Study On The Fault Analysis And Diagnosis Of Single Double-Stage Coupling Heat Pump System (SDSCHPS)

The issue of energy sources and environment protection is always a focus in our current world, and will be a long-term problem existing in future. China is one of the countries which explode and consume great amount of energy sources every year, and in the 21 century, how to keep harmonious development is a strategic question which we have to face. At the present time, the common heating methods in north China mainly are single-direction modes, which will bring huge pressure on our future. Single double-stage coupling heat pump system (SDSCHPS) is a new kind of heating system which based on heat pump theory and zoology recycle heating concept, and also a successful case to extent air-source heat pump to the north. However, because of its complicated structure, peculiar operation environment, variety of operation modes and gradualness of many faults, the operation reliability, efficiency and life of SDSCHPS are influenced in a certain extent. Currently, most fault detection and diagnosis (FDD) systems in HVAC field only have the shut-down function when correlative temperature or pressure exceeds scheduled parameter. The existing FDD systems not only can't monitor unit's operation conditions, but also can't give concrete reason and effective solution of fault. To improve its operation reliability, energy-economy and intellectualized manage ability, this dissertation theoretically analyzed and experimentally studied the mechanism of main faults which may occur in the SDSCHPS, then searched the logic relationship between the faults and symptoms, and construct its distributed FDD system which combines artificial neural network (ANN) and expert system (ES), thereby, brought integrated frame of FDD system in the SDSCHPS.By applying hierarchy-decompose method, the fault trees of the air-to-water heat pump unit and the water-to-water heat pump unit, namely, the central equipment of the SDSCHPS were set up separately, and using occurring frequency and maintenance expense as evaluation index, the important faults and common faults of the SDSCHPS were found out. According to its occurring position, the faults of the SDSCHPS were classified to there kinds, namely, refrigeration system's faults, defrost system's faults and control system's faults. Owing to its performance would be lower when running in unhealthy condition, this dissertation put forward a state-monitor method of the SDSCHPS based on general regression neural network (GRNN). By utilizing the nice forecast ability of GRNN fully, the first role of the SDSCHPS's FDD system was realized, which means that the operation state-monitor was completed by comparing and analyzed the forecasting EER and the real EER of the SDSCHPS. Then, the performance parameters of the SDSCHPS were measured under different operation conditions and modes by experiments, which acted as samples of GRNN model, and the feasibility and validity of the state-monitor method were validated by simulating and analyzing.The common faults of refrigeration system in the SDSCHPS were investigated, and the characteristic parameters were confirmed, which were needed to fault diagnosis and reason. By applying qualitative analysis method, the relationship between the common faults and its symptoms were analyzed and the standard fault mode-base of the SDSCHPS were constructed. Finally, the FDD models based on GRNN and the fault reasoning based on rule of refrigeration system under different operation modes were set up, and the real-time FDD and reasoning of the refrigeration system were realized.The relationship between one kind of common fault occurring in air-source heat pump (ASHP) and its symptom were validated experimentally. This fault will happen when the outdoor heat exchanger's air-side of ASHP jams with ice, snow, dirt or some other stuff, which results the worse of the heat exchanging efficiency. By experiments, the dynamic variety rules of those main operation characteristic parameters were measured and analyzed, the relationship between the fault and its symptom was substantiated and different grade faults'harm on the unit's operation conditions and performance was studied quantificationally.Similarly, the dynamic variety rules of main operation characteristic parameters and performance parameters of an ASHP unit were investigated experimentally when it run under different defrost states, such as normal defrost state, advance defrost state and lag defrost state, at the same time, the defrost faults'harm on the unit's operation and performance was also studied. Then, applying outstanding mode-identify ability of the probability neural network (PNN), a simple defrost FDD model was set up, which helped to detect and diagnose defrost fault of ASHP in time. Finally, to diminish the defrost faults, this dissertation brought out an improved defrost control method, which was based on the change of outdoor fan current and wing surface temperature. The feasibility of this method was analyzed and validated by experiments, and its basic flow was designed elaborately.Because of the redundancy relationship between the multi-sensor measure data in the control system of the SDSCHPS, this dissertation put forward a kind of multi-sensor fault diagnosis and error-tolerance method, which was established on information amalgamation theory and ANN tool. Through simulating with a group of experiment data, the diagnosis and error-tolerance effect on four kinds of common faults, which were prone to occur in the control system of the SDSCHPS, was analyzed and validated thoroughly.Based on the limitation of traditional ES or ANN, this dissertation pointed out a distributed FDD artificial system in the SDSCHPS, which used ANN and ES simultaneously. The distributed FDD system not only could overcome the limitation of ANN or ES, but also take full advantage of these two tools, thus solve the problem which couldn't settled by only one of them. On the other hand, in the distributed FDD system, these problems, such as the decomposition of whole FDD task, solution of every subtask, integration of each subtask's answer, and so on, were researched thoroughly, and the theoretic frame of the distributed FDD system in the SDSCHPS was established, therefore, the theory foundation to design and apply of the distributed FDD artificial system was realized.The study work of this dissertation was very important for these problems'solution, such as advancing artificial machine-electrification incorporation, prolonging the life-span of HVAC equipment, enhancing the operation reliability and efficiency, reducing energy resources consumption, and diminishing maintenance expense, and so on. Therefore, some new methods about artificial FDD system's construction were probed, and a new viable way was offered to settle FDD problem in HVAC field.