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- Lu, Yuqian, et al.
(författare)
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Outlook on human-centric manufacturing towards Industry 5.0
- 2022
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Ingår i: Journal of manufacturing systems. - : Elsevier BV. - 0278-6125 .- 1878-6642. ; 62, s. 612-627
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Tidskriftsartikel (refereegranskat)abstract
- The recent shift to wellbeing, sustainability, and resilience under Industry 5.0 has prompted formal discussions that manufacturing should be human-centric - placing the wellbeing of industry workers at the center of manufacturing processes, instead of system-centric - only driven by efficiency and quality improvement and cost reduction. However, there is a lack of shared understanding of the essence of human-centric manufacturing, though significant research efforts exist in enhancing the physical and cognitive wellbeing of operators. Therefore, this position paper presents our arguments on the concept, needs, reference model, enabling technologies and system frameworks of human-centric manufacturing, providing a relatable vision and research agenda for future work in human-centric manufacturing systems. We believe human-centric manufacturing should ultimately address human needs defined in an Industrial Human Needs Pyramid - from basic needs of safety and health to the highest level of esteem and self-actualization. In parallel, human-machine relationships will change following a 5C evolution map - from current Coexistence, Cooperation and Collaboration to future Compassion and Coevolution. As such, human-centric manufacturing systems need to have bi-directional empathy, proactive communication and collaborative intelligence for establishing trustworthy human-machine coevolution relationships, thereby leading to high-performance human-machine teams. It is suggested that future research focus should be on developing transparent, trustworthy and quantifiable technologies that provide a rewarding working environment driven by real-world needs.
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| 2. |
- Wang, Zengkun, et al.
(författare)
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Block-MUSIC in blade tip timing : Performance study of block snapshot matrix
- 2023
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Ingår i: Mechanical systems and signal processing. - : Elsevier. - 0888-3270 .- 1096-1216. ; 198
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Tidskriftsartikel (refereegranskat)abstract
- Periodic nonuniform sampling can be viewed as a combination of uniform sampling and non-uniform sampling. Blade tip timing (BTT) technique conforms to this sampling pattern, where non-uniformity and uniformity are caused by non-uniform probe layout and rotational motion, respectively. By introducing block structure into multiple signal classification (MUSIC) for the extension of snapshot matrix, Block-MUSIC has been proved to be anti-aliasing and can filter out synchronous frequency in BTT application. However, the theoretical justification of the block structure is lacking. In this paper, a performance study of Block-MUSIC is conducted from three aspects: identifiability, stability, and resolution. Additionally, a pseudo 2-dimensional signal model is proposed to represent the periodic nonuniform sampled signal under the assumption of equally spaced probes. To support the performance study, simulations and experiments are carried out to demonstrate how the size of the snapshot matrix, the noise level, and the amplitude of sinusoidal signals affect algorithm performance. Simulation codes are available at https://github.com/superjdg/block-music4btt.
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| 3. |
- Wang, Zengkun, et al.
(författare)
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Min-Max Probe Placement and Extended Relaxation Estimation Method for Processing Blade Tip Timing Signals
- 2023
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Ingår i: IEEE Transactions on Instrumentation and Measurement. - : Institute of Electrical and Electronics Engineers (IEEE). - 0018-9456 .- 1557-9662. ; 72
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Tidskriftsartikel (refereegranskat)abstract
- Measuring blade displacement using blade tip timing (BTT) enables nonintrusive monitoring of rotating blades and their vibration frequencies. The average sampling frequency of BTT is the product of the number of measurement probes and rotational frequency, which is usually far less than the blade natural frequency due to the limited number of probes. The pattern of the aliasing that arises from under-sampling is rather complex under uneven probe placement. In this article, we consider a probe placement design that is based on minimizing the maximum sidelobe level of the spectral window to suppress the aliasing frequencies in the spectrum. Based on a signal model containing both asynchronous and synchronous sinusoids, we then develop an extended version of the RELAX method (ERELAX) to estimate their parameters simultaneously. Model order selection rules are also used to determine the number of asynchronous sinusoids. The frequency ambiguity that arises from periodic nonuniform sampling (PNS) is also discussed based on the convolution in the frequency domain. Numerical simulations and results of a curved-blade experiment show that the proposed method has a mean squared estimation error less than 25% of that of two state-of-the-art methods (Block-OMP and MUSIC), requires 40% of the data length needed by the latter methods to achieve the same estimation accuracy, and has the smallest standard deviation of the reconstruction errors. Simulation codes are available at https://github.com/superjdg/RELAX_BTT.
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