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This paper proposes an ontology-based fault diagnosis method which overcomes the difficulty of understanding complex fault diagnosis knowledge of loaders and offers a universal approach for fault diagnosis of all loaders. This method contains the following components: (1) An ontology-based fault diagnosis model is proposed to achieve the integrating, sharing and reusing of fault diagnosis knowledge for loaders; (2) combined with ontology, CBR (case-based reasoning) is introduced to realize effective and accurate fault diagnoses following four steps (feature selection, case-retrieval, case-matching and case-updating); and (3) in order to cover the shortages of the CBR method due to the lack of concerned cases, ontology based RBR (rule-based reasoning) is put forward through building SWRL (Semantic Web Rule Language) rules. An application program is also developed to implement the above methods to assist in finding the fault causes, fault locations and maintenance measures of loaders. In addition, the program is validated through analyzing a case study.

Pr x (Co 40 Ag 60 ) 100 -x (x＝0, 0.5, 1, 1.5, 2, 3) granular films have been prepared by DC magneto controlled sputtering method. The XRD data indicated that Pr element favors the (111) plane preferential orientation. Magnetic measurements indicate that the average size of magnetic particles decreases as Pr content increases. For relatively low addition of Pr to CoAg granular films, Pr element can enhance GMR value and a peak value of about -14.3% is obtained at x＝1.

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