Autor: Xie, C. - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Experimental Investigation Of Segregation Of Carbon Atoms Due To Sub-Zero Cryogenic Treatment In Cold Work Tool Steel By Mechanical Spectroscopy And Atom Probe Tomography
Doświadczalne badania segregacji atomów węgla w stali narzędziowej do pracy na zimno po obróbce kriogenicznej metodą spektroskopii mechanicznej i tomografii atomowej
Autorzy:: Min, N.
Li, H. M.
Xie, C.
Wu, X. C.
Powiązania:: https://bibliotekanauki.pl/articles/351716.pdf
Data publikacji:: 2015
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: cryogenic treatment
isothermal martensite
atom probe tomography
mechanical spectroscopy
Cottrell atmosphere
obróbka kriogeniczna
izotermiczny martenzyt
tomografia atomowa
spektroskopia mechaniczna
atmosfera Cottrella
Opis:: In this work, we present mechanical spectroscopy of cold work tool steel subjected to sub-zero cryogenic soaking treatment to reveal the carbon segregation and the subsequent carbides refinement. The maximum of Snoek-Köster (SK) peak height was obtained in the sample subjected to soaking 1h at −130°C cryogenic treatment. The SK peak height is reduced with prolonging the soaking time. The results indicate that an increase in the height of SK peak is connected with an increase in dislocation density and the number of segregated carbon atoms in the vicinity of dislocations or twin planes after martensite transformation at −130°C which is confirmed by corresponding TEM and atom probe tomography measurement. Hence, it is suggested that the isothermal martensite, formed during the cryogenic soaking treatment decreases (APT) the height of SK peak.
W pracy przedstawiono wyniki spektroskopii mechanicznej stali narzędziowej do pracy na zimno poddanej obróbce kriogenicznej w celu odsłonięcia segregacji węgla i późniejszego tworzenia węglików. Dzięki połączeniu transmisyjnej mikroskopii elektronowej (TEM) i tomografii atomowej (APT) uzyskano maksymalny pik Snoek-Köstera (SK) w próbce poddanej obróbce kriogenicznej przez 1 godzinę w −130°C. Wysokość piku SK obniża się wraz z wydłużeniem czasu obróbki. Wyniki wskazują, że zwiększenie wysokości piku SK jest połączone ze wzrostem gęstości dyslokacji i liczby segregowanych atomów węgla w sąsiedztwie dyslokacji lub płaszczyzn bliźniaczych po przemianie martenzytycznej w -130°C, co potwierdzone jest odpowiednimi pomiarami TEM oraz APT. W związku z tym proponuje się, że izotermiczny martenzyt powstały podczas obróbki kriogenicznej zmniejsza wysokość piku SK.
Źródło:: Archives of Metallurgy and Materials; 2015, 60, 2A; 1109-1113
1733-3490
Pojawia się w:: Archives of Metallurgy and Materials
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: A Signal Subspace Speech Enhancement Approach Based on Joint Low-Rank and Sparse Matrix Decomposition
Autorzy:: Sun, C.
Xie, J.
Leng, Y.
Powiązania:: https://bibliotekanauki.pl/articles/177990.pdf
Data publikacji:: 2016
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: subspace speech enhancement
singular value decomposition
joint low-rank and sparse matrix decomposition
Opis:: Subspace-based methods have been effectively used to estimate enhanced speech from noisy speech samples. In the traditional subspace approaches, a critical step is splitting of two invariant subspaces associated with signal and noise via subspace decomposition, which is often performed by singular-value decomposition or eigenvalue decomposition. However, these decomposition algorithms are highly sensitive to the presence of large corruptions, resulting in a large amount of residual noise within enhanced speech in low signal-to-noise ratio (SNR) situations. In this paper, a joint low-rank and sparse matrix decomposition (JLSMD) based subspace method is proposed for speech enhancement. In the proposed method, we firstly structure the corrupted data as a Toeplitz matrix and estimate its effective rank value for the underlying clean speech matrix. Then the subspace decomposition is performed by means of JLSMD, where the decomposed low-rank part corresponds to enhanced speech and the sparse part corresponds to noise signal, respectively. An extensive set of experiments have been carried out for both of white Gaussian noise and real-world noise. Experimental results show that the proposed method performs better than conventional methods in many types of strong noise conditions, in terms of yielding less residual noise and lower speech distortion.
Źródło:: Archives of Acoustics; 2016, 41, 2; 245-254
0137-5075
Pojawia się w:: Archives of Acoustics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Dual manipulator system calibration based on virtual constraints
Autorzy:: Zhu, Q.
Xie, X.
Li, C.
Powiązania:: https://bibliotekanauki.pl/articles/200227.pdf
Data publikacji:: 2019
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: dual manipulators
calibration
virtual constraint
optical axis
robot-robot
hand-eye
Opis:: Calibration is necessary for dual manipulator to complete operational tasks. This paper proposes an effective robot-robot and hand-eye calibration method based on virtual constraints. Firstly, a rotational error model and a translational error model are established based on the relationships between the transformation matrices of the dual manipulator calibration system. Then a poses-alignment method is designed to make the poses of the two robots satisfy the constructed virtual constraints. At the aligned positions, the joint angles of the two robots are saved and used to calculate the values of the variables in the error models. Finally, the robot-robot and hand-eye rotational errors are estimated by an iterative algorithm. These errors are then used to calculate translational errors based on the SVD (singular value decomposition) method. To show the feasibility and effectiveness of the proposed method, experiments of robot-robot and hand-eye calibration for dual manipulators are performed. The experiment results demonstrate that the accuracy of the dual manipulator system is improved greatly.
Źródło:: Bulletin of the Polish Academy of Sciences. Technical Sciences; 2019, 67, 6; 1149-1159
0239-7528
Pojawia się w:: Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Noise Elimination of Reciprocating Compressors Using FEM, Neural Networks Method, and the GA Method
Autorzy:: Chang, Y.-C.
Chiu, M.-C.
Xie, J.-L.
Powiązania:: https://bibliotekanauki.pl/articles/178126.pdf
Data publikacji:: 2017
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: finite element method
polynomial neural network model
genetic algorithm
group method of data handling
reciprocating compressor
optimization
Opis:: Industry often utilizes acoustical hoods to block noise emitted from reciprocating compressors. However, the hoods are large and bulky. Therefore, to diminish the size of the compressor, a compact discharge muffler linked to the compressor outlet is considered. Because the geometry of a reciprocating compressor is irregular, COMSOL, a finite element analysis software, is adopted. In order to explore the acoustical performance, a mathematical model is established using a finite element method via the COMSOL commercialized package. Additionally, to facilitate the shape optimization of the muffler, a polynomial neural network model is adopted to serve as an objective function; also, a Genetic Algorithm (GA) is linked to the OBJ function. During the optimization, various noise abatement strategies such as a reverse expansion chamber at the outlet of the discharge muffler and an inner extended tube inside the discharge muffler, will be assessed by using the artificial neural network in conjunction with the GA optimizer. Consequently, the discharge muffler that is optimally shaped will decrease the noise of the reciprocating compressor.
Źródło:: Archives of Acoustics; 2017, 42, 2; 189-197
0137-5075
Pojawia się w:: Archives of Acoustics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

Tytuł:: Efficient learning variable impedance control for industrial robots
Autorzy:: Li, C.
Zhang, Z.
Xia, G.
Xie, X.
Zhu, Q.
Powiązania:: https://bibliotekanauki.pl/articles/200716.pdf
Data publikacji:: 2019
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: variable impedance control
reinforcement learning
efficient
Gaussian process
industrial robots
impedancja
poprawa efektywności
wydajność
model Gaussa
roboty przemysłowe
Opis:: Compared with the robots, humans can learn to perform various contact tasks in unstructured environments by modulating arm impedance characteristics. In this article, we consider endowing this compliant ability to the industrial robots to effectively learn to perform repetitive force-sensitive tasks. Current learning impedance control methods usually suffer from inefficiency. This paper establishes an efficient variable impedance control method. To improve the learning efficiency, we employ the probabilistic Gaussian process model as the transition dynamics of the system for internal simulation, permitting long-term inference and planning in a Bayesian manner. Then, the optimal impedance regulation strategy is searched using a model-based reinforcement learning algorithm. The effectiveness and efficiency of the proposed method are verified through force control tasks using a 6-DoFs Reinovo industrial manipulator.
Źródło:: Bulletin of the Polish Academy of Sciences. Technical Sciences; 2019, 67, 2; 201-212
0239-7528
Pojawia się w:: Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:: Biblioteka Nauki