A fault diagnosis system for district heating and cooling facilities

Abstract

A B S T R A C Twhich contain the main variable parameter. thus accomplishing adtive adjustment of the threshold level.District Beating and Cmling (DE) facilities produce heat in the lump and supply it for the heating and cooling of districts. A fault diagnosis system has been developed to enable DHC facilities to O B J E C T O F D I A G N O S I Sprovide stable heat supplies and this system has been proved using is a system diagram of the Hakozaki plant for the object of real facilities.diagnosis. These facilities used river water for heat rejectionTo minimize cost. the tvo heat pumps mainly use electric pover at Fig.1 and heat absorption for heat pump for the first time in Japan. ( I 'DHC facilities are provided for public utility. Their purposes are to save energy, to maintain the environment. and to equalize electric pover consumption etc.. They are compased of heat pumps for producing heat, storage tanks for storing hot and chilled rater. rater pumps for supplying buildings vith hot and chilled water. and di s t r i bu t ion pipes.The cooling capability of heat pump, and the condenser pressure are varied by the temperature and flow rate of the cooling water. The supply pumps operating at a particular time and their flow rate are also varied according to the load. Therefore, high sensitivity can not be realized by fault monitoring vith a fixed threshold. making it difficult to detect a malfunction early.night. Of the each four chilled-rater and hot-water pumps, three-are constarst speed pumps which are controlled stepwise. and the other is an inverter pump which strictly controls the supply pressure.Many kinds of faults exist and the requirements of fault diagnosis 1) Check mainly the process. but additionally the machine are as follows.character istks.-2) Predict the fault based on the detected symptom. 3) Guide the administration according to the cause and seriousness of the fault. From this viewpoint. we diagnosed the causes of reduced capability. pressure malfunction. etc., and judged their seriousness.This nev fault diagnosis system uses a causeeffect tree diagraa to find the causes of faults, and introduces.an analytical method for judging the malfunction rate.

A Statistical, Rule-Based Fault Detection and Diagnostic Method for Vapor Compression Air Conditioners

“…Most of the literature for HVAC&R applications has focused on "hard" failures for large central chilled water distribution systems and air handling systems. The literature for fault detection and diagnosis for vapor compression equipment is relatively sparse but includes contributions by McKellar (1987), Stallard (1989), Yoshimua and Noboru (1989), Kumamaru et al (1991), Wagner and Shoureshi (1992), Hiroshi et al (1992), Grimmelius et al (1995), and Rossi and Braun (1996). McKellar (1987) identified many of the common faults for home refrigerators and investigated the effects of several faults on thermodynamic measurements within the vapor compression cycle.…”

“…On-line measurements were statistically compared with normal and fault models in order to perform diagnostic classification. Kumamaru et al (1991) used characteristic curves to obtain quantitative expectations for heat pump performance as a function of cooling water temperature and loading. Diagnostics were performed using residuals as input features.…”

A Petri Net Approach to Remote Diagnosis for Failures of Cardiac Pacemakers

“…On the basis of failure thresholds and warning values, a control chart can be constructed to conduct limit control, as illustrated in Figure 13 12 . The lead time of early detection can be obtained by extrapolating the curve in a control chart with a line slope that is constructed by the last two sampled points on the curve 17 . The lead time is the period between the time point when the warning value is exceeded and the intersection of the extended line and the time axis.…”

Evaluating the Performance of a Fault Detection and Diagnostic System for Vapor Compression Equipment

“…However, contributions have been made by McKellar (1987), Stallard (1989), Yoshimua and Ito (1989), Kumamaru et al (1991), Wagner and Shoureshi (1992), Inatsu et al (1992), Grimmelius et al (1995), Stylianou and Nikanpour (1996), and Rossi andBraun (1996, 1997). For the most part, the methods developed have involved the use of thermodynamic measurements for the on-line detection and diagnosis of common faults such as refrigerant leakage that degrade performance.…”