A sewage system dosing device for VFAs prepared from food waste

Abstract

The present application relates to the field of intelligent kitchen waste preparation, and specifically to a sewage system dosing device for VFAs used in kitchen waste preparation. It obtains the time series of the instantaneous flow of sewage, and calculates the difference between the instantaneous flow of sewage at each two adjacent time points in the time series of the instantaneous flow of sewage to obtain the time series of the instantaneous flow of sewage fluctuation, and uses artificial intelligence-based data analysis and processing algorithms to perform time series feature correlation encoding on the instantaneous flow of sewage and the instantaneous flow fluctuation of sewage, so as to intelligently obtain the recommended value of the dosing pump frequency based on the multi-dimensional time series correlation characteristics of the dynamic interaction synthesis of the instantaneous flow of sewage and the instantaneous flow fluctuation of sewage in the time series, and generate a dosing pump frequency adjustment instruction based on the current dosing pump frequency value. In this way, the frequency of the dosing pump can be more accurately adjusted dynamically according to the real-time changes in the sewage flow, thereby adaptively controlling the flow of the dosing pump.

Description

Technical Field

[0001] The present application relates to the field of intelligent food waste preparation, and specifically to a sewage system dosing device for VFAs used in food waste preparation. Background Art

[0002] At present, the treatment of food waste has become an important part of urban environmental governance. Among them, the use of food waste to prepare volatile fatty acids (VFAs) as an external carbon source for use in sewage treatment systems is a technology with broad application prospects.

[0003] However, in practical applications, most existing reagent dosing devices use manual or simple automatic control systems. That is, operators are required to continuously monitor and adjust the dosage of the reagent, which is not only inefficient but also susceptible to human error. In addition, some automatic control systems may only operate based on preset parameters or simple feedback mechanisms, lacking the ability to respond to sewage flow conditions in real time, making it impossible to achieve accurate quantitative dosing, resulting in unstable dosing effects.

[0004] Therefore, an optimized sewage system dosing device for VFAs prepared from food waste is desired. Summary of the invention

[0005] This application is made in view of the above problems. One object of this application is to provide a sewage system dosing device for VFAs prepared from food waste.

[0006] The embodiment of the present application provides a sewage system dosing device for VFAs prepared from food waste, comprising:

[0007] Sewage instantaneous flow time series acquisition module, used to obtain the time series of sewage instantaneous flow;

[0008] A sewage instantaneous flow fluctuation calculation module, used to calculate the difference of sewage instantaneous flow based on the time series of sewage instantaneous flow to obtain the time series of sewage instantaneous flow fluctuation;

[0009] A sewage flow time series correlation feature extraction module is used to input the time series of the sewage instantaneous flow and the time series of the sewage instantaneous flow fluctuation into a sequence encoder to obtain a sewage instantaneous flow time series correlation feature vector and a sewage instantaneous flow fluctuation time series correlation feature vector;

[0010] A sewage instantaneous flow multi-dimensional time series interaction module is used to perform feature vector dynamic interaction processing based on a gating mechanism on the sewage instantaneous flow time series correlation feature vector and the sewage instantaneous flow fluctuation time series correlation feature vector to obtain the sewage instantaneous flow multi-dimensional time series correlation feature vector as the sewage instantaneous flow multi-dimensional time series correlation feature;

[0011] A dosing pump frequency recommendation module, used to obtain a dosing pump frequency recommendation value based on the multi-dimensional time series correlation characteristics of the sewage instantaneous flow rate;

[0012] The dosing pump frequency adjustment instruction generating module is used to generate a dosing pump frequency adjustment instruction based on the dosing pump frequency recommendation value and the current dosing pump frequency value.

[0013] For example, according to the sewage system dosing device for VFAs prepared from kitchen waste according to an embodiment of the present application, the sewage instantaneous flow fluctuation calculation module is used to:

[0014] The difference between the instantaneous sewage flow rates at every two adjacent time points in the time series of the instantaneous sewage flow rate is calculated to obtain the time series of the instantaneous sewage flow rate fluctuation.

[0015] For example, according to the sewage system dosing device for VFAs prepared from kitchen waste according to an embodiment of the present application, the sewage flow time series correlation feature extraction module is used to:

[0016] The time series of the instantaneous sewage flow and the time series of the instantaneous sewage flow fluctuation are respectively input into the sequence encoder based on the Bi-LSTM model to obtain the sewage instantaneous flow time series correlation feature vector and the sewage instantaneous flow fluctuation time series correlation feature vector.

[0017] For example, according to the sewage system dosing device for VFAs prepared from kitchen waste according to an embodiment of the present application, the sewage instantaneous flow multi-dimensional time series interaction module is used to:

[0018] The sewage instantaneous flow time series correlation feature vector and the sewage instantaneous flow fluctuation time series correlation feature vector are input into the feature vector dynamic interaction synthesis module under the gating mechanism to obtain the sewage instantaneous flow multi-dimensional time series correlation feature vector.

[0019] For example, according to the sewage system dosing device for VFAs prepared from kitchen waste according to an embodiment of the present application, the sewage instantaneous flow multi-dimensional time series interaction module includes:

[0020] A cascade unit, used for inputting the sewage instantaneous flow time series associated feature vector and the sewage instantaneous flow fluctuation time series associated feature vector into a feature combination module for cascade processing to obtain a sewage instantaneous flow-sewage instantaneous flow fluctuation time series joint feature vector;

[0021] A sewage instantaneous flow-sewage instantaneous flow fluctuation time series gated response value calculation unit, used for inputting the sewage instantaneous flow-sewage instantaneous flow fluctuation time series joint feature vector into a gated response function to obtain a sewage instantaneous flow-sewage instantaneous flow fluctuation time series information fusion response gated value;

[0022] The sewage instantaneous flow-sewage instantaneous flow fluctuation time series multi-dimensional fusion unit is used to calculate the position-weighted sum of the sewage instantaneous flow time series associated feature vector and the sewage instantaneous flow fluctuation time series associated feature vector using the sewage instantaneous flow-sewage instantaneous flow fluctuation time series information fusion response gate value as a weight to obtain the sewage instantaneous flow multi-dimensional time series associated feature vector.

[0023] For example, according to the sewage system dosing device for VFAs prepared from kitchen waste according to an embodiment of the present application, the sewage instantaneous flow-sewage instantaneous flow fluctuation timing gated response value calculation unit includes:

[0024] A multiplication and addition subunit is used to calculate the matrix product of the sewage instantaneous flow-sewage instantaneous flow fluctuation time series joint characteristic vector and the parameter matrix, and then add the obtained characteristic vector and the bias vector according to the position to obtain the sewage instantaneous flow-sewage instantaneous flow fluctuation time series joint bias characteristic vector;

[0025] The activation subunit is used to input the sewage instantaneous flow-sewage instantaneous flow fluctuation time series joint bias feature vector into the sigmoid activation function to obtain the sewage instantaneous flow-sewage instantaneous flow fluctuation time series information fusion response gating value.

[0026] For example, according to the sewage system dosing device for VFAs prepared from kitchen waste in an embodiment of the present application, the sewage instantaneous flow-sewage instantaneous flow fluctuation time series multi-dimensional fusion unit includes:

[0027] The first position-based product subunit is used to calculate the position-based product between the sewage instantaneous flow time series associated characteristic vector and the sewage instantaneous flow-sewage instantaneous flow fluctuation time series information fusion response gating value to obtain the sewage instantaneous flow time series associated gating adjustment vector;

[0028] The second position-based product subunit is used to calculate the position-based product between the sewage instantaneous flow fluctuation time series associated characteristic vector and one minus the sewage instantaneous flow - sewage instantaneous flow fluctuation time series information fusion response gating value to obtain the sewage instantaneous flow fluctuation time series associated gating adjustment vector;

[0029] The position adding subunit is used to add the sewage instantaneous flow time series associated gated adjustment vector and the sewage instantaneous flow fluctuation time series associated gated adjustment vector according to the position to obtain the sewage instantaneous flow multi-dimensional time series associated feature vector.

[0030] For example, according to the sewage system dosing device for VFAs prepared from kitchen waste according to an embodiment of the present application, the dosing pump frequency recommendation module is used to:

[0031] The multi-dimensional time series correlation feature vector of the sewage instantaneous flow rate is input into a dosing pump frequency recommender based on a decoder to obtain the dosing pump frequency recommendation value.

[0032] For example, according to the sewage system dosing device for VFAs prepared from kitchen waste according to an embodiment of the present application, the dosing pump frequency adjustment instruction generation module is used to:

[0033] The dosing pump frequency adjustment instruction is generated based on the difference between the recommended dosing pump frequency value and the current dosing pump frequency value.

[0034] According to the sewage system dosing device for VFAs for food waste preparation according to the embodiment of the present application, it can more accurately dynamically adjust the frequency of the dosing pump according to the real-time changes in the sewage flow, thereby adaptively controlling the flow of the dosing pump. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings of the embodiments of the present application are briefly introduced below. Obviously, the drawings described below only relate to some embodiments of the present application, and are not intended to limit the present application.

[0036] Figure 1 A schematic diagram of the application architecture of a sewage system dosing device for VFAs prepared from kitchen waste in an embodiment of the present application is shown;

[0037] Figure 2 The schematic diagram of the structure of the sewage system dosing device for VFAs prepared from kitchen waste in the embodiment of the present application is shown;

[0038] Figure 3 A schematic diagram of the structure of a sewage instantaneous flow multi-dimensional time series interaction module of a sewage system dosing device for VFAs prepared from kitchen waste in an embodiment of the present application is shown;

[0039] Figure 4 A flow chart showing a method for adding VFAs to a sewage system for preparing food waste in an embodiment of the present application; and

[0040] Figure 5 A dosing PID diagram of a sewage system dosing device for VFAs prepared from food waste in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0041] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, not all embodiments. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work also fall within the scope of protection of the present application.

[0042] The terms used in this specification are those common terms currently widely used in the art in consideration of the functions of the present application, but these terms may vary according to the intentions of those skilled in the art, precedents, or new technologies in the art. In addition, specific terms may be selected, and in this case, their detailed meanings will be described in the detailed description of the present application. Therefore, the terms used in the specification should not be understood as simple names, but rather as a general description based on the meaning of the terms and the present application.

[0043] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, any number of different modules can be used and run on the user terminal and / or server. The modules are only illustrative, and different aspects of the system and method can use different modules.

[0044] Flowcharts are used in the present application to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed accurately in order. On the contrary, various steps may be processed in reverse order or simultaneously as required. At the same time, other operations may also be added to these processes, or a certain step or several steps of operations may be removed from these processes.

[0045] Figure 1 A schematic diagram of the application architecture of a sewage system dosing device for VFAs prepared from kitchen waste in an embodiment of the present application is shown, including a server 100 and a terminal device 200.

[0046] The terminal device 200 and the server 100 can be connected via the Internet to achieve mutual communication. Optionally, the above-mentioned Internet uses standard communication technology and / or protocol. The Internet is usually the Internet, but it can also be any network, including but not limited to any combination of a local area network (LAN), a metropolitan area network (MAN), a wide area network (WAN), a mobile, wired or wireless network, a dedicated network or a virtual private network. In some embodiments, the data exchanged through the network is represented by technologies and / or formats including Hyper Text Markup Language (HTML), Extensible Markup Language (XML), etc. In addition, conventional encryption technologies such as Secure Socket Layer (SSL), Transport Layer Security (TLS), Virtual Private Network (VPN), Internet Protocol Security (IPsec) can also be used to encrypt all or some links. In other embodiments, customized and / or dedicated data communication technologies can also be used to replace or supplement the above-mentioned data communication technologies.

[0047] The server 100 can provide various network services for the terminal device 200, wherein the server 100 can be a single server, a server cluster consisting of several servers, or a cloud computing center. Specifically, the server 100 may include a processor 110 (Center Processing Unit, CPU), a memory 120, an input device 130, and an output device 140, etc. The input device 130 may include a keyboard, a mouse, a touch screen, etc., and the output device 140 may include a display device, such as a liquid crystal display (Liquid Crystal Display, LCD), a cathode ray tube (Cathode Ray Tube, CRT), etc.

[0048] The memory 120 may include a read-only memory (ROM) and a random access memory (RAM), and provides the processor 110 with program instructions and data stored in the memory 120. In an embodiment of the present application, the memory 120 may be used to store the method corresponding to the sewage system dosing device for VFAs prepared from food waste in an embodiment of the present application.

[0049] The processor 110 calls the program instructions stored in the memory 120, and the processor 110 is used to execute the steps of any one of the sewage system dosing methods for preparing VFAs from kitchen waste in the embodiments of the present application according to the obtained program instructions.

[0050] In addition, the application architecture diagram in the embodiment of the present application is intended to more clearly illustrate the technical solution in the embodiment of the present application, and does not constitute a limitation on the technical solution provided in the embodiment of the present application. Of course, for other application architectures and business applications, the technical solution provided in the embodiment of the present application is also applicable to similar problems.

[0051] The following is a non-restrictive description of the sewage system dosing device for VFAs for food waste preparation provided in accordance with at least one embodiment of the present application through several examples or embodiments. As described below, different features in these specific examples or embodiments can be combined with each other without conflicting with each other to obtain new examples or embodiments, and these new examples or embodiments also fall within the scope of protection of the present application.

[0052] In response to the above technical problems, the technical concept of the present application is to obtain the time series of the instantaneous flow of sewage, and calculate the difference between the instantaneous flow of sewage at each two adjacent time points in the time series of the instantaneous flow of sewage to obtain the time series of the instantaneous flow of sewage fluctuation, and use artificial intelligence-based data analysis and processing algorithms to perform time series feature association encoding on the instantaneous flow of sewage and the instantaneous flow fluctuation of sewage, so as to intelligently obtain the recommended value of the dosing pump frequency based on the multi-dimensional time series association characteristics of the dynamic interaction synthesis of the instantaneous flow of sewage and the instantaneous flow fluctuation of sewage in the time series, and generate the dosing pump frequency adjustment instruction based on the current dosing pump frequency value. In this way, by real-time monitoring and analysis of the instantaneous flow of sewage and its fluctuation state, the system can more accurately dynamically adjust the frequency of the dosing pump according to the real-time changes of the sewage flow, thereby adaptively controlling the flow of the dosing pump. In this way, the need for human intervention is reduced, and the automation level of the sewage system dosing device is improved to ensure the efficiency and effect of the sewage treatment process.

[0053] Figure 2The schematic diagram of the structure of the sewage system dosing device 800 for VFAs prepared from kitchen waste in an embodiment of the present application is shown. The sewage system dosing device 800 for VFAs prepared from kitchen waste includes: a sewage instantaneous flow time series acquisition module 810, which is used to obtain the time series of sewage instantaneous flow; a sewage instantaneous flow fluctuation calculation module 820, which is used to calculate the difference of sewage instantaneous flow based on the time series of sewage instantaneous flow to obtain the time series of sewage instantaneous flow fluctuation; a sewage flow time series correlation feature extraction module 830, which is used to input the time series of sewage instantaneous flow and the time series of sewage instantaneous flow fluctuation into a sequence encoder respectively to obtain a sewage instantaneous flow time series correlation feature vector and a sewage instantaneous flow fluctuation time series correlation feature vector. quantity; a sewage instantaneous flow multi-dimensional time series interaction module 840, which is used to perform feature vector dynamic interaction processing based on a gating mechanism on the sewage instantaneous flow time series correlation feature vector and the sewage instantaneous flow fluctuation time series correlation feature vector to obtain the sewage instantaneous flow multi-dimensional time series correlation feature vector as the sewage instantaneous flow multi-dimensional time series correlation feature; a dosing pump frequency recommendation module 850, which is used to obtain a dosing pump frequency recommendation value based on the sewage instantaneous flow multi-dimensional time series correlation feature; a dosing pump frequency adjustment instruction generation module 860, which is used to generate a dosing pump frequency adjustment instruction based on the dosing pump frequency recommendation value and the current dosing pump frequency value.

[0054] Specifically, in the technical solution of the present application, first, the time series of the instantaneous flow of sewage is obtained. Next, considering that the instantaneous flow of sewage changes with the passage of time, that is, the instantaneous flow of sewage between different time points has different change rates and amplitudes. Based on this, in order to more carefully understand and analyze the change amplitude and trend of the instantaneous flow of sewage between different time points, in the technical solution of the present application, the difference between the instantaneous flow of sewage at each two adjacent time points in the time series of the instantaneous flow of sewage is calculated to obtain the time series of the fluctuation of the instantaneous flow of sewage. In this way, the fluctuation frequency characteristics of the instantaneous flow of sewage can be highlighted, such as whether the flow is gradually increasing or decreasing, so as to better capture the changing trend and fluctuation of the instantaneous flow of sewage over time.

[0055] Correspondingly, the sewage instantaneous flow rate fluctuation calculation module 820 is used to calculate the difference between the sewage instantaneous flow rates at every two adjacent time points in the time series of the sewage instantaneous flow rate to obtain the time series of the sewage instantaneous flow rate fluctuation.

[0056] Next, in order to capture the temporal correlation and mutual dependence between sewage flows at different time scales in the time series of the instantaneous sewage flow and the time series of the instantaneous sewage flow fluctuation, in the technical solution of the present application, the time series of the instantaneous sewage flow and the time series of the instantaneous sewage flow fluctuation are respectively input into a sequence encoder based on the Bi-LSTM model to obtain the sewage instantaneous flow temporal correlation feature vector and the sewage instantaneous flow fluctuation temporal correlation feature vector, so as to capture the temporal correlation and dynamic characteristics of each time in the data.

[0057] Correspondingly, the sewage flow time series correlation feature extraction module 830 is used to: input the time series of the sewage instantaneous flow and the time series of the sewage instantaneous flow fluctuation into the sequence encoder based on the Bi-LSTM model respectively to obtain the sewage instantaneous flow time series correlation feature vector and the sewage instantaneous flow fluctuation time series correlation feature vector.

[0058] Furthermore, considering that the sewage instantaneous flow time series correlation feature vector captures the pattern and trend of the instantaneous flow of sewage over time, including the peak value, valley value and stable period of the flow, it mainly contains information about the periodicity of the instantaneous flow of sewage, such as hourly changes or flow changes caused by specific events. The sewage instantaneous flow fluctuation time series correlation feature vector focuses on the temporal dynamic characteristics of flow changes, that is, the volatility or irregularity of flow, and mainly includes short-term changes in the instantaneous flow of sewage, such as fluctuation amplitude, frequency and suddenness of fluctuation. Furthermore, in order to be able to more comprehensively describe the dynamic characteristics and potential operating modes of sewage flow, so as to further enhance the model's understanding of sewage flow data, thereby providing more accurate and in-depth decision support for the intelligent control system. In the technical solution of the present application, the sewage instantaneous flow time series correlation feature vector and the sewage instantaneous flow fluctuation time series correlation feature vector are input into the feature vector dynamic interaction synthesis module under the gating mechanism to obtain the multi-dimensional time series correlation feature vector of sewage instantaneous flow. It should be understood that the instantaneous sewage flow time series correlation characteristics and the instantaneous sewage flow fluctuation time series correlation characteristics may have different importance on different time scales, and the interaction between the two in time series has different contributions to the frequency adjustment of the dosing pump. The dynamic interaction synthesis module of the feature vector under the gating mechanism enhances the expression ability of the instantaneous sewage flow characteristics by calculating the position-by-position interaction between the instantaneous sewage flow time series correlation feature vector and the instantaneous sewage flow fluctuation time series correlation feature vector, so that the model can capture the more subtle and critical time series correlation between the flow and flow fluctuation. Then the gating mechanism is used to learn which flow time series information is important and which can be ignored at different time points, so as to dynamically improve the sensitivity of the model to key information, adapt to the dynamic changes of time series data, and obtain a more characteristically expressive multi-dimensional time series correlation feature vector of the instantaneous sewage flow.

[0059] Correspondingly, the sewage instantaneous flow multi-dimensional time series interaction module 840 is used to: input the sewage instantaneous flow time series correlation feature vector and the sewage instantaneous flow fluctuation time series correlation feature vector into the feature vector dynamic interaction synthesis module under the gating mechanism to obtain the sewage instantaneous flow multi-dimensional time series correlation feature vector.

[0060] like Figure 3 As shown, specifically, the sewage instantaneous flow multi-dimensional time series interaction module 840 includes: a cascade unit 841, which is used to input the sewage instantaneous flow time series associated feature vector and the sewage instantaneous flow fluctuation time series associated feature vector into the feature combination module for cascade processing to obtain the sewage instantaneous flow-sewage instantaneous flow fluctuation time series joint feature vector; a sewage instantaneous flow-sewage instantaneous flow fluctuation time series gating response value calculation unit 842, which is used to input the sewage instantaneous flow-sewage instantaneous flow fluctuation time series joint feature vector into the gating response function to obtain the sewage instantaneous flow-sewage instantaneous flow fluctuation time series information fusion response gating value; a sewage instantaneous flow-sewage instantaneous flow fluctuation time series multi-dimensional fusion unit 843, which is used to calculate the position-weighted sum of the sewage instantaneous flow time series associated feature vector and the sewage instantaneous flow fluctuation time series associated feature vector using the sewage instantaneous flow-sewage instantaneous flow fluctuation time series information fusion response gating value as a weight to obtain the sewage instantaneous flow multi-dimensional time series associated feature vector.

[0061] Among them, the sewage instantaneous flow-sewage instantaneous flow fluctuation timing gated response value calculation unit 842 includes: a multiplication and addition subunit, which is used to calculate the matrix product of the sewage instantaneous flow-sewage instantaneous flow fluctuation timing joint feature vector and the parameter matrix, and then add the obtained feature vector and the bias vector by position to obtain the sewage instantaneous flow-sewage instantaneous flow fluctuation timing joint bias feature vector; an activation subunit, which is used to input the sewage instantaneous flow-sewage instantaneous flow fluctuation timing joint bias feature vector into the sigmoid activation function to obtain the sewage instantaneous flow-sewage instantaneous flow fluctuation timing series information fusion response gating value.

[0062] Among them, the sewage instantaneous flow-sewage instantaneous flow fluctuation timing multi-dimensional fusion unit 843 includes: a first positional product sub-unit, used to calculate the positional product between the sewage instantaneous flow timing association characteristic vector and the sewage instantaneous flow-sewage instantaneous flow fluctuation timing information fusion response gating value to obtain the sewage instantaneous flow timing association gating adjustment vector; a second positional product sub-unit, used to calculate the positional product between the sewage instantaneous flow fluctuation timing association characteristic vector and one minus the sewage instantaneous flow-sewage instantaneous flow fluctuation timing information fusion response gating value to obtain the sewage instantaneous flow fluctuation timing association gating adjustment vector; a positional addition sub-unit, used to add the sewage instantaneous flow timing association gating adjustment vector and the sewage instantaneous flow fluctuation timing association gating adjustment vector by position to obtain the sewage instantaneous flow multi-dimensional timing series association characteristic vector.

[0063] In a specific example, the sewage instantaneous flow multi-dimensional time series interaction module 840 is used to: input the sewage instantaneous flow time series correlation feature vector and the sewage instantaneous flow fluctuation time series correlation feature vector into the feature vector dynamic interaction synthesis module under the gating mechanism, and process them with the following dynamic interaction synthesis formula to obtain the sewage instantaneous flow multi-dimensional time series correlation feature vector; wherein the dynamic interaction synthesis formula is:

[0064] r = sigmoid(W[v1,v2]+b)

[0065] v c =v1*r+v2*(1-r)

[0066] Wherein, v1 and v2 are the sewage instantaneous flow time series correlation feature vector and the sewage instantaneous flow fluctuation time series correlation feature vector respectively, [·,·] is the cascade processing, W is the parameter matrix, b is the bias vector, sigmoid(·) is the sigmoid function, r is the sewage instantaneous flow-sewage instantaneous flow fluctuation time series information fusion response gate value, v c It is the multi-dimensional time series correlation feature vector of the instantaneous sewage flow.

[0067] Then, the multi-dimensional time series correlation feature vector of the instantaneous sewage flow is input into the decoder-based dosing pump frequency recommender to obtain the dosing pump frequency recommendation value, and based on the difference between the dosing pump frequency recommendation value and the current dosing pump frequency value, the dosing pump frequency adjustment instruction is generated. That is, the multi-dimensional time series correlation feature of the instantaneous sewage flow obtained by the dynamic interaction of the instantaneous sewage flow time series correlation feature vector and the instantaneous sewage flow fluctuation time series correlation feature vector is decoded and processed to intelligently obtain the dosing pump frequency recommendation value, and generate the dosing pump frequency adjustment instruction based on the current dosing pump frequency value. In this way, by real-time monitoring and analysis of the instantaneous sewage flow and its fluctuation state, the system can more accurately dynamically adjust the frequency of the dosing pump according to the real-time changes in the sewage flow, reducing the need for human intervention to ensure the efficiency and effect of the sewage treatment process, thereby improving the automation level of the operation and the overall treatment efficiency.

[0068] Accordingly, the dosing pump frequency recommendation module 850 is used to: input the multi-dimensional time series correlation feature vector of the sewage instantaneous flow into the decoder-based dosing pump frequency recommender to obtain the dosing pump frequency recommendation value. The dosing pump frequency adjustment instruction generation module 860 is used to: generate the dosing pump frequency adjustment instruction based on the difference between the dosing pump frequency recommendation value and the current dosing pump frequency value.

[0069] Here, considering that the sewage instantaneous flow time series correlation feature vector and the sewage instantaneous flow fluctuation time series correlation feature vector respectively represent the bidirectional short-range and long-range time series correlation characteristics of the absolute value of the sewage instantaneous flow and its relative fluctuation value, when performing dynamic interactive synthesis of time series based on the gating mechanism, it is expected to further compensate for the dynamic interactive offset time series synthesis imbalance caused by the imbalance of correspondence ratio under the fine-grained distribution of time series, so as to improve the expression effect of the multi-dimensional time series correlation feature vector of the sewage instantaneous flow, thereby improving the accuracy of the decoding results.

[0070] Therefore, preferably, the present application corrects the multi-dimensional time series correlation feature vector of the instantaneous sewage flow rate when inputting the multi-dimensional time series correlation feature vector of the instantaneous sewage flow rate into the decoder-based dosing pump frequency recommender to obtain the dosing pump frequency recommendation value.

[0071] Specifically, the dosing pump frequency recommendation module 850 includes: a correction unit, used to correct the multi-dimensional time series correlation feature vector of the sewage instantaneous flow to obtain a corrected multi-dimensional time series correlation feature vector of the sewage instantaneous flow; a decoding unit, used to input the corrected multi-dimensional time series correlation feature vector of the sewage instantaneous flow into the decoder-based dosing pump frequency recommender to obtain the dosing pump frequency recommendation value.

[0072] Wherein, the correction unit is used to: calculate the first norm and second norm of the mean vector of the sewage instantaneous flow time series correlation feature vector and the sewage instantaneous flow fluctuation time series correlation feature vector; calculate the weighted sum of the inverse of the square root of the second norm and the first norm, and perform point multiplication with the point addition sum vector of the sewage instantaneous flow time series correlation feature vector and the sewage instantaneous flow fluctuation time series correlation feature vector to obtain a first sewage instantaneous flow multi-dimensional time series correlation correction subvector; perform the point multiplication of the sewage instantaneous flow time series correlation feature vector and the sewage instantaneous flow fluctuation time series correlation feature vector The product vector is multiplied by the square root of the length of the sewage instantaneous flow multidimensional time series association feature vector to obtain a second sewage instantaneous flow multidimensional time series association correction subvector; the weighted sum of the first sewage instantaneous flow multidimensional time series association correction subvector and the second sewage instantaneous flow multidimensional time series association correction subvector is calculated to obtain a sewage instantaneous flow multidimensional time series association correction vector; the sewage instantaneous flow multidimensional time series association correction vector is multiplied by the sewage instantaneous flow multidimensional time series association feature vector to obtain the corrected sewage instantaneous flow multidimensional time series association feature vector.

[0073] The correction unit is used to correct the sewage instantaneous flow multi-dimensional time series correlation feature vector using the following correction formula to obtain the corrected sewage instantaneous flow multi-dimensional time series correlation feature vector; wherein the correction formula is:

[0074]

[0075] Among them, V1 and V2 are respectively the sewage instantaneous flow time series correlation feature vector and the sewage instantaneous flow fluctuation time series correlation feature vector, V μ is the mean vector of the sewage instantaneous flow time series associated feature vector and the sewage instantaneous flow fluctuation time series associated feature vector, ||·||1 is the norm of the feature vector, ||·||2 -1 / 2 is the reciprocal of the square root of the two-norm of the eigenvector, is the addition by location point, ⊙ is the multiplication by location point, L is the length of the multi-dimensional time series correlation feature vector of the instantaneous sewage flow, and α and β are the weighted sum weights as hyperparameters, and V' is the multi-dimensional time series correlation correction vector of the instantaneous sewage flow.

[0076] Therefore, based on the mean vector norm between the sewage instantaneous flow time series correlation feature vector and the sewage instantaneous flow fluctuation time series correlation feature vector, the constrained representation of the structured foreground and background distinction of the superfluid of the sewage instantaneous flow time series correlation feature vector and the sewage instantaneous flow fluctuation time series correlation feature vector is used to model the feature-level key correspondence between the feature vectors of the sewage instantaneous flow time series correlation feature vector and the sewage instantaneous flow fluctuation time series correlation feature vector, and adjust the global correlation relationship between the corresponding features, so as to make positive fine-grained correspondence suggestions through the unbalanced proportion control between the corresponding feature values ​​of the sewage instantaneous flow time series correlation feature vector and the sewage instantaneous flow fluctuation time series correlation feature vector, so as to avoid the imbalance of fusion domain offset between the sewage instantaneous flow time series correlation feature vector and the sewage instantaneous flow fluctuation time series correlation feature vector by focusing on the focus.

[0077] In this way, by correcting the multi-dimensional time series correlation feature vector of the instantaneous sewage flow rate through the multi-dimensional time series correlation correction vector of the instantaneous sewage flow rate, the expression effect of the multi-dimensional time series correlation feature vector of the instantaneous sewage flow rate can be improved, thereby improving the accuracy of the dosing pump frequency recommendation value obtained by inputting the dosing pump frequency recommender based on the decoder. In this way, by real-time monitoring and analysis of the instantaneous sewage flow rate and its fluctuation state, the system can more accurately dynamically adjust the frequency of the dosing pump according to the real-time changes in the sewage flow rate, reducing the need for human intervention to ensure the efficiency and effect of the sewage treatment process, thereby improving the automation level of the operation and the overall treatment efficiency.

[0078] Based on the above embodiments, see Figure 4 As shown, it is a flow chart of a sewage system dosing method for VFAs prepared from food waste in an embodiment of the present application. For example, the sewage system dosing method for VFAs prepared from food waste can be executed by a server, which can be Figure 1 The server 100 shown in FIG. Figure 4As shown, according to the sewage system dosing method of VFAs for kitchen waste preparation according to the embodiment of the present application, the steps include: S510, obtaining the time series of sewage instantaneous flow; S520, based on the time series of sewage instantaneous flow, calculating the difference of sewage instantaneous flow to obtain the time series of sewage instantaneous flow fluctuation; S530, inputting the time series of sewage instantaneous flow and the time series of sewage instantaneous flow fluctuation into the sequence encoder respectively to obtain the sewage instantaneous flow time series correlation feature vector and the sewage instantaneous flow fluctuation time series correlation feature vector; S540, performing feature vector dynamic interaction processing based on the gating mechanism on the sewage instantaneous flow time series correlation feature vector and the sewage instantaneous flow fluctuation time series correlation feature vector to obtain the sewage instantaneous flow multi-dimensional time series correlation feature vector as the sewage instantaneous flow multi-dimensional time series correlation feature; S550, based on the sewage instantaneous flow multi-dimensional time series correlation feature, obtaining the dosing pump frequency recommended value; S560, based on the dosing pump frequency recommended value and the current dosing pump frequency value, generating the dosing pump frequency adjustment instruction.

[0079] Here, those skilled in the art will appreciate that the specific operations of each step in the above-mentioned sewage system dosing method for VFAs prepared from food waste have been described in the above reference. Figure 2 to Figure 3 The description of the sewage system dosing device 800 for VFAs preparation from food waste has been described in detail, and therefore, its repeated description will be omitted.

[0080] Furthermore, it is worth mentioning that the VFAs prepared from kitchen waste are an organic composite solution with good biodegradability, high B / C, high C / N and high C / P. The denitrification rate can reach up to 0.754 mgNO3-N / (mgVSS·d). It can be used in the denitrification system of sewage treatment to replace traditional carbon sources, improve the denitrification efficiency of sewage treatment plants, and realize the full biological conversion of kitchen waste after impurities are removed.

[0081] VFA, whose Chinese name is Volatile Fatty Acid, is a type of fatty acid. It is generally an organic acid with a carbon chain of 1 to 6 carbon atoms, including formic acid, acetic acid, propionic acid, butyric acid, valeric acid, caproic acid, etc. Their common feature is that they are highly volatile, so they are called volatile fatty acids. VFAs prepared from kitchen waste include VFAs in the traditional sense, as well as some alcohols represented by methanol, ethanol, and propanol, and a small number of branched volatile organic acids represented by 2-methylpropionic acid and isovaleric acid. They are also highly volatile, so the plural form of VFA, VFAs, is used to represent organic acids prepared from kitchen waste, and its Chinese name is volatile fatty acids.

[0082] Combination Figure 5As shown, the materials transported by the material transport vehicle are respectively input into the medicine storage box 1 and the medicine storage box 2 through the feed pump, and then the medicine is added to the sewage treatment line from the medicine storage box 1 and the medicine storage box 2 through the dosing pump 1 and the dosing pump 2. In addition, the sewage is discharged from the sump to the outside through the sewage well by the sewage pump.

[0083] Furthermore, when VFAs prepared from kitchen waste are added to the sewage treatment system, the dosage must change according to the change in the amount of sewage treatment water under the premise of a certain dosage ratio. The frequency of the dosing pump is controlled by a frequency converter constant. After the dosage ratio is set using a PLC (programmable logic controller), when the instantaneous flow signal of the sewage treatment changes, it will be fed back to the PLC to automatically adjust the frequency of the dosing pump, thereby changing the instantaneous flow of the dosing pump. This overall design ensures that after the dosage ratio is determined, the dosage of the VFAs product prepared from kitchen waste changes in conjunction with the change in the sewage inflow of the sewage treatment system, thereby exerting the effect of quantitative dosing.

[0084] Based on the above embodiments, another exemplary embodiment of an electronic device is also provided in the embodiments of the present application. In some possible implementations, the electronic device in the embodiments of the present application may include a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the steps of the sewage system dosing method for VFAs prepared from kitchen waste in the above embodiments can be implemented when the processor executes the program.

[0085] For example, in the case of electronic equipment Figure 1 Taking the server 100 in the example as an example, the processor in the electronic device is the processor 110 in the server 100, and the memory in the electronic device is the memory 120 in the server 100.

[0086] The embodiments of the present application also provide a computer-readable storage medium having computer-executable instructions stored thereon. When the computer-executable instructions are executed by a processor, the sewage system dosing method of VFAs for food waste preparation according to the embodiments of the present application described with reference to the above figures can be executed. The computer-readable storage medium includes, but is not limited to, for example, volatile memory and / or non-volatile memory. The volatile memory may, for example, include a random access memory (RAM) and / or a cache memory (cache), etc. The non-volatile memory may, for example, include a read-only memory (ROM), a hard disk, a flash memory, etc.

[0087] The embodiments of the present application also provide a computer program product or a computer program, which includes computer executable instructions stored in a computer-readable storage medium. The processor of the computer device reads the computer executable instructions from the computer-readable storage medium, and the processor executes the computer executable instructions, so that the computer device executes the sewage system dosing method of VFAs for food waste preparation according to the embodiments of the present application.

[0088] Those skilled in the art will appreciate that the contents disclosed in this application may be subject to various variations and improvements. For example, the various devices or components described above may be implemented by hardware, or by software, firmware, or a combination of some or all of the three.

[0089] In addition, although the present application makes various references to certain units in the system according to embodiments of the present application, any number of different units can be used and run on the client and / or server. The units are only illustrative, and different aspects of the system and method can use different units.

[0090] Those skilled in the art will appreciate that all or part of the steps in the above method can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium, such as a read-only memory, a disk or an optical disk. Optionally, all or part of the steps in the above embodiment can also be implemented using one or more integrated circuits. Accordingly, each module / unit in the above embodiment can be implemented in the form of hardware or in the form of software function modules. The present application is not limited to any particular form of combination of hardware and software.

[0091] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by those of ordinary skill in the art to which this application belongs. It should also be understood that terms such as those defined in common dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant technology, and should not be interpreted in an idealized or extremely formal sense, unless explicitly defined as such herein.

[0092] The above is an explanation of the present application and should not be considered as limiting thereof. Although several exemplary embodiments of the present application have been described, those skilled in the art will readily appreciate that many modifications may be made to the exemplary embodiments without departing from the novel teachings and advantages of the present application.

Claims

1. A sewage system dosing device for VFAs prepared from food waste, characterized in that: include: Sewage instantaneous flow time series acquisition module, used to obtain the time series of sewage instantaneous flow; A sewage instantaneous flow fluctuation calculation module, used to calculate the difference of sewage instantaneous flow based on the time series of sewage instantaneous flow to obtain the time series of sewage instantaneous flow fluctuation; A sewage flow time series correlation feature extraction module is used to input the time series of the sewage instantaneous flow and the time series of the sewage instantaneous flow fluctuation into a sequence encoder to obtain a sewage instantaneous flow time series correlation feature vector and a sewage instantaneous flow fluctuation time series correlation feature vector; A sewage instantaneous flow multi-dimensional time series interaction module is used to perform feature vector dynamic interaction processing based on a gating mechanism on the sewage instantaneous flow time series correlation feature vector and the sewage instantaneous flow fluctuation time series correlation feature vector to obtain the sewage instantaneous flow multi-dimensional time series correlation feature vector as the sewage instantaneous flow multi-dimensional time series correlation feature; A dosing pump frequency recommendation module, used to obtain a dosing pump frequency recommendation value based on the multi-dimensional time series correlation characteristics of the sewage instantaneous flow rate; The dosing pump frequency adjustment instruction generating module is used to generate a dosing pump frequency adjustment instruction based on the dosing pump frequency recommendation value and the current dosing pump frequency value.

2. The sewage system dosing device for VFAs prepared from food waste according to claim 1, characterized in that: The sewage instantaneous flow fluctuation calculation module is used to: The difference between the instantaneous sewage flow rates at every two adjacent time points in the time series of the instantaneous sewage flow rate is calculated to obtain the time series of the instantaneous sewage flow rate fluctuation.

3. The sewage system dosing device for VFAs prepared from food waste according to claim 2, characterized in that: The sewage flow time series correlation feature extraction module is used to: The time series of the instantaneous sewage flow and the time series of the instantaneous sewage flow fluctuation are respectively input into the sequence encoder based on the Bi-LSTM model to obtain the sewage instantaneous flow time series correlation feature vector and the sewage instantaneous flow fluctuation time series correlation feature vector.

4. The sewage system dosing device for VFAs prepared from kitchen waste according to claim 3, characterized in that: The sewage instantaneous flow multi-dimensional time series interaction module is used to: The sewage instantaneous flow time series correlation feature vector and the sewage instantaneous flow fluctuation time series correlation feature vector are input into the feature vector dynamic interaction synthesis module under the gating mechanism to obtain the sewage instantaneous flow multi-dimensional time series correlation feature vector.

5. The sewage system dosing device for VFAs prepared from food waste according to claim 4, characterized in that: The sewage instantaneous flow multi-dimensional time series interaction module includes: A cascade unit, used for inputting the sewage instantaneous flow time series associated feature vector and the sewage instantaneous flow fluctuation time series associated feature vector into a feature combination module for cascade processing to obtain a sewage instantaneous flow-sewage instantaneous flow fluctuation time series joint feature vector; A sewage instantaneous flow-sewage instantaneous flow fluctuation time series gated response value calculation unit, used for inputting the sewage instantaneous flow-sewage instantaneous flow fluctuation time series joint feature vector into a gated response function to obtain a sewage instantaneous flow-sewage instantaneous flow fluctuation time series information fusion response gated value; The sewage instantaneous flow-sewage instantaneous flow fluctuation time series multi-dimensional fusion unit is used to calculate the position-weighted sum of the sewage instantaneous flow time series associated feature vector and the sewage instantaneous flow fluctuation time series associated feature vector using the sewage instantaneous flow-sewage instantaneous flow fluctuation time series information fusion response gate value as a weight to obtain the sewage instantaneous flow multi-dimensional time series associated feature vector.

6. The sewage system dosing device for VFAs prepared from food waste according to claim 5, characterized in that: The sewage instantaneous flow-sewage instantaneous flow fluctuation timing gated response value calculation unit includes: A multiplication and addition subunit is used to calculate the matrix product of the sewage instantaneous flow-sewage instantaneous flow fluctuation time series joint characteristic vector and the parameter matrix, and then add the obtained characteristic vector and the bias vector according to the position to obtain the sewage instantaneous flow-sewage instantaneous flow fluctuation time series joint bias characteristic vector; The activation subunit is used to input the sewage instantaneous flow-sewage instantaneous flow fluctuation time series joint bias feature vector into the sigmoid activation function to obtain the sewage instantaneous flow-sewage instantaneous flow fluctuation time series information fusion response gating value.

7. The sewage system dosing device for VFAs prepared from food waste according to claim 6, characterized in that: The sewage instantaneous flow-sewage instantaneous flow fluctuation time series multi-dimensional fusion unit includes: The first position-based product subunit is used to calculate the position-based product between the sewage instantaneous flow time series associated characteristic vector and the sewage instantaneous flow-sewage instantaneous flow fluctuation time series information fusion response gating value to obtain the sewage instantaneous flow time series associated gating adjustment vector; The second position-based product subunit is used to calculate the position-based product between the sewage instantaneous flow fluctuation time series associated characteristic vector and one minus the sewage instantaneous flow - sewage instantaneous flow fluctuation time series information fusion response gating value to obtain the sewage instantaneous flow fluctuation time series associated gating adjustment vector; The position adding subunit is used to add the sewage instantaneous flow time series associated gated adjustment vector and the sewage instantaneous flow fluctuation time series associated gated adjustment vector according to the position to obtain the sewage instantaneous flow multi-dimensional time series associated feature vector.

8. The sewage system dosing device for VFAs prepared from food waste according to claim 7, characterized in that: The dosing pump frequency recommendation module is used to: The multi-dimensional time series correlation feature vector of the sewage instantaneous flow rate is input into a dosing pump frequency recommender based on a decoder to obtain the dosing pump frequency recommendation value.

9. The sewage system dosing device for VFAs prepared from food waste according to claim 8, characterized in that: The dosing pump frequency adjustment instruction generation module is used to: The dosing pump frequency adjustment instruction is generated based on the difference between the recommended dosing pump frequency value and the current dosing pump frequency value.

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