CN1683254A - Intelligent monitoring and control method for coagulation process based on multisource information fusion technology - Google Patents
Intelligent monitoring and control method for coagulation process based on multisource information fusion technology Download PDFInfo
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- CN1683254A CN1683254A CN 200510009831 CN200510009831A CN1683254A CN 1683254 A CN1683254 A CN 1683254A CN 200510009831 CN200510009831 CN 200510009831 CN 200510009831 A CN200510009831 A CN 200510009831A CN 1683254 A CN1683254 A CN 1683254A
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Abstract
The present invention discloses the real-time optimized control method of intelligent monitoring and coagulating agent throwing in water treatment. The intelligent monitoring and controlling method of coagulation process based on multisource information fusion technology consists of the following steps: obtaining water quality parameter signals I1-I5 with turbidity sensor, pH sensor, conductivity sensor, temperature sensor and flow rate sensor; inputting I1-I5 to time-space fusion system in fuzzy nerve network algorithm and outputting the result to comparator; calculating in the controller of single factor intelligent coagulation controlling system, feeding the coagulating agent throwing amount to the throwing pump, and feeding the current coagulation reaction degree value with the single factor detecting instrument to the comparator; and monitoring intelligently the water quality parameters and variations for comprehensive high quality control of the coagulation process.
Description
Technical field;
The present invention relates in the water treatment dispensing coagulation process,, realize the method for the real-time optimization control of coagulant dosage coagulation administration process intellectual monitoring.
Background technology:
The coagulation administration process of water treatment is the key link that influences water quality treatment, is the emphasis of water treatment research always.Raising along with development of computer and water factory's operation level of automation has realized the automatic control of coagulation administration to a certain extent.But because water treatment procedure complex physico-chemical mechanism, and the time stickiness of the time variation of reaction process water quality parameter, reaction, and it is a lot of influence the coagulant charging quantity factor, determines and to control the dosage of coagulating agent still very difficult.Advanced at present single-factor parameter method (as streaming current method, transmittance pulsation detection method) utilizes monofactor to characterize the influence of multinomial water quality factors to coagulation process, utilize its automatic control that can realize the coagulation administration process, as described in the 3rd phase of " Jilin electric power " June in 2003 " single-factor water treatment coagulation automatic control dosing The Application of Technology " one literary composition.But, make this method in application, be subjected to certain limitation because the variation meeting of raw water quality parameter produces uncertain influence to the measuring result of single-factor detector and the set(ting)value of single-factor coagulation Controlling System.
Summary of the invention:
The purpose of this invention is to provide a kind of coagulation process intellectual monitoring and control method based on multisource information fusion technology, monitor the intensity of variation of raw water quality situation and coagulating accurately, reliably comprehensively,, realize that the real-time optimum of coagulating agent that changes under the condition of water quality adds, can only provide the local message of coagulation process to overcome single-sensor, can not reflect the variation of former water and coagulating process comprehensively, and have that immunity from interference is low, the defective of poor fault tolerance problem.Technical scheme of the present invention is: it comprises step 3, carries out corresponding computing in the controller 7 of single-factor coagulation intelligence control system, the dosage of coagulating agent is outputed to coagulant dosage pump 9, be arranged on the negative input end that single-factor detector 8 in the coagulation reaction tank feeds back to the current coagulating degree of detected representative value of feedback β comparer 10 simultaneously; Before step 3, also comprise step 1, utilize the turbidity transducer 1, pH value transmitter 2, conductivity sensor 3, temperature sensor 4 and the flow sensor 5 that are arranged in the former water to obtain corresponding signal I1, I2, I3, I4 and the I5 that represents water quality parameter respectively; Step 2, the temporal-spatial fusion system 6 of the corresponding signal I1, the I2 that represent water quality parameter, I3, I4 and I5 input utilization fuzzy neural network algorithm, its output valve α is input to the positive input terminal of comparer 10, as the set(ting)value of single-factor coagulation intelligence control system; The multiple water quality parameter realization of the former water of measurement changes in good time, the suitable correction certainly of single-factor coagulation Controlling System set(ting)value under the condition of water quality thereby method of the present invention is passed through in real time, utilization realizes that based on adaptive control and fuzzy logic control method the real-time optimum of coagulating agent that changes under the condition of water quality adds.It has overcome the local message that single-sensor can only provide coagulation process, the defective that can not comprehensively reflect the variation of former water and coagulating process, because the information category of gathering is many, anti-jamming capacity is strong, also is not easy the coagulant charging quantity that makes the mistake because collecting error message.Method of the present invention adopts multisensor Data Fusion technology, on the basis of water factory's existing operation measuring instrument, with the least equipment input, realization is to comprehensive, accurate, reliable intellectual monitoring of raw water quality parameter and variable quantity thereof, having improved the sensing detection unit provides accuracy and the reliability of data, realization with any single-sensor can't realize to comprehensive, high-quality intellectual monitoring of coagulation process and control, reduced power consumption and medicine the consumption, reduced excessive dispensing health hazard.This system also can be used for the dynamic monitoring of automatic monitor procedure of sewage disposal and hydrological environment.
Description of drawings:
Fig. 1 is the synoptic diagram of the inventive method data flow, and Fig. 2 is the synoptic diagram of the data flow of embodiment of the present invention two.
Embodiment:
Embodiment one: present embodiment is made up of following steps: one, utilize the turbidity transducer 1, pH value transmitter 2, conductivity sensor 3, temperature sensor 4 and the flow sensor 5 that are arranged in the former water to obtain corresponding signal I1, I2, I3, I4 and the I5 that represents water quality parameter respectively; Step 2, the temporal-spatial fusion system 6 of the corresponding signal I1, the I2 that represent water quality parameter, I3, I4 and I5 input utilization fuzzy neural network algorithm, its output valve α is input to the positive input terminal of comparer 10, as the set(ting)value of single-factor coagulation intelligence control system; Three, in the controller 7 of single-factor coagulation intelligence control system, carry out corresponding computing, the dosage of coagulating agent is outputed to coagulant dosage pump 9, be arranged on the negative input end that single-factor detector 8 in the coagulation reaction tank feeds back to detected current coagulating degree value of feedback β comparer 10 simultaneously; The controller 7 of single-factor coagulation intelligence control system is selected two-dimensional fuzzy controller for use, perhaps selects controller and single-factor detector in the single-factor water treatment coagulation system in the background technology for use.
Embodiment two: specify present embodiment below in conjunction with Fig. 2.The difference of present embodiment and embodiment one is: the step 2 in the embodiment one is made up of following steps: 201, respectively signal I1, I2, I3, I4 and the I5 of input are carried out data level and merge, promptly obtain the detected value of each transmitter and ask for the velocity of variation of the detected value of each transmitter, analyze each transmitter continuously the data of output whether unconventional variation is arranged determining whether these data reliable, have problems such as malfunctioning, noise jamming, Loss Of Signal thereby whether differentiate instrument; 202, the data that merge through data level are carried out the feature level to be merged, be specially use the input of two data through the data of data level fusion treatment, the fuzzy neural network of 5 layer network structures of one data output, with not isometric information translation is that the consistence of coagulation influence degree is described, carrying out degree of membership at the A of network layer according to the membership function of selecting calculates, finish Fuzzy processing to two input variables of network, the B layer is according to the input of data, determine the relevance grade of rule in the rule base and carry out reasoning that The reasoning results is carried out non-Defuzzication at the C layer with weighted average method and handled; 203, carry out decision level fusion, utilization realizes the definite and adjustment of each detect parameters W1, W2, W3, W4, W5 weights is detected data and is weighted fusion treatment each based on improved BP algorithm neural network.The reason of Chu Liing is the Various Seasonal in different waters and same waters like this, and each water quality parameter is all inequality to the influence and the degree thereof of coagulating; Other step is identical with embodiment one.Present embodiment is at first carried out the pure spatial domain fusion of multisensor homologous information in the data fusion level, carry out the fusion of time, spatial domain at the feature grades of fusion, to obtain to raw water quality and variable quantity thereof, the coagulation reflection effect intellectual monitoring of intensity of variation extremely; Set up dynamic law model and knowledge base at the decision-making grades of fusion then based on dependency between the single-factor detected value of raw water quality parameter variable quantity and coagulation effect, coagulant charging quantity, realize changing single-factor coagulation Controlling System set(ting)value under the condition of water quality in good time, the correction certainly that suits; On this basis, use based on adaptive control and fuzzy logic control method, and will control output action, realize that the real-time optimum of coagulating agent that changes under the condition of water quality adds in the coagulant dosage pump.TaKagi-Sugeno (Gao Mu-Guan Ye) fuzzy reasoning method and neural network algorithm have specifically been used in the temporal-spatial fusion system 6 of utilization fuzzy neural network algorithm.
Claims (2)
1, based on the coagulation process intellectual monitoring and the control method of multisource information fusion technology, it comprises step 3, carries out corresponding computing in the controller (7) of single-factor coagulation intelligence control system, the dosage of coagulating agent is outputed to coagulant dosage pump (9), be arranged on the negative input end that single-factor detector (8) in the coagulation reaction tank feeds back to detected current coagulating degree value of feedback β comparer (10) simultaneously; It is characterized in that before step 3, also comprising step 1, utilize the turbidity transducer (1), pH value transmitter (2), conductivity sensor (3), temperature sensor (4) and the flow sensor (5) that are arranged in the former water to obtain corresponding signal I1, I2, I3, I4 and the I5 that represents water quality parameter respectively; Step 2, the temporal-spatial fusion system (6) of the corresponding signal I1, the I2 that represent water quality parameter, I3, I4 and I5 input utilization fuzzy neural network algorithm, its output valve α is input to the positive input terminal of comparer (10), as the set(ting)value of single-factor coagulation intelligence control system.
2, coagulation process intellectual monitoring and control method based on multisource information fusion technology according to claim 1, it is characterized in that its step 2 is made up of following steps: 201, respectively the signal I1 of input, I2, I3, I4 and I5 carry out data level and merge, promptly obtain the detected value of each transmitter and ask for the velocity of variation of the detected value of each transmitter, analyze each transmitter continuously the data of output whether unconventional variation is arranged to determine these data whether reliable 202, the data that merge through data level are carried out the feature level to be merged, be specially use the input of two data through the data of data level fusion treatment, the fuzzy neural network of 5 layer network structures of one data output, with not isometric information translation is that the consistence of coagulation influence degree is described, carrying out degree of membership at the A of network layer according to the membership function of selecting calculates, finish Fuzzy processing to two input variables of network, the B layer is according to the input of data, determine the relevance grade of rule in the rule base and carry out reasoning that The reasoning results is carried out non-Defuzzication at the C layer with weighted average method and handled; 203, carry out decision level fusion, utilization realizes the definite and adjustment of each detect parameters W1, W2, W3, W4, W5 weights is detected data and is weighted fusion treatment each based on improved BP algorithm neural network.
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Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN101607151B (en) * | 2009-01-09 | 2011-05-18 | 湖南华博科技开发有限公司 | Embedded intelligent dosing controller and control method thereof |
| CN104529009A (en) * | 2014-12-31 | 2015-04-22 | 苏州工业职业技术学院 | Automatic waste water treatment system and technology |
| CN104850225A (en) * | 2015-04-28 | 2015-08-19 | 浙江大学 | Activity identification method based on multi-level fusion |
| CN106596637A (en) * | 2016-10-20 | 2017-04-26 | 浙江农林大学 | Method for judging grade of culturing farm sewage water quality based on 3V algorithm |
| CN107068535A (en) * | 2010-06-04 | 2017-08-18 | 捷通国际有限公司 | Inductively dielectric-barrier discharge lamp |
| CN108121860A (en) * | 2017-12-12 | 2018-06-05 | 电子科技大学 | A kind of biological yeast making process CPS modeling methods based on Multi-source Information Fusion |
| CN108897309A (en) * | 2018-07-13 | 2018-11-27 | 南京航空航天大学 | Aero-Engine Sensor Failure diagnosis and partition method based on fuzzy membership |
| CN109357696A (en) * | 2018-09-28 | 2019-02-19 | 西南电子技术研究所（中国电子科技集团公司第十研究所） | Multiple Source Sensor information merges closed loop test framework |
| CN111320246A (en) * | 2020-03-12 | 2020-06-23 | 青岛道斯康环保科技有限公司 | Coagulant intelligent accurate adding control system based on multivariable control |
| CN111895383A (en) * | 2020-07-08 | 2020-11-06 | 上海汇信能源科技有限公司 | Method and system for controlling working power of electromagnetic steam generator |
| CN113075883A (en) * | 2021-03-29 | 2021-07-06 | 中南林业科技大学 | Coagulation dosing optimization method in water production industry |
| CN113428957A (en) * | 2021-06-29 | 2021-09-24 | 长沙榔梨自来水有限公司 | Polyaluminum chloride adding method suitable for river water |
| CN113582309A (en) * | 2021-07-28 | 2021-11-02 | 长三角(义乌)生态环境研究中心 | Method and device for determining coagulant adding amount |
| CN116378974A (en) * | 2023-05-31 | 2023-07-04 | 宜宾科全矿泉水有限公司 | Intelligent control system of water purifier |
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| JPH06119454A (en) * | 1992-10-08 | 1994-04-28 | Babcock Hitachi Kk | Method and device for detecting abnormality |
| DE4401447A1 (en) * | 1994-01-19 | 1995-07-27 | Rhebau Rheinische Beton Und Ba | Protection circuit for pump motors |
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| CN101607151B (en) * | 2009-01-09 | 2011-05-18 | 湖南华博科技开发有限公司 | Embedded intelligent dosing controller and control method thereof |
| CN107068535A (en) * | 2010-06-04 | 2017-08-18 | 捷通国际有限公司 | Inductively dielectric-barrier discharge lamp |
| CN107068535B (en) * | 2010-06-04 | 2019-01-18 | 捷通国际有限公司 | Inductively dielectric-barrier discharge lamp |
| TWI666680B (en) * | 2010-06-04 | 2019-07-21 | 美商通路實業集團國際公司 | Inductively coupled dielectric barrier discharge lamp assembly and system and method thereof |
| CN104529009A (en) * | 2014-12-31 | 2015-04-22 | 苏州工业职业技术学院 | Automatic waste water treatment system and technology |
| CN104850225A (en) * | 2015-04-28 | 2015-08-19 | 浙江大学 | Activity identification method based on multi-level fusion |
| CN104850225B (en) * | 2015-04-28 | 2017-10-24 | 浙江大学 | A kind of activity recognition method based on multi-level Fusion |
| CN106596637A (en) * | 2016-10-20 | 2017-04-26 | 浙江农林大学 | Method for judging grade of culturing farm sewage water quality based on 3V algorithm |
| CN106596637B (en) * | 2016-10-20 | 2018-12-14 | 浙江农林大学 | Sewage of farm water grade judgment method based on 3V algorithm |
| CN108121860A (en) * | 2017-12-12 | 2018-06-05 | 电子科技大学 | A kind of biological yeast making process CPS modeling methods based on Multi-source Information Fusion |
| CN108897309B (en) * | 2018-07-13 | 2019-09-06 | 南京航空航天大学 | Aero-Engine Sensor Failure diagnosis and partition method based on fuzzy membership |
| CN108897309A (en) * | 2018-07-13 | 2018-11-27 | 南京航空航天大学 | Aero-Engine Sensor Failure diagnosis and partition method based on fuzzy membership |
| CN109357696A (en) * | 2018-09-28 | 2019-02-19 | 西南电子技术研究所（中国电子科技集团公司第十研究所） | Multiple Source Sensor information merges closed loop test framework |
| CN109357696B (en) * | 2018-09-28 | 2020-10-23 | 西南电子技术研究所（中国电子科技集团公司第十研究所） | Multi-source sensor information fusion closed-loop testing framework |
| CN111320246A (en) * | 2020-03-12 | 2020-06-23 | 青岛道斯康环保科技有限公司 | Coagulant intelligent accurate adding control system based on multivariable control |
| CN111895383A (en) * | 2020-07-08 | 2020-11-06 | 上海汇信能源科技有限公司 | Method and system for controlling working power of electromagnetic steam generator |
| CN113075883A (en) * | 2021-03-29 | 2021-07-06 | 中南林业科技大学 | Coagulation dosing optimization method in water production industry |
| CN113428957A (en) * | 2021-06-29 | 2021-09-24 | 长沙榔梨自来水有限公司 | Polyaluminum chloride adding method suitable for river water |
| CN113582309A (en) * | 2021-07-28 | 2021-11-02 | 长三角(义乌)生态环境研究中心 | Method and device for determining coagulant adding amount |
| CN116378974A (en) * | 2023-05-31 | 2023-07-04 | 宜宾科全矿泉水有限公司 | Intelligent control system of water purifier |
| CN116378974B (en) * | 2023-05-31 | 2023-08-04 | 宜宾科全矿泉水有限公司 | Intelligent control system of water purifier |
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