An interorganisational logical time workflow net is formed by composing multiple logical time workflow nets via interface data places. However, even though each logical time workflow net is sound, the soundness of the composed one is indeterminate. This article addresses the issues related to soundness preservation when logical time workflow nets are composed. First, the reasons that the composed interorganisational logical time workflow net does not preserve soundness are discussed. Second, because the soundness is hard to be decided, an important class of interorganisational logical time workflow nets is put forward and the conditions to preserve soundness are proposed. The results can be used by the designers of cooperative workflows because the method in this article can reduce the analysis complexity based on the static structure of interorganisational logical time workflow nets. Next, an example of the online sale system is given to verify the effectiveness of the proposed method. Furthermore, the logical expressions attached to logical input transitions are also studied to prove soundness preservation, and a decision condition is given for interorganisational logical time workflow nets with restricted logical input expressions.

The design of aircraft hydraulic pipeline system is limited by many factors, such as the integrity of aviation structure or narrow installation space, so the limited clamp support position should be considered. This paper studied the frequency adjustment and dynamic responses reduction of the multi-support pipeline system through experiment and numerical simulation. To avoid the resonance of pipeline system, we proposed two different optimization programs, one was to avoid aero-engine working range, and another was to avoid aircraft hydraulic pump pulsation range. An optimization method was introduced in this paper to obtain the optimal clamp position. The experiments were introduced to validate the optimization results, and the theoretical optimization results can agree well with the test. With regard to avoiding the aero-engine vibration frequency, the test results revealed that the first natural frequency was far from the aero-engine vibration frequency. And the dynamic frequency sweep results showed that no resonance occurred on the pipeline in the engine vibration frequency range after optimization. Additionally, with regard to avoiding the pump vibration frequency, the test results revealed that natural frequencies have been adjusted and far from the pump vibration frequency. And the dynamic frequency sweep results showed that pipeline under optimal clamp position cannot lead to resonance. The sensitivity analysis results revealed the changing relationships between different clamp position and natural frequency. This study can provide helpful guidance on the analysis and design of practical aircraft pipeline.

Dissolved gas‐in‐oil analysis (DGA) is a powerful method to diagnose and detect transformer faults. It is of profound significance for the accurate and rapid determination of the fault of the transformer and the stability of the power. In different transformer faults, the concentration of dissolved gases in oil is also inconsistent. Commonly used gases include hydrogen (H₂), methane (CH₄), acetylene (C₂H₂), ethane (C₂H₆), and ethylene (C₂H₄). This paper first combines BP neural network with improved Adaboost algorithm, then combines PNN neural network to form a series diagnosis model for transformer fault, and finally combines dissolved gas‐in‐oil analysis to diagnose transformer fault. The experimental results show that the accuracy of the series diagnosis model proposed in this paper is greatly improved compared with BP neural network, GA‐BP neural network, PNN neural network, and BP‐Adaboost.