To optimize the on‐line cleaning process parameters of aero‐engines, the influence of the engine's dry run Speed on the cleaning flow field was analysed. Through the reverse modelling and numerical simulation of the CFM56‐7B compressor, the changes of static pressure, velocity and vorticity of the cleaning flow field under different dry run speeds were analysed. The results showed that the static pressure and speed of the cleaning flow field increased linearly with the increase of the dry run speed; the vortex of the cleaning flow field decreases with the increase of the speed, but the increase of the speed was beneficial to the cleaning of the compressor. Through the aero‐engines online cleaning test, comparing the recovery of EGTM at different speeds, when the engine dry run speed was 323 r/min, a better cleaning effect and higher economic benefits can be obtained. The research can provide a theory for engine online cleaning.

Carrier frequency offset (CFO) is a challenging problem in the uplink of the single‐carrier frequency division multiple access (SC‐FDMA) system. CFOs effect on the orthogonality between subcarriers and cause inter‐carrier interference (ICI) and multiple access interference (MAI). This paper, analyzes the impact of the CFOs on the performance of the Discrete Sine Transform (DST) SC‐FDMA (DST‐SC‐FDMA) system and investigates with different wireless channels, different modulation schemes and different subcarriers mapping schemes. Furthermore, an efficient equalization and CFOs compensation scheme is proposed to enhance the performance of the DST‐ SC‐FDMA system and transmit images efficiently over DST‐ SC‐FDMA system. The proposed scheme combines the minimum mean square error (MMSE) equalizer and the parallel interference cancellation (PIC). The combined method is referred to as MMSE+PIC. The results show that CFOs degrades the DST‐FDMA performance. The obtained results show a noticeable performance improvement of the proposed MMSE‐PIC scheme over the conventional MMSE equalizer. Moreover, it is found that it is possible to efficiently transmit wireless image using the proposed MMSE+PIC scheme,

Audio signals typically comprise several characteristics to be improved by signal processing and in practice, each of these characteristics has a unique relationship to the controllable system parameters. Quantifying these relationships in a multi‐objective (MO) approach will enable an improved system setup. This paper determines two novel objective functions of a complex audio signal for the real‐time simultaneous improvement of audio peak reduction and speech clarity in a dental drill noise reduction (DDNR) device. The influence of the DDNR system parameters on the outcome of peak reduction and speech clarity is determined by combining response surface methodology and a desirability function to enable MO optimisation. The results show an average improvement of nearly 30% over the original DDNR device performance. The approach described provides an effective means for addressing MO optimisation of other real‐time audio signal processing applications where the signal has similar peak reduction and speech clarity objectives to be processed, particularly where the physical outcome is not easy to evaluate in a virtual environment.

This letter presents a second‐order incremental ADC (IADC) operated in three steps, which extends the performance of a second‐order IADC close to that of a fourth‐order IADC with only two amplifiers. It performs a second‐order noise‐shaping quantization in the first step operation. Reusing the same hardware, the circuit is reconfigured to perform fine quantization as a first‐order IADC in the second and third step. Within a conversion time of 60 clock periods (oversampling ratio OSR = 60), 35 dB signal‐to‐quantization‐noise ratio is boosted. The proposed topology is very suitable for low‐bandwidth high‐resolution data conversion.

This paper presents the optimal load‐shedding strategy of home energy management systems (HEMSs). The HEMS uses the dynamic programming (DP) method to plan the day ahead, schedule, and connects to smart plugs to perform load‐shedding. HEMS solves the shedding schedule of smart plugs considering the prediction of consumption of each smart plug and the consumer's demand response (DR) setting. In addition, the maximum DR capacity was determined by using golden section search (GSS). Some DR experiments were conducted by the proposed method in laboratory and these comprised three different DR durations. The results show that the estimated DR capacities and shedding schedules were feasible. Thus, it helps both the DR participants and aggregator to seize the optimum performance and benefits.

Algae contamination accumulated on the surface of insulators will affect the electrical properties of insulators. At present, the characterization method of algae contamination is the image method, which determines the distribution of algae contamination through colour. The detection results are affected by environmental changes and the growth state of algae. This paper puts forward a method of detecting polluted insulator surface with algae by using laser‐induced breakdown spectroscopy (LIBS) technique, combined with the scanning electron microscope (SEM), inductively coupled plasma emission spectrometer (ICP), analyzed by the spectra of algae contamination. Mg, Ca, Fe are selected as the analytical element. The classification of algae contamination, non‐algae contamination and no contamination are realized with the principal component analysis (PCA). The research results are of great significance for characterization of algal pollution on insulator surface by LIBS.