A method, system, device and water pump for optimizing energy consumption of a pipe network in an industrial circulation system

Abstract

The application discloses a kind of pipe network energy consumption optimization method, system, equipment and water pump in industrial circulation system, belong to industrial pipe network optimization technical field and pump energy-saving technical field.The application selects the pump optimization model and pipeline optimization model corresponding to pipeline by medium parameter;According to the medium parameter of circulating medium in pipeline, and the relevant parameters between the pipeline adjacent to pipeline, the abnormal position of pipeline is calculated;According to the pipeline optimization model, the pipeline optimization scheme for abnormal position is obtained;According to the pump optimization model, the pump optimization scheme corresponding to the pipeline optimization scheme is obtained;According to the pipeline optimization scheme and pump optimization scheme, the pipeline is optimized;After realizing field data acquisition, analysis, by optimizing pipe network resistance, customizing the efficient energy-saving water pump and motor of matching technical transformation system, under the premise of not affecting production safety and not improving the cost of transformation, the optimization of pipe network and water pump is realized, and the upgrading and replacement of pipe network and water pump with energy-saving demand are realized.

Description

Technical Field

[0001] This invention relates to the fields of industrial pipeline network optimization technology and pump energy saving technology, and particularly to a method, system, equipment and pump for optimizing pipeline energy consumption in an industrial circulation system. Background Technology

[0002] The main application of water pumps and corresponding piping networks in industry is in the recycling of media, such as cooling water circulation, where their energy consumption accounts for a large proportion of the overall system energy consumption.

[0003] Most existing water pumps and operating models are based on static models under fixed operating conditions, which cannot effectively meet the actual needs of specific application scenarios and have poor applicability. Moreover, under the above static models, upgrades for energy saving often involve large-scale renovation and replacement of pipe networks and water pumps, which instead increases costs in the industrial production process. Summary of the Invention

[0004] To address the problems of existing technologies, embodiments of the present invention provide a method, system, equipment, and water pump for optimizing pipeline energy consumption in an industrial circulation system, comprising:

[0005] On the one hand, a method for optimizing pipeline energy consumption in an industrial circulation system is provided, wherein the pipeline includes multiple pumps and multiple pipeline outlets, and the method includes:

[0006] Multiple media parameter monitors are installed between the two pipeline outlets;

[0007] A pipeline optimization model corresponding to the pipeline outlet is set up, and the pipeline optimization model is constructed by a first-width neural network;

[0008] Based on the pipeline optimization model and the installation locations of the multiple media parameter monitors, calculate the abnormal location between the two pipeline outlets;

[0009] Calculate the pipeline auxiliary equipment and installation location corresponding to the abnormal location;

[0010] After the pipeline auxiliary equipment is installed at the installation location, a pump optimization model corresponding to the pump is set; the pump optimization model is constructed through a second-width neural network.

[0011] Based on the pump optimization model, calculate the pump parameters and number of pumps corresponding to the multiple pipeline outlets;

[0012] Based on the pipeline network structure parameters between the pump and the plurality of pipeline outlets, the installation position of the pump is calculated, and a pump corresponding to the pump parameters and the number of pumps is installed at the installation position.

[0013] Optionally, after the pump is installed, the method further includes:

[0014] Set a monitoring cycle;

[0015] During the monitoring period, the energy consumption of the pipeline network is monitored by the multiple media parameter monitors.

[0016] Optionally, the provision of multiple media parameter monitors between the two pipe outlets includes:

[0017] Two media parameter monitors are installed at the inlet and outlet of each of the two pipelines, respectively.

[0018] Other media parameter monitors are installed between the two pipe outlets;

[0019] Mark the installation locations of the multiple media parameter monitors in the pipeline.

[0020] Optionally, the pipeline optimization model corresponding to the pipeline outlet includes:

[0021] The inputs to the pipeline optimization model are the medium parameters at the inlet, the desired medium parameters at the outlet, and the installation locations of the other medium parameter monitors.

[0022] The output of the pipeline optimization model is the theoretical media parameters of the other media parameter monitors.

[0023] Optionally, calculating the abnormal location between the two pipeline outlets based on the pipeline optimization model and the installation locations of the multiple media parameter monitors includes:

[0024] Based on the pipeline optimization model and the installation locations of the multiple media parameter monitors, the theoretical media parameters of the other media parameter monitors are obtained;

[0025] Obtain the actual media parameters of the other media parameter monitors;

[0026] Based on the theoretical and actual medium parameters, multiple abnormal medium parameter monitors are obtained.

[0027] The location of the anomaly is determined based on the multiple abnormal medium parameter monitors.

[0028] Optionally, calculating the pipeline auxiliary equipment and installation location corresponding to the abnormal location includes:

[0029] Install a media parameter monitor at the abnormal location;

[0030] Match the corresponding pipeline auxiliary equipment based on the actual medium parameters on the medium parameter monitor and the theoretical medium parameters on the medium parameter monitor;

[0031] Set the abnormal location to the installation location.

[0032] Optional,

[0033] The pump optimization model corresponding to the pump settings includes:

[0034] Calculate the pipeline network structure parameters between the pump and the plurality of pipeline outlets;

[0035] The input to the pump optimization model is the desired medium parameters corresponding to the multiple pipe outlets and multiple pipe network structure parameters, and the output of the pump optimization model is the pump parameters and the number of pumps.

[0036] The step of calculating the pump's installation location based on the pipeline network structure parameters between the pump and the plurality of pipeline outlets includes:

[0037] Based on the pump parameters and the pipeline structure parameters, calculate the energy redundancy locations and energy insufficiency locations in the pipeline structure;

[0038] Based on the energy consumption redundancy locations and the energy consumption insufficiency locations, calculate the installation locations of multiple pumps.

[0039] On the other hand, a pipeline energy consumption optimization system for an industrial circulation system is also provided. This system is applied to a pipeline network including multiple pumps and multiple pipeline outlets. The system includes multiple media parameter monitors, pipeline optimization equipment, pump optimization equipment, and a server, wherein:

[0040] The server is used to set up the plurality of media parameter monitors between the two pipe outlets;

[0041] The pipeline optimization equipment is used for:

[0042] A pipeline optimization model corresponding to the pipeline outlet is set up, and the pipeline optimization model is constructed by a first-width neural network;

[0043] Based on the pipeline optimization model and the installation locations of the multiple media parameter monitors, calculate the abnormal location between the two pipeline outlets;

[0044] Calculate the pipeline auxiliary equipment and installation location corresponding to the abnormal location;

[0045] The pump optimization equipment is used for:

[0046] After the pipeline auxiliary equipment is installed at the installation location, a pump optimization model corresponding to the pump is set; the pump optimization model is constructed through a second-width neural network.

[0047] Based on the pump optimization model, calculate the pump parameters and number of pumps corresponding to the multiple pipeline outlets;

[0048] Based on the pipeline network structure parameters between the pump and the plurality of pipeline outlets, the installation position of the pump is calculated, and a pump corresponding to the pump parameters and the number of pumps is installed at the installation position.

[0049] On the other hand, a pipeline energy consumption optimization device for an industrial circulation system is also provided, the device comprising:

[0050] The pipeline optimization module is used for:

[0051] A pipeline optimization model corresponding to the pipeline outlet is set up, and the pipeline optimization model is constructed by a first-width neural network;

[0052] Based on the pipeline optimization model and the installation locations of the multiple media parameter monitors, calculate the abnormal location between the two pipeline outlets;

[0053] Calculate the pipeline auxiliary equipment and installation location corresponding to the abnormal location;

[0054] The pump optimization module is used for:

[0055] A pump optimization model is set up corresponding to the pump; the pump optimization model is constructed through a second-width neural network;

[0056] Based on the pump optimization model, calculate the pump parameters and number of pumps corresponding to the multiple pipeline outlets;

[0057] The installation location of the pump is calculated based on the pipeline network structure parameters between the pump and the multiple pipeline outlets.

[0058] On the other hand, a water pump is also provided, the water pump comprising:

[0059] Impeller, base, bearing assembly, wear-resistant liner, pump shaft, double-suction horizontally split pump casing;

[0060] The energy consumption monitoring module is used to calculate the medium parameters at the pump outlet and, based on the medium parameters, monitor the gap between the impeller and the cavity wall, as well as the smoothness of the pump impeller flow channel.

[0061] The beneficial effects that can be achieved by the embodiments of the present invention are:

[0062] By selecting the appropriate pump and pipeline optimization models based on the medium parameters, and calculating the abnormal locations of the pipeline according to the medium parameters within the pipeline and the relevant parameters between the pipelines adjacent to it, the pipeline optimization model yields optimization schemes for the abnormal locations. These schemes include the quantity and installation location of pipeline auxiliary equipment. Similarly, the pump optimization model provides corresponding pump optimization schemes, including pump model, impeller diameter, impeller angle, and operating parameters. The pipeline is then optimized based on both the pipeline and pump optimization schemes. After on-site data collection and analysis, the optimization of the pipeline network resistance and the customization of high-efficiency, energy-saving pumps and motors to match the technical upgrade system are achieved without affecting production safety or increasing upgrade costs. This enables pipeline and pump upgrades and replacements based on energy-saving requirements. Attached Figure Description

[0063] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0064] Figure 1 A schematic diagram of a pipeline energy consumption optimization method in an industrial circulation system provided by an embodiment of the present invention;

[0065] Figure 2 This is a schematic diagram of a pipeline provided in an embodiment of the present invention;

[0066] Figure 3 This is a schematic diagram of a pipeline provided in an embodiment of the present invention;

[0067] Figure 4 A schematic diagram of a pipeline energy consumption optimization system in an industrial circulation system provided by an embodiment of the present invention;

[0068] Figure 5 This is a schematic diagram of a pipeline energy consumption optimization device provided in an embodiment of the present invention. Detailed Implementation

[0069] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0070] The method provided in this invention is mainly applied to the optimization of pipeline energy consumption in industrial circulation systems. These systems include water circulation, gas circulation, and circulation of other fluid-like industrial materials. For ease of explanation, this invention refers to all of the above media as circulating media. Furthermore, the media parameter monitor described in this invention is detachably connected to the outside of the pipeline. This media parameter monitor can be radar-type and is equipped with a network module. This network module connects to optimization equipment or an optimization server via 4G / 5G or the Internet of Things.

[0071] Reference Figure 1 As shown, a method for optimizing pipeline energy consumption in an industrial circulation system is provided. The pipeline includes multiple pumps and multiple pipe outlets. (Refer to...) Figure 2 As shown, the method includes:

[0072] 101. Install multiple media parameter monitors between the two pipeline outlets;

[0073] 102. Set up a pipeline optimization model corresponding to the pipeline outlet;

[0074] The pipeline optimization model is constructed using a first-width neural network.

[0075] 103. Based on the pipeline optimization model and the installation locations of multiple media parameter monitors, calculate the abnormal location between the two pipeline outlets;

[0076] 104. Calculate the auxiliary pipeline equipment and installation locations corresponding to abnormal locations;

[0077] 105. After installing the pipeline auxiliary equipment at the installation location, set up the pump optimization model corresponding to the pump;

[0078] The pump optimization model is constructed using a second-width neural network.

[0079] 106. Based on the pump optimization model, calculate the pump parameters and number of pumps corresponding to multiple pipeline outlets;

[0080] 107. Based on the pipeline network structure parameters between the pump and multiple pipeline outlets, calculate the installation location of the pump, and install the pump corresponding to the pump parameters and number of pumps at the installation location.

[0081] Optionally, after the pump is installed, the method also includes:

[0082] 108. Set the monitoring cycle;

[0083] 109. During the monitoring period, the energy consumption of the pipeline network is monitored through multiple media parameter monitors.

[0084] The real-time media parameters measured by all media parameter monitors on the pipeline are obtained in real time.

[0085] The pipeline optimization model is set as follows:

[0086] If any one of these real-time media parameters falls under the following condition:

[0087] If the difference between real-time media parameters and final media parameters is greater than or equal to the media parameter threshold, then the pipeline optimization model is invoked.

[0088] Based on the above formula, calculate the difference between each real-time media parameter and the corresponding final media parameter:

[0089] For any given medium parameter monitor, the following strategy is adopted:

[0090] If the real-time medium parameter minus the final medium parameter is greater than or equal to the medium parameter threshold, and the previous output of the medium parameter monitor is the same as the final monitoring result, then it is recorded as 1.

[0091] If the real-time medium parameter minus the final medium parameter | ≥ the medium parameter threshold, and the previous output of the medium parameter monitor is different from the final monitoring result, then it is recorded as 0.5;

[0092] If the real-time medium parameter - final medium parameter | < medium parameter threshold, and the previous output result of the medium parameter monitor is the same as the final monitoring result, then it is recorded as -1;

[0093] If the real-time medium parameter - final medium parameter | < medium parameter threshold, and the previous output result of the medium parameter monitor is different from the final monitoring result, then it is recorded as -0.5;

[0094] The output results include both abnormal and normal results, and the final monitoring results include both normal and abnormal results.

[0095] If the sum of all values ​​is less than half the number of media parameter monitors, then the final monitoring result is normal.

[0096] If the sum of all values ​​is greater than or equal to half the number of media parameter monitors, the final monitoring result is abnormal.

[0097] The process of setting up a pump optimization model includes:

[0098] Real-time monitoring of media parameters at abnormal locations;

[0099] The first correlation formula between the real-time media parameters and the gap between the impeller and the cavity wall is set as follows:

[0100] Real-time media parameters = F1 (Real-time media parameters) The gap between the impeller and the cavity wall, where F1 (real-time medium parameter) is a relevant parameter that can be obtained from historical data;

[0101] Real-time media parameters = F2 (Real-time media parameters) Surface finish, F2 (real-time media parameter) is a relevant parameter, obtained from historical data;

[0102] If any of the gaps, surface finish, or real-time media parameters are abnormal, the maintenance strategy will be activated.

[0103] Optionally, step 101, which involves installing multiple media parameter monitors between the two pipe outlets, includes:

[0104] Two media parameter monitors are installed at the inlet and outlet of each of the two pipelines, respectively.

[0105] Install additional media parameter monitors between the two pipe outlets;

[0106] Mark the installation locations of multiple media parameter monitors in the pipeline.

[0107] It should be noted that this step involves installing media parameter monitors on multiple pipelines offline, activating these monitors, and then collecting data via a network connection to the optimization equipment. Furthermore, after collecting these multiple media parameters, descriptive information for each pipeline can be labeled.

[0108] Optionally, the pipeline optimization model corresponding to the pipeline outlet described in step 102 includes:

[0109] The inputs to the pipeline optimization model are the medium parameters at the inlet, the desired medium parameters at the outlet, and the installation locations of other medium parameter monitors;

[0110] The output of the pipeline optimization model is the theoretical media parameters of other media parameter monitors.

[0111] The above process can also involve selecting a pipeline optimization model based on medium parameters, including:

[0112] Based on relevant parameters and the functional parameters of multiple pipelines, multiple pipelines are merged; the functional parameters are used to indicate the outlet and inlet functions of multiple pipelines.

[0113] Based on the multiple medium parameters corresponding to the merged pipelines, the energy consumption range of the merged pipelines is obtained, and the pipeline optimization model is selected based on the energy consumption range.

[0114] Optionally, step 103, which involves calculating the abnormal location between the two pipeline outlets based on the pipeline optimization model and the installation locations of multiple media parameter monitors, includes:

[0115] Based on the pipeline optimization model and the installation locations of multiple media parameter monitors, the theoretical media parameters of other media parameter monitors are obtained;

[0116] Obtain the actual media parameters of other media parameter monitors;

[0117] Based on theoretical and actual medium parameters, multiple abnormal medium parameter monitors were obtained;

[0118] The location of the anomaly was determined based on multiple abnormal media parameter monitors.

[0119] In the above process, after the circulation system starts running, media parameter monitors corresponding to multiple pipelines are set up to obtain multiple media parameters; this process can be specifically as follows: multiple media parameter monitors are placed at the outlet, inlet and intermediate positions of multiple pipelines;

[0120] This process can be specifically described as follows:

[0121] The inlet of this pipeline can be the location of the pump, and the outlet can be a branch port or the connection point between the pipeline and the next pump. The branch port is the connection point to the equipment using the circulating medium. The intermediate location can be any point between the inlet and outlet; see reference [link / reference needed] for details. Figure 3 As shown.

[0122] Based on the data collected by the circulating energy consumption monitor, the energy consumption distribution parameters of the circulating medium in multiple pipelines are estimated.

[0123] Based on the energy consumption distribution parameters, the placement of multiple cycle energy consumption monitors is adjusted;

[0124] Acquire the media parameters collected by multiple media parameter monitors respectively;

[0125] Calculate the relevant parameters between multiple pipes based on multiple medium parameters;

[0126] For any given pipe, perform the following steps:

[0127] Based on the medium parameters, select the corresponding pump optimization model and pipeline optimization model;

[0128] Among them, the pump optimization model is generated through a long short-term memory network, and the pipeline optimization model is generated through a multilayer perceptron.

[0129] The abnormal location of the pipeline is calculated based on the medium parameters of the circulating medium in the pipeline and the relevant parameters between the pipeline and the pipeline adjacent to it.

[0130] Optionally, the calculation of the pipeline auxiliary equipment and installation location corresponding to the abnormal location in step 104 includes:

[0131] Install media parameter monitors at abnormal locations;

[0132] Match the corresponding pipeline auxiliary equipment based on the actual medium parameters on the medium parameter monitor and the theoretical medium parameters on the medium parameter monitor;

[0133] Set the abnormal location to the installation location.

[0134] The process of matching the corresponding pipeline auxiliary equipment mentioned above can be as follows:

[0135] Based on the pipeline optimization model, pipeline optimization schemes for abnormal locations are obtained. The pipeline optimization schemes include the number and installation locations of pipeline auxiliary equipment.

[0136] Based on the pump optimization model, the pump optimization scheme corresponding to the pipeline optimization scheme is obtained. The pump optimization scheme includes the pump model, impeller diameter, impeller angle and operating parameters.

[0137] The pipeline is optimized based on the pipeline optimization plan and the pump optimization plan;

[0138] The optimized pipeline corresponding to the second medium parameters is obtained, and the relevant parameters between multiple pipelines are updated.

[0139] Based on the updated parameters, continue optimizing the next pipeline until all pipelines have been optimized.

[0140] The above steps involve optimizing all pipelines online and outputting pipeline optimization and pump optimization schemes. After obtaining the pipeline optimization and pump optimization schemes, these schemes are then executed offline to complete the offline optimization of all pipelines.

[0141] Optionally, the pump optimization model set in step 105 corresponding to the pump includes:

[0142] Calculate the network structure parameters between the pump and multiple pipe outlets;

[0143] The input to the pump optimization model is the desired medium parameters corresponding to multiple pipeline outlets and multiple pipeline structure parameters. The output of the pump optimization model is the pump parameters and the number of pumps.

[0144] The above process can also involve selecting the appropriate pump optimization model based on the medium parameters, including:

[0145] Based on relevant parameters and the functional parameters of multiple pipelines, multiple pipelines are merged; the functional parameters are used to indicate the outlet and inlet functions of multiple pipelines.

[0146] Based on the functional parameters corresponding to the multiple pipelines after merging, a pump optimization model is selected.

[0147] Optionally, step 106, which involves calculating the pump's installation location based on the pipeline network structure parameters between the pump and multiple pipeline outlets, includes:

[0148] Based on pump parameters and pipeline structure parameters, calculate the locations of energy redundancy and energy insufficiency in the pipeline structure.

[0149] Calculate the installation locations of multiple pumps based on the locations of energy redundancy and energy deficiency.

[0150] In practical applications, the above process can also be used to obtain pipeline optimization for abnormal locations based on the pipeline optimization model, and pump optimization corresponding to the pipeline optimization scheme based on the pump optimization model. Specifically, this includes:

[0151] Based on the pipeline optimization model, the pipeline optimization schemes for abnormal locations include:

[0152] Place a circulating energy consumption monitor at the abnormal location and obtain the actual medium parameters at the abnormal location;

[0153] The actual medium parameters and the theoretical medium parameters at the abnormal location are input into the pipeline optimization model, and the pipeline optimization scheme for the abnormal location is output.

[0154] Based on the pump optimization model, the pump optimization schemes corresponding to the pipeline optimization schemes are as follows:

[0155] Calculate the optimized medium parameters at abnormal locations after the pipeline optimization scheme has been implemented;

[0156] Based on the optimized medium parameters, calculate the theoretical operating parameters of the pump corresponding to the pipeline;

[0157] Input the theoretical operating parameters and the location description of the pump installation position into the pump optimization model, and input the pump optimization scheme corresponding to the pipeline optimization scheme.

[0158] To further illustrate the method described in this embodiment of the invention, it is assumed that the system has a total of three 500KW circulating water pumps (circulating water pump A, circulating water pump B, and circulating water pump C), with two pumps operating year-round to supply one terminal oxygen chlorination unit, achieving water circulation. The power consumption statistics before optimization are shown in Table 1, and the power consumption statistics after optimization are shown in Table 2. Through the method described in this embodiment of the invention, based on improvements in pipeline pressure and flow rate, a comparison of Tables 1 and 2 shows a significant improvement in hourly power consumption and total power consumption, thereby saving energy and costs. Tables 1 and 2 are respectively:

[0159] Table 1: Power Consumption Statistics Before Optimization

[0160]

[0161] Table 2: Optimized Power Consumption Statistics

[0162]

[0163] Reference Figure 4 As shown, a pipeline energy consumption optimization system for an industrial circulation system is also provided. The system is applied to a pipeline network that includes multiple pumps and multiple pipe outlets. The system includes multiple media parameter monitors, pipeline optimization equipment, pump optimization equipment, and a server, wherein:

[0164] The server is used to set up multiple media parameter monitors between two pipe outlets;

[0165] Pipeline optimization equipment is used for:

[0166] Set up a pipeline optimization model corresponding to the pipeline outlet. The pipeline optimization model is constructed using a first-width neural network.

[0167] Based on the pipeline optimization model and the installation locations of multiple media parameter monitors, calculate the abnormal location between the two pipeline outlets;

[0168] Calculate the corresponding pipeline auxiliary equipment and installation locations at abnormal locations;

[0169] Pump optimization equipment is used for:

[0170] After installing the pipeline auxiliary equipment at the installation location, a pump optimization model corresponding to the pump is set up; the pump optimization model is constructed through a second-width neural network.

[0171] Based on the pump optimization model, calculate the pump parameters and number of pumps corresponding to multiple pipeline outlets;

[0172] Based on the pipeline network structure parameters between the pump and multiple pipeline outlets, calculate the pump installation location, and install pumps corresponding to the pump parameters and number of pumps at the installation locations.

[0173] Optionally, the server is used for:

[0174] Two media parameter monitors are installed at the inlet and outlet of each of the two pipelines, respectively.

[0175] Install additional media parameter monitors between the two pipe outlets;

[0176] Mark the installation locations of multiple media parameter monitors in the pipeline.

[0177] Optionally, pipeline optimization equipment is used for:

[0178] The inputs to the pipeline optimization model are the medium parameters at the inlet, the desired medium parameters at the outlet, and the installation locations of other medium parameter monitors;

[0179] The output of the pipeline optimization model is the theoretical media parameters of other media parameter monitors.

[0180] Optionally, pipeline optimization equipment is used for:

[0181] Based on the pipeline optimization model and the installation locations of multiple media parameter monitors, the theoretical media parameters of other media parameter monitors are obtained;

[0182] Obtain the actual media parameters of other media parameter monitors;

[0183] Based on theoretical and actual medium parameters, multiple abnormal medium parameter monitors were obtained;

[0184] The location of the anomaly was determined based on multiple abnormal media parameter monitors.

[0185] Optionally, pipeline optimization equipment is used for:

[0186] Install media parameter monitors at abnormal locations;

[0187] Match the corresponding pipeline auxiliary equipment based on the actual medium parameters on the medium parameter monitor and the theoretical medium parameters on the medium parameter monitor;

[0188] Set the abnormal location to the installation location.

[0189] Optionally, pump optimization equipment is used for:

[0190] Calculate the network structure parameters between the pump and multiple pipe outlets;

[0191] The input to the pump optimization model is the desired medium parameters corresponding to multiple pipeline outlets and multiple pipeline structure parameters. The output of the pump optimization model is the pump parameters and the number of pumps.

[0192] Optionally, pump optimization equipment is used for:

[0193] Based on pump parameters and pipeline structure parameters, calculate the locations of energy redundancy and energy insufficiency in the pipeline structure.

[0194] Calculate the installation locations of multiple pumps based on the locations of energy redundancy and energy deficiency.

[0195] Reference Figure 5 As shown, a pipeline energy consumption optimization system in an industrial circulation system is also provided, the equipment including:

[0196] The pipeline optimization module is used for:

[0197] Set up a pipeline optimization model corresponding to the pipeline outlet. The pipeline optimization model is constructed using a first-width neural network.

[0198] Based on the pipeline optimization model and the installation locations of multiple media parameter monitors, calculate the abnormal location between the two pipeline outlets;

[0199] Calculate the corresponding pipeline auxiliary equipment and installation locations at abnormal locations;

[0200] Pump optimization module, used for:

[0201] Set up a pump optimization model corresponding to the pump; the pump optimization model is constructed using a second-width neural network;

[0202] Based on the pump optimization model, calculate the pump parameters and number of pumps corresponding to multiple pipeline outlets;

[0203] Calculate the pump's installation location based on the pipeline network structure parameters between the pump and multiple pipeline outlets.

[0204] Optionally, the pipeline optimization module is used for:

[0205] The inputs to the pipeline optimization model are the medium parameters at the inlet, the desired medium parameters at the outlet, and the installation locations of other medium parameter monitors;

[0206] The output of the pipeline optimization model is the theoretical media parameters of other media parameter monitors.

[0207] Optionally, the pipeline optimization module is used for:

[0208] Based on the pipeline optimization model and the installation locations of multiple media parameter monitors, the theoretical media parameters of other media parameter monitors are obtained;

[0209] Obtain the actual media parameters of other media parameter monitors;

[0210] Based on theoretical and actual medium parameters, multiple abnormal medium parameter monitors were obtained;

[0211] The location of the anomaly was determined based on multiple abnormal media parameter monitors.

[0212] Optionally, the pipeline optimization module is used for:

[0213] Install media parameter monitors at abnormal locations;

[0214] Match the corresponding pipeline auxiliary equipment based on the actual medium parameters on the medium parameter monitor and the theoretical medium parameters on the medium parameter monitor;

[0215] Set the abnormal location to the installation location.

[0216] Optionally, the pump optimization module is used for:

[0217] Calculate the network structure parameters between the pump and multiple pipe outlets;

[0218] The input to the pump optimization model is the desired medium parameters corresponding to multiple pipeline outlets and multiple pipeline structure parameters. The output of the pump optimization model is the pump parameters and the number of pumps.

[0219] Optionally, the pump optimization module is used for:

[0220] Based on pump parameters and pipeline structure parameters, calculate the locations of energy redundancy and energy insufficiency in the pipeline structure.

[0221] Calculate the installation locations of multiple pumps based on the locations of energy redundancy and energy deficiency.

[0222] A water pump is also provided, the water pump comprising:

[0223] Impeller, base, bearing assembly, wear-resistant liner, pump shaft, double-suction horizontally split pump casing;

[0224] The energy consumption monitoring module is used to calculate the medium parameters at the pump outlet and, based on these parameters, monitor the clearance between the impeller and the cavity wall, as well as the smoothness of the pump impeller flow channel. This process can be as follows:

[0225] Real-time monitoring of media parameters at abnormal locations;

[0226] The first correlation formula between the real-time media parameters and the gap between the impeller and the cavity wall is set as follows:

[0227] Real-time media parameters = F1 (Real-time media parameters) The gap between the impeller and the cavity wall, where F1 (real-time medium parameter) is a relevant parameter that can be obtained from historical data;

[0228] Real-time media parameters = F2 (Real-time media parameters) Surface finish, F2 (real-time media parameter) is a relevant parameter, obtained from historical data;

[0229] If any of the gaps, surface finish, or real-time media parameters are abnormal, the maintenance strategy will be activated.

[0230] The optimization module is used to calculate the pump's operating parameters after partial pipeline optimization.

[0231] This water pump is an energy-saving single-stage double-suction pump, which features high operating efficiency, low energy consumption, low net positive suction head (NPSH), low noise, low maintenance costs, and a service life that is more than 1.5 times longer than that of ordinary pumps.

[0232] The above specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0233] The technical features of the above embodiments can be combined in any way (as long as there is no contradiction in the combination of these technical features). For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described; these embodiments not explicitly written should also be considered to be within the scope of this specification.

[0234] The present invention has been described in detail above through general description and specific embodiments. It should be noted that, without departing from the concept of the present invention, various modifications and improvements can be made to these specific embodiments, all of which fall within the scope of protection of this application. Therefore, the scope of protection of this patent application should be determined by the appended claims.

[0235] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for optimizing pipeline energy consumption in an industrial circulation system, characterized in that, The pipeline network includes multiple pumps and multiple pipe outlets, and the method includes: Multiple media parameter monitors are installed between the two pipeline outlets; A pipeline optimization model corresponding to the pipeline outlet is set up, and the pipeline optimization model is constructed by a first-width neural network; Based on the pipeline optimization model and the installation locations of the multiple media parameter monitors, calculate the abnormal location between the two pipeline outlets; Calculate the pipeline auxiliary equipment and installation location corresponding to the abnormal location; After the pipeline auxiliary equipment is installed at the installation location, a pump optimization model corresponding to the pump is set; the pump optimization model is constructed through a second-width neural network. Based on the pump optimization model, calculate the pump parameters and number of pumps corresponding to the multiple pipeline outlets; Based on the pipeline network structure parameters between the pump and the multiple pipeline outlets, calculate the pump installation position, and install a pump corresponding to the pump parameters and the number of pumps at the installation position; The step of calculating the abnormal location between the two pipeline outlets based on the pipeline optimization model and the installation locations of the multiple media parameter monitors includes: Based on the pipeline optimization model and the installation locations of the multiple media parameter monitors, the theoretical media parameters of the other media parameter monitors are obtained; Obtain the actual media parameters of the other media parameter monitors; Based on the theoretical and actual medium parameters, multiple abnormal medium parameter monitors are obtained. The location of the anomaly is determined based on the multiple abnormal medium parameter monitors; The calculation of the pipeline auxiliary equipment and installation location corresponding to the abnormal location includes: Install a media parameter monitor at the abnormal location; Match the corresponding pipeline auxiliary equipment based on the actual medium parameters on the medium parameter monitor and the theoretical medium parameters on the medium parameter monitor; Set the abnormal location to the installation location.

2. The method according to claim 1, characterized in that, After the pump is installed, the method further includes: Set a monitoring cycle; During the monitoring period, the energy consumption of the pipeline network is monitored by the multiple media parameter monitors.

3. The method according to claim 1, characterized in that, The installation of multiple media parameter monitors between the two pipeline outlets includes: Two media parameter monitors are installed at the inlet and outlet of each of the two pipelines, respectively. Other media parameter monitors are installed between the two pipe outlets; Mark the installation locations of the multiple media parameter monitors in the pipeline.

4. The method according to claim 3, characterized in that, The pipeline optimization model corresponding to the pipeline outlet includes: The inputs to the pipeline optimization model are the medium parameters at the inlet, the desired medium parameters at the outlet, and the installation locations of the other medium parameter monitors. The output of the pipeline optimization model is the theoretical media parameters of the other media parameter monitors.

5. The method according to claim 1, characterized in that, The pump optimization model corresponding to the pump settings includes: Calculate the pipeline network structure parameters between the pump and the plurality of pipeline outlets; The input to the pump optimization model is the desired medium parameters corresponding to the multiple pipe outlets and multiple pipe network structure parameters, and the output of the pump optimization model is the pump parameters and the number of pumps. The step of calculating the pump's installation location based on the pipeline network structure parameters between the pump and the plurality of pipeline outlets includes: Based on the pump parameters and the pipeline structure parameters, calculate the energy redundancy locations and energy insufficiency locations in the pipeline structure; Based on the energy consumption redundancy locations and the energy consumption insufficiency locations, calculate the installation locations of multiple pumps.

6. A pipeline energy consumption optimization system in an industrial circulation system, characterized in that, The system is applied to a pipeline network, which includes multiple pumps and multiple pipeline outlets. The system includes multiple media parameter monitors, pipeline optimization equipment, pump optimization equipment, and a server, wherein: The server is used to set up the plurality of media parameter monitors between the two pipe outlets; Pipeline optimization equipment is used for: A pipeline optimization model corresponding to the pipeline outlet is set up, and the pipeline optimization model is constructed by a first-width neural network; Based on the pipeline optimization model and the installation locations of the multiple media parameter monitors, calculate the abnormal location between the two pipeline outlets; Calculate the pipeline auxiliary equipment and installation location corresponding to the abnormal location; Pump optimization equipment is used for: After the pipeline auxiliary equipment is installed at the installation location, a pump optimization model corresponding to the pump is set; the pump optimization model is constructed through a second-width neural network. Based on the pump optimization model, calculate the pump parameters and number of pumps corresponding to the multiple pipeline outlets; Based on the pipeline network structure parameters between the pump and the multiple pipeline outlets, calculate the pump installation position, and install a pump corresponding to the pump parameters and the number of pumps at the installation position; The pipeline optimization equipment is used for: Based on the pipeline optimization model and the installation locations of the multiple media parameter monitors, the theoretical media parameters of the other media parameter monitors are obtained; Obtain the actual media parameters of the other media parameter monitors; Based on the theoretical and actual medium parameters, multiple abnormal medium parameter monitors are obtained. The location of the anomaly is determined based on the multiple abnormal medium parameter monitors; The pipeline optimization equipment is used for: Install a media parameter monitor at the abnormal location; Match the corresponding pipeline auxiliary equipment based on the actual medium parameters on the medium parameter monitor and the theoretical medium parameters on the medium parameter monitor; Set the abnormal location to the installation location.

7. A pipeline energy consumption optimization device in an industrial circulation system, characterized in that, The device includes: The pipeline optimization module is used for: A pipeline optimization model corresponding to the pipeline outlet is set up, and the pipeline optimization model is constructed by a first-width neural network; Based on the pipeline optimization model and the installation locations of multiple media parameter monitors, calculate the abnormal location between the two pipeline outlets; Calculate the pipeline auxiliary equipment and installation location corresponding to the abnormal location; Pump optimization module, used for: A pump optimization model is set up corresponding to the pump; the pump optimization model is constructed through a second-width neural network; Based on the pump optimization model, calculate the pump parameters and number of pumps corresponding to multiple pipeline outlets; The installation location of the pump is calculated based on the pipeline network structure parameters between the pump and the plurality of pipeline outlets. The pipeline optimization module is used for: Based on the pipeline optimization model and the installation locations of the multiple media parameter monitors, the theoretical media parameters of the other media parameter monitors are obtained; Obtain the actual media parameters of the other media parameter monitors; Based on the theoretical and actual medium parameters, multiple abnormal medium parameter monitors are obtained. The location of the anomaly is determined based on the multiple abnormal medium parameter monitors; The pipeline optimization module is used for: Install a media parameter monitor at the abnormal location; Match the corresponding pipeline auxiliary equipment based on the actual medium parameters on the medium parameter monitor and the theoretical medium parameters on the medium parameter monitor; Set the abnormal location to the installation location.

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