A heat network heater inlet and outlet water flow online monitoring device
By combining acquisition, judgment, and multiple maintenance positive modules, the problem of inaccurate monitoring of inlet and outlet water flow of heating network heaters was solved, and high-precision flow monitoring was achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2023-01-03
- Publication Date
- 2026-03-27
AI Technical Summary
In existing technologies, the accuracy of monitoring the inlet and outlet water flow rates of heating network heaters is relatively low, which affects the progress of subsequent work.
The initial flow rate and predicted flow rate are obtained by the acquisition module, the judgment module determines whether correction is needed, the determination module obtains the correction factor, the correction module performs multiple corrections, and finally obtains the final flow rate of the heater inlet and outlet water.
This improves the accuracy and reliability of the inlet and outlet water flow rates of the heater.
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Figure CN116086551B_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of flow monitoring, more particularly, to an online monitoring device for inlet and outlet water flow of a heat network heater. BACKGROUND
[0002] The heat network heater is one of the main devices of the heat network system, and its main function is to heat the circulating water in the water supply system by using the steam extracted from the steam turbine or the steam introduced from the boiler to meet the heating requirements, thereby realizing cogeneration.
[0003] In the prior art, the inlet and outlet water flow of the heater is only monitored by a collection device, and there are many influencing factors, the monitoring accuracy is low, and the inlet and outlet water flow cannot be accurately obtained, thereby affecting the subsequent work.
[0004] Therefore, how to improve the accuracy of the inlet and outlet water flow monitoring of the heater is a technical problem to be solved at present. SUMMARY
[0005] The present application provides an online monitoring device for inlet and outlet water flow of a heat network heater to solve the technical problem of low monitoring accuracy of the inlet and outlet water flow of the heater in the prior art. The method is applied to the heat network heater, and the device comprises:
[0006] An acquisition module is configured to acquire the inlet and outlet water flow of the heater as an initial flow, acquire the steam quantity and the circulating water quantity, and obtain a predicted inlet and outlet water flow of the heater based on the steam quantity and the circulating water quantity as a predicted flow;
[0007] A judgment module is configured to judge whether the initial flow needs to be corrected based on the initial flow and the predicted flow;
[0008] A determination module is configured to acquire an influence parameter and a device parameter if the initial flow needs to be corrected, and obtain a correction factor based on the influence parameter and the device parameter;
[0009] A correction module is configured to correct the initial flow in multiple dimensions based on the correction factor to obtain the inlet and outlet water flow of the heater as a final flow.
[0010] In some embodiments of the present application, the judgment module is specifically configured to:
[0011] If the difference between the initial flow and the predicted flow is within a preset interval, the initial flow does not need to be corrected;
[0012] If the difference between the initial flow and the predicted flow is not within the preset interval, the initial flow needs to be corrected.
[0013] In some embodiments of the present application, the device further comprises a compensation module configured to:
[0014] If the difference between the initial flow rate and the predicted flow rate is within a preset interval, a compensation value is determined based on the difference between the initial flow rate and the predicted flow rate, and a final flow rate is obtained based on the compensation value and the initial flow rate.
[0015] In some embodiments of the present application, the determining module comprises a first module, which is specifically configured to:
[0016] The correction factor comprises a first correction factor, and the first correction factor comprises a heater correction factor and a heat exchanger correction factor.
[0017] The device parameters comprise heater basic parameters and heat exchanger basic parameters.
[0018] The heater correction factor and the heat exchanger correction factor are determined based on the heater basic parameters and the heat exchanger basic parameters.
[0019] In some embodiments of the present application, the determining module further comprises a second module, which is specifically configured to:
[0020] The correction factor further comprises a second correction factor.
[0021] The second correction factor is obtained based on the influential parameters and the initial flow rate.
[0022] In some embodiments of the present application, the second module is specifically configured to:
[0023] A first state space is established according to the influential parameters, and a second state space is established according to the initial flow rate.
[0024] A nonlinear dependence is obtained according to the first state space and the second state space.
[0025] If the nonlinear dependence exceeds a preset value, the corresponding influential parameter is an influential parameter, and the second correction factor is obtained based on the nonlinear dependence.
[0026] In some embodiments of the present application, the correcting module is specifically configured to:
[0027] The initial flow rate is first multi-dimensionally corrected based on the first correction factor to obtain a first corrected flow rate, comprising:
[0028] The initial flow rate is corrected based on the heater correction factor to obtain a corrected initial flow rate, a compensation value is determined based on the corrected initial flow rate, and a first flow rate is obtained based on the corrected initial flow rate and the compensation value.
[0029] The first flow rate is corrected based on the heat exchanger correction factor to obtain a second corrected flow rate.
[0030] In some embodiments of the present application, the correcting module is specifically configured to:
[0031] secondly multi-dimensionally correct the initial flow based on the second correction factor to obtain a secondly corrected flow, comprising:
[0032] determining a correction order of the influential parameters with influence according to the size of each second correction factor;
[0033] correcting the initial flow according to the second correction factor in the correction order, and after each correction, determining a corresponding compensation value according to the corrected value, compensating according to the compensation value, and based on the corrected value and the compensation value, correcting next time, and finally obtaining the secondly corrected flow.
[0034] In some embodiments of the application, the correction module is further specifically used for:
[0035] determining a first weight based on the firstly corrected flow and a second weight based on the secondly corrected flow;
[0036] obtaining a corrected heater inlet and outlet water flow based on the firstly corrected flow, the first weight, the secondly corrected flow and the second weight as a final flow.
[0037] In some embodiments of the application, the device further comprises a second module, which is used for:
[0038] establishing a Markov model under a normal state of the heater, establishing a Markov model under a fault state of the heater, obtaining a heater fault frequency based on the Markov model under the normal state of the heater and the Markov model under the fault state of the heater, and adjusting the correction factor of the heater based on the heater fault frequency;
[0039] establishing a Markov model under a normal state of the heat exchanger, establishing a Markov model under a fault state of the heat exchanger, obtaining a heat exchanger fault frequency based on the Markov model under the normal state of the heat exchanger and the Markov model under the fault state of the heat exchanger, and adjusting the correction factor of the heat exchanger based on the heat exchanger fault frequency.
[0040] By applying the above technical solutions, the obtaining module is used to obtain the heater inlet and outlet water flow as the initial flow, obtain the steam quantity and the circulating water quantity, and obtain the predicted heater inlet and outlet water flow based on the steam quantity and the circulating water quantity as the predicted flow; the judging module is used to judge whether the initial flow needs to be corrected based on the initial flow and the predicted flow; the determining module is used to obtain the influential parameters and the equipment parameters based on the initial flow needs to be corrected; the correction module is used to multi-dimensionally correct the initial flow based on the correction factor to obtain the heater inlet and outlet water flow as the final flow. The application improves the accuracy and reliability of the heater inlet and outlet water flow by multi-dimensionally correcting the initial flow multiple times based on the equipment parameters and the influential parameters. BRIEF DESCRIPTION OF DRAWINGS
[0041] To more clearly illustrate the technical solutions in the embodiments of this application, 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 this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0042] Figure 1 A schematic diagram of the structure of an online monitoring device for the inlet and outlet water flow of a heating network heater, as proposed in an embodiment of the present invention, is shown. Detailed Implementation
[0043] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0044] This application provides an online monitoring device for the inlet and outlet water flow rates of a heating network heater, which is applied in a heating network heater, such as... Figure 1 As shown, the device includes the following modules:
[0045] The acquisition module 201 is used to acquire the inlet and outlet water flow rates of the heater as the initial flow rate, acquire the steam volume and circulating water volume, and obtain the predicted inlet and outlet water flow rates of the heater based on the steam volume and circulating water volume as the predicted flow rate.
[0046] In this embodiment, the initial flow rate is obtained directly from the data collected by the sensor. The heater's function is to use steam extracted from the turbine or steam drawn from the boiler to heat the circulating water in the hot water supply system to meet heating requirements. The inlet and outlet flow rates of the heater are predicted based on the steam volume and the circulating water volume.
[0047] The judgment module 202 is used to determine whether the initial flow needs to be corrected based on the initial flow and the predicted flow.
[0048] To improve the accuracy of the judgment, in some embodiments of this application, the judgment module 202 is specifically used to: if the difference between the initial flow and the predicted flow is within a preset range, then the initial flow does not need to be corrected; if the difference between the initial flow and the predicted flow is not within the preset range, then the initial flow needs to be corrected.
[0049] In some embodiments of this application, the device further includes a compensation module, configured to: determine a compensation value based on the difference between the initial flow and the predicted flow if the difference between the initial flow and the predicted flow is within a preset range, and obtain the final flow based on the compensation value and the initial flow.
[0050] In this embodiment, the final flow rate is the sum of the compensation value and the initial flow rate. The predicted flow rate is only a theoretical value and is not completely accurate. The compensation value is determined based on the difference between the initial flow rate and the predicted flow rate, so as to improve the accuracy of the flow rate.
[0051] The determination module 203 is configured to obtain an influence parameter and an equipment parameter if the initial flow rate needs to be corrected, and obtain a correction factor based on the influence parameter and the equipment parameter.
[0052] In this embodiment, if the initial flow rate needs to be corrected, the correction is performed from two aspects of the influence parameter and the equipment parameter. The influence parameter includes the amount of silicon in the drain water, the amount of water supplement in the main pipe network, the water level of the heater, the amount of drain water greater than the steam flow rate, the water supply pressure and temperature, the pH value and oxygen content of the circulating water, and other parameters that may affect the water in and out. The equipment parameter includes basic parameters of the heat exchanger and the heater, such as model, pressure, heat exchange area, etc. The corresponding correction factor is obtained based on the influence parameter and the equipment parameter.
[0053] In order to improve the accuracy of the correction factor, in some embodiments of the present application, the determination module 203 includes a first module, which is specifically configured to: the correction factor includes a first correction factor, the first correction factor includes a heater correction factor and a heat exchanger correction factor; the equipment parameter includes basic parameters of the heater and the heat exchanger; and the heater correction factor and the heat exchanger correction factor are determined based on the basic parameters of the heater and the heat exchanger.
[0054] In this embodiment, the basic parameters of the equipment parameter are normalized, and finally a comprehensive score of the equipment is obtained. According to the comprehensive score and a preset correction factor table, the corresponding correction factor is determined. The correction factor table has a corresponding correction factor for each interval score.
[0055] In some embodiments of the present application, the correction module 204 is specifically configured to: perform a first multi-dimensional correction on the initial flow rate based on the first correction factor to obtain a first corrected flow rate, including: correcting the initial flow rate based on the heater correction factor to obtain a corrected initial flow rate, determining a compensation value based on the corrected initial flow rate, and obtaining a first flow rate based on the corrected initial flow rate and the compensation value; and correcting the first flow rate based on the heat exchanger correction factor to obtain the first corrected flow rate.
[0056] In this embodiment, the multi-dimensional correction refers to correction in multiple aspects and in a certain order, and the compensation value is added after each correction, so as to improve the accuracy of the next correction. According to the first correction factor, the first multi-dimensional correction is performed twice. First, the initial flow rate is corrected based on the heater correction factor, the compensation value is determined based on the corrected initial flow rate, and the first flow rate is the sum of the corrected initial flow rate and the compensation value. Then, the first flow rate is corrected based on the heat exchanger correction factor to obtain the first corrected flow rate.
[0057] In some embodiments of the present application, the determining module further comprises a second module, which is specifically configured to: the correction factor further comprises a second correction factor; and the influential parameter with influence is screened based on the initial flow, and the second correction factor is obtained based on the influential parameter with influence.
[0058] In some embodiments of the present application, the second module is specifically configured to: a first state space is established according to the influential parameter, and a second state space is established according to the initial flow; a nonlinear dependence degree is obtained according to the first state space and the second state space; if the nonlinear dependence degree exceeds a preset value, the corresponding influential parameter is the influential parameter with influence, and the second correction factor is obtained based on the nonlinear dependence degree.
[0059] In the present embodiment, the influential parameter is only a factor that may affect the water inflow and outflow according to subjective consciousness and theory, and needs to be screened.
[0060] All the influential parameters and the initial flow are subjected to state space establishment, and all possible combinations are performed two by two. It is noted that the influential parameters and the initial flow are combined two by two, and the time of the influential parameters is before or at the time of the initial flow. The first state space is set as X, and the second state space is set as Y. The Euclidean distance average value of Xn and k neighboring points is calculated, and the formula is as follows:
[0061]
[0062] For the sample point xn in X, xrn, 1, xrn, 2, … xrn, k represent k neighboring points of xn in X.
[0063] For the sample point yn in Y, ysn, 1, ysn, 2, … ysn, k represent k neighboring points of yn in Y, which are mapped into the X space. The Euclidean distance average value of xn and k neighboring points xsn, 1, xsn, 2, … xsn, k is calculated, and the formula is as follows:
[0064]
[0065] The causal relationship between the two is determined according to the mapping relationship of the state space, and the nonlinear dependence degree formula is as follows:
[0066]
[0067] 0 < S X→Y ≤ 1, S X→Y tends to 0 (less than a preset threshold value), the state spaces X and Y are independent of each other, that is, the influential parameter and the initial flow are independent of each other, and there is no causal relationship between the two. S X→YObviously greater than 0, there is a causal relationship between X to Y, that is, the causal relationship of the impact parameter and the initial flow. S X→Y The greater the causality is, the stronger the causality is.
[0068] In some embodiments of the present application, the correction module is specifically configured to: based on the second correction factor, perform second multi-dimensional correction on the initial flow to obtain a second correction flow, including: determining a correction order of the influential impact parameters according to the size of each second correction factor; and according to the second correction factor, sequentially correcting the initial flow in the correction order, and after each correction, determining a corresponding compensation value according to the corrected value, compensating according to the compensation value, and based on the corrected value and the compensation value, performing the next correction, and finally obtaining the second correction flow.
[0069] In this embodiment, the larger the second correction factor is, the earlier the correction order is. For example, the influential impact parameters after screening are three, including the amount of hydrophobic silicon, the amount of main pipe network water supplement, and the water supply pressure, which need to be corrected three times.
[0070] If the second correction factors corresponding to the three parameters of the amount of hydrophobic silicon, the amount of main pipe network water supplement, and the water supply pressure are set to be smaller and smaller, then the initial flow is corrected in the order of the amount of hydrophobic silicon, the amount of main pipe network water supplement, and the water supply pressure;
[0071] If the second correction factors corresponding to the three parameters of the amount of hydrophobic silicon, the amount of main pipe network water supplement, and the water supply pressure are set to be smaller and smaller, then the initial flow is corrected in the order of the amount of hydrophobic silicon, the amount of main pipe network water supplement, and the water supply pressure;
[0072] First correction:
[0073] The corrected flow is Q1*A, the first compensation value is determined according to the size of Q1*A, and the value after the first correction is Q1*A+the first compensation value;
[0074] Second correction:
[0075] The corrected flow is (Q1*A+the first compensation value)Q2, the second compensation value is determined according to the size of (Q1*A+the first compensation value)Q2, and the value after the first correction is (Q1*A+the first compensation value)Q2+the second compensation value;
[0076] Third correction:
[0077] The corrected flow is ((Q1*A+the first compensation value)Q2+the second compensation value)Q3, and the second correction flow is ((Q1*A+the first compensation value)Q2+the second compensation value)Q3.
[0078] The compensation value can be obtained according to a preset compensation table corresponding to the parameter, the compensation table includes the compensation value corresponding to the corrected flow, and the compensation value is used to pave the next correction, therefore, the last correction does not need to add the compensation value.
[0079] The correction module 204 is configured to correct the initial flow in multiple dimensions based on the correction factor to obtain the heater inlet and outlet water flow as the final flow.
[0080] In some embodiments of the present application, the correction module 204 is further configured to determine a first weight based on the first correction flow, determine a second weight based on the second correction flow, and obtain the corrected heater inlet and outlet water flow based on the first correction flow, the first weight, the second correction flow, and the second weight as the final flow.
[0081] To improve the accuracy of the first correction factor, in some embodiments of the present application, the device further comprises a second module configured to establish a Markov model under normal state of the heater, establish a Markov model under fault state of the heater, obtain a fault frequency of the heater based on the Markov model under normal state of the heater and the Markov model under fault state of the heater, and adjust the correction factor of the heater based on the fault frequency of the heater; establish a Markov model under normal state of the heat exchanger, establish a Markov model under fault state of the heat exchanger, obtain a fault frequency of the heat exchanger based on the Markov model under normal state of the heat exchanger and the Markov model under fault state of the heat exchanger, and adjust the correction factor of the heat exchanger based on the fault frequency of the heat exchanger.
[0082] In this embodiment, the fault rate and the repair rate of the heater are obtained based on the Markov model under normal state of the heater and the Markov model under fault state of the heater, and the fault frequency is obtained according to the fault rate and the repair rate. Let λ and μ be the fault rate and the repair rate of the device respectively, and let f be the fault frequency. The process is as follows:
[0083]
[0084] The fault condition of the device will to some extent reflect the degradation of the device, and the correction factor of the device needs to be corrected accordingly. The first correction flow is obtained according to the corrected correction factor of the device.
[0085] By applying the above technical solutions, the obtaining module is configured to obtain the heater inlet and outlet water flow as the initial flow, obtain the steam quantity and the circulating water quantity, and obtain the predicted heater inlet and outlet water flow based on the steam quantity and the circulating water quantity as the predicted flow; the judging module is configured to judge whether the initial flow needs to be corrected based on the initial flow and the predicted flow; the determining module is configured to obtain the influence parameter and the device parameter if the initial flow needs to be corrected, and obtain the correction factor based on the influence parameter and the device parameter; and the correction module is configured to correct the initial flow in multiple dimensions based on the correction factor to obtain the heater inlet and outlet water flow as the final flow. The present application improves the accuracy and reliability of the heater inlet and outlet water flow by correcting the initial flow in multiple dimensions based on the device parameter and the influence parameter.
[0086] Those skilled in the art can understand that the modules in the device in the implementation scenario can be distributed in the device in the implementation scenario according to the description of the implementation scenario, or can be changed to be located in one or more devices different from the implementation scenario. The modules of the above implementation scenario can be combined into one module, or can be further split into multiple sub-modules.
[0087] Finally, it should be noted that: the above examples are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing examples, those skilled in the art can understand that the technical solutions recorded in the foregoing examples can still be modified, or some technical features can be replaced by equivalents; and these modifications or replacements do not drive the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.
Claims
1. A heat supply network heater inlet and outlet water flow online monitoring device applied to a heat supply network heater, characterized in that, The device comprises: an acquisition module, configured to acquire a heater inlet and outlet water flow as an initial flow, acquire a steam amount and a circulating water amount, and obtain a predicted heater inlet and outlet water flow based on the steam amount and the circulating water amount as a predicted flow; a judgment module, configured to judge whether the initial flow needs to be corrected based on the initial flow and the predicted flow; a determination module, configured to, if the initial flow needs to be corrected, acquire an influence parameter and an equipment parameter, and obtain a correction factor based on the influence parameter and the equipment parameter; a correction module, configured to correct the initial flow in multiple dimensions based on the correction factor to obtain a heater inlet and outlet water flow as a final flow; The judgment module is specifically configured to: if a difference between the initial flow and the predicted flow is within a preset interval, the initial flow does not need to be corrected; if the difference between the initial flow and the predicted flow is not within the preset interval, the initial flow needs to be corrected; The device further comprises a compensation module, configured to: if the difference between the initial flow and the predicted flow is within the preset interval, determine a compensation value based on the difference between the initial flow and the predicted flow, and obtain the final flow based on the compensation value and the initial flow.
2. The apparatus of claim 1, wherein, The determination module comprises a first module, which is specifically configured to: the correction factor comprises a first correction factor, the first correction factor comprises a heater correction factor and a heat exchanger correction factor; the equipment parameter comprises a heater basic parameter and a heat exchanger basic parameter; the heater correction factor and the heat exchanger correction factor are determined based on the heater basic parameter and the heat exchanger basic parameter.
3. The apparatus of claim 2, wherein, The determination module further comprises a second module, which is specifically configured to: the correction factor further comprises a second correction factor; influential influence parameters are screened out based on the influence parameter and the initial flow, and the second correction factor is obtained based on the influential influence parameters.
4. The apparatus of claim 3, wherein, The second module is specifically configured to: a first state space is established according to the influence parameter, and a second state space is established according to the initial flow; a nonlinear dependence degree is obtained according to the first state space and the second state space; if the nonlinear dependence degree exceeds a preset value, the corresponding influence parameter is an influential influence parameter, and the second correction factor is obtained based on the nonlinear dependence degree.
5. The apparatus of claim 2, wherein, The correction module is specifically configured to: the initial flow is corrected in a first multiple dimension based on the first correction factor to obtain a first corrected flow, including: the initial flow is corrected based on the heater correction factor to obtain a corrected initial flow, a compensation value is determined based on the corrected initial flow, and a first flow is obtained based on the corrected initial flow and the compensation value; the first flow is corrected based on the heat exchanger correction factor to obtain the first corrected flow.
6. The apparatus of claim 3, wherein, The correction module is specifically configured to: the initial flow is corrected in a second multiple dimension based on the second correction factor to obtain a second corrected flow, including: a correction order of the influential influence parameters is determined according to the size of each second correction factor; the initial flow is corrected according to the second correction factor in the correction order, and after each correction, a corresponding compensation value is determined according to the corrected value, corresponding compensation is performed according to the compensation value, the next correction is performed based on the corrected value and the compensation value, and finally the second corrected flow is obtained.
7. The apparatus of claim 6, wherein, The correction module is further specifically configured to: The first multi-dimensional correction is performed on the initial flow based on the first correction factor to obtain a first-revised flow; The second multi-dimensional correction is performed on the initial flow based on the second correction factor to obtain a second-revised flow; The first weight is determined based on the first-revised flow, and the second weight is determined based on the second-revised flow; The corrected heater inlet and outlet water flow is obtained based on the first-revised flow, the first weight, the second-revised flow and the second weight, and is taken as the final flow.
8. The apparatus of claim 2, wherein, The device further comprises an adjusting module, which is configured to: establish a Markov model under a normal state of the heater, establish a Markov model under a fault state of the heater, obtain a heater fault frequency based on the Markov model under the normal state of the heater and the Markov model under the fault state of the heater, and adjust the heater correction factor based on the heater fault frequency; establish a Markov model under a normal state of the heat exchanger, establish a Markov model under a fault state of the heat exchanger, obtain a heat exchanger fault frequency based on the Markov model under the normal state of the heat exchanger and the Markov model under the fault state of the heat exchanger, and adjust the heat exchanger correction factor based on the heat exchanger fault frequency.
Citation Information
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Boiler main steam flowmeter on-line checking and testing system based on Internet-of-Things technology
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