On-line excess sludge discharge control method, device, equipment and storage medium

Abstract

The present application relates to the field of sludge treatment, and in particular to an online excess sludge discharge control method, apparatus, device, and storage medium. The method comprises: upon detecting an information monitoring instruction, obtaining device status information of an online measuring device, then determining whether the online measuring device matches a preset abnormality type based on the device status information, and if so, generating a stop discharge instruction, analyzing the preset abnormality type that matches the online measuring device, determining the abnormal location information and abnormality cause of the online measuring device, and controlling the discharge device to stop discharging excess sludge. Then, keyword extraction is performed on the abnormal location information and abnormality cause to obtain abnormal keyword information, and an abnormality solution is determined based on the keyword information, and then the abnormality solution is controlled and displayed. The present application has the effect of timely troubleshooting and maintenance of online measuring devices.

Description

Technical Field

[0001] The present application relates to the field of sludge treatment, and in particular to an online excess sludge discharge control method, device, equipment and storage medium. Background Art

[0002] Excess activated sludge refers to the activated sludge discharged from the secondary sedimentation tank (or sedimentation area) of an activated sludge system. Excess sludge is generated during the biochemical treatment process, as microorganisms in the activated sludge continuously consume organic matter in the wastewater. Some of this consumed organic matter is oxidized to provide energy for the microorganisms' life activities, while others are used by the microorganisms to synthesize new cytoplasm, enabling their reproduction. As the microorganisms metabolize, some older microorganisms die, resulting in excess sludge.

[0003] The essence of residual sludge discharge is that during the working process of microorganisms, due to the continuous proliferation of microorganisms themselves, the total amount of residual sludge in the degradation tank continues to increase. When the total amount of residual sludge exceeds the capacity of the degradation tank, the excess residual sludge is discharged to maintain the stability of the degradation tank.

[0004] At present, when controlling the discharge of residual sludge, online measuring equipment is installed in the degradation tank to monitor parameters such as the organic matter content and solid content in the degradation tank in real time. After receiving the parameters, the residual sludge control system calculates the total amount of residual sludge in the degradation tank to obtain the total amount of residual sludge currently in the degradation tank. The residual sludge control system then judges the total amount of residual sludge to determine whether the total amount of residual sludge exceeds the standard total amount of residual sludge. If so, the residual sludge is controlled to be discharged until the total amount of residual sludge meets the standard total amount of residual sludge.

[0005] With respect to the above-mentioned related technologies, the inventors believe that when controlling the discharge of residual sludge, once problems such as failure or aging of the online measuring equipment occur, it is impossible to promptly troubleshoot and maintain the problems of the online measuring equipment. Summary of the Invention

[0006] In order to timely check and maintain online measurement equipment, the present application provides an online excess sludge discharge control method, device, equipment and storage medium.

[0007] In the first aspect, the present application provides an online excess sludge discharge control method, which adopts the following technical solution:

[0008] An online excess sludge discharge control method comprising:

[0009] Obtain device status information of online measurement equipment;

[0010] Determining whether the online measurement device matches a preset abnormality type according to the device status information;

[0011] If a match is found, a stop discharge instruction is generated, and the preset abnormality type matching the online measuring device is analyzed to determine the abnormal location information and abnormality cause of the online measuring device. The stop discharge instruction is used to control the discharge device to stop discharging excess sludge;

[0012] Perform keyword extraction on the abnormal location information and the abnormal cause to obtain abnormal keyword information, and determine an abnormal solution based on the keyword information;

[0013] The control displays the exception solution.

[0014] By adopting the above technical solution, when the discharge of residual sludge is controlled, the equipment status information of the online measuring equipment is obtained, and then it is determined whether the online measuring equipment matches the preset abnormality type based on the equipment status information. When the online measuring equipment matches the preset abnormality type, it means that the current online measuring equipment has a fault, and a stop discharge instruction is generated to control the discharge equipment to stop discharging the residual sludge. At the same time, the preset abnormality type matching the online measuring equipment is analyzed to determine the abnormal position information and the cause of the abnormality of the online measuring equipment. Then, keywords are extracted from the abnormal position information and the cause of the abnormality to obtain abnormal keyword information. The abnormal solution is determined based on the keyword information, and the abnormal solution is controlled and displayed to facilitate maintenance personnel to maintain the online measuring equipment according to the abnormal solution, thereby achieving the effect of timely troubleshooting and maintenance of the online measuring equipment.

[0015] In another possible implementation, determining an exception solution based on the keyword information includes:

[0016] Inputting the keyword information into a trained text network model for training to obtain text feature vector information of the keyword information;

[0017] Perform data comparison analysis on the text feature vector information to determine an exception solution that matches the text feature vector information.

[0018] Through the above technical solution, when determining the exception solution based on keyword information, the keyword information is input into the trained text network model for training to obtain the text feature vector information of the keyword information, and then the text feature vector information is subjected to data comparison and analysis to determine the exception solution that matches the text feature vector information, so that maintenance personnel can obtain accurate exception solutions.

[0019] In another possible implementation, the step of inputting the keyword information into a trained text network model for training further includes:

[0020] Acquire a text training sample, wherein the text training sample includes device abnormality solution information and keyword information corresponding to each solution in the device abnormality solution information;

[0021] A text network model is created, and the text network model is trained based on the text training samples to obtain a trained text network model.

[0022] Through the above technical solution, text training samples are prepared in advance, and the text training samples include equipment abnormality solution information and keyword information corresponding to each equipment abnormality solution information. Then, a text network model is created, and the text training samples are input into the text network model to obtain the equipment abnormality solution information and keyword information of the text training samples, thereby obtaining a trained text network model, which is convenient for subsequent identification of abnormal location information and keywords in abnormal causes.

[0023] In another possible implementation, the method further includes:

[0024] If the online measuring device does not match the preset abnormality type, the measurement parameters of the online measuring device are obtained, and a logic cycle judgment is performed on the measurement parameters to generate the excess sludge discharge amount.

[0025] Through the above technical solution, when the online measuring device does not match the preset abnormality type, it indicates that the current online measuring device has not failed. Therefore, the measurement parameters of the online measuring device are obtained, and the measurement parameters are logically judged periodically to finally generate the residual sludge discharge amount, so that the subsequent discharge equipment can perform quantitative discharge.

[0026] In another possible implementation, performing logical periodic judgment on the measurement parameters to generate the excess sludge discharge amount includes:

[0027] Determining parameter category information based on the measured parameters, the parameter category information including an influent volume parameter, an organic matter content parameter, a sludge concentration parameter, and a suspended solids concentration parameter;

[0028] determining whether the water inlet parameter satisfies a preset water inlet parameter range; if the water inlet parameter does not satisfy the preset water inlet parameter range, generating a water inlet parameter adjustment instruction, and adjusting the current water inlet according to the water inlet parameter adjustment instruction;

[0029] If the water inlet parameter satisfies the preset water inlet parameter range, determining whether the organic matter content parameter, the sludge concentration parameter, and the suspended solids concentration parameter in the water inlet meet the preset standard parameter range based on the water inlet parameter; if at least one of the organic matter content parameter, the sludge concentration parameter, and the suspended solids concentration parameter does not meet the preset standard parameter range, detecting the measurement parameters within a preset period, calculating the measurement parameters, and generating the excess sludge discharge amount;

[0030] If the organic matter content parameter, sludge concentration parameter and suspended solids concentration parameter in the influent volume meet the preset standard parameter range, calculation is performed based on the current measurement parameters to generate the excess sludge discharge volume.

[0031] Through the above technical solution, when performing logical judgment on the measurement parameters, the water inlet parameter, organic matter content parameter, sludge concentration parameter and suspended solid concentration parameter are determined according to the measurement parameters, and then it is judged whether the water inlet parameter meets the preset water inlet parameter range. If the water inlet parameter does not meet the preset water inlet parameter range, an inlet parameter adjustment instruction is generated, and the current water inlet is adjusted according to the water parameter adjustment instruction so that the water inlet parameter meets the preset water inlet parameter range. Until the water inlet parameter meets the preset water inlet parameter range, the organic matter content in the inlet is determined according to the inlet parameter. The method is to detect whether the amount parameter, sludge concentration parameter and suspended solid concentration parameter meet the preset standard parameter range. When at least one of the organic matter content parameter, sludge concentration parameter and suspended solid concentration parameter does not meet the preset standard parameter range, the measurement parameters within the preset period are detected, and the measurement parameters are calculated to generate the residual sludge discharge amount. When the organic matter content parameter, sludge concentration parameter and suspended solid concentration parameter in the influent volume all meet the preset standard parameter range, the residual sludge discharge amount is generated according to the current measurement parameters, thereby achieving the effect of improving the accuracy of the residual sludge discharge amount.

[0032] In another possible implementation, the method further includes:

[0033] Acquire image information, perform target recognition on the image information, determine whether there is a suspicious target person in the image information, and if so, warn the suspicious target person, wherein the preset image information is a protection area of the degradation pool;

[0034] Determine whether the image information of the suspicious target person exists after a preset warning time, wherein the preset warning time is the start time of the warning process. If the suspicious target person exists, generate a warning message and control the alarm device to output an alarm signal in a preset manner;

[0035] The preset mode includes at least one of the following: a sound output mode and a light output mode.

[0036] Through the above technical solution, when monitoring the degradation pool, the image information of the protection area of the degradation pool is first obtained, and then the target recognition is performed on the image information, wherein the target recognition object includes the type of personnel, and the current image information is monitored to see whether there is a suspicious target person. When there is a suspicious target person, a warning process is performed, for example: a warning voice is sent to inform the suspicious target person to stay away from the preset range information. If the suspicious target person is still in the image information after the preset time, an early warning message is generated to inform the maintenance personnel to check, and the alarm device is controlled to alarm at the same time, thereby achieving the effect of improving the protection efficiency of the degradation pool.

[0037] In another possible implementation, the generating of warning information further includes:

[0038] Obtaining real-time location information of the suspicious target person in the image information and monitoring location information of the maintenance personnel;

[0039] Navigation route information is generated based on the monitored location information and the real-time location information.

[0040] Through the above technical solution, after the early warning information is generated, the location information of the suspicious target person and the maintenance personnel is detected, and then a navigation route is generated based on the real-time location information and the monitored location information, so that the maintenance personnel can view the current suspicious target person through the navigation route information.

[0041] In a second aspect, the present application provides an online excess sludge discharge control device, which adopts the following technical solution:

[0042] An online excess sludge discharge control device, comprising:

[0043] A status acquisition module is used to obtain device status information of the online measuring device after detecting an information monitoring instruction;

[0044] A status judgment module, configured to judge whether the online measurement device matches a preset abnormality type according to the device status information;

[0045] an abnormality analysis module, configured to generate a stop discharge instruction when the online measuring device matches a preset abnormality type, analyze the preset abnormality type that matches the online measuring device, determine the abnormal location information and abnormality cause of the online measuring device, and the stop discharge instruction is used to control the discharge device to stop discharging excess sludge;

[0046] A solution determination module is used to perform keyword extraction on the abnormal location information and the abnormal cause to obtain abnormal keyword information, and determine an abnormal solution based on the keyword information;

[0047] The control display module is used to control and display the abnormality solution.

[0048] By adopting the above technical solution, when the discharge of residual sludge is controlled, the status acquisition module obtains the equipment status information of the online measuring device, and then the status judgment module judges whether the online measuring device matches the preset abnormality type based on the equipment status information. When the online measuring device matches the preset abnormality type, it means that there is a fault in the current online measuring device. The abnormality analysis module generates a stop discharge instruction to control the discharge device to stop discharging the residual sludge. At the same time, the preset abnormality type matching the online measuring device is analyzed to determine the abnormal location information and the cause of the abnormality of the online measuring device. Then, the solution determination module extracts keywords from the abnormal location information and the cause of the abnormality respectively to obtain abnormal keyword information, determines the abnormal solution based on the keyword information, and controls the display of the abnormal solution to facilitate maintenance personnel to maintain the online measuring device according to the abnormal solution, thereby achieving the effect of timely troubleshooting and maintenance of the online measuring device.

[0049] In a possible implementation, the anomaly analysis module determines an anomaly solution based on the keyword information, specifically for:

[0050] Inputting the keyword information into a trained text network model for training to obtain text feature vector information of the keyword information;

[0051] Perform data comparison analysis on the text feature vector information to determine an exception solution that matches the text feature vector information.

[0052] In another possible implementation, the device further includes: a sample acquisition module and a model creation module, wherein:

[0053] The sample acquisition module is used to acquire text training samples, wherein the text training samples include device abnormality solution information and keyword information corresponding to each solution in the device abnormality solution information;

[0054] The model creation module is used to create a text network model and train the text network model based on the text training samples to obtain a trained text network model.

[0055] In another possible implementation, the device further includes: a logic judgment module, wherein:

[0056] The logic judgment module is used to obtain the measurement parameters of the measurement device when the online measurement device does not match the preset abnormality type, and perform logic cycle judgment on the measurement parameters to generate the excess sludge discharge amount.

[0057] In another possible implementation, the logic judgment module performs logic period judgment on the measurement parameters to generate the excess sludge discharge amount, specifically for:

[0058] Determining parameter category information based on the measured parameters, the parameter category information including an influent volume parameter, an organic matter content parameter, a sludge concentration parameter, and a suspended solids concentration parameter;

[0059] determining whether the water inlet parameter satisfies a preset water inlet parameter range; if the water inlet parameter does not satisfy the preset water inlet parameter range, generating a water inlet parameter adjustment instruction, and adjusting the current water inlet according to the water inlet parameter adjustment instruction;

[0060] If the water inlet parameter satisfies the preset water inlet parameter range, determining whether the organic matter content parameter, the sludge concentration parameter, and the suspended solids concentration parameter in the water inlet meet the preset standard parameter range based on the water inlet parameter; if at least one of the organic matter content parameter, the sludge concentration parameter, and the suspended solids concentration parameter does not meet the preset standard parameter range, detecting the measurement parameters within a preset period, calculating the measurement parameters, and generating the excess sludge discharge amount;

[0061] If the organic matter content parameter, sludge concentration parameter and suspended solids concentration parameter in the influent volume meet the preset standard parameter range, calculation is performed based on the current measurement parameters to generate the excess sludge discharge volume.

[0062] In another possible implementation, the device further includes: an image acquisition module, an image recognition module, a warning module, and an alarm module, wherein:

[0063] The image acquisition module is used to acquire image information, wherein the preset image information is the protection area of the degradation tank;

[0064] The image recognition module is used to perform target recognition on the image information and determine whether there is a suspicious target person in the image information;

[0065] The warning module is used to warn suspicious persons when there are any in the image information;

[0066] The alarm module is used to determine whether the image information of the suspicious target person exists after a preset warning time, and the preset warning time is the start time of the warning process;

[0067] If it exists, it will generate early warning information and control the alarm device to output the alarm signal in a preset way;

[0068] The preset mode includes at least one of the following: a sound output mode and a light output mode.

[0069] In another possible implementation, the device further includes: a location acquisition module and a route generation module, wherein:

[0070] The position acquisition module is used to obtain the real-time position information of the suspicious target person in the image information and the monitoring position information of the maintenance personnel;

[0071] The route generation module is used to generate navigation route information based on the monitored location information and the real-time location information.

[0072] In a third aspect, the present application provides an electronic device, which adopts the following technical solution:

[0073] An electronic device, comprising:

[0074] at least one processor;

[0075] Memory;

[0076] At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the above-mentioned online excess sludge discharge control method.

[0077] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution:

[0078] A computer-readable storage medium includes: a computer program that can be loaded by a processor and executed by the above-mentioned online excess sludge discharge control method.

[0079] In summary, this application has the following beneficial technical effects:

[0080] 1. When controlling the discharge of excess sludge, the device status information of the online measuring device is obtained, and then it is determined whether the online measuring device matches the preset abnormality type based on the device status information. When the online measuring device matches the preset abnormality type, it means that the current online measuring device has a fault, and a stop discharge instruction is generated to control the discharge device to stop discharging the excess sludge. At the same time, the preset abnormality type matching the online measuring device is analyzed to determine the abnormal location information and abnormality cause of the online measuring device. Keywords are then extracted from the abnormal location information and abnormality cause to obtain abnormal keyword information. The abnormality solution is determined based on the keyword information, and the abnormality solution is controlled and displayed to facilitate maintenance personnel to maintain the online measuring device according to the abnormality solution, thereby achieving the effect of timely troubleshooting and maintenance of the online measuring device.

[0081] 2. When making logical judgments on the measurement parameters, the water volume parameter, organic matter content parameter, sludge concentration parameter and suspended solids concentration parameter are determined according to the measurement parameters, and then it is determined whether the water volume parameter meets the preset water volume parameter range. If the water volume parameter does not meet the preset water volume parameter range, an inlet volume parameter adjustment instruction is generated, and the current water volume is adjusted according to the water volume parameter adjustment instruction so that the water volume parameter meets the preset water volume parameter range. When the water volume parameter meets the preset water volume parameter range, the organic matter content parameter in the water volume is determined according to the inlet volume parameter. , sludge concentration parameters and suspended solids concentration parameters meet the preset standard parameter range. When at least one of the organic matter content parameters, sludge concentration parameters and suspended solids concentration parameters does not meet the preset standard parameter range, the measurement parameters within the preset period are detected, and the measurement parameters are calculated to generate the residual sludge discharge. When the organic matter content parameters, sludge concentration parameters and suspended solids concentration parameters in the influent volume all meet the preset standard parameter range, the residual sludge discharge is generated according to the current measurement parameters, thereby achieving the effect of improving the accuracy of the residual sludge discharge. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] Figure 1 Schematic diagram of the process of the online excess sludge discharge control method according to the embodiment of the present application;

[0083] Figure 2 Schematic diagram of an online excess sludge discharge control device according to an embodiment of the present application;

[0084] Figure 3 It is a schematic diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0085] The following is combined with Figure 1-3 This application is described in further detail.

[0086] After reading this specification, those skilled in the art may make non-creative modifications to this embodiment as needed, but as long as they are within the scope of the claims of this application, they are protected by patent law.

[0087] To make the purpose, technical solutions, and advantages of the embodiments of this application more clear, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0088] In this document, the term "and / or" simply describes a relationship between related objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Furthermore, the character " / " in this document, unless otherwise specified, generally indicates an "or" relationship between the related objects.

[0089] The embodiments of the present application are described in further detail below with reference to the accompanying drawings.

[0090] The embodiment of the present application provides an online excess sludge discharge control method, which is executed by an electronic device, which can be a server or a terminal device, wherein the server can be an independent physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc., but is not limited thereto. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, which is not limited in the embodiment of the present application. Figure 1 As shown, the method includes:

[0091] Step S10: Acquire device status information of the online measurement device.

[0092] For the embodiment of the present application, the online measuring equipment includes an online BOD5 meter, an online sludge concentration meter, an inlet flow meter and a residual sludge pump flow meter. The above-mentioned equipment are respectively installed in the degradation tank to measure the data of the sewage in the degradation tank. When obtaining the equipment status information of the online measuring equipment, the corresponding sensor is installed inside the corresponding online measuring equipment. For example, the turbidity sensor is installed at the detection probe of the online sludge concentration meter. By receiving the detection data of the turbidity sensor and comparing the detection data with the data detected by the online sludge concentration meter, when the data detected by the online sludge concentration meter does not correspond to the detection data, it means that there is an abnormality in the equipment status of the current online sludge concentration meter.

[0093] Step S11: judging whether the online measuring device matches a preset abnormality type according to the device status information.

[0094] For the embodiment of the present application, the preset abnormality types include: detection data abnormality, water intake abnormality, display data abnormality and calculation data abnormality.

[0095] Step S12: If a match is found, a stop discharge instruction is generated, and the preset abnormality type matching the online measuring device is analyzed to determine the abnormal location information and abnormality cause of the online measuring device. The stop discharge instruction is used to control the discharge device to stop discharging excess sludge.

[0096] Specifically, when the preset abnormality type matching the online measuring device is display data abnormality, it means that there is an abnormality in the display screen of the current instrument. Therefore, the abnormal location information of the online measuring device is the display screen. The cause of the abnormality may be failure of the sludge concentration meter transmitter button, black screen of the sludge concentration meter LCD display, incorrect current output value of the sludge concentration meter, and failure of RS485 communication of the sludge concentration meter, etc.

[0097] Step S13: extract keywords from the abnormal location information and the abnormal cause to obtain abnormal keyword information, and determine the abnormal solution based on the keyword information.

[0098] For the embodiment of this application, Python technology is used to implement text keyword extraction. The specific operation process is as follows:

[0099] Load the document dataset, which contains historical abnormal location information and historical abnormal causes. Then load the stop word list, segment the text in the document dataset, filter the interference words according to the stop word list, and then train the algorithm based on the document dataset to obtain a trained algorithm. The trained algorithm extracts keywords from the abnormal location information and abnormal causes to obtain abnormal keywords.

[0100] Step S14, controlling the display of abnormality solutions.

[0101] Specifically, exception solutions are obtained through the control layer (controller), business layer (service) and data access layer (dao). The data access layer is only responsible for data interaction with the database and reading data. The business layer needs to write logic code according to the actual business needs of the system. The business logic layer calls the relevant methods of the data access layer to implement interaction with the database and feeds back the execution results to the control layer. The control layer sends the location information to the view renderer, renders the view of the exception solution, and echoes the exception solution.

[0102] An embodiment of the present application provides an online excess sludge discharge control method. When the excess sludge is discharged, the device status information of the online measuring device is obtained, and then it is determined whether the online measuring device matches the preset abnormality type based on the device status information. When the online measuring device matches the preset abnormality type, it indicates that there is a fault in the current online measuring device, and a stop discharge instruction is generated to control the discharge device to stop discharging the excess sludge. At the same time, the preset abnormality type matching the online measuring device is analyzed to determine the abnormal position information and the cause of the abnormality of the online measuring device. Then, keywords are extracted from the abnormal position information and the cause of the abnormality to obtain abnormal keyword information. The abnormal solution is determined based on the keyword information, and the abnormal solution is controlled and displayed to facilitate maintenance personnel to maintain the online measuring device according to the abnormal solution, thereby achieving the effect of timely troubleshooting and maintenance of the online measuring device.

[0103] In a possible implementation of the embodiment of the present application, step S13 specifically includes step S131 (not shown in the figure) and step S132 (not shown in the figure), wherein:

[0104] Step S131: input the keyword information into the trained text network model for training to obtain text feature vector information of the keyword information.

[0105] In the embodiment of the present application, CNN technology is used for text classification. However, pure CNN will cause convolution and pooling to lose the arrangement relationship of local words in the sentence. Therefore, NLP is added on the basis of CNN technology, that is, CNN IN NLP. The input of the NLP task is a sentence or document represented by a matrix. Each row of the matrix corresponds to a word or character, that is, each row represents a word feature vector information.

[0106] Step S132: performing data comparison analysis on the text feature vector information to determine an exception solution that matches the text feature vector information.

[0107] Specifically, after data analysis of the text features into the information, an exception solution is obtained. For example, if the cause of the exception is the failure of RS485 communication of the sludge concentration meter, then there are three solutions corresponding to the exception cause: A. The cable wiring is incorrect. Please refer to the wiring instruction diagram of the sludge concentration meter for correct wiring; B. The signal transmission distance is too long or the signal transmission cable does not meet the installation requirements. Please shorten the signal transmission distance or select a cable that meets the installation requirements; C. The communication protocol is wrong. Please refer to the instruction manual to set the communication protocol.

[0108] In a possible implementation of the embodiment of the present application, step S131 may further include step SA1 (not shown in the figure) and step SA2 (not shown in the figure), wherein:

[0109] Step SA1: Acquire text training samples, where the text training samples include device abnormality solution information and keyword information corresponding to each solution in the device abnormality solution information.

[0110] Step S1322: Create a text network model, and train the text network model based on the text training samples to obtain a trained text network model.

[0111] Specifically, the text network model is a neural network model. Neural networks (NNs) are complex network systems formed by a large number of extensively interconnected, simple processing units (called neurons). They reflect many fundamental characteristics of human brain function and are highly complex nonlinear dynamic learning systems. Neural networks possess large-scale parallelism, distributed storage and processing, self-organization, self-adaptation, and self-learning capabilities, making them particularly well-suited for handling imprecise and ambiguous information processing problems that require simultaneous consideration of numerous factors and conditions. The development of neural networks is intertwined with neuroscience, mathematical science, cognitive science, computer science, artificial intelligence, information science, cybernetics, robotics, microelectronics, psychology, optical computing, and molecular biology.

[0112] In a possible implementation of the embodiment of the present application, after step S14, the following steps are further included:

[0113] If the online measuring device does not match the preset abnormality type, the measurement parameters of the online measuring device are obtained, and a logical cycle judgment is performed on the measurement parameters to generate the residual sludge discharge amount.

[0114] Specifically, when the online measuring device does not match the preset abnormality type, it indicates that the current online measuring device has not failed. Therefore, the measurement parameters of the online measuring device are obtained, and the measurement parameters are logically judged to finally generate the excess sludge discharge amount.

[0115] A possible implementation of the embodiment of the present application is that step S14 specifically includes determining parameter category information based on the measurement parameters, where the parameter category information includes an inlet water parameter, an organic matter content parameter, a sludge concentration parameter, and a suspended solids concentration parameter, determining whether the inlet water parameter meets a preset inlet water parameter range, if the inlet water parameter does not meet the preset inlet water parameter range, generating an inlet water parameter adjustment instruction, and adjusting the current inlet water according to the water parameter adjustment instruction, if the inlet water parameter meets the preset inlet water parameter range, then determining whether the organic matter content parameter, the sludge concentration parameter, and the suspended solids concentration parameter in the inlet water meet a preset standard parameter range based on the inlet water parameter, if at least one parameter among the organic matter content parameter, the sludge concentration parameter, and the suspended solids concentration parameter does not meet the preset standard parameter range, detecting the measurement parameters within a preset period, and calculating the measurement parameters to generate the excess sludge discharge amount, if the organic matter content parameter, the sludge concentration parameter, and the suspended solids concentration parameter in the inlet water meet the preset standard parameter range, then calculating based on the current measurement parameters to generate the excess sludge discharge amount.

[0116] In a possible implementation of the embodiment of the present application, step S13 further includes step S15 (not shown in the figure) and step S16 (not shown in the figure), wherein:

[0117] Step S15, acquiring image information, and performing target recognition on the image information to determine whether there is a suspicious target person in the image information. If so, a warning is issued to the suspicious target person, and the image information is preset as the protection area of the degradation pool.

[0118] Specifically, when protecting the degradation pool, an electronic fence is used to form a protection area around the degradation pool, and GPS positioning and a camera are installed on the electronic fence. Image information is determined by acquiring images taken by the electronic fence camera.

[0119] Specifically, target detection technology can determine the position of each person target type in the image information, and select each person target type with a bounding box. At this time, the image area within the bounding box is the image area corresponding to the target in the image.

[0120] Specifically, the warning information may be displayed on a display screen or transmitted through sound, and the specific circumstances are not limited.

[0121] Step S16, determine whether there is image information of the suspicious target person after the preset warning time. The preset warning time is the starting time of the warning process. If there is, an early warning message is generated, and the alarm device is controlled to output an alarm signal in a preset manner.

[0122] The preset mode includes at least one of the following: a sound output mode and a light output mode.

[0123] Specifically, assuming that the preset warning time is 3 minutes, the timing starts when a suspicious target person is monitored. For example, a suspicious target person is monitored approaching at 5:20, and the suspicious target person is still in the image information after 5:23.

[0124] Specifically, when a suspicious target person enters a preset range for a period exceeding a preset warning time, the electronic device transmits a control signal to the alarm device to control the alarm device to emit an alarm signal through sound and light output.

[0125] For example, devices that send out alarm signals through sound include buzzers, bells, whistles, and sirens, etc., and devices that send out alarm signals through light output include breathing lights, flashing lights, engineering warning lights, etc.

[0126] In a possible implementation of the embodiment of the present application, step S16 further includes step S161 (not shown in the figure) and step S162 (not shown in the figure), wherein:

[0127] Step S161: Acquire the real-time location information of the suspicious target person in the image information and the monitoring location information of the maintenance personnel.

[0128] Specifically, based on the GPS positioning operation in HTML5, the person is positioned. In HTML5, there is a Geolocation API, which is used to obtain the user's geographic location through GPS, which is commonly known as GPS positioning.

[0129] Step S162: Generate navigation route information based on the monitored location information and the real-time location information.

[0130] Specifically, the GPS navigation system generates navigation routes based on monitored and real-time location information. The GPS navigation system is a radio navigation and positioning system based on 24 global positioning satellites, providing three-dimensional position, three-dimensional velocity, and other information to all locations around the world around the clock. It consists of three components: a ground control component, comprising a master control station, ground antennas, monitoring stations, and auxiliary communication systems; a space component, comprising 24 satellites distributed across six orbital planes; and a user device component, comprising a GPS receiver and satellite antenna. Civilian positioning accuracy can reach within 10 meters.

[0131] The above embodiment introduces an online excess sludge discharge control method from the perspective of method flow, and the following embodiment introduces an online excess sludge discharge control device from the perspective of a virtual module or virtual unit. Please refer to the following embodiment for details.

[0132] The present application embodiment provides an online excess sludge discharge control device, such as Figure 2 As shown, the device 20 may specifically include: a state acquisition module 21, a state judgment module 22, an abnormality analysis module 23, a solution determination module 24 and a control display module 25, wherein:

[0133] A status acquisition module 21 is used to obtain device status information of an online measurement device;

[0134] A status judgment module 22 judges whether the online measurement device matches a preset abnormality type based on the device status information;

[0135] The abnormality analysis module 23 is used to generate a stop discharge instruction when the online measuring device matches a preset abnormality type, analyze the preset abnormality type that matches the online measuring device, determine the abnormal location information and abnormality cause of the online measuring device, and the stop discharge instruction is used to control the discharge device to stop discharging excess sludge;

[0136] Solution determination module 24, configured to extract keywords from the abnormal location information and the abnormal cause to obtain abnormal keyword information, and determine an abnormal solution based on the keyword information;

[0137] The control and display module 25 is used to control and display abnormality solutions.

[0138] In one possible implementation of the embodiment of the present application, the exception analysis module 23 determines an exception solution based on keyword information, specifically for:

[0139] Input the keyword information into the trained text network model for training to obtain the text feature vector information of the keyword information;

[0140] Perform data comparison analysis on the text feature vector information to determine the exception solution that matches the text feature vector information.

[0141] In another possible implementation of the embodiment of the present application, the apparatus 20 further includes: a sample acquisition module and a model creation module, wherein:

[0142] A sample acquisition module is used to acquire text training samples, where the text training samples include device abnormality solution information and keyword information corresponding to each solution in the device abnormality solution information;

[0143] The model creation module is used to create a text network model and train the text network model based on text training samples to obtain a trained text network model.

[0144] In another possible implementation of the embodiment of the present application, the device 20 further includes: a logic judgment module, wherein:

[0145] The logic judgment module is used to obtain the measurement parameters of the measurement equipment when the online measurement equipment does not match the preset abnormality type, and perform logic cycle judgment on the measurement parameters to generate the residual sludge discharge amount.

[0146] In another possible implementation of the embodiment of the present application, the logic judgment module performs logic period judgment on the measurement parameters to generate the excess sludge discharge amount, which is specifically used to:

[0147] Determining parameter category information based on the measured parameters, the parameter category information including an influent volume parameter, an organic matter content parameter, a sludge concentration parameter, and a suspended solids concentration parameter;

[0148] Determine whether the water inlet parameter meets the preset water inlet parameter range. If the water inlet parameter does not meet the preset water inlet parameter range, generate a water inlet parameter adjustment instruction, and adjust the current water inlet according to the water parameter adjustment instruction;

[0149] If the water inlet parameter meets the preset water inlet parameter range, then determine whether the organic matter content parameter, sludge concentration parameter and suspended solids concentration parameter in the water inlet meet the preset standard parameter range based on the water inlet parameter; if at least one of the organic matter content parameter, sludge concentration parameter and suspended solids concentration parameter does not meet the preset standard parameter range, then detect the measurement parameters within the preset period, calculate the measurement parameters, and generate the excess sludge discharge;

[0150] If the organic matter content parameter, sludge concentration parameter and suspended solids concentration parameter in the influent meet the preset standard parameter range, the residual sludge discharge is generated based on the current measurement parameters.

[0151] In another possible implementation of the embodiment of the present application, the device 20 further includes: an image acquisition module and an alarm module, wherein:

[0152] An image acquisition module is used to acquire image information and perform target recognition on the image information to determine whether there is a suspicious target person in the image information. If so, a warning is issued to the suspicious target person, and the image information is preset as the protection area of the degradation pool;

[0153] The alarm module is used to determine whether there is image information of the suspicious target person after the preset warning time. The preset warning time is the starting time of the warning process. If there is, an early warning message is generated and the alarm device is controlled to output an alarm signal in a preset manner;

[0154] The preset mode includes at least one of the following: a sound output mode and a light output mode.

[0155] In another possible implementation of the embodiment of the present application, the device 20 further includes: a location acquisition module and a route generation module, wherein:

[0156] Position acquisition module, used to obtain the real-time position information of suspicious target personnel in the image information and the monitoring position information of maintenance personnel;

[0157] The route generation module is used to generate navigation route information based on the monitored location information and real-time location information.

[0158] In the embodiment of the present application, in addition to the above-mentioned devices, it also includes: an online control device for total nitrogen compliance in sewage treatment, an online sludge return control device, an online nitrification liquid return control device, and an online nutrient element addition system device, wherein,

[0159] The online control device for total nitrogen in sewage reaching the standard includes:

[0160] A data acquisition module is used to obtain the ammonia nitrogen concentration data and nitrate nitrogen concentration data in the biochemical pool in real time;

[0161] A setting module is used to receive the upper and lower concentration thresholds of dissolved oxygen, as well as the standard ranges of ammonia nitrogen concentration and nitrate nitrogen concentration from the user terminal, and to determine in real time whether the ammonia nitrogen concentration and nitrate nitrogen concentration exceed the standard ranges based on the standard ranges of ammonia nitrogen concentration and nitrate nitrogen concentration;

[0162] The upward adjustment module is used to increase the upper and lower concentration thresholds by one unit when the ammonia nitrogen concentration data exceeds the standard, and set the maintenance time;

[0163] The carbon injection control module is used to send a carbon source injection instruction to the carbon source terminal if the nitrate nitrogen concentration data exceeds the standard within the maintenance period. The carbon source terminal is used to inject a fixed amount of carbon source into the biochemical pool upon receiving the carbon source injection instruction.

[0164] Specifically, by adopting the above technical solution, the ammonia nitrogen concentration and nitrate nitrogen concentration in the sewage can be obtained in real time, and the upper and lower concentration thresholds and the standard ranges of ammonia nitrogen and nitrate nitrogen concentrations can be pre-set according to the ammonia nitrogen concentration and nitrate nitrogen concentration. When the ammonia nitrogen concentration exceeds the standard, the system can automatically increase the upper and lower thresholds of dissolved oxygen, so that the content of dissolved oxygen in the water increases, and the increased value is fixed and a maintenance time is set, so that the addition of dissolved oxygen is more stable, and it is not easy to cause a sudden increase in nitrate nitrogen due to excessive addition, and the changes in the concentrations of ammonia nitrogen and nitrate nitrogen in the sewage can be observed during the maintenance time; if the nitrate nitrogen concentration exceeds the standard within the maintenance time, that is, the ammonia nitrogen and nitrate nitrogen concentrations exceed the standard, the system will automatically increase the upper and lower thresholds of dissolved oxygen, so that the content of dissolved oxygen in the water increases, and the increased value is fixed and a maintenance time is set, so that the addition of dissolved oxygen is more stable, and it is not easy to cause a sudden increase in nitrate nitrogen due to excessive addition, and the changes in the concentrations of ammonia nitrogen and nitrate nitrogen in the sewage can be observed during the maintenance time. When the nitrogen content is unbalanced, the carbon source terminal is instructed to add carbon to the biochemical pool to promote the denitrification reaction of nitrate nitrogen, accelerate the denitrification process of nitrate nitrogen, and thus reduce the concentration of nitrate nitrogen. At this time, the concentrations of ammonia nitrogen and nitrate nitrogen in the sewage can be maintained within the standard range, achieving a balance between ammonia nitrogen and nitrate nitrogen in the sewage; the system can automatically adjust the upper and lower thresholds of dissolved oxygen according to the ammonia nitrogen concentration, and automatically control the carbon addition operation according to the nitrate nitrogen concentration, reducing the tedious steps of manual debugging, making it easier for staff to control the ammonia nitrogen and nitrate nitrogen contents in sewage treatment within the standard range, and making it more convenient to control the total nitrogen content in sewage treatment.

[0165] Online sludge return control device, including:

[0166] A data acquisition module is used to obtain in real time the water quality feedback data of the water inlet, the first sludge concentration data of the reaction zone, and the second sludge concentration data of the sedimentation tank;

[0167] A data input module is used to input the real-time acquired water quality feedback data, the first sludge concentration data, and the second sludge concentration data into a standard judgment model, wherein the standard judgment model is preset with a water quality exceeding standard threshold;

[0168] a data comparison module for determining the numerical value of the water quality feedback data and the water quality exceeding standard threshold value, and determining the numerical value of the first sludge concentration data and the second sludge concentration data when the standard judgment model receives the water quality feedback data, the first sludge concentration data, and the second sludge concentration data;

[0169] The interval upward adjustment module is used to increase the flow control interval of the sludge return flow and set the maintenance time when the water quality feedback data is greater than the water quality exceeding the standard threshold or the second sludge concentration data is greater than the first sludge concentration data;

[0170] The interval down-adjustment module is used to down-adjust the flow control interval and set the maintenance time if the second sludge concentration data is less than or equal to the first sludge concentration data and the water quality feedback data is less than the water quality exceeding the standard threshold within the maintenance time.

[0171] Specifically, by adopting the above technical solution, the water quality feedback data of the water inlet, the sludge concentration in the reaction zone and the concentration in the sedimentation tank are obtained in real time. By comparing whether the water quality feedback data of the water inlet is greater than the water quality exceeding standard threshold, it is determined whether the water quality of the water inlet has deteriorated. By comparing the sludge concentrations in the reaction zone and the sedimentation tank, it is determined whether the sludge concentration in the sedimentation tank is too large. When the water quality deteriorates, the flow control interval of the sludge return flow is automatically increased to increase the sludge return flow. The increase in the sludge return flow accelerates the nitrification and denitrification reactions in the reaction zone. When the sludge concentration in the sedimentation tank is too large, increasing the sludge return flow also improves the adsorption of the sludge and increases the utilization rate of the sludge sedimentation function, while making the effluent quality less susceptible to being affected, which can alleviate the deterioration of the water quality in the reaction zone. When the water quality at the inlet end meets the standard again and the sludge concentration in the sedimentation tank is less than or equal to the sludge concentration in the reaction zone, the flow control interval can be automatically adjusted downward, that is, when the water quality meets the standard again and the sludge concentrations in the sedimentation tank and the reaction zone are relatively balanced, the sludge return flow rate is adjusted back to the initial state. Therefore, when the water quality deteriorates or the sludge concentration in the sedimentation tank is too high, the sludge return flow rate can be automatically monitored and adjusted based on the acquired data, so that the sludge treatment is not easily affected, saving time for manual data calculation and labor for manual debugging and monitoring, thereby achieving the purpose of a more time-saving and labor-saving sludge return flow adjustment method.

[0172] Online nitration liquid reflux control device, including:

[0173] A monitoring module for monitoring the concentration of control indicators in the biochemical pool, such as influent total nitrogen, effluent total nitrogen, and sludge return flow, wherein the control indicator concentrations include ammonia nitrogen concentration and / or nitrate concentration;

[0174] a calculation module, configured to calculate, when the control indicator concentration exceeds a concentration threshold, a first nitrification liquid return rate of the biochemical pool based on the influent total nitrogen, the effluent total nitrogen, and the sludge return rate, wherein the concentration threshold includes a concentration threshold of the control indicator concentration, and the first nitrification liquid return rate includes the nitrification liquid return rate actually required by the biochemical pool when the control indicator concentration exceeds the concentration threshold;

[0175] a control module, configured to control the concentration of the control indicator according to the reflux rate of the first nitrification liquid and the concentration threshold;

[0176] A monitoring subsystem for monitoring the monitoring information of a dissolved oxygen concentration monitoring device, an ammonia nitrogen concentration monitoring device, a nitrate concentration monitoring device, and / or a nitrification liquid reflux monitoring device;

[0177] The control subsystem is used to control the nitrification liquid reflux control device to regulate the concentration of the control index in the biochemical pool in cooperation with the dissolved oxygen control system based on the monitoring information.

[0178] Specifically, by adopting the above technical solution, the concentration of the control index, the inlet total nitrogen, the effluent total nitrogen and the sludge return rate in the biochemical pool are monitored. When the control index concentration exceeds the concentration threshold, the first nitrification liquid return rate of the biochemical pool is calculated based on the inlet total nitrogen, the effluent total nitrogen and the sludge return rate. Subsequently, the control index concentration is regulated based on the first nitrification liquid return rate and the concentration threshold. This can improve the current control method for nitrification liquid return based on manual settings, in which the nitrification liquid return rate is generally a constant value of the equipment and cannot be automatically adjusted when the water quality or indicator status changes. In addition, the problem of poor treatment effect or high energy consumption due to insufficient or excessive return rate cannot be achieved, and the precise control of the total nitrogen reduction of the system can be achieved. The nitrification liquid return rate can be automatically controlled, and energy consumption can be reduced under the premise of better effect, thereby improving the precision of total nitrogen reduction.

[0179] Online nutrient element dosing system, including:

[0180] A monitoring module, for monitoring the influent concentration of elements to be added to the biochemical pool, wherein the elements to be added include phosphorus, nitrogen and / or carbon;

[0181] An acquisition module, configured to acquire water quality data in the biochemical pool within a preset period when the influent concentration is lower than a concentration threshold of the element to be added;

[0182] A first calculation module is used to calculate the addition concentration of the element to be added according to the concentration threshold and the influent concentration;

[0183] The second calculation module is used to calculate the dosage of the agent to be added according to the agent information, the dosage concentration and the water quality data, so as to achieve the addition of the element to be added;

[0184] A monitoring subsystem for monitoring monitoring information of a biochemical oxygen demand monitoring device, a chemical oxygen demand monitoring device, a sludge concentration monitoring device and / or a water quality analysis device;

[0185] The control subsystem is used to control the nutrient element dosing device to add the agent according to the monitoring information.

[0186] Specifically, by adopting the above technical solution, the influent concentration of the element to be added in the biochemical pool is monitored; when the influent concentration is lower than the concentration threshold of the element to be added, the water quality data in the biochemical pool within a preset period is obtained; then, based on the concentration threshold and the influent concentration, the addition concentration of the element to be added is calculated; then, based on the added agent information, the addition concentration and the water quality data, the agent dosage of the element to be added is calculated, and the addition of the element to be added is realized. This can improve the problem of poor accuracy in controlling the dosage of the agent in the measures based on manually setting the timed discharge of the agent containing nutrient elements. When the water quality or indicator status changes, it can adaptively adjust, calculate and predict the amount of agent required by the system, and add it in a timely and accurate manner, thereby achieving the effect of improving the accuracy of controlling the dosage of the agent, and saving energy consumption and operating costs. For the embodiment of the present application, the added agent information includes the type of agent, dry matter content and / or dissolved concentration of the added agent.

[0187] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0188] The embodiment of the present application also introduces an electronic device from the perspective of a physical device, such as Figure 3 As shown, Figure 3 The electronic device 300 shown includes a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, for example, via a bus 302. Optionally, the electronic device 300 may further include a transceiver 304. It should be noted that in actual applications, the number of transceivers 304 is not limited to one, and the structure of the electronic device 300 does not constitute a limitation on the embodiments of the present application.

[0189] Processor 301 can be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic device, transistor logic device, hardware component, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 301 can also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0190] Bus 302 may include a path for transmitting information between the above components. Bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. Bus 302 may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, Figure 3 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0191] The memory 303 may be a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory) or other type of dynamic storage device that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0192] The memory 303 is used to store application code for executing the solution of the present application, and the execution is controlled by the processor 301. The processor 301 is used to execute the application code stored in the memory 303 to implement the content shown in the above method embodiment.

[0193] Electronic devices include, but are not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. They may also include servers, etc. Figure 3 The electronic device shown is merely an example and should not limit the functions and scope of use of the embodiments of the present application.

[0194] It should be understood that although the steps in the flowcharts of the accompanying drawings are shown in sequence as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some of the steps in the flowcharts of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0195] The above are only some of the implementation methods of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. An online excess sludge discharge control method, characterized in that: include Obtain device status information of online measurement equipment; Determining whether the online measurement device matches a preset abnormality type according to the device status information; If a match is found, a stop discharge instruction is generated, and the preset abnormality type matching the online measuring device is analyzed to determine the abnormal location information and abnormality cause of the online measuring device. The stop discharge instruction is used to control the discharge device to stop discharging excess sludge; Perform keyword extraction on the abnormal location information and the abnormal cause to obtain abnormal keyword information, and determine an abnormal solution based on the keyword information; Controlling display of the abnormality solution; If the online measuring device does not match the preset abnormality type, obtaining the measurement parameters of the online measuring device, performing a logic cycle judgment on the measurement parameters, and generating the excess sludge discharge amount; The step of performing logical periodic judgment on the measurement parameters to generate the amount of excess sludge discharged includes: Determining parameter category information based on the measured parameters, the parameter category information including an influent volume parameter, an organic matter content parameter, a sludge concentration parameter, and a suspended solids concentration parameter; determining whether the water inlet parameter satisfies a preset water inlet parameter range; if the water inlet parameter does not satisfy the preset water inlet parameter range, generating a water inlet parameter adjustment instruction, and adjusting the current water inlet according to the water inlet parameter adjustment instruction; If the water inlet parameter satisfies the preset water inlet parameter range, determining whether the organic matter content parameter, the sludge concentration parameter, and the suspended solids concentration parameter in the water inlet meet the preset standard parameter range based on the water inlet parameter; if at least one of the organic matter content parameter, the sludge concentration parameter, and the suspended solids concentration parameter does not meet the preset standard parameter range, detecting the measurement parameters within a preset period, calculating the measurement parameters, and generating the excess sludge discharge amount; If the organic matter content parameter, sludge concentration parameter and suspended solids concentration parameter in the influent volume meet the preset standard parameter range, calculation is performed based on the current measurement parameters to generate the excess sludge discharge volume.

2. The method according to claim 1, characterized in that The determining of an exception solution based on the keyword information includes: Inputting the keyword information into a text network model to obtain text feature vector information of the keyword information; Perform data comparison analysis on the text feature vector information to determine an exception solution that matches the text feature vector information.

3. The method according to claim 2, characterized in that The step of inputting the keyword information into a text network model to obtain text feature vector information of the keyword information further includes: Acquire a text training sample, wherein the text training sample includes device abnormality solution information and keyword information corresponding to each solution in the device abnormality solution information; A text network model is created, and the text network model is trained based on the text training samples to obtain a trained text network model.

4. The method according to claim 1, wherein The method further comprises: Acquire image information, perform target recognition on the image information, determine whether there is a suspicious target person in the image information, and if so, warn the suspicious target person, wherein the image information is a protection area of the degradation pool; Determine whether the image information of the suspicious target person exists after a preset warning time, wherein the preset warning time is the start time of the warning process. If the suspicious target person exists, generate a warning message and control the alarm device to output an alarm signal in a preset manner; The preset mode includes at least one of the following: a sound output mode and a light output mode.

5. The method according to claim 4, characterized in that The generating of warning information further includes: Obtaining real-time location information of the suspicious target person in the image information and monitoring location information of the maintenance personnel; Navigation route information is generated based on the monitored location information and the real-time location information.

6. An online excess sludge discharge control device, characterized in that: include: A status acquisition module is used to obtain device status information of online measurement devices; A status judgment module, configured to judge whether the online measurement device matches a preset abnormality type according to the device status information; an abnormality analysis module, configured to generate a stop discharge instruction when the online measuring device matches a preset abnormality type, analyze the preset abnormality type that matches the online measuring device, determine the abnormal location information and abnormality cause of the online measuring device, and the stop discharge instruction is used to control the discharge device to stop discharging excess sludge; A solution determination module is used to perform keyword extraction on the abnormal location information and the abnormal cause to obtain abnormal keyword information, and determine an abnormal solution based on the keyword information; A control display module, configured to control and display the abnormality solution; a logic judgment module, configured to obtain measurement parameters of the measurement device when the online measurement device does not match a preset abnormality type, and perform logic period judgment on the measurement parameters to generate excess sludge discharge; The logic judgment module performs logic period judgment on the measurement parameters to generate the excess sludge discharge amount, which is specifically used to: Determining parameter category information based on the measured parameters, the parameter category information including an influent volume parameter, an organic matter content parameter, a sludge concentration parameter, and a suspended solids concentration parameter; determining whether the water inlet parameter satisfies a preset water inlet parameter range; if the water inlet parameter does not satisfy the preset water inlet parameter range, generating a water inlet parameter adjustment instruction, and adjusting the current water inlet according to the water inlet parameter adjustment instruction; If the water inlet parameter satisfies the preset water inlet parameter range, determining whether the organic matter content parameter, the sludge concentration parameter, and the suspended solids concentration parameter in the water inlet meet the preset standard parameter range based on the water inlet parameter; if at least one of the organic matter content parameter, the sludge concentration parameter, and the suspended solids concentration parameter does not meet the preset standard parameter range, detecting the measurement parameters within a preset period, calculating the measurement parameters, and generating the excess sludge discharge amount; If the organic matter content parameter, sludge concentration parameter and suspended solids concentration parameter in the influent volume meet the preset standard parameter range, calculation is performed based on the current measurement parameters to generate the excess sludge discharge volume.

7. An electronic device, characterized in that: The electronic device includes: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the online excess sludge discharge control method according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed in a computer, the computer is caused to execute the online excess sludge discharge control method according to any one of claims 1 to 5.

Images