{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T06:28:14Z","timestamp":1778826494021,"version":"3.51.4"},"reference-count":15,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2015,10,23]],"date-time":"2015-10-23T00:00:00Z","timestamp":1445558400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Ultrasonic concentration meters have widely been used at water purification, sewage treatment and waste water treatment plants to sort and transfer high concentration sludges and to control the amount of chemical dosage. When an unusual substance is contained in the sludge, however, the attenuation of ultrasonic waves could be increased or not be transmitted to the receiver. In this case, the value measured by a concentration meter is higher than the actual density value or vibration. As well, it is difficult to automate the residuals treatment process according to the various problems such as sludge attachment or sensor failure. An ultrasonic multi-beam concentration sensor was considered to solve these problems, but an abnormal concentration value of a specific ultrasonic beam degrades the accuracy of the entire measurement in case of using a conventional arithmetic mean for all measurement values, so this paper proposes a method to improve the accuracy of the sludge concentration determination by choosing reliable sensor values and applying a neuro-fuzzy learning algorithm. The newly developed meter is proven to render useful results from a variety of experiments on a real water treatment plant.<\/jats:p>","DOI":"10.3390\/s151026961","type":"journal-article","created":{"date-parts":[[2015,10,24]],"date-time":"2015-10-24T08:27:06Z","timestamp":1445675226000},"page":"26961-26977","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["An Ultrasonic Multi-Beam Concentration Meter with  a Neuro-Fuzzy Algorithm for Water Treatment Plants"],"prefix":"10.3390","volume":"15","author":[{"given":"Ho-Hyun","family":"Lee","sequence":"first","affiliation":[{"name":"School of of Electrical Engineering and Computer Science, Chungbuk National University, Cheongju 28644, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sang-Bok","family":"Jang","sequence":"additional","affiliation":[{"name":"K-Water Research Institute, Korea Water Resources Corporation, Daejeon 34045, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gang-Wook","family":"Shin","sequence":"additional","affiliation":[{"name":"K-Water Research Institute, Korea Water Resources Corporation, Daejeon 34045, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sung-Taek","family":"Hong","sequence":"additional","affiliation":[{"name":"K-Water Research Institute, Korea Water Resources Corporation, Daejeon 34045, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dae-Jong","family":"Lee","sequence":"additional","affiliation":[{"name":"School of of Electrical Engineering and Computer Science, Chungbuk National University, Cheongju 28644, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Myung","family":"Chun","sequence":"additional","affiliation":[{"name":"School of of Electrical Engineering and Computer Science, Chungbuk National University, Cheongju 28644, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2015,10,23]]},"reference":[{"key":"ref_1","unstructured":"Kawamura, S. (2003). Integrated Design and Operation of Water Treatment Facilities, Wiley. [2nd ed.]."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"6220","DOI":"10.2175\/193864709793957012","article-title":"Comparison of Centrifuge and Belt Press for Compressible Digested After Thermal Hydrolysis","volume":"2009","author":"Panter","year":"2009","journal-title":"Proc. Water Environ. Fed."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.seppur.2015.06.030","article-title":"Evaluation on the dewatering process of cyanobacteria-containing AlCl3 and PACl drinking water sludge","volume":"150","author":"Sun","year":"2015","journal-title":"Sep. Purif. Technol."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Sun, Y., Fan, W., Zheng, H., Zhang, Y., Li, F., and Chen, W. (2015). Evaluation of Dewatering Performance and Fractal Characteristics of Alum Sludge. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0130683"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"53","DOI":"10.2166\/wst.1996.0005","article-title":"New type of sludge density meter using microwaves for application in sewage treatment plants","volume":"33","author":"Yamaguchi","year":"1996","journal-title":"Water Sci. Technol."},{"key":"ref_6","first-page":"77","article-title":"Study on optimal operation of residual treatment process automation","volume":"20","author":"Baek","year":"2008","journal-title":"J. Korea Soc. Fluid Mach."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"557","DOI":"10.3795\/KSME-B.2015.39.7.557","article-title":"Prediction of two-phase taylor flow characteristics in a rectangular micro channel","volume":"39","author":"Lee","year":"2015","journal-title":"Trans. Korean Soc. Mech. Eng."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/j.expthermflusci.2015.02.022","article-title":"On the accuracy of wire mesh sensors in dependence of bubble sizes and liquid flow rates","volume":"65","author":"Nuryadin","year":"2015","journal-title":"Exp. Therm. Fluid Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"665","DOI":"10.1109\/21.256541","article-title":"ANFIS: Adaptive-network-based fuzzy inference system","volume":"23","author":"Jang","year":"1993","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_10","first-page":"147","article-title":"Intelligent Controller for Constant Control of Residual Chlorine in Water Treatment Process","volume":"24","author":"Lee","year":"2014","journal-title":"Int. J. Fuzzy Intell. Syst."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2005","DOI":"10.3390\/s120202005","article-title":"A Method Based on Multi-Sensor Data Fusion for Falut Detection of Planetary Gearboxes","volume":"12","author":"Lei","year":"2012","journal-title":"Sensors"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1593","DOI":"10.1016\/j.eswa.2007.08.072","article-title":"A new approach to intelligent fault diagnosis of rotating machinery","volume":"35","author":"Lei","year":"2008","journal-title":"Expert Syst. Appl."},{"key":"ref_13","unstructured":"Jang, J., Sun, C., and Mizutani, E. (1997). Neuro-Fuzzy and Soft Computing, Prentice-Hall Inc."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"327","DOI":"10.5391\/IJFIS.2009.9.4.327","article-title":"Short-Term Electrical Load Forecasting Using Neuro-Fuzzy Model with Error Compensation","volume":"9","author":"Wang","year":"2009","journal-title":"Int. J. Fuzzy Intell. Syst."},{"key":"ref_15","first-page":"192","article-title":"Neuro-Fuzzy Rule Generation for Backing up Navigation of Car-like Mobile Robots","volume":"11","author":"Park","year":"2009","journal-title":"Int. J. Fuzzy Syst."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/15\/10\/26961\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T20:50:43Z","timestamp":1760215843000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/15\/10\/26961"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,10,23]]},"references-count":15,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2015,10]]}},"alternative-id":["s151026961"],"URL":"https:\/\/doi.org\/10.3390\/s151026961","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,10,23]]}}}