A smart city hydropower station sensing detection method and system

Abstract

The embodiment of the present invention provides a method and system for sensing and detecting a hydropower station in a smart city, belonging to the technical field of water and electricity flow detection. It includes: obtaining a simulated and drawn hydropower flow diagram of a hydropower station unit; obtaining current sensor information reflecting the working status of each component in the hydropower station unit, and displaying the current sensor information at the designated position corresponding to each component in the hydropower flow diagram; determining the estimated fault time and estimated fault type corresponding to the current sensor information; and determining and executing the current display effect corresponding to the current estimated fault time and the current fault type based on the correspondence between the preset estimated fault time and the estimated fault type and the display effect. The present invention can obtain the operation and detection results of the generator unit, estimate the service life of the generator, and finally complete the repair or replacement of the generator, thereby avoiding the waste of energy, loss of resources and huge safety hazards caused by real problems.

Description

Technical Field

[0001] The present invention relates to the technical field of hydroelectric flow detection, and in particular to a sensing detection method and system for a smart city hydropower station. Background Art

[0002] Smart cities are a recently emerging field, primarily originating in the media industry. They utilize various information technologies and innovative concepts to connect and integrate urban systems and services to improve resource efficiency, optimize urban management and services, and enhance the quality of life for citizens. Hydropower generation is currently a crucial component of the orderly management of smart cities. Residents' lives are increasingly dependent on the power system, and a power system failure can paralyze the entire city.

[0003] At present, hydropower generation mainly supplies the generated electricity directly or indirectly to cities. Due to the large uncertainty of hydropower generation, it often suffers damage, and the damage process has a lag, which ultimately leads to energy waste and resource loss. Summary of the Invention

[0004] The purpose of the embodiments of the present invention is to provide a smart city hydropower station sensing detection method and system. The smart city hydropower station sensing detection method and system can obtain the operation and detection results of the generator set, estimate the service life of the generator, and ultimately complete the repair or replacement of the generator, avoiding the waste of energy, loss of resources and huge safety hazards caused by real problems.

[0005] To achieve the above objectives, an embodiment of the present invention provides a smart city hydropower station sensing detection method, the smart city hydropower station sensing detection method comprising:

[0006] Obtain the simulated hydropower flow diagram of the hydropower station unit;

[0007] Acquiring current sensor information reflecting the working status of each component in the hydropower station unit, and displaying the current sensor information at a designated position corresponding to each component in the hydropower flow diagram;

[0008] Determining an estimated fault time and an estimated fault type corresponding to the current sensor information; and

[0009] According to the preset correspondence between the estimated fault time and the estimated fault type and the display effect, the current display effect corresponding to the current estimated fault time and the current fault type is determined and executed.

[0010] Preferably, determining the estimated fault time and the estimated fault type corresponding to the current sensor information includes:

[0011] Obtaining historical fault types and their corresponding historical sensor information in a previously preset time period; and

[0012] The current sensor information is compared with the historical sensor information, and an estimated fault time and an estimated fault type corresponding to the current sensor information are determined according to the comparison result.

[0013] Preferably, the historical sensor information includes historical sensor values ​​and their change rates;

[0014] Furthermore, comparing the current sensor information with the historical sensor information and determining the estimated fault time and the estimated fault type corresponding to the current sensor information according to the comparison result includes:

[0015] Determining an error range threshold for the historical sensor values ​​and their rate of change;

[0016] Obtain the number of times the current sensor value and its rate of change have continuously overlapped with the error range threshold;

[0017] When the number of consecutive overlaps exceeds a preset number threshold, the historical fault type corresponding to the error range threshold and the interval time from the occurrence of the fault in history are obtained, the historical fault type is used as the estimated fault type, and the estimated fault time is determined based on the interval time.

[0018] Preferably, the smart city hydropower station sensing detection method further includes: determining the probability of a fault occurring based on the number of consecutive overlaps.

[0019] Preferably, the determination of the probability of a fault occurrence based on the number of consecutive reclosing times is configured to be associated with a ratio of the number of consecutive reclosing times to a total number of times acquired in a previous preset time period.

[0020] Preferably, the current sensor information includes: current parameters, unit temperature parameters, active power parameters, and reactive power parameters.

[0021] In addition, the present invention also provides a smart city hydropower station sensing detection system, the smart city hydropower station sensing detection system comprising:

[0022] A diagram acquisition unit, used to acquire a simulated hydropower flow diagram of a hydropower station unit;

[0023] an information display unit, configured to obtain current sensor information reflecting the working status of each component in the hydropower station unit, and display the current sensor information at a designated position corresponding to each component in the hydropower flow diagram;

[0024] a time type determination unit, configured to determine an estimated fault time and an estimated fault type corresponding to the current sensor information; and

[0025] The effect determination unit is used to determine and execute the current display effect corresponding to the current estimated fault time and the current fault type according to the correspondence between the preset estimated fault time and the estimated fault type and the display effect.

[0026] Preferably, the time type determination unit includes:

[0027] A history acquisition module, used to obtain historical fault types and their corresponding historical sensor information in a previous preset time period; and

[0028] The time type determination module is used to compare the current sensor information with the historical sensor information, and determine the estimated fault time and the estimated fault type corresponding to the current sensor information according to the comparison result.

[0029] Preferably, the historical sensor information includes historical sensor values ​​and their change rates;

[0030] Furthermore, the time type determination module includes:

[0031] A threshold determination submodule, configured to determine an error range threshold of the historical sensor value and its rate of change;

[0032] The number acquisition submodule is used to obtain the number of times the current sensor value and its change rate have continuously overlapped with the error range threshold;

[0033] The time type determination submodule is used to obtain the historical fault type corresponding to the error range threshold and the interval time from the occurrence of the fault in history when the number of consecutive overlaps exceeds a preset number threshold, use the historical fault type as the estimated fault type, and determine the estimated fault time based on the interval time.

[0034] Preferably, the smart city hydropower station sensing detection system further includes: a probability determination unit, configured to determine the probability of a fault occurring based on the number of consecutive overlaps.

[0035] Through the above technical solution, the present invention can automatically obtain the operation and detection results of the generator set, estimate the failure probability and service life of the generator, and then facilitate the maintenance or replacement of the hydropower station unit in the generator, thereby avoiding the waste of energy caused by problems and avoiding huge safety hazards after failures.

[0036] Other features and advantages of the embodiments of the present invention will be described in detail in the subsequent detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following detailed description, they are used to explain the embodiments of the present invention, but do not constitute a limitation of the embodiments of the present invention. In the accompanying drawings:

[0038] Figure 1 It is a flow chart illustrating a smart city hydropower station sensing detection method of the present invention.

[0039] Figure 2 This is a diagram illustrating the hydropower tidal current display effect of the present invention;

[0040] Figure 3 is a display effect diagram illustrating current sensor information of the present invention; and

[0041] Figure 4 It is a module block diagram illustrating a smart city hydropower station sensing detection system of the present invention. DETAILED DESCRIPTION

[0042] The following describes the specific implementation of the embodiment of the present invention in detail with reference to the accompanying drawings. It should be understood that the specific implementation described herein is only used to illustrate and explain the embodiment of the present invention and is not used to limit the embodiment of the present invention.

[0043] Figure 1 This is a flow chart of a smart city hydropower station sensing detection method of the present invention, such as Figure 1 As shown, the smart city hydropower station sensing detection method includes:

[0044] S101, obtain the simulated hydropower flow diagram of the hydropower station unit; its specific display effect is as follows Figure 2 shown.

[0045] S102, obtaining current sensor information reflecting the working status of each component in the hydropower station unit, and displaying the current sensor information at the designated position corresponding to each component in the hydropower flow diagram; wherein, Figure 2 As shown, select the "Real-time Data" menu item in the "Real-time Data" menu, or click the "X" button on the toolbar to enter the real-time data dialog box shown in the figure; in the real-time data dialog box, select the station and device in the tree diagram on the left, and then select the label on the right to view the relevant data of the selected device. The color of the data in the data value column indicates the different status of the data. Green or red indicates normal collection data, gray indicates invalid data, and blue indicates manually set data.

[0046] S103: Determine an estimated fault time and an estimated fault type corresponding to the current sensor information. The estimated fault time is the estimated time point at which a fault may occur corresponding to the current sensor information. The estimated fault type is the type of fault estimated based on the sensor information, such as overvoltage, loose generator rotor, or generator shaft damage.

[0047] S104: Based on the pre-set correspondence between the estimated fault time and the estimated fault type and the display effect, a current display effect corresponding to the current estimated fault time and the current fault type is determined and executed. The display effect color gradually darkens based on the interval between the estimated fault times, while the color of the estimated fault type increases with severity. The fault size is pre-stored, with different colors corresponding to different fault sizes.

[0048] Preferably, the step S103 of determining the estimated fault time and the estimated fault type corresponding to the current sensor information may include:

[0049] Obtaining historical fault types and their corresponding historical sensor information in a previously preset time period; and

[0050] The current sensor information is compared with the historical sensor information, and the estimated fault time and the estimated fault type corresponding to the current sensor information are determined according to the comparison result.

[0051] Among them, the previous preset time period is a preset time period in advance, such as 7 days, and the sensor information is data collected at every time point, such as 1 hour. The estimated fault time is the estimated time point when the fault occurs and the estimated fault type is the specific type of fault that is estimated to occur.

[0052] Preferably, the historical sensor information includes historical sensor values ​​and their change rates; the change rate is the change rate between a sampling point and a previous sampling point.

[0053] Furthermore, comparing the current sensor information with the historical sensor information and determining the estimated fault time and the estimated fault type corresponding to the current sensor information according to the comparison result may include:

[0054] Determine the error range threshold for the historical sensor values ​​and their rate of change. For example, taking the current parameter as an example, the historical sensor values ​​are 12A, 11.1A, 11.0A, 10.9A, and 10.2A. With these as the center point, the error range threshold is within a range of 0.1A above and below the center point. For example, the first value range is between 11.9 and 12.1A, and so on. The 0.1A threshold value can be determined based on actual conditions.

[0055] Get the number of times the current sensor value and its rate of change have consecutively overlapped with the error range threshold. For example, if the current sensor value has previously been within the error range four times, and this is the fifth time, then the number of consecutive overlaps is five.

[0056] When the number of consecutive reclosings exceeds a preset number threshold, the historical fault type corresponding to the error range threshold and the interval time from the occurrence of the fault in history are obtained, and the historical fault type is used as the estimated fault type, and the estimated fault time is determined based on the interval time. The number threshold can be 20 times. For example, taking the current parameter as an example, when its value is under a certain change (the value is within an interval), it is determined that the historical fault type corresponding to the current parameter is valve damage, then valve damage is used as the estimated fault type. For example, if the current number of consecutive reclosings is 32 times, then the estimated fault time is 5 days and 16 hours later, and the calculation method is 168-32=136.

[0057] Preferably, the smart city hydropower station sensing detection method may further include: determining the probability of a fault occurring based on the number of consecutive overlaps.

[0058] Preferably, the probability of a fault occurring determined based on the number of consecutive reclosings is configured to be associated with a ratio of the number of consecutive reclosings to the total number of times acquired in a previous preset time period, for example, the ratio is 32 / 136, which is approximately equal to 23.5%.

[0059] Preferably, the current sensor information includes: current parameters, unit temperature parameters, active power parameters, and reactive power parameters. Figure 3 This is a diagram showing the specific values ​​after the sensor is clicked.

[0060] In addition, the present invention also provides a smart city hydropower station sensing detection system, the smart city hydropower station sensing detection system comprising:

[0061] A diagram acquisition unit, used to acquire a simulated hydropower flow diagram of a hydropower station unit;

[0062] an information display unit, configured to obtain current sensor information reflecting the working status of each component in the hydropower station unit, and display the current sensor information at a designated position corresponding to each component in the hydropower flow diagram;

[0063] a time type determination unit, configured to determine an estimated fault time and an estimated fault type corresponding to the current sensor information; and

[0064] The effect determination unit is used to determine and execute the current display effect corresponding to the current estimated fault time and the current fault type according to the correspondence between the preset estimated fault time and the estimated fault type and the display effect.

[0065] Preferably, the time type determination unit includes:

[0066] A history acquisition module, used to obtain historical fault types and their corresponding historical sensor information in a previous preset time period; and

[0067] The time type determination module is used to compare the current sensor information with the historical sensor information, and determine the estimated fault time and the estimated fault type corresponding to the current sensor information according to the comparison result.

[0068] Preferably, the historical sensor information includes historical sensor values ​​and their change rates;

[0069] Furthermore, the time type determination module includes:

[0070] A threshold determination submodule, configured to determine an error range threshold of the historical sensor value and its rate of change;

[0071] The number acquisition submodule is used to obtain the number of times the current sensor value and its change rate have continuously overlapped with the error range threshold;

[0072] The time type determination submodule is used to obtain the historical fault type corresponding to the error range threshold and the interval time from the occurrence of the fault in history when the number of consecutive overlaps exceeds a preset number threshold, use the historical fault type as the estimated fault type, and determine the estimated fault time based on the interval time.

[0073] Preferably, the smart city hydropower station sensing detection system further includes: a probability determination unit, configured to determine the probability of a fault occurring based on the number of consecutive overlaps.

[0074] Among them, compared with the existing technology, the smart city hydropower station sensing detection system has the same distinguishing technical features and technical effects as the smart city hydropower station sensing detection method, which will not be repeated here.

[0075] The above are merely embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A sensing detection method for a smart city hydropower station, characterized in that: The smart city hydropower station sensing detection method includes: Obtain the simulated hydropower flow diagram of the hydropower station unit; Acquiring current sensor information reflecting the working status of each component in the hydropower station unit, and displaying the current sensor information at a designated position corresponding to each component in the hydropower flow diagram; Determining an estimated fault time and an estimated fault type corresponding to the current sensor information; and According to the preset correspondence between the estimated fault time and the estimated fault type and the display effect, determine and execute the current display effect corresponding to the current estimated fault time and the current fault type; Determining the estimated fault time and the estimated fault type corresponding to the current sensor information includes: Obtaining historical fault types and their corresponding historical sensor information in a previously preset time period; and Comparing the current sensor information with the historical sensor information, and determining an estimated fault time and an estimated fault type corresponding to the current sensor information based on the comparison result; The historical sensor information includes historical sensor values ​​and their change rates; Furthermore, comparing the current sensor information with the historical sensor information and determining the estimated fault time and the estimated fault type corresponding to the current sensor information according to the comparison result includes: Determining an error range threshold for the historical sensor values ​​and their rate of change; Obtain the number of times the current sensor value and its rate of change have continuously overlapped with the error range threshold; When the number of consecutive overlaps exceeds a preset number threshold, the historical fault type corresponding to the error range threshold of the last overlap and the interval time from the occurrence of the fault in history are obtained, and the historical fault type is used as the estimated fault type, and the estimated fault time is determined based on the interval time.

2. The smart city hydropower station sensing detection method according to claim 1, characterized in that: The smart city hydropower station sensing detection method further includes: determining the probability of a fault occurring based on the number of consecutive overlaps.

3. The sensing detection method for a smart city hydropower station according to claim 2, characterized in that: The determination of the probability of a fault occurrence based on the number of consecutive reclosing times is configured to be associated with a ratio of the number of consecutive reclosing times to a total number of times acquired in a previous preset time period.

4. The sensing detection method for a smart city hydropower station according to claim 1, characterized in that: The current sensor information includes: current parameters, unit temperature parameters, active power parameters, and reactive power parameters.

5. A smart city hydropower station sensing detection system, characterized in that: The smart city hydropower station sensing detection system includes: A diagram acquisition unit, used to acquire a simulated hydropower flow diagram of a hydropower station unit; an information display unit, configured to obtain current sensor information reflecting the working status of each component in the hydropower station unit, and display the current sensor information at a designated position corresponding to each component in the hydropower flow diagram; a time type determination unit, configured to determine an estimated fault time and an estimated fault type corresponding to the current sensor information; and An effect determination unit, configured to determine and execute a current display effect corresponding to a current estimated fault time and a current fault type according to a preset correspondence between the estimated fault time and the estimated fault type and the display effect; The time type determination unit includes: A history acquisition module, used to obtain historical fault types and their corresponding historical sensor information in a previous preset time period; and a time type determination module, configured to compare current sensor information with the historical sensor information, and determine an estimated fault time and an estimated fault type corresponding to the current sensor information based on the comparison result; The historical sensor information includes historical sensor values ​​and their change rates; Furthermore, the time type determination module includes: A threshold determination submodule, configured to determine an error range threshold of the historical sensor value and its rate of change; The number acquisition submodule is used to obtain the number of times the current sensor value and its change rate have continuously overlapped with the error range threshold; The time type determination submodule is used to obtain the historical fault type corresponding to the error range threshold of the last overlap and the interval time from the occurrence of the fault in history when the number of consecutive overlaps exceeds a preset number threshold, use the historical fault type as the estimated fault type, and determine the estimated fault time based on the interval time.

6. The smart city hydropower station sensing detection system according to claim 5, characterized in that: The smart city hydropower station sensing detection system further includes: a probability determination unit, configured to determine the probability of a fault occurring based on the number of consecutive overlaps.

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