[ieee 2013 international conference on open source systems and technologies (icosst) - lahore,...

2013 International Conference on Open Source Systems and Technologies (ICOSST)

978-1-4799-2046-4/13/$31.00 ©2013 IEEE 13

Appliance Performance Monitoring and Warranty Alert System

Dr. Raziq Yaqub

Director Technical Training, NIKSUN Inc.

100 Nassau Park Blvd, Princeton, New Jersey, NJ08854, USA

[email protected]

Engr. Bilal Hamid Graduate student at CECOS

University, Lecturer GIST. F-3, Phase 6, Hayatabad Peshawar, Pakistan

[email protected]

Dr. Azzam ul Asar, Dean Faculty of Engineering,

CCECOS University, F-5, Phase 6, Peshawar, Pakistan

Abstract—The manufactures include a huge price of the warranties in the original cost of the appliance. However, most of th etimes, the consumers do not take a full advantage of it because either they do not comprehend the increased complexity of products technical specifications. or they do not have adequate time to track the appliance performance. Thus they do not claim warranty even if the warranty is live or about to expire, consequently they do not get the relief they deserve. To address the issue we propose a domestic appliance health monitoring system. The proposed system consists of sensors that continuously monitor the appliance performance, and send the performance data to a personal computer where the captured data is compared with the appliance technical specification stored/downloaded from the manufacturer’s website. Alarms or alerts are generated to inform them about the deteriorated performance and to take advantage of the warranty. Key Words—Appliance Health Monitoring, Warranty Compliance,

Performance Alarms, Sensors Network, M2M Communication, Energy Efficiency Ratio (EER).

Keywords—component; formatting; style; styling; insert (key words)

I. INTRODUCTION

About all products on the market today come with a standard manufacturer's warranty. Also occasionally the marketers sell extended warranties. The warranty does not come for free but includes an outrageous price. However, the consumers, do not understand its terms and coverage; mainly either because they do not comprehend the products’ technical specifications and complexity, or they do not have adequate time or interest to track the appliance performance. Thus they do not claim warrenty they qualify for, or get the relief they deserve for. We propose a system for abnormal operation of an appliance by using appliance health monitoring sensors. Such sensors will continuously monitor the performance, generate data about the appliance’s health and feed it to a personal computer through wireless modem. In computer the data will be compared with standard performance specifications fetched from the manufacturer’s website. If appliance underperforms during the warranty period, the consumer will be alarmed. After the expiry of the warranty period the proposed monitoring will detect the fault in its preliminary stage, which otherwise (if goes unnoticed) could lead to the total collapse of the appliance.

Literature survey shows that preventive maintenance techniques based on monitoring system already exist, but existing art is completely different in its objective, scope and use, as compared to our propose system. For example: 1. A wireless sensor network for health monitoring of civil

structures was designed, implemented, deployed and tested on the Golden Gate Bridge (GGB) in the USA for its structural health assessment [1]. The approach detected the changes in structural properties caused through ambient vibrations and strong motion. [2].

2. Structural health monitoring for a helicopter is proposed to enhance flight safety in [3]. It uses ultrasonic Lamb wave technology for the fast inspection of a helicopter structure, to ensure that vital structural components, more specifically, a helicopter tail boom, are not degraded by impact damage. Data analysis, in this case is performed by optical image processing, instead of multitude of semiconductor sensors.

3. In Korea, the Jindo Bridge structural health monitoring system, (that constitutes the largest deployment of wireless smart sensors for civil infrastructure monitoring to date), deploys 70 sensor nodes and two base stations to monitor the bridge. The monitoring mechanism stays off by default, and turns on with excessive wind and vibration [4].

Forth mentioned examples, clearly indicate that existing techniques are completely different in their objective, scope and implementation as compared to our propose system. Our system deploys sensors that collect the performance data from vital components of an appliance, stores the captured data in a data repository, compares it with the manufactures’ technical specifications downloaded from the manufacturer’s website, and generates alarm or alert if the appliance underperforms, or deviates from the manufacturers’ specifications. Thus the consumers can take a full advantage while the appliance warranty is live or may detect the fault in its preliminary stage, which otherwise could lead to total collapse of the appliance. Moreover, optimum maintenance schedule can be determined to avoid malfunctioning or major damage.


14

Though the proposed solution is valid for all domestic or commercial appliances, we took a domestic refrigerator as an example. Thus the solution is not limited it to a refrigerator only. Also though we are proposing to collect temperature and line frequency samples, in addition to power usage, for the performance evaluation, however, in the simulation we are using power usage only for the sake of simplicity. The rest of the paper is divided into the following sections. Section-2 provides the detailed description of the proposed system including the algorithm, Section-3 elucidates system analysis, Section-4 pronounces future work, Section-5 concludes the paper, and section 6 lists references.

II. DETAILED DESCRIPTION

The main components of the solution consist of sensor nodes, central node, transmitter, receiver, a Personal Computer (PC) and the appliance under warranty (i.e. refrigerator in this case). Sensor nodes collect the data from the compressor and the condenser and send it to the central node over radio that forwards it to the PC for further analysis, as shown in Figure-1 and Figure-2. An algorithm, running in the laptop, compares the real time appliance performance with the manufacturers’ specified performance at predefined intervals. These intervals are adjusted based on self-learning mechanism. Sensor nodes are simple, robust and multipurpose so that minimum sensors could be used for system simplicity and cost effusiveness. A. Algorithm The sensor nodes collect the data related to power consumption, from the compressor and the condenser at the regular intervals. The data is transferred to the PC via central node using standard interfaces, as shown in figure-1. PC compares the data collected by the sensors with the data disclosed in the manufacturer’s technical specifications of the appliance. Manufacturer’s technical specifications are downloaded into the PC directly from the manufacturer’s website through M2M communication with appliance’s microprocessor. The comparison allows PC to scrutinize the performance deviation of the refrigerator.

Figure-1: Concept of Proposed System

Figure-2: Block Diagram of Proposed System

The detailed algorithm governing the performance and warranty alert system is presented in figure 2, and is explained in the following paragraphs.

The proposed system communicates with the microprocessor of the appliance and acquires the IP address of the microprocessor of the appliance using Address Resolution Protocol (ARP) that involves encoding the IP address of the intended recipient in a broadcast message. It is sent over a Local Area Network (LAN) to allow the intended recipient of an IP datagram to respond to the source with its data link layer address through a request/reply method. Once the communication channel is established, the algorithm requests the appliance to provide its model number and manufacturer’s URL (Uniform Resource Locator) where the technical specification, warranty information and other appliance performance related information are available. Though it is not a normal practice these days, but we strongly recommend the department of consumers’ affairs & consumer protection, and Energy Commission to mandate it for all the manufactures to provide such information in a standard format and at a specified directory.

The algorithm waits for user input on purchase related data such as purchase date, appliance price, extended warranty (if any), and comments/notes/memo (if any) for user to be reminded. The algorithm records this information along with the time stamp. Time stamp may be received from the PC, or from GPS (that needs provisioning of GPS Receiver). The algorithm also sets the delay value X = 0. This is the time the system will wait before fetching the appliance performance parameters from the Central Node. This value may increase or decrease based on self-learning algorithm. The algorithm is


15

not discussed in this paper; however, it will determine how frequently the system needs to fetch the performance data from the Central Node. If the performance is satisfactory, the time window size will be increased and if the performance is deteriorating, the window size will be reduced and more frequently performance data will be fetched.

The algorithm will then compare the fetched data with the data provided in the standard technical specification. In this research paper, energy consumption and Energy Efficiency Ratio (EER), are considered to be the appliance’s performance evaluators for the simplicity, however, in our future work, we plan to consider more parameters such as frequency, temperature, compressor speed, vibration and pressure etc.

The algorithm then records the comparative analysis and also displays it on Graphical User Interphase (GUI) for the user review. If the appliance is under performing, and warranty is still valid/usable, an alert is sent to the user that informs him to cash his warranty privilege, otherwise time window is calculated for next check based on the self-learning algorithm. If the appliance is underperforming and warranty is expired, a different type of notification that relates to the appliance maintenance is sent and the time window is calculated for next check based on the self-learning algorithm. The alert sent to the user may be in the form of a visible alarm, a text message, an e- mail, or any other type of state of the art communication means.

III. ANALYSIS

A fault is an abnormal condition which is undesirable, but cannot be avoided. A fault can result in complete shutdown of an appliance, or may damage some component. Fault can be impulsive or it may lead to degradation .Fault is modeled as an event with high power absorption. In case of fault high current and therefore power flows through an appliance. During fault power absorption will increase from the upper bound of the expected value. The expected value is retrieved from power consumption data provided by manufacturer. Similarly if some part of refrigerator stop working then energy consumption of refrigerator will decrease thus a lower boundary is also selected.

Figure 4 shows performance analysis of refrigerator for two years. In this figure, our monitoring system has detected irregularity in actual power consumed of the refrigerator. The power consumption in September 2011 is much greater than the power consumption specified by manufacturer (indicated by red line). A similar violation is again observed in December 2012, (see purple line) when the power consumption has decreased then minimum allowed power

consumption. In both the cases, the monitoring system will notify the user.

Figure-3: Performance monitoring and warranty alert algorithm


16

Refer figure 5, if the appliance is under warranty, a warrantyusable notification will be generated (orange column), and if warranty is expired, a maintenance required notification will be generated. In figure 5 the first fault occurred in time period when warranty was usable, so warranty usable alarm (yellow line) was raised. The second fault occurred when the warrant was expired Thus only fault alarm (blue column) was raised.

Degradation refers to decrease in efficiency of refrigerator with passage of time. This decrease may be due to low quality refrigerant, leakage of refrigerant, condenser coil fouling and compressor oil quality degradation. Degradation is not a quick process it take a lot of time to decrease efficiency of refrigerator. For different operating condition the rate of degradation is different. The baseline is Energy Efficiency Ratio. Energy Efficiency Ratio (EER) is the ratio of Cooling Capacity of a refrigerator system in British Thermal Units for every hour, to the electrical input power under certain specified tests.

EER value selected in this case is 1.8.if the value of EER decreases from 1.6 it is considered as degradation. Figure 6 shows that initially the performance of refrigerator is within the bound (From Jan 2011 to Jan 2012), hence no degradation is detected .But as the EER decreases further, monitoring system detects it as a fault (degradation). Once fault is detected, fault alarm is activated .Next the monitoring system will check the warranty if warranty is valid it will raise warranty alarm and inform the customer about the fault .Degradation alarm, warranty alarm is shown in figure 7.

Figure 4: Power monitoring and comparison

IV. FUTURE WORK Develop a protocol for acquiring product specification, warranty information and other product related information automatically from the equipment manufacturer’s website automatically in a standard format. The protocol will be introduced to standards organization such as IEEE and regulatory organization such as Energy Commission for mandating and implementations.

Figure 5: Fault , warrant check and alarms

Figure 6: EER monitoring and comparision

Figure 7 Degradation ,warrant check and alarms

In this research paper, energy consumption and Energy Efficiency Ratio (EER), are considered to be the appliance’s performance evaluators for the simplicity, however, in our future work, we plan to consider more evaluation parameters such as frequency, temperature, compressor speed, and pressure etc.


17

Performance monitoring can be extended further to detect vibration (due to any mechanical phenomenon, such as loosening of a component of an appliance during operation, or due to stress/overloading the appliance. Vibrations may lead to damage the loose component itself or another component in the close vicinity to it. In our future work we plan consider viberation phenomemn as well.

V. CONCLUSION

Evaluating performance of home appliance is difficult task for a common customer. Customer is not able to judge performance of appliance due to lack of technical knowledge or lack of time or interest to track performance on daily basis. The goal of this research paper is to develop an autonomous system which can help customer monitor the performance of the appliance. Performance monitoring helps customer to evaluate appliance performance and claim warranty if appliance’s performance is under warranty and is not performing satisfactorily. Thus by introducing this low cost system, customer can save a lot, get mental relief and extend the life of appliance.

REFRENCES [1] Kim, S., Pakzad, S., Culler, D.E., Demmel, D., Fenves, D., Glaser, S. and Turon, M. 2006. “Health Monitoring of Civil Infrastructures Using Wireless Sensor Networks” Technical report No. UCB/EECS-2006-121, University of California, Berkeley, CA. [2] R. Andrew Swartz, Andrew Zimmerman and Jerome P. Lynch “Structural Health Monitoring System with the Latest Information Technologies” Proceedings of 5th Infrastructure & Environmental Management Symposium, Yamaguchi, Japan, September 28, 2007 [3] Maria Ercsey-Ravasz , Fran Fransens , Helge Pfeiffer , Gaël Monavon , Caroline Korosec , Wolfgang Hillger , Sabine Van Huffel , Martine Wevers “Structural Health Monitoring of a helicopter tail boom using Lamb waves – Advanced data analysis of results obtained with integrated optical fiber sensing technology” EU Project Meeting on Aircraft Integrated Structural Health Assessment (AISHA), Leuven, Belgium, June 2007 [4] Shinae Jang, Hongki Jo , Soojin Cho, Kirill Mechitov, Jennifer A. Rice, Sung-Han Sim, Hyung-Jo Jung, Chung-Bang Yun,Billie F. Spencer, Jr.and Gul Agha” Structural health monitoring of a cable-stayed bridge using smart sensor technology: deployment and evaluation” Smart Structures and Systems, Vol. 6, No. 5-6 (2010) 439-459

BIBILIOGRAPHY

Dr. Yaqub earned a Ph.D. in Wireless Communication from Keio University, Japan, and MBA in Marketing from Fairleigh Dickenson University, USA. Dr. Yaqub remained an Executive Director of Toshiba America Research, Inc. from 2001 to 2009, Sr. Consultant to the State of New Jersey for 700 MHz LTE Public Safety Network/grant writing. His research

interests address LTE, Smart Grid and Electric Vehicles issues. He filed several patents (16 issued), published numerous papers in international conferences, and submitted 150+ contributions in technical standards organizations. He remained a working group chairman in Mobile Wireless Internet Forum, Chairman IEEE Membership Development, Rapporteur 3GPP, keynote speaker, panelist, and guest speaker in numerous International Conferences.

Engr. Bilal Hamid completed graduate program in 2008 from N-W.F.P UET, Pakistan in 2008, and securing Bachelor degree in Electrical Engineering. In 2012 he completed Master Degree in power and control engineering from CECOS University .He is now a student of Ph.D. at CECOS University. He possess four year of field experience in substation civil work, erection, Testing and commissioning.

Currently he is Lecturer at Gandhara Institute of Science and Technology, Peshawar, Pakistan.

Prof. Azzam ul Asar did his bachelor’s degree in Electrical Engineering from University of Engineering and Technology (UET) Peshawar and received his M.Sc. and Ph.D. degree from the University Of Strathclyde Glasgow U.K. Dr. Azzam-ul-Asar Dean, Faculty of Engineering Post Doctorate in Electrical Engineering (New Jersey Institute of Tech, USA). Glasgow U.K. His research

area include smart grid, power system, microgrid and intelligent system. He is currently Dean of Faculty of Engineering at CECOS University.

[ieee 2013 international conference on open source systems and technologies (icosst) - lahore,...

Documents