This paper presents a non-destructive approach for evaluating steel fiber distribution in Steel Fiber Reinforced Concrete (SFRC). The method utilizes a measurement system based on eddy currents combined with an automated scanning system, enabling precise sensor movements along the SFRC sample. The proposed method is first applied to a set of samples with known fiber distribution along the samples to test its effectiveness. The impedance response clearly indicates the highest and lowest fiber volume fractions along the samples, allowing for a straightforward correlation between the impedance data and fiber distribution through the established methodology. Then it is applied to another set of samples with random fiber distribution. In this case, the impedance response is compared to the Brazilian destructive test results. The obtained results affirm a robust correlation between impedance measurements and the observed cracks on the SFRC samples. This approach proves instrumental in identifying vulnerable areas susceptible to crack development in the SFRC sample. The comprehensive insights gained through this method contribute significantly to showing the detailed zonal distribution of SFRC which allows an understanding of the behaviour of the SFRC under mechanical stress.

The gas-liquid two-phase acoustic emission (AE) signal contains rich flow information, but it is also accompanied by a large number of interference signals. To accurately extract the characteristics of gas-liquid two-phase flow, the removal of interference signals is very important. In this paper, AE technology is used to detect the signal of gas-liquid two-phase flow in a vertical pipeline. The support degree of the sensor is checked by the trust function to confirm the consistency of the sensor and eliminate wrong data. The decomposition level of the wavelet base and wavelet transform is determined by four parameters such as the signal-to-noise ratio. By comparing the wavelet exponential window smoothing method and the wavelet soft threshold method, the wavelet exponential window smoothing method which is more suitable for the denoising effect is selected, and the real-time denoising effect is evaluated by using the measurement dynamic uncertainty theory. The results show that the wavelet exponential window denoising method improves the signal-to-noise ratio, reduces the energy leakage during denoising, and significantly improves the pseudo-Gibbs phenomenon, while dynamic uncertainty can effectively evaluate the denoising effect of AE signals.

Given the potential negative impact of delayed response from a magnetorheological (MR) damper on the effectiveness of semi-active suspension (SAS), a specialized time-delay dependent H∞ robust controller has been developed to address this issue. The controller accounts for the actuator response delay and determines the system theoretical critical delay. To mitigate the response delay within the electromagnetic loop of the actuator, a technique has been proposed and tested. The technique minimizes the overall response delay, ensuring it is less than the theoretical critical delay. Subsequently, feedback gain is determined and comparative performance tests are conducted to validate the efficacy of the proposed control method. Compared with a delay-independent H∞ robust controller, it has been demonstrated that the body acceleration and dynamic tire load peak-to-peak responses generated by the proposed controller are decreased by 16.4% and 7.4% respectively under bumpy road conditions, while under stochastic road conditions, body acceleration decreases by 3.5%, suspension deflection by 17.1%, and DTL by 0.89%.

Gas sensors, like any other type of sensors, are affected by external influencing factors among which the most aggressive are the ambient temperature and humidity. If the influence is small, their effect on the global accuracy of the sensor is reduced, and the error caused by these factors is included in the admissible error provided in the datasheet. However, if the influence ais significant, their effect can no longer be neglected and compensation of these errors is necessary based on the known influence characteristics found in the datasheet of the sensor. Unfortunately, these characteristics are not linear and the compensation must be accomplished according to an analytical relationship, if it can be known, or based on look-up tables implemented in the memory of the measuring device. Things get complicated when there are several influence factors. The paper describes a method for compensating the influence of ambient temperature and humidity on an MQ7 metal oxide gas (MOG) sensor, mainly dedicated to measuring carbon monoxide (CO), by mathematically modelling the surfaces of the characteristics given in the sensor’s datasheet and their implementation on a microcontroller platform. Experimental data show that, for a temperature variation between 10 and 50 Celsius degrees (°C) and a relative humidity (RH) variation between 30 and 90%, a reduction of the total amount of error is obtained by compensating the influence quantities resulting in an accuracy improvement of more than 60%.

Modern devices for dynamic calibration of pressure sensors (shock tubes, power simulators of pressure impulse, etc.) have a number of drawbacks stemming from the principles of creating a test impact. Besides, the problem of rational choice of the method of calibrating pressure sensors depending on the dynamic parameters of the sensor and the required test accuracy has not been solved for modern test systems. The paper presents a solution to the problem of correlation between the test parameters, dynamic parameters of the pressure sensor and test accuracy. The obtained analytical dependencies of such a relationship make it possible to reasonably select or develop a method for studying the dynamic characteristics of sensors. Based on theoretical studies, the principle of creating a test impact has been proposed, and a method and device for implementing dynamic calibration of pressure sensors have been devised. The developed device allows the transient response of the sensor to be obtained, as well as setting the decay time of its natural vibration. Based on the transient response, other dynamic characteristics of the sensor, namely the impulse transient and frequency response, can be calculated.

The paper presents the theoretical properties of power-of-sine time windows, including the property of maximum sidelobe decay. This family of windows is a generalisation of the widely known Maximum Sidelobe Decay (MSD) windows and is referred to as Generalised Maximum Sidelobe Decay (GMSD) windows. GMSD windows are used in methods such as DFT spectrum interpolation (IpDFT), due to their desirable properties for such applications. The paper presents the key results, including the analytical form of the frequency characteristics of GMSD windows and some of their properties. The formulas derived are useful for describing these properties.