack depth on a massive specimen used in aeronautical industry. A set of C-scan eddy current images is analyzed to reduce the noise and to select suitable features, which can be used to estimate the crack depth. Based on this study, a method relying on polynomial forward models of the relationship between crack depth and the maximum value of the sensor impedance is proposed. The least square and the non-negative least square techniques are applied to analyze the usability of proposed models. The error of obtained estimations is smaller than 10%, for almost used experimental data.

A novel approach named active–disturbance–rejection–control (ADRC) and fractional–order–proportional–integral–derivative (FOPID) hybrid control scheme is proposed for hydroturbine speed governor system, which is based on ADRC and FOPID control methods. By combining the advantages of ADRC and FOPID controllers, the proposed ADRC–FOPID hybrid control scheme can actively reject the unpredictable disturbance, even with random noises, and can be adapted to the nonlinearities as well as unknown dynamics of hydroturbine speed governor system. The control performances of ADRC–FOPID, ADRC, FOPID as well as conventional proportional–integral–derivative (PID) controllers have been compared. And ADRC–FOPID has been proved to be an effective control scheme for hydroturbine speed governor system.