CN113248025B - Control method, cloud server and system for rural domestic sewage treatment - Google Patents
Control method, cloud server and system for rural domestic sewage treatment Download PDFInfo
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- C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F3/00—Biological treatment of water, waste water, or sewage
- C02F3/34—Biological treatment of water, waste water, or sewage characterised by the microorganisms used
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Abstract
本申请提供了一种农村生活污水处理的控制方法、云端服务器及系统，其中应用于云端服务器的方法，包括：接收多个用于农村生活污水处理的一体化设备实时上传的数据信息；当根据数据信息确定目标设备处于当前工艺处理周期内的第一预设环节时，获取当前的处理工艺参考模型；根据数据信息中目标设备在当前工艺处理周期内的进水参数信息，从处理工艺参考模型中匹配得到一目标处理工艺；当检测到目标设备的菌落调整信息时，根据菌落调整信息对目标处理工艺进行调整；将包括目标处理工艺的处理结果发送至目标设备。本申请结合物联网技术、人工智能技术、大数据技术、生态环境调整等及时调整污水处理工艺，有利于保证污水处理的效果。
The application provides a control method, cloud server and system for rural domestic sewage treatment, wherein the method applied to the cloud server includes: receiving data information uploaded in real time by a plurality of integrated equipment used for rural domestic sewage treatment; When the data information determines that the target equipment is in the first preset link in the current process treatment cycle, the current treatment process reference model is obtained; A target treatment process is obtained by matching in the middle; when the colony adjustment information of the target device is detected, the target treatment process is adjusted according to the colony adjustment information; the treatment result including the target treatment process is sent to the target device. This application combines the Internet of Things technology, artificial intelligence technology, big data technology, ecological environment adjustment, etc. to adjust the sewage treatment process in time, which is conducive to ensuring the effect of sewage treatment.
Description
Technical Field
The application relates to the technical field of sewage treatment, in particular to a control method, a cloud server and a system for rural domestic sewage treatment.
Background
Rural domestic sewage treatment has different conditions from urban domestic sewage treatment, and because of the dispersibility characteristic of rural living environment, the rural domestic sewage cannot be collected and treated uniformly like a city. The currently common rural domestic sewage treatment methods mainly include pipe network building, a traditional anaerobic Aerobic (AO) process method, and a Sequencing Batch Biofilm Reactor (SBBR) method. The method for centralized collection and unified treatment of the pipe building network uses the same mode as the urban domestic sewage treatment, and has high construction and later operation and maintenance costs. The traditional AO method is a method mostly adopted by large-scale water plants, but if the AO method is used for small-scale equipment, the water outlet index is unstable due to the lack of impact resistance, and meanwhile, the AO method cannot culture sludge with unique functions due to the absence of an independent sludge return system, and the degradation rate of substances difficult to degrade is low. The SBBR method is a sequencing batch reaction method, has good stability in urban domestic sewage treatment, but has fixed working procedures, fixed reaction time of each working procedure and low nitrogen and phosphorus removal efficiency, and is difficult to ensure the activity of flora and the stability of effluent under the condition of uncertain water using time and water using amount of rural domestic sewage.
Most of the existing sewage treatment processes are oriented to the field of general urban sewage treatment, and few methods are applicable to the specific field of rural domestic sewage, most of the existing sewage treatment processes are evolved from the treatment mode of a large-scale water plant, need to be regularly maintained, clearly drew and supplement fillers, and need to be regularly checked by a large number of maintainers, so that problems cannot be timely found, when the problems are found, the ecological balance in the equipment is disordered, most of strains lose activity, the labor cost is wasted, and seven-minute construction pipes are built.
In the specific field of rural domestic sewage, the sewage treatment process method is considered, and the conditions of water inlet time and water quantity of each household are also considered, so that the traditional sewage treatment process has little effect in the rural domestic sewage treatment field. Therefore, the development of a treatment process suitable for rural domestic sewage becomes a strategic target.
Disclosure of Invention
The technical purpose to be achieved by the embodiment of the application is to provide a control method, a cloud server and a system for rural domestic sewage treatment, so as to solve the problem that the existing treatment process is poor in effect in the current rural domestic sewage treatment process.
In order to solve the above technical problem, an embodiment of the present application provides a control method for rural domestic sewage treatment, which is applied to a cloud server, and includes:
receiving data information uploaded by a plurality of integrated devices for rural domestic sewage treatment in real time, and performing supplementary updating on a data set in a database;
when the target equipment is determined to be in a first preset link in the current process processing period according to the data information, acquiring a current processing process reference model;
matching to obtain a target treatment process from the treatment process reference model according to the water inlet parameter information of the target equipment in the current process treatment period in the data information;
when bacterial colony adjustment information of the target equipment is detected, the target processing technology is adjusted according to the bacterial colony adjustment information to obtain the adjusted target processing technology, wherein the bacterial colony adjustment information comprises: information on the flow direction of the strain and/or the organic matter;
and sending a processing result comprising the target processing technology to the target equipment, wherein the processing result is used for enabling the target equipment to execute the target processing technology after the current technology processing cycle is finished.
Preferably, after the step of receiving data information uploaded by a plurality of integrated devices for rural domestic sewage treatment in real time and performing supplementary update on the data set in the database, the control method further comprises:
when the current time is detected to be at a creation node of the model creation cycle, the process reference model is reconstructed from the data set.
Specifically, the control method as described above, the step of reconstructing the process reference model from the data set includes:
pre-training a data set according to a pre-training neural network model to obtain a process vector and a time vector, and dividing the data set into a training set and a testing set according to a preset verification method;
constructing a neural network model based on an attention mechanism according to the process vector, the time vector and the test set;
training the neural network model according to the training set to obtain a target neural network model;
and determining a processing technology reference model according to the target neural network model and a preset judgment condition.
Further, the control method as described above, pre-training the data set according to the pre-training neural network model to obtain the process vector and the time vector, includes:
preprocessing the data set, the preprocessing comprising: decoding and standardizing the label;
and training the preprocessed data set according to the pre-training neural network model to obtain a time vector and a process vector.
Preferably, after the step of receiving data information uploaded by a plurality of integrated devices for rural domestic sewage treatment in real time and performing supplementary update on the data set in the database, the control method further comprises:
when detecting that the current time is one polling node of a polling period, acquiring target data information uploaded by target equipment between the last polling node and the current time;
determining the current ecological environment state of the target equipment according to the target data information;
and when determining that the ecological environment of the target equipment needs to be adjusted according to the current ecological environment state, generating bacterial colony adjustment information according to the current ecological environment state.
Specifically, the control method as described above, the step of determining the current ecological environment state of the target device according to the target data information includes:
comparing according to the target data information and a preset data model to obtain a comparison result, wherein the preset data model comprises: the corresponding relation between the strain components and the growth state and the data information;
determining the current proportional relation of each strain in the current ecological environment according to the comparison result;
and determining the current ecological environment state according to the current proportional relation and the preset proportional relation.
Preferably, after the step of receiving data information uploaded by a plurality of integrated devices for rural domestic sewage treatment in real time and performing supplementary update on the data set in the database, the control method further comprises:
when the target equipment is detected to be in a second preset link in the current process treatment period, acquiring water inlet parameter information in the current process treatment period;
obtaining estimated target water inlet parameter information of the next process treatment period according to the water inlet parameter information;
when the target equipment needs bacterial colony adjustment according to the target water inlet parameter information, bacterial colony adjustment information is generated.
Preferably, the control method as described above, further comprising:
when the target equipment is detected to be in a third preset link in the current process treatment period, acquiring the water inflow of the target equipment in a preset time interval;
and when the water inflow of the target equipment in the preset time interval is zero, sending a dormancy signal to the target equipment.
Further, the control method as described above, after the step of sending the sleep signal to the target device, further includes:
and when the water inflow is detected to be more than zero in the data information uploaded from the target equipment, sending an activation signal to the target equipment.
Preferably, after the steps of receiving data information uploaded by a plurality of integrated devices for rural domestic sewage treatment in real time and performing supplementary update on the data set in the database, the control method further comprises:
and when the data information uploaded by the target equipment carries fault information, generating an electronic early warning work order according to the fault information, and issuing the electronic early warning work order to an operation and maintenance terminal corresponding to the target equipment.
In another preferred embodiment of the present application, there is further provided a cloud server, including:
the first processing module is used for receiving data information uploaded by a plurality of integrated devices for rural domestic sewage treatment in real time and performing supplementary updating on a data set in a database;
the second processing module is used for acquiring a current processing technology reference model when the target equipment is determined to be in a first preset link in the current processing cycle according to the data information;
the third processing module is used for matching a target processing technology from the processing technology reference model according to the current water inlet parameter information in the data information;
the fourth processing module is used for adjusting the target processing technology according to the bacterial colony adjustment information when bacterial colony adjustment information of the target equipment is detected, and obtaining the adjusted target processing technology, wherein the bacterial colony adjustment information comprises: information on the flow direction of the strain and/or the organic matter;
and the fifth processing module is used for sending a processing result comprising the target processing technology to the target equipment, and the processing result is used for enabling the target equipment to execute the target processing technology after the current processing technology cycle is finished.
Preferably, the cloud server as described above further includes:
and the sixth processing module is used for reconstructing the processing technology reference model according to the data set when detecting that the current time is positioned at one creation node of the model creation period.
Specifically, as described above, the sixth processing module of the cloud server includes:
the first processing unit is used for pre-training the data set according to the pre-training neural network model to obtain a process vector and a time vector, and dividing the data set into a training set and a testing set according to a preset verification method;
the second processing unit is used for constructing a neural network model based on an attention mechanism according to the process vector, the time vector and the test set;
the third processing unit is used for training the neural network model according to the training set to obtain a target neural network model;
and the fourth processing unit is used for determining a processing technology reference model according to the target neural network model and a preset judgment condition.
Further, as described above, in the cloud server, the first processing unit includes:
a first processing subunit configured to perform a preprocessing on the data set, the preprocessing including: decoding and standardizing the label;
and the second processing subunit is used for training the preprocessed data set according to the pre-training neural network model to obtain a time vector and a process vector.
Preferably, the cloud server as described above further includes:
the seventh processing module is used for acquiring target data information uploaded by the target equipment between the previous polling node and the current time when the polling node with the current time as the polling period is detected;
the eighth processing module is used for determining the current ecological environment state of the target equipment according to the target data information;
and the ninth processing module is used for generating bacterial colony adjustment information according to the current ecological environment state when determining that the ecological environment adjustment needs to be carried out on the target equipment according to the current ecological environment state.
Specifically, as described above, the eighth processing module of the cloud server includes:
the fifth processing unit is used for comparing the target data information with a preset data model to obtain a comparison result, and the preset data model comprises: the corresponding relation between the strain components and the growth state and the data information;
the sixth processing unit is used for determining the current proportional relation of each strain in the current ecological environment according to the comparison result;
and the seventh processing unit is used for determining the current ecological environment state according to the current proportional relation and the preset proportional relation.
Preferably, the cloud server as described above further includes:
the tenth processing module is used for acquiring water inlet parameter information in the current process treatment cycle when the target equipment is detected to be in a second preset link in the current process treatment cycle;
the eleventh processing module is used for obtaining estimated target water inlet parameter information of the next process processing period according to the water inlet parameter information;
and the twelfth processing module is used for generating bacterial colony adjustment information when determining that the target equipment needs bacterial colony adjustment according to the target water inlet parameter information.
Preferably, the cloud server as described above further includes:
the thirteenth processing module is used for acquiring the water inflow of the target equipment within a preset time interval when the target equipment is detected to be in a third preset link in the current process treatment cycle;
and the fourteenth processing module is used for sending the dormancy signal to the target equipment when the water inflow of the target equipment in the preset time interval is zero.
Further, the cloud server as described above further includes:
and the fifteenth processing module is used for sending an activation signal to the target equipment when the water inflow is detected to be more than zero in the data information uploaded from the target equipment.
Preferably, the cloud server as described above further includes:
and the sixteenth processing module is used for generating an electronic early warning work order according to the fault information when the fault information is carried in the data information uploaded by the target equipment, and issuing the electronic early warning work order to the operation and maintenance terminal corresponding to the target equipment.
In still another preferred embodiment of the present application, there is provided a rural domestic sewage treatment system, including: a plurality of integrated devices and the cloud server as described above;
the integrated equipment is used for monitoring the running condition of the equipment per se and sending the generated data information to the cloud server; and receiving the target processing technology fed back by the cloud server, and executing the target processing technology in the next processing cycle after the current processing cycle is finished.
Specifically, as above rural domestic sewage treatment system is provided with a plurality of monitoring facilities in the integrated equipment for the equipment behavior of monitoring integrated equipment, monitoring facilities includes: at least one of a dissolved oxygen and pH value detector, a temperature sensor, an oxidation-reduction potential monitor, an NH-N sensor, an NO-N sensor, a suspended matter monitor, an inflow sensor and an outflow sensor.
In still another preferred embodiment of the present application, a readable storage medium is further provided, on which a computer program is stored, and the computer program is executed by a processor to implement the control method for rural domestic sewage treatment as described above.
Compared with the prior art, the control method, the cloud server and the system for rural domestic sewage treatment provided by the embodiment of the application have the following beneficial effects at least:
the control method for rural domestic sewage treatment obtains data information of a plurality of integrated devices based on the Internet of things technology, matches treatment processes based on the artificial intelligence technology according to the data information of target devices, obtains the treatment processes meeting the current conditions of the target devices and sends the treatment processes to the target devices for execution, namely, the sewage treatment processes are adjusted in time, the effect of sewage treatment is favorably ensured, the problem of waste or poor treatment effect caused by uncertain rural sewage inlet parameters is solved, meanwhile, ecological environment adjustment is combined into the treatment processes, ecological balance in the devices is favorably ensured, the situation that the treatment effect is not ideal caused by disordered ecological balance is avoided, and the sewage treatment effect is further ensured.
Drawings
FIG. 1 is a schematic flow chart of a rural domestic sewage treatment control method according to the present application;
FIG. 2 is a second schematic flow chart of the rural domestic sewage treatment control method of the present application;
FIG. 3 is a schematic diagram of the structure of a target neural network of the present application;
FIG. 4 is a third schematic flow chart of the rural domestic sewage treatment control method of the present application;
FIG. 5 is a fourth flowchart of the rural domestic sewage treatment control method according to the present application;
FIG. 6 is a fifth flowchart of the rural domestic sewage treatment control method according to the present application;
FIG. 7 is a sixth schematic flow chart of the rural domestic sewage treatment control method of the present application;
FIG. 8 is a seventh schematic flow chart of the rural domestic sewage treatment control method of the present application;
fig. 9 is a schematic structural diagram of a cloud server according to the present application;
FIG. 10 is a schematic structural view of the rural domestic sewage treatment system of the present application.
Detailed Description
To make the technical problems, technical solutions and advantages to be solved by the present application clearer, the following detailed description is made with reference to the accompanying drawings and specific embodiments. In the following description, specific details such as specific configurations and components are provided only to help the embodiments of the present application be fully understood. Accordingly, it will be apparent to those skilled in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present application. In addition, descriptions of well-known functions and constructions are omitted for clarity and conciseness.
It should be appreciated that reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present application. Thus, the appearances of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
In various embodiments of the present application, it should be understood that the sequence numbers of the following processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.
It should be understood that the term "and/or" herein is merely one type of association relationship that describes an associated object, meaning that three relationships may exist, e.g., a and/or B may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
In the embodiments provided herein, it should be understood that "B corresponding to a" means that B is associated with a from which B can be determined. It should also be understood that determining B from a does not mean determining B from a alone, but may also be determined from a and/or other information.
Referring to fig. 1, a preferred embodiment of the present application provides a control method for rural domestic sewage treatment, applied to a cloud server, including:
step S101, receiving data information uploaded by a plurality of integrated devices for rural domestic sewage treatment in real time, and performing supplementary updating on a data set in a database;
step S102, when the target equipment is determined to be in a first preset link in the current process processing period according to the data information, a current processing process reference model is obtained;
step S103, matching and obtaining a target treatment process from the treatment process reference model according to the water inlet parameter information of the target equipment in the current process treatment period in the data information;
step S104, when bacterial colony adjustment information of the target equipment is detected, adjusting the target processing technology according to the bacterial colony adjustment information to obtain the adjusted target processing technology, wherein the bacterial colony adjustment information comprises: information on the flow direction of the strain and/or the organic matter;
and step S105, sending a processing result including the target processing technology to the target equipment, wherein the processing result is used for enabling the target equipment to execute the target processing technology after the current technology processing cycle is finished.
In a specific embodiment of the application, a control method for rural domestic sewage treatment applied to a cloud server is provided, wherein the cloud server is connected with a plurality of integrated devices for rural domestic sewage treatment through internet of things, the cloud server can receive data information uploaded by the integrated devices in real time, and the data set in a database of the cloud server is supplemented and updated according to the data information by utilizing a big data technology for filing, the subsequent running state of the integrated devices is judged according to the data information uploaded by the integrated devices, and then the treatment process of the integrated devices is adjusted, so that the stability of the effluent quality is ensured, wherein the integrated devices are preferably integrated devices with mud-film cooperation, wherein the data information can include: water inlet parameter information, water outlet parameter information, processing process parameter information, equipment running state information and the like. Wherein, the parameter information of intaking includes: dissolved oxygen, pH value; the effluent parameter information comprises: ammonia nitrogen, nitrate nitrogen, and the like; the processing procedure parameter information includes: suspended matter, etc.; the device operation state information includes: temperature, redox potential, etc.
When the target equipment is determined to be in a first preset link in the current process treatment period according to the data information, determining that the target equipment needs to plan the next process treatment period, wherein the first preset treatment link is preferably the last link or a certain action in the last link of the current process treatment period, acquiring a current treatment process reference model at the moment, predicting water inlet parameter information of the next process treatment period according to the water inlet parameter information of the target equipment in the current process treatment period, or directly using the water inlet parameter information as the water inlet parameter information of the next process treatment period, matching the treatment process reference model to obtain a target treatment process which is used as a basic process of the next process treatment period, and indicating that the target equipment is any one of a plurality of integrated equipment.
Whether bacterial colony adjustment information about the target equipment exists in the cloud server or not is also detected, if the bacterial colony adjustment information does not exist, the ecological environment in the target equipment is in a preset normal state, and therefore the target processing technology is directly used as the processing technology of the next processing period of the target equipment; if the colony adjustment information exists, the ecological environment in the target equipment is indicated to be in an abnormal state, for example: namely, the disordered state or the initial disordered state, so that in order to ensure the stability of the ecological environment in the target equipment, the target treatment process needs to be adjusted according to the bacterial colony adjustment information to obtain an adjusted target treatment process, and the adjusted target treatment process is used as a treatment process of the next process treatment period of the target treatment process; and then, sending the treatment result comprising the target treatment process to target equipment, so that the target equipment executes the target treatment process when the current process treatment cycle is finished and the next process treatment cycle is started, and purifying the rural domestic sewage. The target treatment process includes, but is not limited to, specific limitations on the water lifting amount, the aeration amount, the sludge returning amount and the water discharging amount.
To sum up, the control method of rural domestic sewage treatment of this application acquires the data information of a plurality of integration equipment based on internet of things, construct the database based on big data technology, and carry out the matching of processing technology according to the data information of target equipment based on artificial intelligence technique, obtain the best processing technology who accords with the current condition of target equipment, and issue to the target equipment and carry out, through adjusting sewage treatment process in time promptly, be favorable to guaranteeing sewage treatment's effect and water outlet stability, solve because of rural sewage intake parameter is unset, lead to appearing extravagant or the not good problem of treatment effect, combine ecological environment adjustment to the processing technology in the while, be favorable to guaranteeing the ecological balance in the equipment, avoid leading to the unsatisfactory condition of treatment effect to appear because of ecological balance disorder, further assurance sewage treatment effect.
Preferably, after the step of receiving data information uploaded by a plurality of integrated devices for rural domestic sewage treatment in real time and performing supplementary update on the data set in the database, the control method further comprises:
when the current time is detected to be at a creation node of the model creation cycle, the process reference model is reconstructed from the data set.
In another preferred embodiment of the present application, the data set is also subjected to periodic modeling, that is, when the current time is located at a creation node of a model creation period, a processing technology reference model is reconstructed according to the current data set, that is, the cloud server processes data information uploaded by the plurality of integrated devices based on a big data technology, and constructs the processing technology reference model, which is beneficial to ensuring the application range and the processing effect of the obtained processing technology reference model; and the periodic modeling is carried out, so that the processing technology reference model can be adjusted in time according to the latest data information of the integrated equipment, and the applicability and the real-time performance of the processing technology reference model are ensured.
Referring to fig. 2, in particular, the step of reconstructing a process reference model from the data set, as described above, comprises:
step S201, pre-training a data set according to a pre-training neural network model to obtain a process vector and a time vector, and dividing the data set into a training set and a testing set according to a preset verification method;
step S202, constructing a neural network model based on an attention mechanism according to the process vector, the time vector and the test set;
step S203, training the neural network model according to the training set to obtain a target neural network model;
and step S204, determining a processing technology reference model according to the target neural network model and a preset judgment condition.
In a specific embodiment of the present application, a step of reconstructing a processing technology reference model according to a data set is specifically disclosed, wherein when reconstructing the processing technology reference model, first, a current data set is pre-trained according to a pre-trained neural network model set in advance to obtain a time vector and a process vector, and meanwhile, in this process, division of the data set can be synchronously performed, that is, the data set is divided into a training set and a test set according to a preset verification method, so as to facilitate subsequent construction and training of the neural network; in one embodiment, the pre-trained neural network Model is preferably a Continuous Bag Of Words Model (CBOW); the preset verification method is preferably a ten-fold cross verification method; it should be noted that, the sequence of the pre-training step and the data set dividing step is not specifically limited, that is, the pre-training step and the data set dividing step may be performed in tandem or simultaneously.
After the time vector, the process vector, the test set and the training set are obtained, a neural network model is constructed according to the time vector, the process vector and the test set, and an attention mechanism is added in the neural network model for capturing preset specific words and adding weights, so that the problem of semantic dilution of the front end of the long sequence is solved, and the obtained neural network model is more in line with the flow description requirement of the processing technology. In one embodiment of the present application, the neural network model is constructed as shown in FIG. 3, which is constructed based on BILSM-CRF (Bi-directional Long Short-Term Memory-Conditional Random Field) and attention mechanism.
After the neural network model is obtained, the neural network model is trained according to a training set, namely, the neural network model is adjusted, so that the obtained target neural network model corresponds to the current state of the integrated equipment, and the real-time performance and the applicability of the processing technology reference model obtained based on the target neural network are ensured.
When the treatment process reference model is obtained according to the target neural network model, the treatment process reference model is fused with preset judgment conditions, so that on the basis of meeting the treatment according to water inlet parameter information, parameters and/or formulas for screening are set by technical personnel according to factors such as actual environment conditions, policy requirements and the like, the treatment process reference model is further constrained, and the applicability and the real-time performance of the treatment process reference model are further ensured.
Optionally, the target neural network model mainly obtains a treatment process reference model according to the water inlet parameter, and the judgment condition mainly screens the treatment process reference model according to the water outlet parameter.
Referring to fig. 4, in a further control method as described above, the step of pre-training the data set according to the pre-trained neural network model to obtain the process vector and the time vector includes:
step S401, preprocessing the data set, wherein the preprocessing comprises: decoding and standardizing the label;
and S402, training the preprocessed data set according to the pre-training neural network model to obtain a time vector and a process vector.
In another preferred embodiment of the present application, the pre-training the data set according to the pre-training neural network model to obtain the process vector and the time vector includes: firstly, preprocessing data in a data set so that the data meet form requirements trained in a pre-trained neural network model, wherein the preprocessing step comprises the following steps: decoding and standardizing the annotation, wherein the annotation is preferably performed according to the BIO annotation system when the standardized annotation is performed. And then, bringing the preprocessed data set into a pre-training neural network model, and training to obtain the required time vector and process vector.
Referring to fig. 5, preferably, after the step of receiving data information uploaded in real time by a plurality of integrated devices for rural domestic sewage treatment and performing supplementary update on the data set in the database, the control method further comprises:
step S501, when detecting that the current time is one polling node of a polling period, acquiring target data information uploaded by target equipment between the last polling node and the current time;
step S502, determining the current ecological environment state of the target equipment according to the target data information;
step S503, when determining that the ecological environment adjustment needs to be performed on the target device according to the current ecological environment state, generating bacterial colony adjustment information according to the current ecological environment state.
In another preferred embodiment of the present application, when the current time is a polling node of a polling period, it is determined that polling needs to be performed on data information corresponding to each integrated device in the database at this time, target data information of a target device between the last polling node and the current time is obtained at this time, and by processing the target data information, a current ecological environment state in the target device can be determined, that is, an ecological environment state in the device is inferred from the data information. For example, when the ratio of strains in the ecological environment state exceeds a preset range, it is determined that the ecological environment is about to be disturbed, and at this time, it is determined that ecological environment adjustment needs to be performed on the target equipment, and then bacterial colony adjustment information is generated according to the current ecological environment state and the normal ecological environment state, so that the target treatment process is adjusted according to the bacterial colony adjustment information before the target treatment process is issued, and the target equipment can realize ecological environment adjustment by adjusting the duration of a certain link, changing the flow direction of sludge and other forms in the next process treatment period, so as to ensure the stability of the ecological environment in the target equipment, and avoid the problems that the target equipment cannot treat sewage or the treatment effect is not ideal due to the disturbance of the ecological environment.
In a specific embodiment, the strains are preferably nitrifying bacteria and denitrifying bacteria, and when the proportion of the nitrifying bacteria in the target equipment is too large, the bacterial colony adjustment information is to increase the mud returning time, namely, the nitrifying bacteria are returned to the sedimentation tank; when the proportion of the denitrifying bacteria in the target equipment is too high, the bacterial colony adjustment information is to return part of the sludge to the liquid dung separation area.
Referring to fig. 6, in particular, the control method as described above, the step of determining the current eco-environment status of the target device according to the target data information includes:
step S601, comparing the target data information with a preset data model to obtain a comparison result, wherein the preset data model comprises: the corresponding relation between the strain components and the growth state and the data information;
step S602, determining the current proportional relationship of each strain in the current ecological environment according to the comparison result;
and step S603, determining the current ecological environment state according to the current proportional relation and the preset proportional relation.
In a specific embodiment of the present application, when determining the current ecological environment state of the target device according to the target data information, the target data information is compared with a preset data model to obtain a comparison result, where the preset data model includes: the corresponding relation between the strain components and the growth state and the data information enables the current proportional relation of each strain in the current ecological environment to be automatically determined according to the comparison result, and the current ecological environment state can be determined to be normal, namely to be disordered or disordered by judging the obtained current proportional relation and the preset proportional relation when the ecological environment is in the normal state.
Optionally, in the correspondence between the strain components and growth states and the data information, the data information is preferably dissolved oxygen and suspended substances.
Referring to fig. 7, preferably, after the step of receiving data information uploaded in real time by a plurality of integrated devices for rural domestic sewage treatment and performing supplementary update on the data set in the database, the control method further comprises:
step S701, when detecting that the target equipment is located in a second preset link in the current process treatment period, acquiring water inlet parameter information in the current process treatment period;
step S702, obtaining estimated target water inlet parameter information of the next process treatment period according to the water inlet parameter information;
and step S703, when determining that the target equipment needs bacterial colony adjustment according to the target water inlet parameter information, generating bacterial colony adjustment information.
In another preferred embodiment of the present application, after receiving the data information, when it is detected that the target device is in a second preset loop of the current process processing cycle, water inlet parameter information in the current process processing cycle is obtained, and a deep learning method is used to estimate target water inlet parameter information of a next process processing cycle, so as to evaluate the ecological environment of the target device according to the target water inlet parameter information, if it is determined that there is a possibility that the ecological environment is disturbed when processing is performed according to the target, it is determined that bacterial colony adjustment needs to be performed, and at this time, bacterial colony adjustment information is generated to ensure that the ecological environment is adjusted in the next process processing cycle, thereby ensuring normal operation of the target device.
Optionally, the step of determining whether the bacterial colony adjustment is needed according to the water inlet parameter information may be combined with the step of determining the current ecological environment state of the target device according to the target data information during the inspection.
Referring to fig. 8, preferably, the control method as described above, further includes:
step S801, when detecting that the target equipment is in a third preset link in the current process treatment cycle, acquiring the water inflow of the target equipment in a preset time interval;
step S802, when the water inflow of the target equipment in the preset time interval is zero, a sleep signal is sent to the target equipment.
Preferably, when it is detected that the target device is in a third preset loop in the current process processing period, the control method includes mainly acquiring a water inflow of the target device in a preset time interval, when the water inflow in the preset time interval is zero, it can be inferred that a person using the target device is zero, in order to save cost, sending a sleep signal to the target device to enable the target device to enter a sleep state, where the target device is in the sleep state, and other parts stop operating except necessary parts for maintaining a dynamic environment in the target device according to a preset flow. Preferably, the preset time interval is two days.
It should be noted that, the third preset link, the second preset link and the first preset link in this document may be the same link.
Further, the control method as described above, after the step of sending the sleep signal to the target device, further includes:
and when the water inflow is detected to be more than zero in the data information uploaded from the target equipment, sending an activation signal to the target equipment.
In another preferred embodiment of the present application, after sending the sleep signal to the target device to enable the target device to enter the sleep state, the data information uploaded by the target device is monitored, and when the data information indicates that the water inflow is greater than zero, it is determined that a person is currently using the target device, and at this time, an activation signal is sent to the target device to enable the target device to enter a normal operation mode, so as to ensure timely and effective treatment of sewage.
Optionally, the step of controlling the target device to be dormant or activated according to the water inflow may be combined with the routing inspection node in a processing process.
Preferably, after the steps of receiving data information uploaded by a plurality of integrated devices for rural domestic sewage treatment in real time and performing supplementary update on the data set in the database, the control method further comprises:
and when the data information uploaded by the target equipment carries fault information, generating an electronic early warning work order according to the fault information, and issuing the electronic early warning work order to an operation and maintenance terminal corresponding to the target equipment.
In another preferred embodiment of the present application, when the data information uploaded by the target device carries failure information, a failure of the target device is determined, and at this time, an electronic early warning work order is generated according to the failure information and is issued to the operation and maintenance terminal corresponding to the target device, so that the operation and maintenance personnel in charge of the operation and maintenance terminal can maintain the target device in an online or offline manner, and the influence of the long-time failure of the target device on sewage treatment and the living environment of the user is avoided.
Referring to fig. 9, in another preferred embodiment of the present application, there is provided a cloud server, including:
the first processing module 901 is used for receiving data information uploaded by a plurality of integrated devices for rural domestic sewage treatment in real time and performing supplementary updating on a data set in a database;
a second processing module 902, configured to obtain a current processing technology reference model when it is determined that the target device is in a first preset link in a current processing cycle according to the data information;
a third processing module 903, configured to obtain a target treatment process by matching from the treatment process reference model according to current influent parameter information in the data information;
a fourth processing module 904, configured to, when bacterial colony adjustment information of the target device is detected, adjust the target processing technology according to the bacterial colony adjustment information to obtain an adjusted target processing technology, where the bacterial colony adjustment information includes: information on the flow direction of the strain and/or the organic matter;
a fifth processing module 905, configured to send a processing result including the target processing technology to the target device, where the processing result is used to enable the target device to execute the target processing technology after the current processing technology cycle is ended.
Preferably, the cloud server as described above further includes:
and the sixth processing module is used for reconstructing the processing technology reference model according to the data set when detecting that the current time is positioned at one creation node of the model creation period.
Specifically, as described above, the sixth processing module of the cloud server includes:
the first processing unit is used for pre-training the data set according to the pre-training neural network model to obtain a process vector and a time vector, and dividing the data set into a training set and a testing set according to a preset verification method;
the second processing unit is used for constructing a neural network model based on an attention mechanism according to the process vector, the time vector and the test set;
the third processing unit is used for training the neural network model according to the training set to obtain a target neural network model;
and the fourth processing unit is used for determining a processing technology reference model according to the target neural network model and a preset judgment condition.
Further, as described above, in the cloud server, the first processing unit includes:
a first processing subunit configured to perform a preprocessing on the data set, the preprocessing including: decoding and standardizing the label;
and the second processing subunit is used for training the preprocessed data set according to the pre-training neural network model to obtain a time vector and a process vector.
Preferably, the cloud server as described above further includes:
the seventh processing module is used for acquiring target data information uploaded by the target equipment between the previous polling node and the current time when the polling node with the current time as the polling period is detected;
the eighth processing module is used for determining the current ecological environment state of the target equipment according to the target data information;
and the ninth processing module is used for generating bacterial colony adjustment information according to the current ecological environment state when determining that the ecological environment adjustment needs to be carried out on the target equipment according to the current ecological environment state.
Specifically, as described above, the eighth processing module of the cloud server includes:
the fifth processing unit is used for comparing the target data information with a preset data model to obtain a comparison result, and the preset data model comprises: the corresponding relation between the strain components and the growth state and the data information;
the sixth processing unit is used for determining the current proportional relation of each strain in the current ecological environment according to the comparison result;
and the seventh processing unit is used for determining the current ecological environment state according to the current proportional relation and the preset proportional relation.
Preferably, the cloud server as described above further includes:
the tenth processing module is used for acquiring water inlet parameter information in the current process treatment cycle when the target equipment is detected to be in a second preset link in the current process treatment cycle;
the eleventh processing module is used for obtaining estimated target water inlet parameter information of the next process processing period according to the water inlet parameter information;
and the twelfth processing module is used for generating bacterial colony adjustment information when determining that the target equipment needs bacterial colony adjustment according to the target water inlet parameter information.
Preferably, the cloud server as described above further includes:
the thirteenth processing module is used for acquiring the water inflow of the target equipment within a preset time interval when the target equipment is detected to be in a third preset link in the current process treatment cycle;
and the fourteenth processing module is used for sending the dormancy signal to the target equipment when the water inflow of the target equipment in the preset time interval is zero.
Further, the cloud server as described above further includes:
and the fifteenth processing module is used for sending an activation signal to the target equipment when the water inflow is detected to be more than zero in the data information uploaded from the target equipment.
Preferably, the cloud server as described above further includes:
and the sixteenth processing module is used for generating an electronic early warning work order according to the fault information when the fault information is carried in the data information uploaded by the target equipment, and issuing the electronic early warning work order to the operation and maintenance terminal corresponding to the target equipment.
The embodiment of the cloud server of the application is the cloud server corresponding to the embodiment of the control method, all implementation means in the embodiment of the control method are applicable to the embodiment of the cloud server, and the same technical effect can be achieved.
Referring to fig. 10, in yet another preferred embodiment of the present application, there is provided a rural sewage treatment system comprising: a plurality of integrated devices 1 and a cloud server 2 as described above;
the integrated device 1 is used for monitoring the running condition of the device and sending the generated data information to the cloud server 2; and receiving the target processing technology fed back by the cloud server 2, and executing the target processing technology in the next processing cycle after the current processing cycle is finished.
In a preferred embodiment of the present application, a rural domestic sewage treatment system is further provided, which includes a plurality of integrated devices 1 and the cloud server 2 as described above, wherein the cloud server 2 can implement the steps of the control method for rural sewage treatment based on the cloud server 2 in the using process, and the steps are not described herein again; the integrated equipment 1 is used for monitoring the running condition of the equipment and sending the generated data information to the cloud server 2; when the integrated device 1 is used as a target device, the target processing technology fed back by the cloud server 2 is received, and when the next processing cycle is started, the target processing technology is executed.
Preferably, in another embodiment, when a sleep signal sent by the cloud server 2 is received, the cloud server enters a sleep state, and is reactivated after receiving an activation signal. And when the integrated equipment is in the dormant state, the other parts stop running except the necessary part for maintaining the ecological environment in the integrated equipment according to the preset flow.
Specifically, as above rural domestic sewage treatment system is provided with a plurality of monitoring facilities in the integrated equipment for the equipment behavior of monitoring integrated equipment, monitoring facilities includes: at least one of a dissolved oxygen and pH value detector, a temperature sensor, an oxidation-reduction potential monitor, an NH-N sensor, an NO-N sensor, a suspended matter monitor, an inflow sensor and an outflow sensor.
In yet another preferred embodiment of the present application, there is also provided a readable storage medium on which a computer program is stored, the computer program, when executed by a processor, implementing the control method for rural domestic sewage treatment as described above.
Further, the present application may repeat reference numerals and/or letters in the various examples. This repetition is for the purpose of simplicity and clarity and does not in itself dictate a relationship between the various embodiments and/or configurations discussed.
It is further noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion.
The foregoing is a preferred embodiment of the present application, and it should be noted that, for those skilled in the art, several modifications and refinements can be made without departing from the principle described in the present application, and these modifications and refinements should be regarded as the protection scope of the present application.
Claims (12)
1. A control method for rural domestic sewage treatment is applied to a cloud server and is characterized by comprising the following steps:
receiving data information uploaded by a plurality of integrated devices for rural domestic sewage treatment in real time, and supplementing and updating a data set in a database, wherein the data information comprises: water inlet parameter information, water outlet parameter information, processing process parameter information and equipment running state information;
when the target equipment is determined to be in a first preset link in the current process processing period according to the data information, acquiring a current processing process reference model;
matching to obtain a target treatment process from the treatment process reference model according to the water inlet parameter information of the target equipment in the current process treatment period in the data information;
detecting whether bacterial colony adjustment information about the target equipment exists in the cloud server; if the colony adjustment information is not detected, taking the target processing technology as the processing technology of the next processing cycle of the target equipment; when bacterial colony adjustment information of the target equipment is detected, adjusting the target processing technology according to the bacterial colony adjustment information to obtain the adjusted target processing technology, and taking the adjusted target processing technology as a processing technology of the next processing cycle of the target equipment, wherein the bacterial colony adjustment information comprises: information on the flow direction of the strain and/or the organic matter;
sending a processing result comprising the target processing technology to the target equipment, wherein the processing result is used for enabling the target equipment to execute the target processing technology after the current technology processing cycle is finished;
after the step of receiving data information uploaded by a plurality of integrated devices for rural domestic sewage treatment in real time and performing supplementary updating on a data set in a database, the step of generating the bacterial colony adjustment information comprises the following steps:
when detecting that the current time is one polling node of a polling period, acquiring target data information uploaded by the target equipment between the last polling node and the current time; determining the current ecological environment state of the target equipment according to the target data information; when determining that ecological environment adjustment needs to be performed on the target equipment according to the current ecological environment state, generating the bacterial colony adjustment information according to the current ecological environment state and a normal ecological environment state;
when the target equipment is detected to be in a second preset link in the current process treatment cycle, acquiring the water inlet parameter information in the current process treatment cycle; obtaining estimated target water inlet parameter information of the next process treatment period according to the water inlet parameter information; and evaluating the ecological environment of the target equipment according to the target water inlet parameter information, and generating the bacterial colony adjustment information when the target equipment is determined to need bacterial colony adjustment according to the target water inlet parameter information.
2. The control method according to claim 1, wherein after the step of receiving data information uploaded in real time by a plurality of integrated devices for rural domestic sewage treatment and performing supplementary update on the data set in the database, the method further comprises the following steps:
and when the current time is detected to be positioned at one creation node of the model creation period, reconstructing the treatment process reference model according to the data set.
3. The control method of claim 2, wherein said step of reconstructing said process reference model from said data set comprises:
pre-training the data set according to a pre-training neural network model to obtain a process vector and a time vector, and dividing the data set into a training set and a test set according to a preset verification method;
constructing a neural network model based on an attention mechanism according to the process vector, the time vector and the test set;
training the neural network model according to the training set to obtain a target neural network model;
and determining the treatment process reference model according to the target neural network model and a preset judgment condition.
4. The control method of claim 3, wherein the pre-training the data set according to a pre-trained neural network model to obtain a process vector and a time vector comprises:
pre-processing the data set, the pre-processing comprising: decoding and standardizing the label;
and training the preprocessed data set according to the pre-training neural network model to obtain the time vector and the process vector.
5. The control method according to claim 1, wherein the step of determining the current eco-environment status of the target device according to the target data information comprises:
comparing the target data information with a preset data model to obtain a comparison result, wherein the preset data model comprises: the corresponding relation between the strain components and the growth state and the data information;
determining the current proportional relation of each strain in the current ecological environment according to the comparison result;
and determining the current ecological environment state according to the current proportional relation and a preset proportional relation.
6. The control method according to claim 1, characterized by further comprising:
when the target equipment is detected to be in a third preset loop in the current process treatment cycle,
acquiring the water inflow of the target equipment within a preset time interval;
and when the water inflow of the target equipment in the preset time interval is zero, sending a sleep signal to the target equipment.
7. The method of claim 6, further comprising, after the step of sending a sleep signal to the target device:
and when the water inflow is detected to be larger than zero in the data information uploaded from the target equipment, sending an activation signal to the target equipment.
8. The control method according to claim 1, after the step of receiving data information uploaded in real time by a plurality of integrated devices for rural domestic sewage treatment and performing supplementary update on the data set in the database, further comprising:
and when the data information uploaded by the target equipment carries fault information, generating an electronic early warning work order according to the fault information, and issuing the electronic early warning work order to an operation and maintenance terminal corresponding to the target equipment.
9. A cloud server, comprising:
the first processing module is used for receiving data information uploaded by a plurality of integrated devices for rural domestic sewage treatment in real time and performing supplementary updating on a data set in a database;
the second processing module is used for acquiring a current processing technology reference model when the target equipment is determined to be in a first preset link in the current processing cycle according to the data information;
the third processing module is used for matching a target processing technology from the processing technology reference model according to the current water inlet parameter information in the data information;
the fourth processing module is used for detecting whether bacterial colony adjustment information about the target equipment exists in the cloud server or not; if the colony adjustment information is not detected, taking the target processing technology as the processing technology of the next processing cycle of the target equipment; when bacterial colony adjustment information of the target equipment is detected, adjusting the target processing technology according to the bacterial colony adjustment information to obtain the adjusted target processing technology, and taking the adjusted target processing technology as a processing technology of the next processing cycle of the target equipment, wherein the bacterial colony adjustment information comprises: information on the flow direction of the strain and/or the organic matter;
the fifth processing module is used for sending a processing result comprising the target processing technology to the target equipment, and the processing result is used for enabling the target equipment to execute the target processing technology after the current processing technology cycle is finished;
the cloud server as described above further includes:
the seventh processing module is used for acquiring target data information uploaded by the target equipment between the previous polling node and the current time when the polling node with the current time as the polling period is detected; the eighth processing module is used for determining the current ecological environment state of the target equipment according to the target data information; the ninth processing module is used for generating bacterial colony adjustment information according to the current ecological environment state when determining that the ecological environment adjustment needs to be carried out on the target equipment according to the current ecological environment state;
the tenth processing module is used for acquiring water inlet parameter information in the current process treatment cycle when the target equipment is detected to be in a second preset link in the current process treatment cycle; the eleventh processing module is used for obtaining estimated target water inlet parameter information of the next process processing period according to the water inlet parameter information; and the twelfth processing module is used for generating bacterial colony adjustment information when determining that the target equipment needs bacterial colony adjustment according to the target water inlet parameter information.
10. A rural domestic sewage treatment system is characterized by comprising: a plurality of integrated devices and the cloud server of claim 9;
the integrated equipment is used for monitoring the running condition of the equipment per se and sending the generated data information to the cloud server; and receiving a target processing process fed back by the cloud server, and executing the target processing process in the next processing cycle after the current processing cycle is finished.
11. The rural domestic sewage treatment system of claim 10 wherein a plurality of monitoring devices are provided in said integrated device for monitoring the device operating conditions of said integrated device, said monitoring devices comprising: at least one of a dissolved oxygen and pH value detector, a temperature sensor, an oxidation-reduction potential monitor, an NH-N sensor, an NO-N sensor, a suspended matter monitor, an inflow sensor and an outflow sensor.
12. A readable storage medium, characterized in that the readable storage medium has stored thereon a computer program, which when executed by a processor, implements the control method of rural domestic sewage treatment according to any one of claims 1 to 8.
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