Method, device, equipment and storage medium for processing broadband measurement data

Abstract

The present invention provides a method, apparatus, device, and storage medium for processing broadband measurement data, relating to the technical field of power systems. The method comprises: obtaining broadband measurement data of a power system, such as power frequency, harmonic, and interharmonic measurements, wherein different types of broadband measurement data correspond to different standardized data structures; determining spectrum analysis results and cluster analysis results based on the broadband measurement data; and invoking a target query data interface to perform a data query in a target table of a target database, wherein the target table of the target database includes the broadband measurement data, spectrum analysis results, and cluster analysis results, wherein the table structure corresponding to the target table is predetermined using standard SQL syntax based on different types of broadband measurement data, and the target database is a file database with a self-describing table structure; and the target query data interface is determined based on different types of broadband measurement data. The present invention improves the flexibility of broadband measurement data application and data exchange.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and in particular to a method, device, equipment and storage medium for processing broadband measurement data. Background Art

[0002] With the massive access of new energy sources (such as wind power and photovoltaics) to modern power systems, more high-order harmonics and interharmonics have appeared in the power grid, which have an adverse effect on the stability and power quality of the system.

[0003] Existing broadband measurement data management systems primarily use traditional relational databases (such as MySQL or PostgreSQL) for storage. However, due to the fixed table structure and lack of self-describing capabilities, relational databases cannot intuitively express the specific content and structure of data. Especially in multi-business scenarios, traditional table structure designs cannot meet the requirements for rapid data exchange and reuse between different business systems in the power system, resulting in inconvenient applications and difficult data exchange. Summary of the Invention

[0004] In response to the technical problems in the prior art, the present invention provides a method, device, equipment and storage medium for processing broadband measurement data, which are used to solve the defects of broadband measurement data in the prior art, such as inconvenient application and difficult data exchange, and improve the flexibility of broadband measurement data application and data exchange.

[0005] In a first aspect, the present invention provides a method for processing broadband measurement data, the method comprising the following steps:

[0006] Acquire broadband measurement data of the power system; the broadband measurement data includes at least one of the following types: power frequency measurement, harmonic measurement, and interharmonic measurement, and different types of broadband measurement data correspond to different standardized data structures;

[0007] Determining spectrum analysis results and cluster analysis results based on the broadband measurement data;

[0008] A general target query data interface is called to perform data query in a target table of a target database; the target table of the target database includes the broadband measurement data, the spectrum analysis results, and the cluster analysis results; the table structure corresponding to the target table of the target database is predetermined based on different types of broadband measurement data using standard SQL syntax; the target database is a file database having a self-describing table structure; the target query data interface is predetermined based on different types of broadband measurement data.

[0009] According to a method for processing broadband measurement data provided by the present invention, before calling a universal target query data interface and performing a data query in a target table of a target database, the method further includes:

[0010] Calling a general target insertion data interface to write the broadband measurement data, the spectrum analysis results, and the cluster analysis results into a target table of a target database;

[0011] The target insertion data interface is predetermined based on different types of broadband measurement data.

[0012] According to a method for processing broadband measurement data provided by the present invention, any type of broadband measurement data is a broadband measurement and analysis extended structure WMAX structure, the main structure of the WMAX structure includes a device name field, a start time field, an end time field, and a structure of the broadband measurement data of the type; the target table includes a plant station table, an equipment table, a line table, a raw data measurement table, a broadband oscillation analysis record table, and a broadband oscillation statistics record table; the target insertion data interface includes a first insertion data interface, a second insertion data interface, and a third insertion data interface.

[0013] According to a method for processing broadband measurement data provided by the present invention, calling a universal target insertion data interface to write the broadband measurement data, the spectrum analysis results, and the cluster analysis results into a target table of a target database includes:

[0014] Calling the first data insertion interface to write the broadband measurement data into the corresponding raw data measurement table in the target database and the plant table, equipment table, and line table corresponding to the broadband measurement data;

[0015] calling the second data insertion interface to write the spectrum analysis result into the broadband oscillation analysis record table in the target database;

[0016] The third data insertion interface is called to write the cluster analysis result into the broadband oscillation statistical record table in the target database.

[0017] According to a method for processing broadband measurement data provided by the present invention, the target query data interface includes a first query data interface, a second query data interface, and a third query data interface; calling the universal target query data interface to perform data query in a target table of the target database includes:

[0018] Calling the first data insertion interface to query the broadband measurement data in the corresponding original measurement data table in the target database;

[0019] calling the second data insertion interface to query the spectrum analysis result in the broadband oscillation analysis record table;

[0020] The third data insertion interface is called to query the cluster analysis result in the broadband oscillation statistical record table.

[0021] According to a method for processing broadband measurement data provided by the present invention, the method further includes:

[0022] Visually displaying the broadband measurement data within a preset time period;

[0023] Conduct trend analysis based on the results of the visual display.

[0024] According to a method for processing broadband measurement data provided by the present invention, visually displaying the broadband measurement data within a preset time period includes:

[0025] Using the first timing curve to display the power frequency measurement data within a preset time period;

[0026] Displaying harmonic measurement data within the preset time period using the second timing curve and the first spectrum analysis graph;

[0027] The interharmonic measurement data within the preset time period is displayed using a third timing curve, a second spectrum analysis diagram, and a frequency table waterfall diagram; and the time axes of the first timing curve, the second timing curve, and the third timing curve are consistent.

[0028] In a second aspect, the present invention further provides a device for processing broadband measurement data, the device comprising the following modules:

[0029] An acquisition module is configured to acquire broadband measurement data of the power system; the broadband measurement data includes at least one of the following types: power frequency measurement, harmonic measurement, and interharmonic measurement, and different types of broadband measurement data correspond to different standardized data structures;

[0030] An analysis module, configured to determine a spectrum analysis result and a cluster analysis result based on the broadband measurement data;

[0031] A query module is configured to call a universal target query data interface to perform a data query in a target table of a target database; the target table of the target database includes the broadband measurement data, the spectrum analysis results, and the cluster analysis results; the table structure corresponding to the target table of the target database is predetermined using standard SQL syntax based on different types of broadband measurement data; the target database is a file database having a self-describing table structure; and the target query data interface is predetermined based on different types of broadband measurement data.

[0032] In a third aspect, the present invention further provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method for processing broadband measurement data as described above is implemented.

[0033] In a fourth aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-described methods for processing broadband measurement data.

[0034] In a fifth aspect, the present invention further provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements any one of the above-mentioned methods for processing broadband measurement data.

[0035] The broadband measurement data processing method, apparatus, device, and storage medium provided by the present invention obtain broadband measurement data of an electric power system; the types of broadband measurement data include at least one of the following: power frequency measurement, harmonic measurement, and interharmonic measurement, and different types of broadband measurement data correspond to different standardized data structures; then, based on the broadband measurement data, spectrum analysis results and cluster analysis results are determined; further, a general target query data interface is called to perform data query in a target table of a target database, the target table of the target database includes broadband measurement data, spectrum analysis results, and cluster analysis results, the table structure corresponding to the target table of the target database is predetermined based on different types of broadband measurement data using standard SQL syntax, the target database is a file database, and the file database is a database with a self-describing table structure; the target query data interface is predetermined based on different types of broadband measurement data.

[0036] The types of broadband measurement data in the present invention include at least one of the following: power frequency measurement, harmonic measurement, and interharmonic measurement. Different types of broadband measurement data correspond to different standardized data structures, that is, a unified data structure is designed. In addition, a target query data interface is predetermined based on the different types of broadband measurement data. The present invention performs data queries in a target table of a target database by calling a universal target query data interface. The present invention uses standard SQL syntax to predetermine the table structure corresponding to the target table of the target database based on different types of broadband measurement data. The target database is a file database with a self-describing table structure. The target database is independent and can be easily transferred and used between different operating systems and business systems, simplifying the data exchange process and increasing the flexibility of broadband measurement data application and data exchange. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0038] Figure 1 This is one of the flow charts of the method for processing broadband measurement data provided by the present invention.

[0039] Figure 2 It is a data structure diagram of the broadband measurement data provided by the present invention.

[0040] Figure 3 This is a schematic diagram of the effect of the multi-band joint display of broadband measurement data provided by the present invention.

[0041] Figure 4 It is a structural diagram of the device for processing broadband measurement data provided by the present invention.

[0042] Figure 5 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0043] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0044] The terms "first", "second" etc. in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequential order. It should be understood that the terms used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first" and "second" are generally a class, and the number of objects is not limited, for example, the first node can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally represents that the objects associated before and after are a kind of "or" relationship. For example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0045] In order to more clearly understand the various embodiments provided by the present invention, the technical content involved in the present invention is first introduced as follows.

[0046] Existing broadband measurement data storage and management methods mainly use relational databases, time series databases, and file storage, but they still have the following major drawbacks in power system applications:

[0047] 1. Strong platform dependence and complex integration

[0048] Relational databases rely on fixed table structures and typically require deployment on specific database management platforms. This platform dependency limits the convenient exchange of data between different business systems. Sharing data across platforms or multiple systems often requires developing additional interfaces and performing data format conversions, increasing the complexity of system integration.

[0049] Although time series databases are optimized for time series data, they typically need to run on specific platforms or frameworks and cannot be independent of database management systems. This platform limitation also creates obstacles when exchanging data between different business systems.

[0050] 2. Data exchange is inflexible and lacks self-descriptiveness

[0051] Relational databases have fixed table structures and lack self-describing capabilities, making it difficult to intuitively express the specific content and structure of data, especially in multi-business scenarios. Traditional table structure designs are difficult to meet the needs of rapid data exchange and reuse between different business systems in the power system.

[0052] While time-series databases offer good performance for storing time-series data, their data models are typically simplistic and lack flexible metadata support, making them unsuitable for storing and transmitting data containing complex spectral information. This limits data sharing and application across multiple systems and increases the complexity of data analysis.

[0053] 3. Lack of efficient structured query and analysis support

[0054] File storage formats (such as CSV and JSON) enable simple data transfer between different systems, but they only store raw data and cannot support complex structured queries and analysis operations. In practical applications, each analysis requires reloading and parsing large amounts of raw data, resulting in low computational efficiency and making it difficult to meet the real-time and high-efficiency requirements of power systems.

[0055] Although time series databases have good performance in time series data query, they lack support for advanced query requirements such as complex spectrum analysis and feature extraction, and cannot directly store analysis results. Users need to process the analyzed data themselves, which increases the system burden.

[0056] 4. Single visual display method

[0057] Existing systems lack a comprehensive approach to displaying power frequency, interharmonics, and harmonics data, making it impossible to intuitively reflect the dynamic changes in multi-frequency data. This is particularly true in applications such as power quality monitoring and oscillation analysis, where existing display methods fail to provide complete and clear spectral trend charts, limiting user visualization and decision support.

[0058] To address the shortcomings of existing methods for storing and managing broadband measurement data, the present invention proposes a structured storage and analysis method for broadband measurement data based on a file database, and designs a unified broadband measurement and analysis eXtension (WMAX) data structure to solve the above problems.

[0059] 1. Eliminate platform dependence and achieve cross-system data sharing

[0060] A file database is used to store broadband measurement data. The file database is independent and can be easily transferred and used between different operating systems and business systems. It avoids the operating platform limitations of traditional relational databases and time series databases and simplifies the system integration and data exchange process.

[0061] 2. Improve the flexibility and portability of data exchange

[0062] This invention uses a self-describing table structure within a file database. Table structure definitions and data are stored in the same file, providing self-explanatory capabilities. Different business systems can directly read and parse the file database without requiring additional data conversion steps, enabling rapid data exchange and reuse across multiple systems.

[0063] 3. Support efficient structured query and analysis

[0064] A unified WMAX data structure is designed to store raw data and analysis results in a structured manner. The file database supports standard SQL queries, allowing for direct execution of complex structured queries and spectrum analysis operations without reloading the raw data, significantly improving the system's query efficiency and analysis performance.

[0065] 4. Provide multi-band comprehensive display and visual analysis

[0066] This paper proposes a multi-band joint display method that enables comprehensive visualization of power frequency, interharmonic, and harmonic data. Using a variety of display methods, such as time series curves, scatter plots, and heat maps, it intuitively demonstrates the dynamic changes in data, enhancing users' visualization analysis and decision-making support capabilities.

[0067] Through the above technical solutions, the present invention solves the shortcomings in existing broadband measurement data storage and management, realizes the efficiency, flexibility and portability of data storage and analysis, and is suitable for various application scenarios such as power quality monitoring, harmonic analysis, and oscillation pattern recognition.

[0068] The following combination Figure 1-Figure 5 The invention describes a method, apparatus, device and storage medium for processing broadband measurement data.

[0069] Figure 1 This is one of the flow charts of the method for processing broadband measurement data provided by the present invention. Figure 1 As shown, the method includes the following:

[0070] Step 101: Obtain broadband measurement data of the power system; the broadband measurement data may include at least one of the following: power frequency measurement, harmonic measurement, and interharmonic measurement; different types of broadband measurement data may correspond to different standardized data structures;

[0071] Specifically, it should be noted that the execution subject of this embodiment is an electronic device with data processing capabilities. The electronic device can be a server with data processing capabilities, or a terminal device with data processing capabilities. The server can be a standalone server or a server cluster consisting of multiple servers. The terminal device can be any user device with data processing capabilities, including but not limited to: existing, under development, or future smartphones, tablet computers, laptop personal computers, desktop personal computers, minicomputers, mid-range computers, mainframe computers, etc. The present invention is used to achieve increased flexibility in broadband measurement data application and data exchange.

[0072] The method for processing broadband measurement data provided in this embodiment is implemented by the following steps:

[0073] First, broadband measurement data of the power system is obtained, for example, by using a broadband measurement device in a discontinuous frequency hopping transmission sequence format to collect broadband measurement data, which is rich spectrum data.

[0074] Broadband measurement data includes rich spectrum data, including power frequency, interharmonics, and harmonics. Power frequency generally refers to the fundamental frequency in the power system, typically 50Hz or 60Hz. Interharmonics: Interharmonics are waveform components with frequencies that are non-integer multiples of the fundamental frequency. Harmonics: Harmonics are waveform components with frequencies that are integer multiples of the fundamental frequency. Power frequency is primarily used for transmission and distribution of power systems and is the fundamental frequency of the power system. Interharmonics can cause voltage fluctuations and audio interference in power systems, affecting the normal operation of equipment. They are typically generated by nonlinear loads such as arc welding and variable frequency speed control devices. Harmonic applications: Harmonic analysis is used in power quality monitoring to identify and suppress nonlinear distortion in power systems. Harmonic generation is often associated with nonlinear loads such as UPSs and switching power supplies.

[0075] The present invention proposes a standardized WMAX data structure for uniformly representing various data types output by broadband measurement devices, including power frequency measurement, harmonic measurement, interharmonic measurement, second-level analysis data, and harmonic proportion statistics.

[0076] Step 102: Determine spectrum analysis results and cluster analysis results based on the broadband measurement data;

[0077] Specifically, after the broadband measurement data is acquired, spectrum analysis is performed on the broadband measurement data to obtain spectrum analysis results, and cluster analysis is performed on the broadband measurement data to obtain cluster analysis results.

[0078] The spectrum analysis process is as follows:

[0079] For example, spectrum analysis is performed on the active power, frequency and other data in the power frequency measurement data using a spectrum algorithm to obtain spectrum analysis results.

[0080] Spectral algorithms include but are not limited to the Porny algorithm, the Fast Fourier Transform (FFT) algorithm, and the Empirical Mode Decomposition (EMD).

[0081] Among them, the Prony algorithm is a classic signal processing method. This algorithm is mainly used to extract signal parameters such as frequency, amplitude, phase and attenuation factor from a set of measurement data. It is particularly suitable for analyzing signals with multiple exponential decay or sinusoidal wave components.

[0082] The Fast Fourier Transform (FFT) algorithm efficiently computes the Discrete Fourier Transform (DFT) and its inverse transform. The DFT is a crucial tool in signal processing, used to convert time-domain signals into frequency-domain signals. The FFT algorithm makes this process more efficient by reducing computational complexity.

[0083] Empirical Mode Decomposition (EMD) is an adaptive signal decomposition method for processing nonlinear and nonstationary signals. Its core concept is to decompose a complex signal into a series of Intrinsic Mode Functions (IMFs) and a residual term. Each IMF represents a vibration mode in the signal, has a single frequency, and can reflect the local characteristics of the signal.

[0084] The basic steps of the EMD algorithm include the following:

[0085] 1. Find local extreme points: Find all local maximum and minimum points in the signal.

[0086] 2. Construct upper and lower envelopes: Connect the maximum and minimum points through interpolation (usually using cubic spline interpolation) to obtain the upper and lower envelopes respectively.

[0087] 3. Calculate the mean envelope: take the average of the upper and lower envelopes as the mean envelope.

[0088] 4. Extract detail component: Subtract the mean envelope from the original signal to obtain a detail component.

[0089] 5. Screening process: Repeat the above steps for the detail component until the component meets the IMF conditions.

[0090] 6. Iterative decomposition: Remove the extracted IMF from the original signal and repeat the above steps on the remaining signal until the remaining signal cannot be decomposed any further.

[0091] Specifically, the spectrum analysis is performed with an analysis window length of M seconds and a step length of N seconds to calculate the oscillation mode results of each analysis window, including oscillation frequency, amplitude, damping ratio, initial phase, and energy proportion;

[0092] Each analysis window may calculate multiple oscillation modes. The oscillation mode with an energy proportion greater than 40% is selected, and the spectrum analysis results are formed according to the device name, analysis window start time, analysis window end time, oscillation frequency, oscillation amplitude, damping ratio, initial phase, energy proportion and other values, and then written into the target database.

[0093] The cluster analysis process is as follows:

[0094] For example, the frequency characteristics of the spectrum analysis results are input into clustering algorithms, including the K-means algorithm and the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, to automatically group them according to the similarity of oscillation frequencies to form clusters.

[0095] The K-means algorithm is a classic partitioning clustering algorithm widely used in data mining and machine learning. It is used to divide a dataset into K clusters. The following is a detailed introduction to the K-means algorithm:

[0096] The goal of the K-means algorithm is to partition the samples in a dataset into K clusters, such that the samples within each cluster are as similar as possible, while the samples between different clusters are as dissimilar as possible. Specifically, the algorithm achieves this goal by minimizing the mean squared error (SSE) of the samples within a cluster.

[0097] Among them, the DBSCAN algorithm is a classic density clustering algorithm that can identify clusters through dense areas of sample points and can handle noise points.

[0098] The core idea of ​​the DBSCAN algorithm is to define clusters based on density, using two main parameters: the neighborhood radius (eps), which defines the neighborhood range of each point, and the minimum number of points (minPts), which defines the minimum number of points that must be included in the neighborhood for the point to be considered a core point.

[0099] Based on these parameters, DBSCAN classifies the data points into three categories:

[0100] Core point: A point that contains at least minPts points in its neighborhood.

[0101] Boundary point: a point that is not in the neighborhood of a core point but is connected to the neighborhood of a core point.

[0102] Noise point: a point that is neither a core point nor a boundary point.

[0103] The main advantages of DBSCAN include: it does not require the number of clusters to be specified in advance, it can discover clusters of arbitrary shapes, and it is highly robust to noise.

[0104] Based on the above algorithm, operation and maintenance personnel can adjust clustering parameters (such as the K value or radius threshold) to focus the results on high-energy and broadband oscillation events with similar frequencies, making it easier to define events for oscillation analysis.

[0105] For the obtained clusters, broadband oscillation events are named according to the center frequency and representative devices. The energy proportion is further calculated to form a list of involved devices, and possible risk sources are marked and stored in the database.

[0106] It supports in-depth analysis of clusters with excessively high energy proportions or abnormal oscillation frequencies, including troubleshooting equipment failures, line problems, or external disturbances, and supports the formulation of corresponding scheduling and maintenance strategies.

[0107] Step 103: Call a general target query data interface to perform a data query in a target table of a target database. The target table of the target database includes broadband measurement data, spectrum analysis results, and cluster analysis results. The table structure corresponding to the target table of the target database is predetermined based on different types of broadband measurement data using standard SQL syntax. The target database is a file database having a self-describing table structure. The target query data interface is predetermined based on different types of broadband measurement data.

[0108] Specifically, the target query data interface can be pre-designed, and data query is performed in the target table of the target database by calling a universal target query data interface. The target query data interface is pre-determined based on different types of broadband measurement data.

[0109] The target table of the target database has a table structure predetermined using standard SQL syntax based on different types of broadband measurement data. The target database is a file database with a self-describing table structure. The target database is compatible with various databases, ensuring its use in file databases such as SQLite, DuckDB, and H2 Database. The target table of the target database includes the broadband measurement data, the spectrum analysis results, and the cluster analysis results.

[0110] It should be noted that the file database supports standard SQL queries and can directly execute complex structured queries and spectrum analysis operations without reloading the original data, significantly improving the system's query efficiency and analysis performance.

[0111] The method provided in this embodiment obtains broadband measurement data of the power system; the types of broadband measurement data include at least one of the following: power frequency measurement, harmonic measurement, and interharmonic measurement, and different types of broadband measurement data correspond to different standardized data structures; then, based on the broadband measurement data, spectrum analysis results and cluster analysis results are determined; further, a general target query data interface is called to perform data query in a target table of a target database, the target table of the target database includes broadband measurement data, spectrum analysis results, and cluster analysis results, the table structure corresponding to the target table of the target database is predetermined based on different types of broadband measurement data using standard SQL syntax, the target database is a file database, and the file database is a database with a self-describing table structure; the target query data interface is predetermined based on different types of broadband measurement data.

[0112] The types of broadband measurement data in the present invention include at least one of the following: power frequency measurement, harmonic measurement, and interharmonic measurement. Different types of broadband measurement data correspond to different standardized data structures, that is, a unified data structure is designed. In addition, a target query data interface is predetermined based on the different types of broadband measurement data. The present invention performs data queries in a target table of a target database by calling a universal target query data interface. The present invention uses standard SQL syntax to predetermine the table structure corresponding to the target table of the target database based on different types of broadband measurement data. The target database is a file database with a self-describing table structure. The target database is independent and can be easily transferred and used between different operating systems and business systems, simplifying the data exchange process and increasing the flexibility of broadband measurement data application and data exchange.

[0113] According to a method for processing broadband measurement data provided by the present invention, before calling a general target query data interface and performing a data query in a target table of a target database, the method further includes:

[0114] Calling a general target insertion data interface to write the broadband measurement data, the spectrum analysis results, and the cluster analysis results into a target table of a target database;

[0115] The target insertion data interface is predetermined based on different types of broadband measurement data.

[0116] Specifically, after obtaining the broadband measurement data, spectrum analysis results and cluster analysis results, the general target insertion data interface can be further called to write the broadband measurement data, spectrum analysis results and cluster analysis results into the target table of the target database to achieve efficient data storage.

[0117] The table structure corresponding to the target table of the target database is predetermined based on different types of broadband measurement data using standard SQL syntax. The target database is a file database with a self-describing table structure. The target database is compatible with multiple databases, ensuring that it can be used in file databases such as SQLite, DuckDB, and H2 Database.

[0118] The target insertion data interface is predetermined based on different types of broadband measurement data. Different insertion data interfaces correspond to different types of broadband measurement data, thereby achieving efficient storage.

[0119] The method provided in this embodiment writes broadband measurement data, spectrum analysis results, and cluster analysis results into a target table in a target database by calling a target insertion data interface. This facilitates subsequent data queries in the target table of the target database by calling a general target query data interface. The present invention employs standard SQL syntax to predetermine the table structure corresponding to the target table in the target database based on different types of broadband measurement data. The target database is a file database with a self-describing table structure. The target database is independent and can be easily transferred and used across different operating systems and business systems, simplifying the data exchange process and increasing the flexibility of broadband measurement data application and exchange.

[0120] According to a method for processing broadband measurement data provided by the present invention, any type of broadband measurement data is a broadband measurement and analysis extended structure WMAX structure, the main structure of the WMAX structure includes a device name field, a start time field, an end time field, and a structure of the type of broadband measurement data; the target table includes a plant station table, an equipment table, a line table, a raw data measurement table, a broadband oscillation analysis record table, and a broadband oscillation statistics record table; the target insertion data interface includes a first insertion data interface, a second insertion data interface, and a third insertion data interface.

[0121] Specifically, in some embodiments, any type of broadband measurement data is a broadband measurement and analysis extended structure WMAX structure, wherein the main structure of the WMAX structure includes a device name field deviceName, a start time field startTime, an end time field endTime, and a structure of broadband measurement data of the type.

[0122] For example, Figure 2 This is a schematic diagram of the data structure of the broadband measurement data provided by the present invention. Figure 2 As shown, the main structure of WMAX is as follows:

[0123] Device Name

[0124] Start time startTime

[0125] End time endTime

[0126] Power frequency measurement data fundamentalData

[0127] Harmonic measurement data harmonicData

[0128] Interharmonic Measurement DatainterharmonicData

[0129] Second-level K-line data list kLineData[ ]

[0130] Energy ratio statistics list energyRatios[ ]

[0131] For example, the structure FundamentalData of the power frequency measurement data structure is as follows:

[0132] Active power list activePower[ ]

[0133] Reactive power list reactivePower[ ]

[0134] frequency list frequency[ ]

[0135] Voltage list voltage[ ]

[0136] For example, the structure of the harmonic measurement structure HarmonicMeasurement is as follows:

[0137] Active harmonic list activePowerHarmonics[HarmonicData]

[0138] Voltage Harmonics List voltageHarmonics[HarmonicData]

[0139] Current harmonics list currentHarmonics[HarmonicData]

[0140] For example, the structure of the interharmonic measurement structure InterharmonicMeasurement is as follows:

[0141] Active interharmonics list activePowerInterharmonics[HarmonicData]

[0142] Voltage Interharmonics[HarmonicData]

[0143] Current interharmonics list currentInterharmonics[HarmonicData].

[0144] Among them, the target tables in the file database include plant table, equipment table, line table, raw data measurement table, broadband oscillation analysis record table, and broadband oscillation statistics record table, and each table can be self-describing.

[0145] The pre-designed target insertion data interfaces in this embodiment include a first insertion data interface, a second insertion data interface, and a third insertion data interface. The first insertion data interface is used to write broadband measurement data into the corresponding table, the second insertion data interface is used to write spectrum analysis results, and the third insertion data interface is used to write cluster analysis results. The universal insertion and query interfaces designed in this invention support adaptation to different file databases, achieving efficient data storage and retrieval.

[0146] The method provided in this embodiment pre-designs a unified WMAX data structure and implements data storage and query by calling common data query and data insertion interfaces, thereby simplifying the data processing and data exchange process and improving data processing efficiency.

[0147] According to a method for processing broadband measurement data provided by the present invention, a universal target insertion data interface is called to write broadband measurement data, spectrum analysis results, and cluster analysis results into a target table of a target database, including:

[0148] Calling the first data insertion interface to write the broadband measurement data into the corresponding raw data measurement table in the target database and the plant table, equipment table, and line table corresponding to the broadband measurement data;

[0149] Calling the second data insertion interface to write the spectrum analysis results into the broadband oscillation analysis record table in the target database;

[0150] The third data insertion interface is called to write the cluster analysis results into the broadband oscillation statistical record table in the target database.

[0151] Specifically, in some embodiments, the data insertion interface is pre-designed through a SQL statement, for example: insertStationData(database, stationID, stationName, stationType, voltageLevel, timestamp_bgn, timestamp_end, description). The corresponding interface can be called by executing an SQL statement.

[0152] The process of writing data in step 103 is implemented as follows:

[0153] For example, the first data insertion interface is called to write the broadband measurement data into the corresponding raw data measurement table in the target database and the plant table, equipment table, and line table corresponding to the broadband measurement data. For example, the following statement is executed to implement data writing:

[0154] / / Insert plant station data

[0155] Procedure insertStationData(database, stationID, stationName, stationType, voltageLevel, timestamp_bgn, timestamp_end, description):

[0156] Execute the following SQL statement:

[0157] INSERT INTO stationTable (stationID, stationName, stationType, voltageLevel, timestamp_bgn, timestamp_end, description)

[0158] VALUES (stationID, stationName, stationType, voltageLevel, timestamp_bgn, timestamp_end, description)

[0159] / / Insert device data

[0160] Procedure insertDeviceData(database, stID, deviceID, deviceName,deviceType, voltageLevel, description):

[0161] Execute the following SQL statement:

[0162] INSERT INTO deviceTable (stID, deviceID, deviceName, deviceType, voltageLevel, description)

[0163] VALUES (stID, deviceID, deviceName, deviceType, voltageLevel, description)

[0164] / / Insert line data

[0165] Procedure insertLineData(database, dev1ID, dev2ID, lineID, lineName,lineType, description):

[0166] Execute the following SQL statement:

[0167] INSERT INTO lineTable (dev1ID, dev2ID, lineID, lineName, lineType,description)

[0168] VALUES (dev1ID, dev2ID, lineID, lineName, lineType, description)

[0169] / / Insert raw measurement data

[0170] Procedure insertSourceData(database, devID, measName, description, measType, measurement):

[0171] Execute the following SQL statement:

[0172] INSERT INTO sourceData (devID, measName, description, measType, measurement)

[0173] VALUES (devID, measName, description, measType, measurement)

[0174] For example, the predefined table structures of each table are as follows:

[0175] Table 1: Station Table

[0176]

[0177] Table 2: Equipment table stationTable

[0178]

[0179] Table 3: Line Table lineTable

[0180]

[0181] Table 4: Raw data measurement table sourceData

[0182]

[0183] Furthermore, the second data insertion interface is called to write the spectrum analysis results into the broadband oscillation analysis record table in the target database. Exemplarily, the following statement is executed to write data into the broadband oscillation analysis record table:

[0184] / / Insert broadband oscillation analysis record data

[0185] Procedure insertWideFreqRecordData(database, devID, stID, type,harmonicType, frequency, max_amplitude, average_amplitude, timestamp_bgn,timestamp_end, freqData, ampData, phaseData)

[0186] Execute the following SQL statement:

[0187] INSERT INTO wideFreqRecordData (devID, stID, type, harmonicType,frequency, max_amplitude, average_amplitude, timestamp_bgn, timestamp_end,freqData, ampData, phaseData)

[0188] VALUES (devID, stID, type, harmonicType, frequency, max_amplitude,average_amplitude, timestamp_bgn, timestamp_end, freqData, ampData,phaseData)

[0189] For example, the broadband oscillation analysis record table is shown in Table 5 below:

[0190] Table 5: Wide-frequency oscillation analysis record table wideFreqRecordData

[0191]

[0192] Call the third insert data interface to write the cluster analysis results into the broadband oscillation statistics record table in the target database. For example, execute the following statement to write data into the broadband oscillation statistics record table:

[0193] / / Insert broadband oscillation statistics record data

[0194] Procedure insertAnalyData(database,type,harmonicType,frequency,stationCount, deviceCount)

[0195] Execute the following SQL statement:

[0196] INSERT INTO analyzeData (type, harmonicType, frequency, stationCount, deviceCount)

[0197] VALUES (type, harmonicType, frequency, stationCount, deviceCount)

[0198] For example, the broadband oscillation statistics record table is shown in Table 6 below:

[0199] Table 6: Broadband Oscillation Statistics Record Table analyData

[0200]

[0201] The method provided in this embodiment designs a universal data insertion interface, supports adaptation to different file databases, and realizes efficient storage of broadband measurement data.

[0202] According to a method for processing broadband measurement data provided by the present invention, a target query data interface includes a first query data interface, a second query data interface, and a third query data interface; calling a universal target query data interface to perform data query in a target table of a target database includes:

[0203] Calling a first data insertion interface to query the broadband measurement data in the corresponding original measurement data table in the target database;

[0204] Call the second insertion data interface to query the spectrum analysis results in the broadband oscillation analysis record table;

[0205] The third data insertion interface is called to query the cluster analysis results in the broadband oscillation statistical record table.

[0206] Specifically, in some embodiments, the query data interface is pre-designed using a SQL statement, as shown in the following example: queryStationData(database, stationID). The corresponding interface can be called by executing an SQL statement.

[0207] The process of querying data in step 104 is implemented as follows:

[0208] Call the first insert data interface to query the broadband measurement data in the corresponding raw measurement data table in the target database. For example, execute the following statement to query the raw measurement data:

[0209] / / Query plant station data

[0210] Function queryStationData(database, stationID):

[0211] Execute the following SQL statement:

[0212] SELECT FROM stationTable WHERE stationID = stationID

[0213] Return query results

[0214] / / Query device data

[0215] Function queryDeviceData(database, stID):

[0216] Execute the following SQL statement:

[0217] SELECT FROM deviceTable WHERE stID = stID

[0218] Return query results

[0219] / / Query line data

[0220] Function queryLineData(database, lineID):

[0221] Execute the following SQL statement:

[0222] SELECT FROM lineTable WHERE lineID = lineID

[0223] Return query results

[0224] / / Query the raw measurement data

[0225] Function querySourceData(database, devID, measType):

[0226] Execute the following SQL statement:

[0227] SELECT FROM sourceData WHERE devID = devID AND measType = measType

[0228] Return query results

[0229] Furthermore, the second insertion data interface is called to query the spectrum analysis results in the broadband oscillation analysis record table. For example, the following statement is executed to query the spectrum analysis results:

[0230] / / Query broadband oscillation analysis record data

[0231] Function queryWideFreqRecordData(database, devID, type, timestamp_bgn, timestamp_end):

[0232] Execute the following SQL statement:

[0233] SELECT FROM wideFreqRecordData

[0234] WHERE devID = devID AND type = type AND timestamp_bgn>= timestamp_bgnAND timestamp_end<= timestamp_end

[0235] Return query results

[0236] Furthermore, the third insertion data interface is called to query the cluster analysis results in the broadband oscillation statistical record table. For example, the following statement is executed to query the cluster analysis results:

[0237] / / Query the broadband oscillation statistics record data

[0238] Function queryAnalyData(database, type, harmonicType):

[0239] Execute the following SQL statement

[0240] SELECT FROM analyzeData WHERE type = type AND harmonicType =harmonicType

[0241] Return query results

[0242] In the method provided in this embodiment, a universal data query interface is designed to support adaptation to different file databases and achieve efficient reading of broadband measurement data.

[0243] According to a method for processing broadband measurement data provided by the present invention, the method further includes:

[0244] Visualize the broadband measurement data within a preset time period;

[0245] Conduct trend analysis based on the results of the visual display.

[0246] Specifically, in some embodiments, the method further includes integrating power frequency measurement data, higher harmonic measurement data, and interharmonic measurement data, and combining them with a timeline linkage design to achieve intuitive and efficient spectrum analysis and visualization. An example of the implementation process is as follows:

[0247] First, the broadband measurement data within a preset time period is visualized, and different types of broadband measurement data share the same time axis.

[0248] Trend analysis is performed based on the results of the visualization. For example, the visualization of power frequency measurement data can be used to identify voltage and current fluctuations in the power system, thereby predicting and detecting transient disturbances and power quality anomalies in the system. The visualization of harmonic measurement data (higher harmonics) can be used to identify the frequency characteristics and changing trends of harmonic signals, thereby determining the impact of higher harmonics on system power quality. The visualization of interharmonic measurement data can be used to identify the dynamic changes of interharmonics in time and frequency.

[0249] The method provided in this embodiment achieves intuitive and efficient spectrum analysis and visualization by integrating power frequency measurement data, harmonic measurement data, and interharmonic measurement data and combining it with a timeline linkage design.

[0250] According to a method for processing broadband measurement data provided by the present invention, broadband measurement data within a preset time period is visually displayed, including:

[0251] Using the first timing curve to display the power frequency measurement data within a preset time period;

[0252] Displaying harmonic measurement data within a preset time period using the second timing curve and the first spectrum analysis graph;

[0253] The interharmonic measurement data within a preset time period is displayed using the third timing curve, the second spectrum analysis diagram, and the frequency table waterfall diagram; the time axes of the first timing curve, the second timing curve, and the third timing curve are consistent.

[0254] Specifically, in some embodiments, the specific implementation process of visually displaying broadband measurement data within a preset time period includes the following steps:

[0255] The first timing curve displays power frequency measurement data for a preset time period. Specifically, the timing curve shows the dynamic changes in indicators such as power frequency voltage (Ua, Ub, Uc) and power frequency current (Ia, Ib, Ic), helping users identify voltage and current fluctuations in the power system in real time. The timing curve intuitively reflects the changing trends of power frequency signals over time, facilitating the detection of transient disturbances and power quality anomalies in the system.

[0256] The system uses a second time series curve and a first spectrum analysis plot to display harmonic measurement data within a preset time period. Specifically, for high-order harmonic data, the system uses time series curves and spectrum plots to show the changing trends of harmonic currents (IAJ, IBJ, ICJ) and harmonic voltages (UAJ, UBJ, UCJ). Combined with the spectrum analysis plot, users can identify the frequency characteristics and changing trends of harmonic signals, thereby determining the impact of high-order harmonics on system power quality. The spectrum plot displays harmonic amplitudes through color intensity changes, helping users quickly locate abnormal spectral components.

[0257] The tool uses a third timing curve, a second spectrum analysis chart, and a frequency table waterfall chart to display interharmonic measurement data within a preset time period. The time axes of the first, second, and third timing curves are consistent. Specifically, the tool uses a spectrum waterfall chart to display interharmonic data, with time on the horizontal axis and frequency on the vertical axis, and color indicating amplitude. This chart shows the dynamic changes of interharmonics in time and frequency, with brighter colors indicating larger amplitudes. The spectrum analysis chart also provides the energy distribution of the interharmonics. Users can visually observe the changes in spectrum energy in different time periods through the chart, which helps to identify the interharmonic characteristics of specific frequency bands. Figure 3 This is a schematic diagram of the effect of the multi-band joint display of broadband measurement data provided by the present invention.

[0258] The method provided in this embodiment achieves intuitive and efficient spectrum analysis and visualization by integrating power frequency measurement data, harmonic measurement data, and interharmonic measurement data and combining it with a timeline linkage design.

[0259] The following describes a device for processing broadband measurement data provided by the present invention. The device for processing broadband measurement data described below and the method for processing broadband measurement data described above can be referenced to each other.

[0260] Figure 4 FIG. 1 is a schematic diagram of the structure of the apparatus for processing broadband measurement data provided by the present invention. Figure 4 As shown, the broadband measurement data processing device 400 includes the following modules:

[0261] An acquisition module 410 is configured to acquire broadband measurement data of the power system; the broadband measurement data may include at least one of the following types: power frequency measurement, harmonic measurement, and interharmonic measurement; different types of broadband measurement data may correspond to different standardized data structures;

[0262] An analysis module 420 is configured to determine a spectrum analysis result and a cluster analysis result based on the broadband measurement data;

[0263] Query module 430 is used to call a general target query data interface to perform data query in a target table of a target database; the target table of the target database includes the broadband measurement data, the spectrum analysis results, and the cluster analysis results; the table structure corresponding to the target table of the target database is predetermined using standard SQL syntax based on different types of broadband measurement data; the target database is a file database having a self-describing table structure; the target query data interface is predetermined based on different types of broadband measurement data.

[0264] The apparatus provided in this embodiment includes an acquisition module 410, an analysis module 420, and a query module 430. The acquisition module 410 acquires broadband measurement data of the power system. The types of broadband measurement data include at least one of the following: power frequency measurement, harmonic measurement, and interharmonic measurement. Different types of broadband measurement data correspond to different standardized data structures. The analysis module 420 determines spectrum analysis results and cluster analysis results based on the broadband measurement data. Furthermore, the query module 430 calls a general target query data interface to perform data query in a target table of a target database. The target table of the target database includes broadband measurement data, spectrum analysis results, and cluster analysis results. The table structure corresponding to the target table of the target database is predetermined based on different types of broadband measurement data using standard SQL syntax. The target database is a file database, which has a self-describing table structure. The target query data interface is predetermined based on different types of broadband measurement data.

[0265] The types of broadband measurement data in the present invention include at least one of the following: power frequency measurement, harmonic measurement, and interharmonic measurement. Different types of broadband measurement data correspond to different standardized data structures, that is, a unified data structure is designed. In addition, a target query data interface is predetermined based on the different types of broadband measurement data. The present invention performs data queries in a target table of a target database by calling a universal target query data interface. The present invention uses standard SQL syntax to predetermine the table structure corresponding to the target table of the target database based on different types of broadband measurement data. The target database is a file database with a self-describing table structure. The target database is independent and can be easily transferred and used between different operating systems and business systems, simplifying the data exchange process and increasing the flexibility of broadband measurement data application and data exchange.

[0266] According to a broadband measurement data processing device 400 provided by the present invention, the device further includes a writing module; the writing module is specifically configured to:

[0267] Calling a general target insertion data interface to write the broadband measurement data, the spectrum analysis results, and the cluster analysis results into a target table of a target database;

[0268] The target insertion data interface is predetermined based on different types of broadband measurement data.

[0269] According to a broadband measurement data processing device 400 provided by the present invention, any type of broadband measurement data is a broadband measurement and analysis extended structure WMAX structure, the main structure of the WMAX structure including a device name field, a start time field, an end time field, and a structure of the broadband measurement data of the type; the target table includes a plant table, a device table, a line table, a raw data measurement table, a broadband oscillation analysis record table, and a broadband oscillation statistics record table; the target insertion data interface includes a first insertion data interface, a second insertion data interface, and a third insertion data interface;

[0270] According to the broadband measurement data processing device 400 provided by the present invention, the writing module is specifically configured to:

[0271] Calling the first data insertion interface to write the broadband measurement data into the corresponding raw data measurement table in the target database and the plant table, equipment table, and line table corresponding to the broadband measurement data;

[0272] calling the second data insertion interface to write the spectrum analysis result into the broadband oscillation analysis record table in the target database;

[0273] The third data insertion interface is called to write the cluster analysis result into the broadband oscillation statistical record table in the target database.

[0274] According to a broadband measurement data processing device 400 provided by the present invention, the target query data interface includes a first query data interface, a second query data interface, and a third query data interface; the query module 430 is specifically configured to:

[0275] Calling the first data insertion interface to query the broadband measurement data in the corresponding original measurement data table in the target database;

[0276] calling the second data insertion interface to query the spectrum analysis result in the broadband oscillation analysis record table;

[0277] The third data insertion interface is called to query the cluster analysis result in the broadband oscillation statistical record table.

[0278] According to a broadband measurement data processing device 400 provided by the present invention, the device further includes a display module, which is configured to:

[0279] Visually displaying the broadband measurement data within a preset time period;

[0280] Conduct trend analysis based on the results of the visual display.

[0281] According to a broadband measurement data processing device 400 provided by the present invention, the display module is further configured to:

[0282] Using the first timing curve to display the power frequency measurement data within a preset time period;

[0283] Displaying harmonic measurement data within the preset time period using the second timing curve and the first spectrum analysis graph;

[0284] The interharmonic measurement data within the preset time period is displayed using a third timing curve, a second spectrum analysis diagram, and a frequency table waterfall diagram; and the time axes of the first timing curve, the second timing curve, and the third timing curve are consistent.

[0285] Figure 5 An example of a physical structure diagram of an electronic device is shown below. Figure 5 As shown, the electronic device may include: a processor 510, a communication interface 520, a memory 530, and a communication bus 540, wherein the processor 510, the communication interface 520, and the memory 530 communicate with each other via the communication bus 540. The processor 510 may call logic instructions in the memory 530 to execute a method for processing broadband measurement data, which includes:

[0286] Acquire broadband measurement data of the power system; the broadband measurement data includes at least one of the following types: power frequency measurement, harmonic measurement, and interharmonic measurement, and different types of broadband measurement data correspond to different standardized data structures;

[0287] Determining spectrum analysis results and cluster analysis results based on the broadband measurement data;

[0288] A general target query data interface is called to perform data query in a target table of a target database; the target table of the target database includes the broadband measurement data, the spectrum analysis results, and the cluster analysis results; the table structure corresponding to the target table of the target database is predetermined based on different types of broadband measurement data using standard SQL syntax; the target database is a file database having a self-describing table structure; the target query data interface is predetermined based on different types of broadband measurement data.

[0289] Furthermore, the logic instructions in the aforementioned memory 530 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0290] In another aspect, the present invention further provides a computer program product, comprising a computer program. The computer program may be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can perform the method for processing broadband measurement data provided by the above methods, the method comprising:

[0291] Acquire broadband measurement data of the power system; the broadband measurement data includes at least one of the following types: power frequency measurement, harmonic measurement, and interharmonic measurement, and different types of broadband measurement data correspond to different standardized data structures;

[0292] Determining spectrum analysis results and cluster analysis results based on the broadband measurement data;

[0293] A general target query data interface is called to perform data query in a target table of a target database; the target table of the target database includes the broadband measurement data, the spectrum analysis results, and the cluster analysis results; the table structure corresponding to the target table of the target database is predetermined based on different types of broadband measurement data using standard SQL syntax; the target database is a file database having a self-describing table structure; the target query data interface is predetermined based on different types of broadband measurement data.

[0294] In another aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for processing broadband measurement data provided by the above methods is implemented, the method comprising:

[0295] Acquire broadband measurement data of the power system; the broadband measurement data includes at least one of the following types: power frequency measurement, harmonic measurement, and interharmonic measurement, and different types of broadband measurement data correspond to different standardized data structures;

[0296] Determining spectrum analysis results and cluster analysis results based on the broadband measurement data;

[0297] A general target query data interface is called to perform data query in a target table of a target database; the target table of the target database includes the broadband measurement data, the spectrum analysis results, and the cluster analysis results; the table structure corresponding to the target table of the target database is predetermined based on different types of broadband measurement data using standard SQL syntax; the target database is a file database having a self-describing table structure; the target query data interface is predetermined based on different types of broadband measurement data.

[0298] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0299] Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a necessary general-purpose hardware platform, or of course, hardware. Based on this understanding, the essence of the above technical solution, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for causing a computer device (such as a personal computer, server, or network device) to execute the methods described in each embodiment or certain portions of the embodiments.

[0300] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for processing broadband measurement data, characterized in that: include: Obtain broadband measurement data of the power system; the broadband measurement data may include at least one of the following types: power frequency measurement, harmonic measurement, and interharmonic measurement; different types of broadband measurement data may correspond to different standardized data structures; any type of broadband measurement data may be a broadband measurement and analysis extended structure (WMAX) structure, wherein the main structure of the WMAX structure includes a device name field, a start time field, an end time field, and a structure of the broadband measurement data of the type; Determining spectrum analysis results and cluster analysis results based on the broadband measurement data; Call the general target query data interface to query data in the target table of the target database; the target table includes the plant table, equipment table, line table, raw data measurement table, broadband oscillation analysis record table, and broadband oscillation statistics record table; each table is self-describing; The target table of the target database includes the broadband measurement data, the spectrum analysis results, and the cluster analysis results. The table structure corresponding to the target table of the target database is predetermined based on different types of broadband measurement data using standard SQL syntax. The target database is a file database having a self-describing table structure. The target query data interface is predetermined based on different types of broadband measurement data; The calling of the general target query data interface, before performing data query in the target table of the target database, further includes: Calling a general target insertion data interface to write the broadband measurement data, the spectrum analysis results, and the cluster analysis results into a target table of a target database; Among them, the target insertion data interface is predetermined based on different types of broadband measurement data; the target insertion data interface includes a first insertion data interface, a second insertion data interface and a third insertion data interface; the first insertion data interface is used to write each type of broadband measurement data into the corresponding table, the second insertion data interface is used to write the spectrum analysis results, and the third insertion data interface is used to write the cluster analysis results; the universal target insertion data interface and target query data interface are used to support adaptation to different file databases to achieve efficient storage and reading of data.

2. The method for processing broadband measurement data according to claim 1, wherein: The calling of a universal target insertion data interface to write the broadband measurement data, the spectrum analysis results, and the cluster analysis results into a target table of a target database includes: Calling the first data insertion interface to write the broadband measurement data into the corresponding raw data measurement table in the target database and the plant table, equipment table, and line table corresponding to the broadband measurement data; calling the second data insertion interface to write the spectrum analysis result into the broadband oscillation analysis record table in the target database; The third data insertion interface is called to write the cluster analysis result into the broadband oscillation statistical record table in the target database.

3. The method for processing broadband measurement data according to claim 1, wherein: The target query data interface includes a first query data interface, a second query data interface, and a third query data interface; calling the universal target query data interface to perform data query in the target table of the target database includes: Calling the first data query interface to query the broadband measurement data in the corresponding original measurement data table in the target database; calling the second query data interface to query the spectrum analysis result in the broadband oscillation analysis record table; The third query data interface is called to query the cluster analysis result in the broadband oscillation statistical record table.

4. The method for processing broadband measurement data according to any one of claims 1 to 3, characterized in that: The method further comprises: Visually displaying the broadband measurement data within a preset time period; Conduct trend analysis based on the results of the visual display.

5. The method for processing broadband measurement data according to claim 4, wherein: The visual display of the broadband measurement data within a preset time period includes: Using the first timing curve to display the power frequency measurement data within a preset time period; Displaying harmonic measurement data within the preset time period using the second timing curve and the first spectrum analysis graph; The interharmonic measurement data within the preset time period is displayed using a third timing curve, a second spectrum analysis diagram, and a frequency table waterfall diagram; and the time axes of the first timing curve, the second timing curve, and the third timing curve are consistent.

6. A device for processing broadband measurement data, characterized in that: include: An acquisition module is configured to acquire broadband measurement data of the power system; the broadband measurement data may include at least one of the following types: power frequency measurement, harmonic measurement, and interharmonic measurement; different types of broadband measurement data correspond to different standardized data structures; any type of broadband measurement data is a broadband measurement and analysis extended structure (WMAX) structure, the main structure of which includes a device name field, a start time field, an end time field, and a structure of the broadband measurement data of the type; An analysis module, configured to determine a spectrum analysis result and a cluster analysis result based on the broadband measurement data; A query module is used to call a universal target query data interface to query data in the target table of the target database; the target tables include plant table, equipment table, line table, raw data measurement table, broadband oscillation analysis record table, and broadband oscillation statistics record table; each table is self-describing; The target table of the target database includes the broadband measurement data, the spectrum analysis results, and the cluster analysis results. The table structure corresponding to the target table of the target database is predetermined based on different types of broadband measurement data using standard SQL syntax. The target database is a file database having a self-describing table structure. The target query data interface is predetermined based on different types of broadband measurement data. The device further includes a writing module; The writing module is configured to call a universal target insertion data interface to write the broadband measurement data, the spectrum analysis results, and the cluster analysis results into a target table of a target database; wherein the target insertion data interface is predetermined based on different types of broadband measurement data; and the target insertion data interface includes a first insertion data interface, a second insertion data interface, and a third insertion data interface; The first data insertion interface is used to write each type of broadband measurement data into the corresponding table, the second data insertion interface is used to write the spectrum analysis results, and the third data insertion interface is used to write the cluster analysis results; the universal target insertion data interface and target query data interface are used to support adaptation to different file databases to achieve efficient storage and reading of data.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method for processing broadband measurement data according to any one of claims 1 to 5 is implemented.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for processing broadband measurement data according to any one of claims 1 to 5 is implemented.

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