CN117591890A - Sewage treatment evaluation system and method based on big data - Google Patents
Sewage treatment evaluation system and method based on big data Download PDFInfo
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Abstract
The invention relates to the technical field of sewage treatment evaluation, in particular to a sewage treatment evaluation system and method based on big data. The big data evaluation system is used for acquiring historical terminal record data formed by the ceramic membrane tanks in the sewage treatment system; the characteristic factor set analysis module in the big data evaluation system is used for analyzing a characteristic factor set of the sewage treatment system, and the safety evaluation module is used for constructing an operation safety evaluation module corresponding to the target characteristic factors and calculating a safety evaluation index; the inspection unmanned aerial vehicle is used for collecting state data of the sewage treatment area and is also matched with a safety evaluation module in the big data evaluation system based on the 5G base station; the evaluation response module is used for positioning the ceramic membrane and the position of the acquisition sensor and storing data such as water quality of a sewage treatment area; the Web display device displays the evaluation data, and can quickly find out and process abnormal problems.
Description
Technical Field
The invention relates to the technical field of sewage treatment evaluation, in particular to a sewage treatment evaluation system and method based on big data.
Background
The sewage treatment is widely applied to various fields of construction, agriculture, traffic, energy, petrifaction, environmental protection, urban landscapes, medical treatment, catering and the like, and the sewage treatment is increasingly carried into the daily life of common people. The existing sewage treatment plant has large occupied area, the water quality data and the environment data of sewage treatment are generally obtained by manual on-site sampling detection and recording, and the problems of long period, low efficiency and untimely finding of abnormal conditions exist, so that the sewage treatment evaluation is very inconvenient.
The construction production wastewater mainly comes from excavation of construction sites, wastewater of sand and stone processing systems, flushing of construction machinery equipment, automobile maintenance, machine repair oily wastewater, concrete maintenance and the like. The main pollutants of the production wastewater are suspended matters and petroleum substances, the main pollutants of the field excavation and drainage are silt, and the engineering construction domestic sewage comprises constructors' fecal sewage, shower sewage, washing sewage, kitchen oily sewage and the like, and mainly contains pollutants such as COD, SS, ammonia nitrogen, animal and vegetable oil, fecal coliform and the like. Most of the power plant projects are farmlands, for example, wastewater generated in a capital construction period is not timely treated or discharged into a local river water body after reaching standards, and huge side effects are generated on local farmland irrigation; the existing MBR technology in the field of sewage treatment and water resource reuse, namely a Membrane bioreactor (Membrane Bi o-Reactor), is a sewage treatment technology combined with a Membrane separation technology by an activated sludge method, but is difficult to combine with a sewage treatment evaluation system with big data, and in the aspects of sewage recording operation management and automatic control, intelligent operation is difficult to realize, and auxiliary equipment is generally required to record evaluation data in the sewage field, so that the development and maintenance cost of the system is increased.
Disclosure of Invention
The invention aims to provide a sewage treatment evaluation system and a sewage treatment evaluation method based on big data so as to solve the problems in the background technology. The invention provides the following technical scheme: a big data based sewage treatment evaluation system comprising:
the big data sewage treatment evaluation system comprises a sewage treatment system, a big data evaluation system, a patrol unmanned aerial vehicle, a 5G base station and an evaluation web display device;
the sewage treatment system includes: the regulating tank, the anoxic tank and the ceramic membrane tank are embedded into a recording chip, sewage treatment data is recorded, and the device is terminal equipment for data acquisition of a big data evaluation system;
the big data evaluation system comprises water quality monitoring data and equipment operation data in the sewage treatment process, and the data are processed and evaluated by utilizing a data analysis and algorithm model so as to realize optimization and improvement of the sewage treatment system;
the patrol unmanned aerial vehicle transmits information to a big data evaluation system in real time through a 5G base station;
the 5G base station is used for collecting real-time data of the sewage treatment tank environment and providing high-speed data transmission and remote monitoring capability;
the evaluation web display device displays the position, water quality data, environmental data and emission water quality evaluation data of the early-warning ceramic membrane device and the acquisition sensor in the sewage treatment evaluation system with big data.
As a preferable scheme of the sewage treatment evaluation system based on big data, the sewage treatment evaluation system based on big data is characterized in that the regulating tank is connected with the anoxic tank through a sewage lifting pump, a filling frame and a first aeration device are arranged in the anoxic tank, and filling is arranged on the filling frame; the anoxic tank and the ceramic membrane tank are connected through a water inlet pump, a ceramic membrane assembly and a membrane supporting layer are arranged in the ceramic membrane tank, the water outlet end of the membrane assembly is connected with a clean water pump, and the membrane supporting layer is positioned on the outer surface of the ceramic membrane; the ceramic membrane chip, namely the SPI chip, is connected with the sensor, so that data are transmitted from the sensor to the chip;
as a preferable mode of the big data based sewage treatment evaluation system of the present invention, the big data evaluation system includes: the system comprises a terminal historical data module, a characteristic factor analysis module, a safety evaluation module, a patrol unmanned aerial vehicle acquisition module and an evaluation response module;
the terminal historical data module is used for recording and storing historical data of the ceramic membrane pool, including various indexes, parameters and event records; through analysis and statistics of historical data, information such as the running condition of the terminal equipment, the occurrence reason and frequency of faults and the like can be known;
the characteristic factor analysis module is used for carrying out deep mining and analysis on the terminal historical data and finding out main factors influencing the operation and faults of the terminal equipment; key characteristic factors affecting the performance of the equipment can be identified by establishing a mathematical model and an algorithm;
the safety evaluation module evaluates and analyzes the safety of sewage treated by the ceramic membrane pool, and can evaluate the safety risks and potential threats existing in the flow, temperature, pressure and PH value parameters of the sewage in the sewage pool environment by collecting and analyzing the data such as solid particles, suspended matters, microorganisms and the like in the sewage pool;
the inspection unmanned aerial vehicle acquisition module receives real-time information transmitted by the inspection unmanned aerial vehicle through the 5G base station;
the evaluation response module predicts possible faults, accidents or abnormal conditions in advance according to the terminal historical data and the characteristic factor analysis result, combines the sewage inspection information transmitted by the inspection unmanned aerial vehicle through the 5G base station in real time, and sends out an alarm and evaluation response in time after checking; by establishing an early warning model and rules, the water quality index, the flow index and the running state of the ceramic membrane device of sewage treatment can be monitored and early warned in real time.
As a preferable scheme of the sewage treatment evaluation system based on big data, the inspection unmanned aerial vehicle acquisition module comprises: the high-definition camera, the sewage environment monitoring sensor and the data storage unit transmit information to the big data evaluation system in real time through the 5G base station; the high-definition camera can transmit the conditions in the corridor to the sewage treatment evaluation system with big data in real time through the 5G base station, and the environment monitoring sensor is used for collecting sewage environment information and transmitting the sewage environment information to the sewage treatment evaluation system with big data in real time through the 5G base station; the inspection unmanned plane can remotely collect and monitor the water quality state after sewage treatment through a 5G network, is used for unmanned inspection in a sewage area, and transmits collected information to a sewage treatment evaluation system of big data in real time through a 5G base station.
As a preferable scheme of the sewage treatment evaluation system based on big data, the 5G base station receives and forwards the processed water quality data, the environment data and the discharged water quality data sent by the inspection unmanned aerial vehicle to the sewage treatment evaluation system of big data; the data collected in the sewage treatment process can be quickly transmitted to a big data evaluation system for treatment through the 5G base station; meanwhile, the operation state and water quality parameter information of the ceramic membrane device can be obtained through a 5G technology, and remote multi-system setting and allocation are performed; the 5G base station can also support simultaneous connection of multiple devices, so that data sharing in a sewage treatment evaluation system of big data is realized.
As a preferable scheme of the sewage treatment evaluation system based on big data, the evaluation web display equipment displays an electronic map of a pre-stored sampling position of the ceramic membrane device and a position map of a pre-sampled position of the ceramic membrane device, and simultaneously transmits water quality information acquired by the inspection unmanned aerial vehicle to the sewage treatment evaluation system based on big data in real time through a 5G base station, and finally displays the water quality information on the evaluation web display equipment.
The sewage treatment evaluation method of big data comprises the following steps:
step S1: a terminal history data module for acquiring terminal history data composed of m ceramic membranes in the sewage treatment system, wherein the terminal history module automatically acquires first operation data of a data unit of a membrane supporting layer in the ceramic membranes and second operation data of a data unit of a separating layer of sewage treatment, and m is a positive integer greater than 1;
step S2: analyzing a characteristic factor set of the sewage treatment block based on the first operation data record of the data unit and the second operation data record of the data unit; the characteristic factor set comprises classified characteristic factors and target characteristic factors;
step S3: based on target characteristic factors in the characteristic factor set, constructing an operation safety evaluation module corresponding to the target characteristic factors and calculating a safety evaluation index;
step S4: the inspection unmanned aerial vehicle acquires the real-time monitored data after sewage treatment, matches the operation safety module in the step S3, calculates a real-time safety evaluation index and carries out sewage treatment evaluation.
Step S5: the position, water quality data, environment data and emission water quality evaluation data of an early warning ceramic membrane device and an acquisition sensor in a sewage treatment evaluation system for evaluating big data displayed by web display equipment;
as a preferable scheme of the sewage treatment evaluation method based on big data according to the present invention, the step S1 is as follows: a terminal history data module for acquiring terminal history data composed of m ceramic membranes in the sewage treatment system, wherein the terminal history data module automatically acquires first operation data of a data unit of a membrane supporting layer in the ceramic membranes and second operation data of a data unit of a separating layer of sewage treatment, and m is a positive integer greater than 1;
as a preferable mode of the sewage treatment evaluation method based on big data according to the present invention, the steps S2 and S3 include:
the terminal history data module data unit I comprises interval duration recorded by the automatic cleaning equipment, data of cleaning objects and the automatic cleaning equipment, wherein the interval duration refers to interval duration from the last time the automatic cleaning equipment is used;
the terminal history data module data unit II comprises an operation block of the sewage treatment block, operation time length corresponding to the operation block and related data of sensing equipment in the sewage treatment block, wherein the related data of the sensing equipment refers to liquid level data sensed by a liquid level sensor;
the first extraction target data of the terminal historical data module data unit is a first target data pair, the second extraction target data of the terminal historical data module data unit is a second target data pair, the standard deviation value of the running time of the first target data and the second target data and the standard deviation value of the total water yield are calculated, and characteristic factors are analyzed according to the first target difference value and the second target difference value compared with a preset difference value threshold;
judging the number of matching data pairs to which target characteristic factors belong, and constructing a first operation safety evaluation model as a fitting curve to which the matching data pairs belong when the number of the matching data pairs is only one; when the number of the matching data pairs is equal to two and the matching data pairs are different, a second operation safety evaluation model is constructed as a fitting curve to which the two matching data pairs belong.
As a preferable mode of the sewage treatment evaluation method based on big data according to the present invention, the step S4 includes:
the inspection unmanned plane acquires real-time monitored sewage treated data, and according to normalized historical discharged water quality data, the standard deviation V is used in the step S3 1 、V 2 、W 1 、W 2 ]As a loss function of the Z-score normalization data preprocessing method, the normalized mean value is in the safety evaluation model [ ed1, ed2 ]]The distribution characteristics of the data are more stable, the method is suitable for the data which are not affected by outliers and need to keep the original distribution characteristics, and the data keeping the original distribution characteristics are transmitted to the evaluation web display equipment.
As a preferable mode of the sewage treatment evaluation method based on big data according to the present invention, the step S5 includes:
and the signals received by the plurality of acquisition sensors sent by the 5G base station are judged, the sampling positions of the plurality of acquisition sensors are judged, and the processed water quality data, the environment data, the discharged water quality data and the sampling positions of the plurality of acquisition sensors are sent to the evaluation Web display device.
Compared with the prior art, the invention is based on the sewage treatment data recorded by the ceramic membrane device in the sewage treatment system, analyzes the relativity between the two data by the operation data of the first data unit and the operation data of the second data unit of the terminal history data module in the sewage treatment evaluation system of big data to find out the characteristic factors of corresponding influence, and the characteristic factor analysis module constructed based on the history big data is used for evaluating whether the operation data acquired in real time can reflect the normal working condition of the sewage treatment block or not by analyzing and matching the characteristic factors; collecting the state of the sewage after treatment in real time through the inspection unmanned plane, matching based on a safety evaluation module, and transmitting an evaluation signal; the evaluation response module is used for receiving the evaluation signal, and according to the evaluation result, corresponding measures can be taken to treat the abnormal condition of the sewage treatment block; the evaluation Web display device is used for displaying the position positioning of the ceramic membrane and the acquisition sensor and the water quality data of the sewage treatment area, so that workers can quickly find out abnormal problems and timely treat the abnormal problems in the whole process of evaluating and monitoring the sewage treatment.
Drawings
FIG. 1 is a diagram of a sewage treatment evaluation system architecture for big data of the present invention.
FIG. 2 is a schematic diagram of a sewage treatment system according to the present invention.
FIG. 3 is a flow chart of the sewage treatment evaluation method based on big data.
Detailed Description
A preferred embodiment of the present invention will be described in detail with reference to the accompanying drawings.
As shown in fig. 1, the sewage treatment evaluation system based on big data includes:
a sewage treatment system: the sewage treatment system avoids the technical problems of environmental pollution caused by production sewage and domestic wastewater generated in the engineering construction period and water resource waste; the sewage treatment system comprises: the regulating tank, the anoxic tank and the ceramic membrane tank, in particular to a record chip embedded in the ceramic membrane tank, records sewage treatment data, and is terminal equipment for data acquisition of a big data evaluation system;
big data evaluation system: the big data evaluation system is used for collecting a large amount of data in sewage treatment, including water quality monitoring data, equipment operation data and the like in the sewage treatment process, and then processing and evaluating the data by utilizing a data analysis and algorithm model so as to realize optimization and improvement of the sewage treatment system;
unmanned aerial vehicle patrols and examines: the patrol unmanned aerial vehicle transmits information to a big data evaluation system in real time through a 5G base station;
5G base station: the 5G base station is used for collecting real-time data of the sewage treatment tank environment, and intelligent feedback of a sewage treatment system is realized by providing high-speed data transmission and remote monitoring capability.
Evaluating the web display device: the evaluation web display device displays the position, water quality data, environmental data and emission water quality early warning data of the early warning ceramic membrane device and the acquisition sensor in the sewage treatment evaluation system with big data.
The sewage treatment evaluation system based on big data comprises an adjusting tank, an anoxic tank and a ceramic membrane tank; the regulating tank is connected with the anoxic tank through a sewage lifting pump, a filling frame and a first aeration device are arranged in the anoxic tank, and filling is arranged on the filling frame; the anoxic tank and the ceramic membrane tank are connected through a water inlet pump, a ceramic membrane assembly and a membrane supporting layer are arranged in the ceramic membrane tank, the water outlet end of the membrane assembly is connected with a clean water pump, and the membrane supporting layer is positioned on the outer surface of the ceramic membrane and used for supporting a recording chip and reinforcing the structure of the ceramic membrane; the ceramic membrane chip (SPI) sensor is connected to ensure that data can be transferred from the sensor to the chip.
The sewage treatment evaluation system based on big data comprises a terminal historical data module, a characteristic factor analysis module, a safety evaluation module, a patrol unmanned aerial vehicle acquisition module and an evaluation response module;
terminal history data module: the terminal historical data module is used for recording and storing historical data of the ceramic membrane pool, including various indexes, parameters, event records and the like; through analysis and statistics of historical data, information such as the running condition of the terminal equipment, the occurrence reason and frequency of faults and the like can be known;
the characteristic factor analysis module: the characteristic factor analysis module is used for carrying out deep mining and analysis on the terminal historical data and finding out main factors influencing the operation and faults of the terminal equipment; by establishing a mathematical model and an algorithm, key characteristic factors influencing the performance of equipment can be identified, so that basis is provided for equipment optimization, fault prediction and prevention; the module can help the user to better understand the working mechanism and the operation rule of the equipment and provide decision support;
and a security evaluation module: the safety evaluation module evaluates and analyzes the safety of sewage treated by the ceramic membrane pool, and can evaluate the safety risks and potential threats of parameters such as the flow, temperature, pressure, PH value and the like of the sewage in the sewage pool environment by collecting and analyzing data such as solid particles, suspended matters, microorganisms and the like in the sewage pool; the module can help users to find potential safety hazards in time, and corresponding safety measures are adopted to protect the safety of equipment and data.
Unmanned aerial vehicle collection module patrols and examines: the inspection unmanned aerial vehicle acquisition module is used for receiving real-time information transmitted by the inspection unmanned aerial vehicle through the 5G base station;
and an evaluation response module: the evaluation response module predicts possible faults, accidents or abnormal conditions in advance according to the terminal historical data and the characteristic factor analysis result, combines the sewage inspection information transmitted by the inspection unmanned aerial vehicle through the 5G base station in real time, and sends out an alarm and evaluation response in time after checking; by establishing an early warning model and rules, the water quality index, the flow index and the running state of the ceramic membrane device of sewage treatment can be monitored and early warned in real time, and measures can be taken in time to avoid or reduce potential risks.
The system comprises a sewage treatment evaluation system based on big data, wherein the inspection unmanned aerial vehicle comprises a high-definition camera, a sewage environment monitoring sensor and a data storage unit, and information is transmitted to the big data evaluation system in real time through a 5G base station; the high-definition camera can transmit the conditions in the corridor to the sewage treatment evaluation system with big data in real time through the 5G base station, and the environment monitoring sensor is used for collecting sewage environment information and transmitting the sewage environment information to the sewage treatment evaluation system with big data in real time through the 5G base station; the inspection unmanned plane can remotely collect and monitor the water quality state after sewage treatment through a 5G network, is used for unmanned inspection in a sewage area, and transmits collected information to a sewage treatment evaluation system of big data in real time through a 5G base station.
The 5G base station receives and forwards the processed water quality data, the environment data and the discharged water quality data sent by the inspection unmanned aerial vehicle to the sewage treatment evaluation system based on the big data; and (3) data transmission: the 5G base station provides a high-speed and low-delay data transmission channel, and can rapidly transmit a large amount of data collected in the sewage treatment process to a big data evaluation system for treatment. Compared with the prior communication network, the 5G can transmit more data faster, and the timeliness and the integrity of the data are ensured;
by the 5G technology, the running state, water quality parameters and other information of the ceramic membrane device can be obtained in real time, and remote setting and adjustment can be performed, so that the monitoring and management efficiency is improved; meanwhile, the 5G base station can also support simultaneous connection of multiple devices, so that data sharing in a sewage treatment evaluation system of big data is realized, and remote monitoring of the whole sewage treatment system is more intelligent and convenient.
The system comprises a sewage treatment evaluation system based on big data, wherein the evaluation web display equipment is used for displaying an electronic map of sampling positions pre-stored in a ceramic membrane display device, and the electronic map of sampling positions comprises a discharge device, a plurality of ceramic membrane devices and positions of collecting sensors in the discharge device and a plurality of processing devices; the inspection unmanned aerial vehicle sent by the 5G base station receives signals sent by the 5G base station at all sampling positions to control and judge the sampling positions of the plurality of acquisition sensors, and sends the processed water quality data, the environment data, the discharged water quality data and the sampling positions of the plurality of acquisition sensors to the evaluation Web display device;
the sewage treatment evaluation method of big data comprises the following steps:
step S1: a terminal history data module for acquiring terminal history data composed of m ceramic membranes in the sewage treatment system, wherein the terminal history module automatically acquires first operation data of a data unit of a membrane supporting layer in the ceramic membranes and second operation data of a data unit of a separating layer of sewage treatment, and m is a positive integer greater than 1;
step S2: analyzing a characteristic factor set of the sewage treatment block based on the first operational data record and the second operational data record; the characteristic factor set comprises classified characteristic factors and target characteristic factors;
step S3: based on target characteristic factors in the characteristic factor set, constructing an operation safety evaluation module corresponding to the target characteristic factors and calculating a safety evaluation index;
step S4: the inspection unmanned aerial vehicle acquires the real-time monitored data after sewage treatment, matches the operation safety module in the step S3, calculates the real-time safety evaluation index and carries out sewage treatment response early warning.
Step S5: the position, water quality data, environment data and emission water quality evaluation data of an early warning ceramic membrane device and an acquisition sensor in a sewage treatment evaluation system for evaluating big data displayed by web display equipment;
the step S2 includes the steps of:
the terminal history data module data unit I comprises interval duration recorded by the automatic cleaning equipment, data of cleaning objects and the automatic cleaning equipment, wherein the interval duration refers to interval duration from the last time the automatic cleaning equipment is used;
the terminal history data module data unit II comprises an operation block of the sewage treatment block, operation time length corresponding to the operation block and related data of sensing equipment in the sewage treatment block, wherein the related data of the sensing equipment refers to liquid level data sensed by a liquid level sensor;
s21, step: establishing a target data pair (A) ij ,B ij ,C ij ) Wherein A is ij Representing the number of operation blocks recorded by the jth use of the ith automatic cleaning equipment, C ij Representing the operation time length of the sewage treatment block in the jth use record of the ith automatic cleaning equipment, C ij Indicating the total water storage amount in the jth use record of the ith automatic cleaning equipment; i is less than or equal to m, j is less than or equal to n, and n is the total number of times of using the automatic cleaning equipment in the monitoring period;
setting interval duration recorded by any automatic cleaning equipment and data of cleaning objects as calibration data, acquiring a target data pair-column set corresponding to the calibration data, and extracting the data A ij ＝X α Time target data pairFor the first target data pair column, calculating the standard deviation of the operation time length in the first target data pair columnWherein->Is the average of the first target data versus column; standard deviation of total water storage>Wherein Y is α Is the set value of the total water yield, < > and->Is the average value of the total water storage amount;
s22, step: extraction of sweepia ij ＝X β The corresponding target data pair column is a second target data pair column, and the standard deviation of the operation time length in the second target data pair is calculatedWherein->Is the standard deviation of the average value and the total water storage amount of the second target data pair column +.> Wherein Y is β Is the set value of the total water yield, < > and->Is the average value of the total water storage amount;
the denominator of the sample standard deviation is here n-1 instead of n, because we use the average of the sample data as an estimate of the overall data when calculating the sample standard deviation. Since there is a certain error in estimating using the average value of the sample data, adjusting the denominator to n-1 can better reflect the difference between the sample data and the overall data when calculating the sample standard deviation.
S23, step: and calculating a first target difference value of |v1-v2| and a second target difference value of |w1-w2|, outputting operation content in the first operation data as a classification characteristic factor if at least any one of the first target difference value and the second target difference value is larger than or equal to a preset difference threshold value, and continuously analyzing the characteristic factor if both the first target difference value and the second target difference value are smaller than the preset difference threshold value.
The step S3 includes the steps of:
the method comprises the steps of constructing an operation safety evaluation module corresponding to target characteristic factors and calculating a safety evaluation index according to the target characteristic factors in the characteristic factor set;
s31, step: when no classification characteristic factors exist, acquiring a part of target data pair set Q, wherein the part of target data pair set Q comprises running time vij and total water storage capacity wij; acquiring interval duration xij and data yij of the cleaning object in the data unit-data corresponding to the set Q, and constructing a user, wherein the data set R and R are = { (xij and yij) }; the data of the cleaning object refers to load data of the cleaning object recorded by the automatic cleaning equipment;
sequentially constructing a sequence pair corresponding to data in a set R by a set Q, wherein the sequence pair comprises a sequence pair set Z1 with interval duration corresponding to running time, a sequence pair Z2 with interval duration corresponding to total water storage capacity, a sequence pair set Z3 with data of cleaning objects corresponding to running time and the number of the cleaning objects;
s32, step: judging the number of matching data pairs to which the target characteristic factors belong, and constructing a data unit-safety evaluation model as a fitting curve to which the matching data pairs belong when the number of the matching data pairs is only one; when the number of the matching data pairs is equal to two and the matching data pairs are different, constructing a data unit two safety evaluation model as a fitting curve to which the two matching data pairs belong;
s33, step: when the number of the proportion data pairs is greater than two or the number of the proportion data pairs is equal to two, the data units are two data phasesMeanwhile, constructing an operation safety evaluation model f of the d-th matching data on the comparison line segment in the belonging fitting curve d ＝[ed1,ed2]*[V ij ,W ij ；X ij ,Y ij ,Z ij ]Wherein [ ed1, ed2 ]]Is a coefficient matrix [ V ] ij ,W ij ；X ij ,Y ij ,Z ij ]As a variable matrix, ed1 represents a coefficient corresponding to the d-th proportioning data pair, and ed2 represents a constant corresponding to the d-th proportioning data pair;
if the number of the matching data pairs is zero, acquiring the related data of the input block except the first operation data in the step S1, and continuing to analyze the steps S2-S3 until the number of the matching data pairs is not zero.
The step S4 includes the steps of:
s41, step: the inspection unmanned aerial vehicle acquires the data after sewage treatment of real-time supervision, and according to the historical emission quality of water data of normalization for the value range is the same between the different data, conveniently carries out data comparison and analysis. Normalization formula: x '=x' (-X max -X min )+X min Wherein X' represents the normalized predicted emission water quality data; X'/X (X max -X min )+X min Representation de-normalization, representation linear scaling of the raw data such that the range of data values becomes (X max -X min ) The method comprises the steps of carrying out a first treatment on the surface of the X '' derived predicted emission water quality data; then add X min The range is translated to be between the minimum value of X and the maximum value of X, and can be adjusted according to specific conditions and requirements, so that predicted water quality data is ensured to be in a reasonable range, and normalization is realized.
S42, step: here we use the standard deviation V in step S3, assuming that the raw data has a linear relationship and that the xmax is not equal to xmax, to avoid zero-divide errors 1 、V 2 、W 1 、W 2 ]As a loss function of a Z-score standardized data preprocessing method, converting data acquired by the inspection unmanned aerial vehicle into a standardized data set, and calculating standard deviation of each feature based on the standardized data set; according to the standard deviation used in step S3Defining a loss function, wherein the standard deviation of each feature is used as the input of the loss function; the goal of the loss function is to minimize the standard deviation, i.e., to make the degree of dispersion of the data as small as possible. To achieve this objective, a suitable optimization algorithm is selected according to the optimization objective of the loss function, and the loss function is minimized by adjusting the value of the standard deviation; after optimization, the obtained standard deviation can be used for further feature factor analysis, and the standard deviation can help us understand the contribution degree of each feature to the data change, so that the features of the data can be further analyzed and understood; finally, normalizing the standard reaching pre-discharge water quality data mean value to be in a safety evaluation model f d ＝[ed1,ed2]*[V ij ,W ij ；X ij ,Y ij ,Z ij ]In the matrix of (2), the distribution characteristics of the obtained data are more stable, the method is applicable to the data which are not affected by outliers and need to keep the original distribution characteristics, and the data keeping the original distribution characteristics are transmitted to the evaluation web display equipment; when the predicted emission water quality data does not reach the emission standard, the predicted emission water quality data can be displayed on the evaluation web display device, so that workers can conveniently control the treatment, and the emission water quality is ensured to reach the standard requirement.
The step S5 includes the steps of:
the evaluation Web display device is used for displaying the electronic map of the sampling position; the sampling position electronic map comprises the positions of the emission device, the plurality of processing devices and the positions of the acquisition sensors in the emission device and the plurality of processing devices, and comprises the positions of the acquisition sensors, the processing devices and the emission device; and the plurality of inspection unmanned aerial vehicles receive signal control sent by the 5G base station at each sampling position, judge the water quality data, the environment data and the emission water quality data of the sewage treatment area, and send the sampling positions of the plurality of ceramic membranes and the acquisition sensors to the evaluation Web display equipment.
The preferred embodiments of the invention disclosed above are merely intended to help illustrate the invention, and the preferred embodiments do not describe all details in detail nor limit the invention to the specific embodiments only; obviously, many modifications and variations are possible in light of the above teachings; the embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention; the invention is limited only by the claims and the full scope and equivalents thereof.
Claims (10)
1. The sewage treatment evaluation system based on the big data is characterized by comprising a sewage treatment system, a big data evaluation system, a patrol unmanned aerial vehicle, a 5G base station and an evaluation web display device;
the sewage treatment system includes: the regulating tank, the anoxic tank and the ceramic membrane tank are embedded into a recording chip, sewage treatment data is recorded, and the device is terminal equipment for data acquisition of a big data evaluation system;
the big data evaluation system comprises water quality monitoring data and equipment operation data in the sewage treatment process, and the data are processed and evaluated by utilizing a data analysis and algorithm model so as to realize optimization and improvement of the sewage treatment system;
the patrol unmanned aerial vehicle transmits information to a big data evaluation system in real time through a 5G base station;
the 5G base station is used for collecting real-time data of the sewage treatment tank environment and providing high-speed data transmission and remote monitoring capability;
the evaluation web display device displays the position, water quality data, environmental data and emission water quality evaluation data of the early-warning ceramic membrane device and the acquisition sensor in the sewage treatment evaluation system with big data.
2. The sewage treatment evaluation system based on big data according to claim 1, wherein the regulating tank is connected with the anoxic tank through a sewage lifting pump, a filler frame and a first aeration device are arranged in the anoxic tank, and a filler is arranged on the filler frame; the anoxic tank and the ceramic membrane tank are connected through a water inlet pump, a ceramic membrane assembly and a membrane supporting layer are arranged in the ceramic membrane tank, the water outlet end of the membrane assembly is connected with a clean water pump, and the membrane supporting layer is positioned on the outer surface of the ceramic membrane; the ceramic membrane chip, namely the SPI chip, is connected with the sensor, so that data is transmitted from the sensor to the chip.
3. The big data based sewage treatment evaluation system according to claim 2, wherein the big data evaluation system comprises a terminal history data module, a characteristic factor analysis module, a safety evaluation module, a patrol unmanned aerial vehicle acquisition module and an evaluation response module;
the terminal historical data module is used for recording and storing historical data of the ceramic membrane pool, including various indexes, parameters and event records; through analysis and statistics of historical data, information such as the running condition of the terminal equipment, the occurrence reason and frequency of faults and the like can be known;
the characteristic factor analysis module is used for carrying out deep mining and analysis on the terminal historical data and finding out main factors influencing the operation and faults of the terminal equipment; key characteristic factors affecting the performance of the equipment can be identified by establishing a mathematical model and an algorithm;
the safety evaluation module evaluates and analyzes the safety of sewage treated by the ceramic membrane pool, and can evaluate the safety risks and potential threats existing in the flow, temperature, pressure and PH value parameters of the sewage in the sewage pool environment by collecting and analyzing the data such as solid particles, suspended matters, microorganisms and the like in the sewage pool;
the inspection unmanned aerial vehicle acquisition module receives real-time information transmitted by the inspection unmanned aerial vehicle through the 5G base station;
the evaluation response module predicts possible faults, accidents or abnormal conditions in advance according to the terminal historical data and the characteristic factor analysis result, combines the sewage inspection information transmitted by the inspection unmanned aerial vehicle through the 5G base station in real time, and sends out an alarm and evaluation response in time after checking; by establishing an early warning model and rules, the water quality index, the flow index and the running state of the ceramic membrane device of sewage treatment can be monitored and early warned in real time.
4. The big data based sewage treatment evaluation system according to claim 3, wherein the inspection unmanned aerial vehicle comprises a high-definition camera, a sewage environment monitoring sensor and a data storage unit, and the information is transmitted to the big data evaluation system in real time through a 5G base station; the high-definition camera can transmit the conditions in the corridor to the sewage treatment evaluation system with big data in real time through the 5G base station, and the environment monitoring sensor is used for collecting sewage environment information and transmitting the sewage environment information to the sewage treatment evaluation system with big data in real time through the 5G base station; the inspection unmanned plane can remotely collect and monitor the water quality state after sewage treatment through a 5G network, is used for unmanned inspection in a sewage area, and transmits collected information to a sewage treatment evaluation system of big data in real time through a 5G base station.
5. The big data based sewage treatment evaluation system according to claim 4, wherein the 5G base station receives and forwards the processed water quality data, the environmental data, and the discharged water quality data sent by the inspection unmanned aerial vehicle to the big data based sewage treatment evaluation system; the data collected in the sewage treatment process can be quickly transmitted to a big data evaluation system for treatment through the 5G base station; meanwhile, the operation state and water quality parameter information of the ceramic membrane device can be obtained through a 5G technology, and remote multi-system setting and allocation are performed; the 5G base station can also support simultaneous connection of multiple devices, so that data sharing in a sewage treatment evaluation system of big data is realized.
6. The big data-based sewage treatment evaluation system according to claim 5, wherein the evaluation web display device is used for displaying an electronic map of a sampling position pre-stored in the ceramic membrane device and a map of a position sampled by the ceramic membrane device, simultaneously transmitting the water quality information acquired by the inspection unmanned aerial vehicle to the big data-based sewage treatment evaluation system in real time through the 5G base station, and finally displaying the water quality information on the evaluation web display device.
7. A sewage treatment evaluation method based on big data, using the sewage treatment evaluation system of big data according to any one of claims 1 to 6, comprising the steps of:
step S1: a terminal history data module for acquiring terminal history data composed of m ceramic membranes in the sewage treatment system, wherein the terminal history module automatically acquires first operation data of a data unit of a membrane supporting layer in the ceramic membranes and second operation data of a data unit of a separating layer of sewage treatment, and m is a positive integer greater than 1;
step S2: analyzing a characteristic factor set of the sewage treatment block based on the first operation data of the data unit of the membrane supporting layer and the second operation data of the data unit of the separating layer; the characteristic factor set comprises classified characteristic factors and target characteristic factors;
step S3: based on target characteristic factors in the characteristic factor set, constructing an operation safety evaluation module corresponding to the target characteristic factors and calculating a safety evaluation index;
step S4: the inspection unmanned plane acquires the data after sewage treatment monitored in real time, matches the operation safety module in the step S3, calculates a real-time safety evaluation index and carries out sewage treatment response evaluation results;
step S5: the position, water quality data, environment data and emission water quality evaluation data of the ceramic membrane device and the acquisition sensor are early-warned in the sewage treatment evaluation system for displaying big data by the evaluation web display device.
8. The sewage treatment evaluation method based on big data according to claim 7, wherein the steps S2, S3 include:
the terminal history data module data unit I comprises interval duration recorded by the automatic cleaning equipment, data of cleaning objects and the automatic cleaning equipment, wherein the interval duration refers to interval duration from the last time the automatic cleaning equipment is used;
the terminal history data module data unit II comprises an operation block of the sewage treatment block, operation time length corresponding to the operation block and related data of sensing equipment in the sewage treatment block, wherein the related data of the sensing equipment refers to liquid level data sensed by a liquid level sensor;
the first extraction target data of the terminal historical data module data unit is a first target data pair, the second extraction target data of the terminal historical data module data unit is a second target data pair, the standard deviation value of the running time of the first target data and the second target data and the standard deviation value of the total water yield are calculated, and characteristic factors are analyzed according to the first target difference value and the second target difference value compared with a preset difference value threshold;
judging the number of matching data pairs to which target characteristic factors belong, and constructing a first operation safety evaluation model as a fitting curve to which the matching data pairs belong when the number of the matching data pairs is only one; when the number of the matching data pairs is equal to two and the matching data pairs are different, a second operation safety evaluation model is constructed as a fitting curve to which the two matching data pairs belong.
9. The sewage treatment evaluation method based on big data according to claim 8, wherein the step S4 includes:
the inspection unmanned plane acquires real-time monitored sewage treated data, and according to normalized historical emission water quality data, the standard deviation is used in step S3
[V 1 、V 2 、W 1 、W 2 ]As a loss function of the Z-score standardized data preprocessing method, the normalized mean value is in the safety evaluation model f d ＝[ed1,ed2]*
[V ij ,W ij ；X ij ,Y ij ,Z ij ]And transmitting the data that maintains the original distribution characteristics to the evaluating web display device.
10. The sewage treatment evaluation method based on big data according to claim 9, wherein the step S5 includes:
and the signals received by the plurality of acquisition sensors sent by the 5G base station are judged, the sampling positions of the plurality of acquisition sensors are judged, and the processed water quality data, the environment data, the discharged water quality data and the sampling positions of the plurality of acquisition sensors are sent to the evaluation Web display device.
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