國立虎尾科技大學 |

Automated Fault Detection, Diagnostics, Impact Evaluation, and Service Decision-Making for Direct Expansion Air Conditioners.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Automated Fault Detection, Diagnostics, Impact Evaluation, and Service Decision-Making for Direct Expansion Air Conditioners./
作者:	Hjortland, Andrew L.
面頁冊數:	1 online resource (298 pages)
附註:	Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B.
Contained By:	Dissertation Abstracts International79-10B(E).
標題:	Mechanical engineering. -
電子資源:	click for full text (PQDT)
ISBN:	9780438018600

Automated Fault Detection, Diagnostics, Impact Evaluation, and Service Decision-Making for Direct Expansion Air Conditioners.
Hjortland, Andrew L.

Automated Fault Detection, Diagnostics, Impact Evaluation, and Service Decision-Making for Direct Expansion Air Conditioners. - 1 online resource (298 pages)

Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B.

Thesis (Ph.D.)--Purdue University, 2018.

Includes bibliographical references

This work describes approaches for automatically detecting, diagnosis, and evaluating the impacts of common faults in unitary rooftop air conditioning equipment. A semi-empirical component-based modeling approach using virtual sensors has been implemented using low-cost microcontrollers and tested on fixed-speed and variable-speed equipment using laboratory psychrometric test chambers. A previously developed virtual refrigerant charge sensor was applied to a fixed-speed rooftop unit with combinations of condenser types and expansion valve types and resulted in average prediction errors less than 10%. In addition, a methodology was developed that can be used to tune the empirical parameters of the model using data collected without psychrometric chambers, greatly reducing the experimental effort and costs required for the model. Virtual sensors previously developed for fixed-speed systems were also implemented for a variable-speed rooftop unit without significant loss of accuracy.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780438018600Subjects--Topical Terms:

557493
Mechanical engineering.
Index Terms--Genre/Form:

554714
Electronic books.

Automated Fault Detection, Diagnostics, Impact Evaluation, and Service Decision-Making for Direct Expansion Air Conditioners.
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500 $a Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B.
500 $a Adviser: James E. Braun.
502 $a Thesis (Ph.D.)--Purdue University, 2018.
504 $a Includes bibliographical references
520 $a This work describes approaches for automatically detecting, diagnosis, and evaluating the impacts of common faults in unitary rooftop air conditioning equipment. A semi-empirical component-based modeling approach using virtual sensors has been implemented using low-cost microcontrollers and tested on fixed-speed and variable-speed equipment using laboratory psychrometric test chambers. A previously developed virtual refrigerant charge sensor was applied to a fixed-speed rooftop unit with combinations of condenser types and expansion valve types and resulted in average prediction errors less than 10%. In addition, a methodology was developed that can be used to tune the empirical parameters of the model using data collected without psychrometric chambers, greatly reducing the experimental effort and costs required for the model. Virtual sensors previously developed for fixed-speed systems were also implemented for a variable-speed rooftop unit without significant loss of accuracy.
520 $a Much of this work has been devoted to estimating the performance impacts of faults that grow over time, like heat exchanger fouling or refrigerant charge leakage. To estimate these impacts, semi-empirical models for predicting the normal performance of fixed-speed and variable-speed systems have been developed and evaluated using experimentally collected data. In addition, the virtual sensor approaches for estimating the actual performance of systems using low-cost sensor measurements were evaluated. Together, normal performance models and virtual sensor estimations were used to estimate the overall impacts of several faults on system performance. A methodology for quantifying the performance impacts of simultaneously occurring faults has been developed and tested using a detailed system model and experimental results. While relatively simple, simulated and experimentally collected results showed the fault impact models were accurate within 10% of the actual fault impacts. The fault impact evaluation models could be embedded in an AFDD system and used to determine when performance degradation faults should be serviced from an operating cost perspective.
520 $a In addition, different service and maintenance strategies are compared in this work using a simulation environment that was developed. A data-driven artificial neural network model of a rooftop unit with faults has been derived for this purpose using a detailed fault impact model for direct expansion cooling equipment. This model was coupled with a building model to simulate operating cost impacts of performance degradations and service over the life of cooling equipment. An optimization problem was formulated with the goal to minimize lifetime energy and service costs and was solved using dynamic programming. Using the optimal solution as a baseline, suboptimal service decision-making strategies were implemented and simulated using the building model. It was found that condition-based maintenance strategies using the outputs of automated fault detection and diagnostics tools can significantly reduce lifetime operating costs over periodic service policies.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Mechanical engineering. $3 557493
655 7 $a Electronic books. $2 local $3 554714
690 $a 0548
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710 2 $a Purdue University. $b Mechanical Engineering. $3 845672
773 0 $t Dissertation Abstracts International $g 79-10B(E).
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