In this study, a new nonlinear fatigue damage accumulation model is proposed to consider the effects of loading history and loading sequence under multi-level stress loading based on the Miner–Palmgren rule and S-N curve. By using damage equivalence, the new model is simplified and another form of the model is given. This model improves the application of the traditional Miner–Palmgren rule, by considering not only the loading sequence effect but also the loading history effect. The methods for calculating the degree of safety of specimens and cumulative damage of low-amplitude loads are also presented. Applicability of the new model is validated by predicting the fatigue life of 16Mn and 45 steel specimens under two-level stress loading. Further validation is carried out for the case of 41Cr4 and Aluminum alloys 6082 T6 under multi-level stress loading, and the strengthening and damaging effect of low-amplitude loads is considered. Comparing with the Miner–Palmgren rule and some new models, this new model gives more accurate and reliable prediction.

Ultrasonic liquid level measuring technology has been extensively applied in the industrial field, which is characterized by its high accuracy, strong ability of anti-electromagnetic interference and simple structure. However, its measurement results are easily affected by the tilt of liquid level and ripple. In this study, the traditional gas-liquid interface was transformed into a solid-liquid interface based on the acoustic scattering by a rigid sphere and a circular waveguide, and the liquid level was measured with the stable reflecting surface by complying with the liquid level in the duct. Such a method could overcome the effect of the tilt of liquid level and ripple on the measurement results. In this study, a signal processing method to improve the signal to noise ratio of the direct wave was proposed. To improve the sound intensity of the direct wave and reduce the effect of high-order mode waves on the signal, the transceiver was applied with a matching layer, and the appropriate waveguide material should be selected to absorb a portion of high-order mode waves. As revealed from the experimentally achieved results, an optimized lightweight ultrasonic liquid level sensor was proposed to eliminate the effect of ripple, and the tilt of liquid level increased from 20° to 60°.

There are several intelligent algorithms that are continually being improved for better performance when solving the flexible job-shop scheduling problem (FJSP); hence, there are many improvement strategies in the literature. To know how to properly choose an improvement strategy, how different improvement strategies affect different algorithms and how different algorithms respond to the same strategy are critical questions that have not yet been addressed. To address them, improvement strategies are first classified into five basic improvement strategies (five structures) used to improve invasive weed optimization (IWO) and genetic algorithm (GA) and then seven algorithms (S1–S7) used to solve five FJSP instances are proposed. For the purpose of comparing these algorithms fairly, we consider the total individual number (TIN) of an algorithm and propose several evaluation indexes based on TIN. In the process of decoding, a novel decoding algorithm is also proposed. The simulation results show that different structures significantly affect the performances of different algorithms and different algorithms respond to the same structure differently. The results of this paper may shed light on how to properly choose an improvement strategy to improve an algorithm for solving the FJSP.

Gas turbine converts chemical energy into mechanical energy and provide energy for aircraft, ships, etc. The performance diagnosis of rotating components of gas turbine are essential in terms of the high failure rate of these parts. A problem that the sudden changing of operation state of turbines may lead to the misdiagnosis due to the defect of gas turbine’s model. This paper constructs the strong tracking filter based on the unscented Kalman filter to achieve accurate estimation of gas turbine’s measured parameters when the state changes suddenly. In the strong tracking filter, a parameter optimization method based on the residual similarity of measured parameters is proposed. Next, adopt the measured parameters filtered by the strong tracking filter to construct the health parameters estimation algorithm based on the particle filter. The particle weight is optimized by the mean adjustment method. Performance diagnosis is realized by checking the changes of health parameters output by particle filter. The results show that the proposed method improves the accuracy of performance diagnosis obviously.

With recent industrial upgrades, it is essential to transform the current forward supply networks (FSNs) into closed-loop supply networks (CLSNs), which are formed by the integration of forward and reverse logistics. The method chosen in this paper for building reverse logistics is to add additional functions to the existing forward logistics. This process can be regarded as adding reverse edges to the original directed edges in an FSN. Due to the limitation of funds and the demand for reverse flow, we suppose that a limited number of reverse edges can be built in a CLSN. To determine the transformation schemes with excellent robustness against malicious attacks, this paper proposes a multi-population evolutionary algorithm with novel operators to optimize the robustness of the CLSN, and this algorithm is abbreviated as MPEA-RSN. Then, both the generated and realistic SNs are taken as examples to validate the effectiveness of MPEA-RSN. The simulation results show that the index R, introduced to evaluate the robustness of CLSNs, can be improved by more than 95%, and this indicates that (1) the different schemes for adding reverse routes to an FSN can lead to different robustness values, and (2) the robustness of the transformed CLSN to malicious attacks can be significantly improved after optimization by MPEA-RSN. When an FSN is to be transformed into a CLSN, this paper can provide a frame of reference for building a CLSN that is robust to malicious attacks from a network structural perspective.