Research On Testability Technology For Equipment Health Management

With the gradual transformation of equipment maintenance support modes and theever increasing maturity of fault prognostics technologies, equipment healthmanagement (EHM) is bound to become an important part in the design, production andusage of future equipments. On the one hand, EHM performance relies on informationprocessing and decision making, and is more dependent on information acquisition onthe other hand. With the increase of equipment complexity, it is necessary to taketestability into account according to EHM requirements at equipment design stage, e.g.,how to select comprehensive test items, configure rational sensors, make scientific testtiming and adopt the corresponding technologies to realize the testability design. Thecurrent testability theory and technology, which are mainly for condition monitoringand fault diagnostics, do not consider the requirements of fault size, fault evolution andhealth evaluation for testability. How to develop testability design concurrentlyaccording to EHM requirements at the early design stage is a fundamental way toimprove EHM performance and further improve maintenance decision ability, and isalso a problem urgently to be solved during the development of equipments.In view of the fact that after considering EHM requirements in testability, theconnotations and architecture are not yet clear and the key technologies still await to bebreakthrough, this dissertation conducts in-depth studies on testability index, testabilitymodel and testability optimization design. The main content and outcomes are listed asfollows:1. Based on the current testability theory and framework and according to thefunctional requirements of EHM, the connotation of testability for EHM is defined andthe technology architecture of testability for EHM is proposed.2. To address the problems that the current testability indices are mainly used toevaluate fault detectability level and fault isolability level and are unable to describetestability level for EHM comprehensively, based on the qualitative intrinsicrequirements analysis of EHM for testability, testability indices architecture for EHM isconstructed from the aspects of “accuracy” and “timelines”, and the relationshipsbetween the indices are further analyzed.3. The modeling requirements after considering EHM functions in testability areanalyzed systematically and a quantified uncertainty hierarchical model (QUHM) isconstructed. At the system level, fault-test dependency is modeled through quantifieddirected graph and functional fault analysis; meanwhile fault attributes, test attributesand fault propagation attributes are assigned to the nodes and directed edges in the formof probability, fuzziness and uncertainty. At the component level, fault evolution-testdependency is obtained by physics-of-failure models or extended failure modes, mechanisms and effects analysis. The QUHM can be represented by a multipledependency matrix, based on which testability analysis and evaluation for EHM can berealized.4. The requirements of test item for EHM are analyzed, and a general process fortest optimization selection and sensor optimization configuration is proposed. Based onthe process, test preliminary selection rules and approaches are presented firstly. Then, atest selection and optimization model for EHM is formulated and a Boolean logic-basedoptimization method is also designed. Finally, fault detection uncertainty is analyzedsystematically from fault attributes, sensor attributes and fault-sensor matchingattributes. Based on the framework and fault detection uncertainty analysis, a sensoroptimization configuration model is formulated, which takes total sensor cost asoptimization object and the testability indices under uncertain detection as constraintconditions. Due to NP-hard property of the model, a genetic algorithm is designed toobtain the optimal sensor configuration.5. Based on the connotations and technology architecture of testability for EHM,the necessity and new requirements of test timing optimization are analyzed, and aMarkov-based test timing optimization method is studied. Firstly, for the storageequipments, a periodic test timing optimization approach based on Markov renewalprocess is presented. Further, for the usage equipments, the requirements of EHM fordynamic sequential test (DST) are analyzed. According to the characteristics of DST,the partially observable semi-Markov decision processes (POSMDP) is formulated.Then, POSMDP is converted to be completely observable belief semi-Markov decisionprocesses, based on which a dynamic sequential test timing optimization model isconstructed. The goal is to minimize the long-run expected average cost per unit time.The proposed method, which decides the next test timing based on equipment healthstate and considers the health evaluation uncertainty, is more suitable for the functionalrequirements of EHM. The DST is also applicable to storage equipments.A typical electromechanical servo system is taken as an example to verify andvalidate the proposed models and methods in the corresponding sections. The resultsshow that the testability indexes, testability model and testability design methods arefeasible, reasonable and available, and are of great engineering significance.