Fault diagnosis using structural knowledge, namely, the signed directed graph (SDG), is presented.A design procedure is proposed to overcome several problems associated with the SDG: (1) it produces spurious (multiple) interpretations and (2) it may delete the true interpretation when the process variable is going through nonsingle transition (this is frequently encountered in a control loop). The proposed method has the following features: (1) discretize a continuous process response into several states, and different conditions (truth tables) are imposed to check the consistency of fault propagation; (2) find the dominant path of fault propagation using steady-state gains; and (3) express the variable associated with the integrator in the velocity form. The first feature improves the modularity of the diagnostic system, which in term makes the design and maintenance of the diagnostic system easy. Furthermore, improved diagnostic resolution can be achieved by imposing more stringent conditions a t different states and by finding the dominant path. The third feature enables the system to handle variables with nonsingle transition in a control loop. A CSTR example is used to illustrate the design procedure. Simulation results show that the proposed approach based on the SDG provides an attractive alternative for process diagnosis. IntroductionIn an operating chemical plant, product quality and plant safety are maintained by controlling process variables. If there are any equipment malfunctions or human error, the product quality may suffer, the plant may be forced to shut down, and catastrophic events such as explosions, fires, or the release of toxic chemicals may occur. In most chemical plants, abnormal measurements trigger alarms in the central control room, which alert process operators. It is normally the operator's responsibility to take remedial actions to restore the plant to normal operation or to initiate the shut-down procedure. Hence, operators must find out the causes of process upsets, i.e., the fault origin. The process of finding the fault origin is called "fault diagnosis".Conventionally, fault diagnosis is the responsibility of the process operators. It is not an easy task for the operators to diagnose process faults because many factors affect the performance of the operators responding to a process alarm. These factors include the number and frequency of alarm firing, the mode of presentation of data to process operators, the complexity of the plant, and the operator's training, experience, alertness, and reaction to stress. These factors make the fault diagnosis by operators difficult. Therefore, the automated diagnostic system becomes attractive.Techniques for automated diagnosis can be classified into qualitative approach and quantitative approach depending on how rigorous the model is. Quantitative fault diagnosis utilizes a rigorous process model and on-line measurements to back-calculate unmeasured process variables as well as model parameters (Isermann, 1984). This kind of approach can a...
Ultra-thin titanium films were deposited via ultra-high vacuum ion beam sputter deposition. Since the asymmetric electric field of the metal foil plane matches the B-band absorption of chlorophyll a, the ultra-thin titanium nanolayers were able to generate surface plasmon resonance, thus enhancing the photoluminescence of chlorophyll a. Because the density of the states of plasmon resonance increases, the enhancement of photoluminescence also rises. Due to the biocompatibility and inexpensiveness of titanium, it can be utilized to enhance the bioluminescence of chloroplast in biological light emitting devices, bio-laser, and biophotonics.
Ultra-thin titanium nanolayers for plasmon-assisted enhancement of bioluminescence of chloroplast in biological light emitting devices Appl.
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