Acoustic emission-based intelligent identification of piston aero-engine ignition advance angle anomalies.

Ignition advance angle is one of the important factors affecting the performance of the engine, when it occurs abnormally will make the engine power and economy worse, and even cause serious damage to the engine. Therefore, it is very necessary to recognize the abnormal ignition advance angle of the engine. However, the engine system is closed and has a complex structure, which makes traditional diagnostic methods difficult. This paper proposes an intelligent identification method based on acoustic emission (AE) signals, which collects the AE signals from the engine surface and divides their spectra into equal parts, and selects the frequency bands with high contribution to the classification based on the minimum distance method to construct feature maps, which is used as the input to the convolutional neural network (CNN). The extracted frequency band features of this method can better characterize the AE signals, and the constructed feature maps make the fault information more obvious. Experiments show that the accuracy of this method for abnormal ignition advance angle under normal operating conditions of piston aero-engine is 100%, which is better than the traditional methods. In addition, the recognition accuracies under the other two operating conditions are 99.75% and 98.5%, respectively, indicating that the method has a certain universality.

Revisiting the plasmon radiation damping of gold nanorods.

Noble metal nanoparticles have been utilized for a vast amount of optical applications. For applications that use metal nanoparticles as nanosensors and for optical labeling, higher radiative efficiency is preferred. To get a deeper knowledge about the radiation damping of noble metal nanoparticles, we used gold nanorods with different geometry factors (aspect ratios) as the model system to study. We investigated theoretically how the radiation damping of a nanorod depends on the material, and shape of the particle. Surprisingly, a simple analytical equation describes radiation damping very accurately and allows the disentanglement of the maximal radiation damping parameter for gold nanorods with resonance energy Eres around 1.81 eV (685 nm). We found very good agreement with theoretical predictions and experimental data obtained by single-particle spectroscopy. Our results and approaches may pave the way for designing and optimizing gold nanostructures with higher optical signal and better sensing performance.

Single-particle spectroscopic investigation on the scattering spectrum of Au@MoS2 core-shell nanosphere heterostructure.

Owing to the uniform shape of the nanospheres, the Au@MoS2 core-shell nanosphere heterostructure enables us to design nano-optoelectronic devices and nanosensors with highly tunable and reproducible optical properties. However, until now, at the single-particle level, there is still uncertainty as to how much the scattering characteristics depend on the particle size and the local environment. In this letter, we performed an in situ single-particle study of the scattering spectrum of the Au@MoS2 core-shell nanosphere heterostructure before and after coating with the MoS2 layer. Single-particle characterization confirms that the classic quasi-static approximation (QSA) theory can be used to predict the scattering spectra of Au@MoS2 core-shell nanoparticles. Moreover, we have found that the A and B-exciton absorption peaks do not rely on the local refractive index change, while the position of the particle plasmon resonances does. Such features can be used as an internal reference for sensing applications against measurement errors, such as defocusing the imaging. Our results show that Au@MoS2 core-shell nanoparticles have the potential to become one of the promising nanosensors in the field of single-particle sensing.