@article{ laughman_power_2003,
  title = {Power signature analysis},
  volume = {1},
  issn = {1540-7977},
  doi = {10.1109/MPAE.2003.1192027},
  abstract = {Nonintrusive load monitoring ({NILM}) can determine operating schedule of electrical loads in a target system from measurements made at a centralized location, such as the electric utility service entry. {NILM} is an ideal platform for extracting useful information about any system that uses electromechanical devices. It has a low installation cost and high reliability because it uses a bare minimum of sensors. It is possible to use modem state and parameter estimation algorithms to verify remotely the "health" of electromechanical loads by using {NILM} to analyze measured waveforms associated with the operation of individual loads. {NILM} can also monitor the operation of the electrical distribution system itself, identifying situations where two or more otherwise healthy loads interfere with each other's operation through voltage waveform distortion or power quality problems. Strategies for nonintrusive monitoring have developed over the last 20 years. Advances in computing technology make a new wealth of computational tools useful in practical, field-based {NILM} systems. This article reviews techniques for high-performance nonintrusive load and diagnostic monitoring and illustrates key points with results from field tests.},
  number = {2},
  journal = {{IEEE} Power and Energy Magazine},
  author = {Laughman, C. and Lee, Kwangduk and Cox, R. and Shaw, S. and Leeb, S. and Norford, L. and Armstrong, P.},
  month = {March},
  year = {2003},
  keywords = {Algorithm design and analysis, Costs, Data mining, Electric variables measurement, Electromechanical sensors, Modems, Monitoring, Parameter estimation, Power industry, computerised monitoring, diagnostic monitoring, distribution networks, distribution system operation monitoring, electric utility service entry, electrical loads, electromechanical devices, harmonic distortion, high reliability, load (electric), measured waveforms analysis, nonintrusive load monitoring, parameter estimation algorithms, power quality, power signature analysis, power supply quality, power system harmonics, power system measurement, state estimation algorithms, voltage waveform distortion, waveform analysis},
  pages = {56--63}
}

{"_id":"6zyu6yi2PtdbGAJDe","authorIDs":[],"author_short":["Laughman, C.","Lee, K.","Cox, R.","Shaw, S.","Leeb, S.","Norford, L.","Armstrong, P."],"bibbaseid":"laughman-lee-cox-shaw-leeb-norford-armstrong-powersignatureanalysis-2003","bibdata":{"abstract":"Nonintrusive load monitoring (NILM) can determine operating schedule of electrical loads in a target system from measurements made at a centralized location, such as the electric utility service entry. NILM is an ideal platform for extracting useful information about any system that uses electromechanical devices. It has a low installation cost and high reliability because it uses a bare minimum of sensors. It is possible to use modem state and parameter estimation algorithms to verify remotely the \"health\" of electromechanical loads by using NILM to analyze measured waveforms associated with the operation of individual loads. NILM can also monitor the operation of the electrical distribution system itself, identifying situations where two or more otherwise healthy loads interfere with each other's operation through voltage waveform distortion or power quality problems. Strategies for nonintrusive monitoring have developed over the last 20 years. Advances in computing technology make a new wealth of computational tools useful in practical, field-based NILM systems. This article reviews techniques for high-performance nonintrusive load and diagnostic monitoring and illustrates key points with results from field tests.","author":["Laughman, C.","Lee, Kwangduk","Cox, R.","Shaw, S.","Leeb, S.","Norford, L.","Armstrong, P."],"author_short":["Laughman, C.","Lee, K.","Cox, R.","Shaw, S.","Leeb, S.","Norford, L.","Armstrong, P."],"bibtex":"@article{ laughman_power_2003,\n title = {Power signature analysis},\n volume = {1},\n issn = {1540-7977},\n doi = {10.1109/MPAE.2003.1192027},\n abstract = {Nonintrusive load monitoring ({NILM}) can determine operating schedule of electrical loads in a target system from measurements made at a centralized location, such as the electric utility service entry. {NILM} is an ideal platform for extracting useful information about any system that uses electromechanical devices. It has a low installation cost and high reliability because it uses a bare minimum of sensors. It is possible to use modem state and parameter estimation algorithms to verify remotely the \"health\" of electromechanical loads by using {NILM} to analyze measured waveforms associated with the operation of individual loads. {NILM} can also monitor the operation of the electrical distribution system itself, identifying situations where two or more otherwise healthy loads interfere with each other's operation through voltage waveform distortion or power quality problems. Strategies for nonintrusive monitoring have developed over the last 20 years. Advances in computing technology make a new wealth of computational tools useful in practical, field-based {NILM} systems. This article reviews techniques for high-performance nonintrusive load and diagnostic monitoring and illustrates key points with results from field tests.},\n number = {2},\n journal = {{IEEE} Power and Energy Magazine},\n author = {Laughman, C. and Lee, Kwangduk and Cox, R. and Shaw, S. and Leeb, S. and Norford, L. and Armstrong, P.},\n month = {March},\n year = {2003},\n keywords = {Algorithm design and analysis, Costs, Data mining, Electric variables measurement, Electromechanical sensors, Modems, Monitoring, Parameter estimation, Power industry, computerised monitoring, diagnostic monitoring, distribution networks, distribution system operation monitoring, electric utility service entry, electrical loads, electromechanical devices, harmonic distortion, high reliability, load (electric), measured waveforms analysis, nonintrusive load monitoring, parameter estimation algorithms, power quality, power signature analysis, power supply quality, power system harmonics, power system measurement, state estimation algorithms, voltage waveform distortion, waveform analysis},\n pages = {56--63}\n}","bibtype":"article","doi":"10.1109/MPAE.2003.1192027","id":"laughman_power_2003","issn":"1540-7977","journal":"IEEE Power and Energy Magazine","key":"laughman_power_2003","keywords":"Algorithm design and analysis, Costs, Data mining, Electric variables measurement, Electromechanical sensors, Modems, Monitoring, Parameter estimation, Power industry, computerised monitoring, diagnostic monitoring, distribution networks, distribution system operation monitoring, electric utility service entry, electrical loads, electromechanical devices, harmonic distortion, high reliability, load (electric), measured waveforms analysis, nonintrusive load monitoring, parameter estimation algorithms, power quality, power signature analysis, power supply quality, power system harmonics, power system measurement, state estimation algorithms, voltage waveform distortion, waveform analysis","month":"March","number":"2","pages":"56--63","title":"Power signature analysis","type":"article","volume":"1","year":"2003","bibbaseid":"laughman-lee-cox-shaw-leeb-norford-armstrong-powersignatureanalysis-2003","role":"author","urls":{},"keyword":["Algorithm design and analysis","Costs","Data mining","Electric variables measurement","Electromechanical sensors","Modems","Monitoring","Parameter estimation","Power industry","computerised monitoring","diagnostic monitoring","distribution networks","distribution system operation monitoring","electric utility service entry","electrical loads","electromechanical devices","harmonic distortion","high reliability","load (electric)","measured waveforms analysis","nonintrusive load monitoring","parameter estimation algorithms","power quality","power signature analysis","power supply quality","power system harmonics","power system measurement","state estimation algorithms","voltage waveform distortion","waveform analysis"],"downloads":0,"html":""},"bibtype":"article","biburl":"http://bibbase.org/zotero/alspereira","creationDate":"2014-12-11T16:27:23.986Z","downloads":0,"keywords":["algorithm design and analysis","costs","data mining","electric variables measurement","electromechanical sensors","modems","monitoring","parameter estimation","power industry","computerised monitoring","diagnostic monitoring","distribution networks","distribution system operation monitoring","electric utility service entry","electrical loads","electromechanical devices","harmonic distortion","high reliability","load (electric)","measured waveforms analysis","nonintrusive load monitoring","parameter estimation algorithms","power quality","power signature analysis","power supply quality","power system harmonics","power system measurement","state estimation algorithms","voltage waveform distortion","waveform analysis"],"search_terms":["power","signature","analysis","laughman","lee","cox","shaw","leeb","norford","armstrong"],"title":"Power signature analysis","year":2003,"dataSources":["ndsqabutJ3xHr3adK"]}