Recent studies to explore the enhanced electromagnetic properties of TiN and TiC reported that TiNC has a good performance in EM wave absorption. We prepared TiNC with quantificational percentages of carbon doping in this work. Nanotitanium oxide precursor was prepared via sol–gel method, then submicron TiN(1–x)C x with different carbon content (x = 0, 0.2, 0.4, 0.6, 0.8) was obtained via solid–gas reaction by nitriding at 900 °C with nitrogen and carbon doping at 1700 °C with argon. The composition and structure of TiN(1–x)C x change with the increase of carbon content, the lattice distortion and dipole moments were introduced into TiN crystal via carbon doping which leads to optimization of the electromagnetic properties. The influence of carbon doping was analyzed, and at carbon = 0.8, the attenuation factor “α” and impedance matching “Δ” of the sample achieved a better balance that results in a better wave absorbing effect. The resulting bandwidth lower than −10 dB is in the range 11.1 to 13.6 GHz, and the reflection loss reached to −40.1 dB at 12.4 GHz with the sample thickness of 1.32 mm. The frequency of maximum reflection loss obeys the quarter-wavelength matching model. TiN(1–x)C x shows good electromagnetic absorbing properties and it is in accordance with the “thin, light, wide, strong” application requirements of microwave absorption materials.

Summary Real‐time dynamic hybrid testing (RTDHT) is a state‐of‐the‐art experimental technique for evaluating the performance of a structural system subjected to time‐varying loads. Because of the superiority of shaking table for testing rate‐dependent and inertial effect existing in structural system, shaking table‐based RTDHT is an important branch in RTDHT family, in which shaking table is used to impose inertial forces on physical substructure. Owing to the mass of the seismic platform, shaking table has a relatively narrow testing bandwidth akin to a stand‐alone actuator RTDHT system. Furthermore, structure–table interaction confines the physical substructure to a very small mass and linear stage, such that shaking table‐based RTDHT is unable to test the structural performance with consideration of high frequency input or non‐linearity using large‐scale physical substructure. Actually, this is why we develop RTDHT. In this work, a control strategy named full state control via simulation (FSCS) was proposed to extend the testing capacity of shaking table‐based RTDHT. The efficiency of FSCS‐controlled RTDHT for testing high frequency and non‐linear structural performance was verified by a small‐ and large‐scale shaking table‐based RTDHT, respectively.

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Real-time dynamic substructuring (RTDS) is a state-of-the-art experimental technique for evaluating the dynamic performance of a structural system subjected to time-varying loads in civil engineering. The accuracy and stability of RTDS is affected by the natural dynamics of the constituent transfer system. Of various control strategies, and due to the merits of simple implementation and low computational cost, delay-compensation methods have become most pervasive. In this paper, the performance of delay compensation based methods for RTDS is assessed in terms of accuracy and stability. Three commonly-used delay compensation schemes are considered: two time variant and one time invariant. Stability is assessed analytically, numerically and experimentally. Accuracy is assessed numerically and experimentally. To provide a suitable test for the delay compensation control schemes, a shaking table is adopted as the RTDS transfer system. It is demonstrated numerically, analytically and experimentally that when applied to transfer systems such as these, delay compensation can work to the detriment of test accuracy and test stability. Adequate performance of delay compensated, shaking-table based RTDS is confined a narrow low frequency bandwidth which severely restricts the range of potential application.

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Online denoising is motivated by real-time applications in the industrial process, where the data must be utilizable soon after it is collected. Since the noise in practical process is usually colored, it is quite a challenge for denoising techniques. In this paper, a novel online denoising method was proposed to achieve the processing of the practical measurement data with colored noise, and the characteristics of the colored noise were considered in the dynamic model via an adaptive parameter. The proposed method consists of two parts within a closed loop: the first one is to estimate the system state based on the second-order adaptive statistics model and the other is to update the adaptive parameter in the model using the Yule–Walker algorithm. Specifically, the state estimation process was implemented via the Kalman filter in a recursive way, and the online purpose was therefore attained. Experimental data in a reinforced concrete structure test was used to verify the effectiveness of the proposed method. Results show the proposed method not only dealt with the signals with colored noise, but also achieved a tradeoff between efficiency and accuracy.

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