Power utilization information acquisition terminal detection system

Abstract

The invention discloses an electricity utilization information acquisition terminal detection system, relates to the technical field of electricity utilization information acquisition terminal detection, and solves the problem of low detection of an electricity utilization information acquisition terminal. Wherein the analog signal acquisition circuit, the digital-to-analog conversion module, the level matching circuit, the digital signal acquisition circuit and the information classification module realize comprehensive acquisition of power utilization data of power utilization equipment, and the automatic acquisition control module adopts an embedded acquisition control model to control an embedded information acquisition module to acquire the power utilization data. The power consumption information analysis and detection module adopts a quantitative analysis algorithm model to perform analysis and calculation according to the power consumption data to obtain the energy consumption, the power factor and the load of the detected equipment; and the data visualization module realizes visual display of the power consumption data and the power consumption data analysis and detection result through a data visualization interface configuration design method. According to the invention, the comprehensiveness and accuracy of the power consumption data acquired by the power consumption information acquisition terminal are greatly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power consumption information collection terminal detection technology, and more specifically to a power consumption information collection terminal detection system. Background Art

[0002] The power consumption information collection terminal detection system is an electrification technology system that can monitor and diagnose the operating status of power-consuming equipment. Its main function is to collect data and signals from power-consuming equipment to achieve real-time monitoring and diagnosis of the equipment status, and to promptly alarm when equipment abnormalities are found. The system consists of multiple parts such as the collection terminal, data transmission module, data processing module, alarm module and visualization display module. Its basic principle is to use sensors to collect, process and analyze the power consumption data and electrical data of the equipment in real time, and finally form visual data for users to perform data analysis and decision support, which greatly improves the reliability and economy of equipment operation and reduces the losses caused by equipment failures.

[0003] In the prior art, there are many drawbacks in the power consumption information collection terminal detection system. On the one hand, the power consumption data collection of power equipment is not comprehensive enough, resulting in an inability to fully understand the power consumption of power equipment and to control the power consumption data collection process, so as to achieve large-scale data collection and correction. On the other hand, the lack of power consumption data processing and analysis of power equipment results in the inability to detect the energy consumption, power factor and load characteristic indicators of power equipment, making it difficult to display power consumption data and power consumption data analysis results, and the power consumption information collection terminal detection is delayed. Therefore, the present invention proposes a power consumption information collection terminal detection system, which aims to provide a power consumption information collection terminal detection system that can realize abnormal power equipment detection to improve the detection capability. Summary of the invention

[0004] In view of the deficiencies of the above-mentioned technologies, the present invention discloses an electricity consumption information collection terminal detection system, wherein the embedded information collection module realizes comprehensive collection of electricity consumption data of electric equipment through analog signal collection circuit, digital-to-analog conversion module, level matching circuit, digital signal collection circuit and information classification module, thereby solving the problem that the electricity consumption of electric equipment cannot be fully understood; the automatic collection control module adopts an embedded collection control model to control the embedded information collection module to collect electricity consumption data, thereby improving the quality of electricity consumption data; the electricity consumption information analysis and detection module adopts a quantitative analysis algorithm model to analyze and calculate according to the electricity consumption data, thereby obtaining the energy consumption, power factor and load of the detected equipment, thereby solving the problem that the energy consumption, power factor and load characteristic indicators of the electric equipment cannot be detected; the data visualization module realizes the visualization display of electricity consumption data and electricity consumption data analysis and detection results through a data visualization interface configuration design method, thereby solving the problem that the system and user interaction cannot be realized.

[0005] The present invention adopts the following technical solutions: An electricity consumption information collection terminal detection system includes a power supply module, a data wireless transmission module, a blockchain data storage module, an embedded information collection module, an automatic collection control module, an electricity consumption information analysis and detection module, and a data visualization module; The power supply module uses an AC power grid to supply power to the power consumption information collection terminal detection system; The data wired transmission module uses an RS485 serial port wired communication module or a wireless communication module with a blockchain interface to transmit the power consumption data to the blockchain data storage module; The power supply module uses an AC power grid to supply power to the power consumption information collection terminal detection system; The data wireless transmission module uses a wireless communication network with a blockchain interface to transmit the power consumption data to the blockchain data storage module; The blockchain data storage module uses the blockchain centralized data storage library built into the electricity consumption information collection terminal to centrally store the electricity consumption data and the electricity consumption data analysis and detection results; The embedded information acquisition module is used to collect power consumption data of the electrical equipment, and the power consumption data at least includes voltage, current, temperature, pressure, switch quantity state, power and pulse signal frequency. The embedded information acquisition module comprises an analog signal acquisition circuit, a digital-to-analog conversion module, a level matching circuit, a digital signal acquisition circuit and an information classification module; the output end of the analog signal acquisition circuit is connected to the input end of the digital-to-analog conversion module, the output end of the digital-to-analog conversion module is connected to the input end of the level matching circuit, the analog signal acquisition circuit, the level matching circuit and the digital signal acquisition circuit are connected in parallel, and the output end of the digital signal acquisition circuit is connected to the input end of the information classification module; The automatic collection control module is used to control the automatic collection of electricity consumption data. The automatic collection control module uses an embedded collection control model to control the embedded information collection module to collect electricity consumption data, thereby realizing the automation of electricity consumption data collection and improving the speed and quality of electricity consumption data collection; The power consumption information analysis and detection module is used to enable the power consumption information collection terminal to analyze and detect the energy consumption, power factor and load of the detected equipment. The power consumption information analysis and detection module uses a quantitative analysis algorithm model to analyze and calculate according to the power consumption data to obtain the energy consumption, power factor and load of the detected equipment; The data visualization module is used to display the power consumption data and the power consumption data analysis and detection results to the user in real time. The data visualization module realizes the visualization display of the power consumption data and the power consumption data analysis and detection results through the data visualization interface configuration design method; The output end of the automatic acquisition control module is connected to the input end of the embedded information acquisition module, the output end of the embedded information acquisition module is connected to the input end of the data wireless transmission module, the output end of the data wireless transmission module is connected to the input end of the blockchain data storage module, the output end of the blockchain data storage module is connected to the input end of the power consumption information analysis and detection module, the output end of the power consumption information analysis and detection module and the output end of the blockchain data storage module are connected to the input end of the data visualization module, and the output end of the power supply module is respectively connected to the input ends of the data wireless transmission module, the blockchain data storage module, the embedded information acquisition module, the automatic acquisition control module, the power consumption information analysis and detection module and the data visualization module.

[0006] As a further technical solution of the present invention, the analog signal acquisition circuit adopts an integral approximation conversion method to linearize and filter the physical quantities of electrical equipment obtained by voltage transformers, Hall sensors, thermistors and pressure sensors to obtain accurate voltage, current, temperature and pressure analog signals. The integral approximation conversion method samples and discretizes continuous analog signals through random sampling to achieve signal mode conversion, and amplifies, filters and samples analog signals. The integral approximation conversion method adopts analog filtering to integrate analog signals through an integration circuit to achieve analog signal filtering. The integral approximation conversion method amplifies the analog signal to 5.5 times through an analog amplifier circuit to reduce the noise and interference of the analog signal. The integral approximation conversion method periodically samples from the analog signal through analog sampling processing to achieve equal-interval sampling of the analog signal.

[0007] As a further technical solution of the present invention, the digital-to-analog conversion circuit adopts an analog-to-digital conversion quantization method to convert the analog signal collected by the analog signal acquisition circuit into a discrete digital signal. The analog-to-digital conversion quantization method adopts a sampling and holding circuit to discretely sample the collected continuously changing analog signal to obtain a series of equally spaced sampling points. The analog-to-digital conversion quantization method then quantizes each sample point through quantization coding to map the sampling points of voltage, current, temperature and pressure into digital quantities with fixed precision. The level matching circuit adopts a cascade feedback control loop to confirm that the sampling frequency and sampling precision of the sampling and holding circuit match the analog signal, so as to ensure the precision and quality of the digital quantity when converting the signal from analog to digital quantity. The cascade feedback control loop confirms that the sampling frequency of the sampling and holding circuit matches the analog signal according to Nyquist sampling. The cascade feedback control loop confirms that the sampling precision of the sampling and holding circuit matches the analog signal according to the quantization precision and the signal-to-noise ratio.

[0008] As a further embodiment of the present invention, the digital signal acquisition module adopts a pulse recording and analysis method to record the switch state, power and pulse signal frequency without distortion. The pulse recording and analysis method adopts a programmable gate array counting to accurately record the time and number of switch state changes. The pulse recording and analysis method performs discrete temporal sampling of the input signal through an analog-to-digital converter, and detects and identifies the sampling signal power through threshold comparison to achieve power extraction of the detected sampling signal. The pulse recording and analysis method uses a real-time sampling digital oscilloscope to continuously and stably record the pulse signal frequency to obtain a complete pulse signal frequency waveform; the information classification module uses an automatic execution smart contract to automatically classify, verify and transfer the collected electricity consumption data, so as to allocate the electricity consumption data to the blockchain data storage module for storage and subsequent analysis and processing.

[0009] As a further embodiment of the present invention, The quantitative analysis algorithm model includes an energy consumption detection module, a power factor detection module and a load characteristic index detection module. The energy consumption detection module divides the power consumption data according to the time interval by dividing the data into equal intervals. The energy consumption detection module analyzes the power consumption data within the time interval by linear integration and exponential integration to obtain the power consumption within the time interval. The energy consumption detection module then accumulates the power consumption within the time interval by an integral function to obtain the energy consumption of the electrical equipment. The energy consumption calculation formula of the electrical equipment is: (1) In formula (1), is the energy consumption of electrical equipment, is the time interval, is the power consumption in the time interval, is the output voltage of the electrical equipment, is the output current of the electrical equipment; The power factor detection module uses a principal component extraction calculation algorithm to extract active power and reactive power from the power consumption data. The principal component extraction calculation algorithm performs standardization processing on the power consumption data through principal component dimensionality reduction analysis. The principal component extraction calculation algorithm then calculates the active power and reactive power in the principal components of the power consumption data through covariance matrix and singular value decomposition. The power factor detection module calculates the power factor of the power fluctuation of the power consumption equipment during the power consumption time according to the active power and reactive power in the power consumption data through a linear regression function. The active power extraction calculation formula in the power consumption data is: (2) In formula (2), is the active power in the power consumption data, is the sampling frequency of the Hall sensor for current, is the covariance power matrix of electricity consumption data, is the product of current and voltage; The calculation formula for reactive power extraction in the power consumption data is: In formula (3), F is the reactive power in the power consumption data, is the sampling frequency of the voltage transformer for voltage, The power collected by the electrical equipment; The calculation formula of the power factor is: (4) In formula (4), is the power factor, is the linear regression function, The pulse signal frequency of the electrical equipment; The load characteristic index detection module uses a state filtering conversion method to convert the power consumption data into a load curve and perform quantitative analysis on the load curve. The state filtering conversion method accumulates the power values ​​of the power consumption data on the time axis according to time intervals through recursive conversion to obtain a load curve. The state filtering conversion method identifies the peak and trough of the load curve through a load curve fitting function and extracts the load characteristic index. The load characteristic index calculation formula is: (5) In formula (5), is the load characteristic index, is the peak value of the load curve, The trough of the load curve. is the load curve fitting function, The temperature of the electrical equipment.

[0010] As a further embodiment of the present invention, the embedded acquisition control model includes a timing control module, a time-sharing acquisition control module and a data verification control module. The output end of the timing control module is connected to the input end of the time-sharing acquisition control module, and the output end of the time-sharing acquisition control module is connected to the input end of the data verification control module; the timing control module adopts an external crystal oscillator clock control method to generate a clock control signal to trigger the information acquisition module to collect power consumption data according to a sampling period. The external crystal oscillator clock control method configures the pre-division value and counting pulse value of the clock source to realize that the clock source generates a clock control signal according to the sampling period. When the pre-division value of the clock source is 7999, a counting pulse of 1ms is obtained. The clock control signal triggers the embedded information acquisition module to collect power consumption data through an external crystal oscillator pin.

[0011] As a further embodiment of the present invention, the time-sharing collection control module adopts time-division multiplexing collection control to divide the task of collecting electricity consumption data into at least 7 sub-tasks, and completes all electricity consumption data collection within at least 7 sampling cycles, thereby reducing the burden on the electricity consumption information collection terminal and ensuring the correctness of electricity consumption data collection. The time-division multiplexing collection control controls the embedded information collection module through time-division multiplexing time and task allocation to only collect the sub-tasks that currently need to be collected within each sampling cycle, thereby avoiding the pressure and delay caused by collecting electricity consumption data tasks at the same time.

[0012] As a further embodiment of the present invention, the data calibration control module adopts a cyclic redundancy check method and a data error calibration method to check and correct the collected electricity consumption data, so as to improve the integrity and accuracy of the collected electricity consumption data. The cyclic redundancy check method adopts a check code operation to perform an XOR operation on each bit of the electricity consumption data to generate a check code. The cyclic redundancy check method adopts a CRC polynomial to check the electricity consumption data according to the check code, so as to identify and mark abnormal data points. The data error calibration method adopts a data interpolation algorithm to repair and reconstruct abnormal data points according to the marked abnormal data points, so as to ensure the integrity of the electricity consumption data. The data interpolation algorithm derives the value of the missing data point according to the known electricity consumption data through polynomial fitting. The data interpolation algorithm performs smooth fitting on the known abnormal data points according to the value of the missing data points through a spline difference fitting function, so as to correct the electricity consumption data.

[0013] As a further embodiment of the present invention, the data visualization interface configuration design method adopts a BI data visualization library to add real-time updated electricity consumption data in a visualization display screen. The BI data visualization library is connected to a blockchain centralized data storage library built into a power consumption information collection terminal through an application program interface to obtain power consumption data and power consumption data analysis and detection results. The BI data visualization library adopts visualization design to map the power consumption data analysis results into chart elements of energy consumption statistics, power factor and load analysis in real time.

[0014] The present invention has the following positive and beneficial effects compared with the prior art: The present invention discloses an electricity consumption information collection terminal detection system. The embedded information collection module realizes comprehensive collection of electricity consumption data of electric equipment through an analog signal collection circuit, a digital-to-analog conversion module, a level matching circuit, a digital signal collection circuit and an information classification module, so as to realize a comprehensive understanding of the electricity consumption of the electric equipment. The automatic collection control module adopts an embedded collection control model to control the embedded information collection module to collect electricity consumption data, so as to improve the quality of electricity consumption data. The electricity consumption information analysis and detection module adopts a quantitative analysis algorithm model to analyze and calculate according to the electricity consumption data, so as to obtain the energy consumption, power factor and load of the detected equipment, so as to realize the detection of energy consumption, power factor and load characteristic indicators of the electric equipment. The data visualization module realizes the visualization display of electricity consumption data and electricity consumption data analysis and detection results through a data visualization interface configuration design method. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work, among which: Figure 1 This is a schematic diagram of the overall architecture of a power consumption information collection terminal detection system of the present invention; Figure 2 This is a schematic diagram of the overall architecture of the embedded information acquisition module used in the present invention; Figure 3 This is a schematic diagram of the structure of the embedded acquisition control model adopted by the present invention; Figure 4 This is a schematic diagram of the quantitative analysis algorithm model structure adopted by the present invention; Figure 5 This is a schematic diagram of the blockchain centralized data storage structure adopted by the present invention.

[0016] Figure 6 The figure is a schematic diagram of an embodiment of the embedded information acquisition module of the present invention. DETAILED DESCRIPTION

[0017] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0018] like Figure 1-Figure 6 As shown, a power consumption information collection terminal detection system includes a power supply module, a data wireless transmission module, a blockchain data storage module, an embedded information collection module, an automatic collection control module, a power consumption information analysis and detection module and a data visualization module; The power supply module uses an AC power grid to supply power to the power consumption information collection terminal detection system; The data wireless transmission module uses a wireless communication network with a blockchain interface to transmit the power consumption data to the blockchain data storage module; The blockchain data storage module uses the blockchain centralized data storage library built into the electricity consumption information collection terminal to centrally store the electricity consumption data and the electricity consumption data analysis and detection results; The embedded information acquisition module is used to collect power consumption data of the electrical equipment, and the power consumption data at least includes voltage, current, temperature, pressure, switch quantity state, power and pulse signal frequency. The embedded information acquisition module comprises an analog signal acquisition circuit, a digital-to-analog conversion module, a level matching circuit, a digital signal acquisition circuit and an information classification module; the output end of the analog signal acquisition circuit is connected to the input end of the digital-to-analog conversion module, the output end of the digital-to-analog conversion module is connected to the input end of the level matching circuit, the analog signal acquisition circuit, the level matching circuit and the digital signal acquisition circuit are connected in parallel, and the output end of the digital signal acquisition circuit is connected to the input end of the information classification module; The automatic collection control module is used to control the automatic collection of electricity consumption data. The automatic collection control module uses an embedded collection control model to control the embedded information collection module to collect electricity consumption data, thereby realizing the automation of electricity consumption data collection and improving the speed and quality of electricity consumption data collection; The power consumption information analysis and detection module is used to enable the power consumption information collection terminal to analyze and detect the energy consumption, power factor and load of the detected equipment. The power consumption information analysis and detection module uses a quantitative analysis algorithm model to analyze and calculate according to the power consumption data to obtain the energy consumption, power factor and load of the detected equipment; The data visualization module is used to display the power consumption data and the power consumption data analysis and detection results to the user in real time. The data visualization module realizes the visualization display of the power consumption data and the power consumption data analysis and detection results through the data visualization interface configuration design method; The output end of the automatic acquisition control module is connected to the input end of the embedded information acquisition module, the output end of the embedded information acquisition module is connected to the input end of the data wireless transmission module, the output end of the data wireless transmission module is connected to the input end of the blockchain data storage module, the output end of the blockchain data storage module is connected to the input end of the power consumption information analysis and detection module, the output end of the power consumption information analysis and detection module and the output end of the blockchain data storage module are connected to the input end of the data visualization module, and the output end of the power supply module is respectively connected to the input ends of the data wireless transmission module, the blockchain data storage module, the embedded information acquisition module, the automatic acquisition control module, the power consumption information analysis and detection module and the data visualization module.

[0019] During the implementation of the present invention, first, the power supply module is responsible for providing a stable power supply for the entire system to ensure the normal operation of each module. It can be connected to an AC power supply or a DC power supply, and provide the voltage and current required for the system operation through conversion and adjustment. Secondly, the automatic acquisition control module controls the embedded information acquisition module to collect power consumption data through an embedded acquisition control model to achieve an efficient, accurate, stable and reliable data acquisition process. Then, the embedded information acquisition module monitors and collects power consumption information in real time, such as power, current, voltage and other parameters. This module can collect and process data for power-consuming equipment. Then, the data wireless transmission module transmits the power consumption data to the blockchain data storage module through a wireless communication network with a blockchain interface. The blockchain data storage module is used to store the power consumption data transmitted from the information acquisition module. Then, the power consumption information analysis and detection module processes and analyzes the collected power consumption data, which can realize the analysis and calculation of the energy consumption, power factor and load of the power-consuming equipment. Finally, the data visualization module is responsible for displaying the power consumption data and the power consumption data analysis and detection results to the user in real time. It can also display the collected power consumption data in a visual form, which is convenient for users to view in real time.

[0020] In a further embodiment, the detection principle of the embedded information acquisition module may also be: Metering: The electricity consumption information collection terminal can be installed on the electrical equipment to measure the electricity consumption through the energy meter. The energy meter can measure the energy consumption of the electrical equipment, including current, voltage, power and other information.

[0021] Data collection: The power consumption information collection terminal can collect the power consumption data of power-consuming equipment in real time and transmit it to the central server. The collected data includes voltage, current, power, power and other information.

[0022] Data analysis: The central server can analyze the collected data and calculate various power indicators, such as power consumption, electricity charges, etc. In addition, the central server can also monitor and analyze power data in real time to adjust power consumption plans and electricity prices in a timely manner.

[0023] In short, the embedded information collection module realizes the monitoring and collection of electricity consumption information through processes such as metering, data collection and data analysis. This information can be used for electricity management and control of electricity users such as enterprises and residents, helping them to better understand electricity consumption and optimize electricity consumption plans.

[0024] In a further embodiment, the analog signal acquisition circuit adopts an integral approximation conversion method to linearize and filter the physical quantities of electrical equipment obtained by voltage transformers, Hall sensors, thermistors and pressure sensors to obtain accurate voltage, current, temperature and pressure analog signals. The integral approximation conversion method samples and discretizes continuous analog signals through random sampling to achieve signal mode conversion, and amplifies, filters and samples analog signals. The integral approximation conversion method adopts analog filtering to integrate analog signals through an integration circuit to achieve analog signal filtering. The integral approximation conversion method amplifies the analog signal to 5.5 times through an analog amplification circuit to reduce noise and interference of the analog signal. The integral approximation conversion method periodically samples from the analog signal through analog sampling processing to achieve equal-interval sampling of the analog signal.

[0025] In a further embodiment, the digital-to-analog conversion circuit uses an analog-to-digital conversion quantization method to convert the analog signal collected by the analog signal acquisition circuit into a discrete digital signal. The analog-to-digital conversion quantization method uses a sampling and holding circuit to discretely sample the collected continuously changing analog signal to obtain a series of equally spaced sampling points. The analog-to-digital conversion quantization method then quantizes each sample point through quantization coding to map the sampling points of voltage, current, temperature and pressure into digital quantities with fixed precision. The level matching circuit uses a cascade feedback control loop to confirm that the sampling frequency and sampling precision of the sampling and holding circuit match the analog signal, so as to ensure the accuracy and quality of the digital quantity when converting the signal from analog to digital. The cascade feedback control loop confirms that the sampling frequency of the sampling and holding circuit matches the analog signal according to Nyquist sampling. The cascade feedback control loop confirms that the sampling precision of the sampling and holding circuit matches the analog signal according to the quantization precision and the signal-to-noise ratio.

[0026] In a further embodiment, the digital signal acquisition module adopts a pulse recording and analysis method to record the switch state, power and pulse signal frequency without distortion. The pulse recording and analysis method adopts a programmable gate array count to accurately record the time and number of switch state changes. The pulse recording and analysis method performs discrete temporal sampling of the input signal through an analog-to-digital converter, and detects and identifies the sampling signal power through threshold comparison to achieve power extraction of the detected sampling signal. The pulse recording and analysis method uses a real-time sampling digital oscilloscope to continuously and stably record the pulse signal frequency to obtain a complete pulse signal frequency waveform; the information classification module uses an automatic execution of smart contracts to automatically classify, verify and transfer the collected electricity consumption data, so as to allocate the electricity consumption data to the blockchain data storage module for storage and subsequent analysis and processing.

[0027] In a specific embodiment, the embedded information acquisition module includes components such as an analog signal acquisition circuit, a digital-to-analog conversion module, a level matching circuit, a digital signal acquisition circuit, and an information classification module, and their respective functions are as follows: Analog signal acquisition circuit: implements the sampling and acquisition functions of analog signals, converts physical signals into electrical signals, and digitally processes the signals in a quantized manner for subsequent processing and analysis; Digital-to-analog conversion module: converts the collected analog signals into digital signals after sampling and quantization, and performs filtering, denoising and other processing operations at the same time to improve the quality and accuracy of digital signals. Level matching circuit: performs level matching on digital signals, matches the level of electrical signals to the level range acceptable to the final output device, thereby realizing the transmission and analysis of digital signals. Digital signal acquisition circuit: receives and processes digital signals output from the analog signal acquisition circuit and the digital-to-analog conversion module, and performs operations such as amplification, filtering and processing on the signals during the digital signal transmission process to improve the signal quality and reliability. Information classification module: classifies, processes and analyzes the various collected data, obtains the correlation and rules between the data through analysis and comparison, and provides strong support and reference for subsequent decision-making and adjustment. To sum up, the various components in the embedded information acquisition module are responsible for different functional modules, playing various roles such as acquisition, processing, conversion and transmission, and together constitute a complete information acquisition and processing system, and provide important support and foundation for subsequent data analysis and decision-making.

[0028] Voltage transformer, Hall sensor, thermistor and pressure sensor are sensors used to obtain physical quantities of electrical equipment. Their principles are as follows: Voltage transformer: A voltage transformer is a transformer that converts a high voltage signal on a high voltage line into a low voltage signal. The principle is to use the mutual inductance between the high voltage coil and the low voltage coil to convert the high voltage signal at the input end into a low voltage signal. This low-level signal can be connected to the acquisition system for digital processing. Hall sensor: A Hall sensor is a sensor based on the Hall effect. It uses the Hall effect caused by the movement of free carriers in semiconductor materials under the influence of the magnetic field to detect the strength and direction of the magnetic field. When there is an external magnetic field, a transverse magnetic field will be generated inside the semiconductor chip. This transverse magnetic field will cause different sizes of Hall effect potential differences on both sides of the Hall element, thereby realizing the detection of information such as the strength and direction of the magnetic field. Thermistor: A thermistor is a sensor based on the thermal effect. Its resistance value changes with the change of temperature. When the ambient temperature changes, the motion state of the electrons inside the thermistor will also change, resulting in a change in the resistance value. By measuring the change in this resistance value, physical quantities such as the ambient temperature can be inferred. Pressure sensor: A pressure sensor is a sensor used to measure pressure or load. Its principle is to use the deformation of the material under the force to cause changes in signals such as resistance, capacitance or vibration, and to establish a relationship between these signals and pressure or load for conversion. Common pressure sensors include strain gauge, piezoresistive, micromechanical and other types. In summary, these sensors all use different physical principles to detect and collect physical quantities of electrical equipment, and convert them into digital signals and output them to the acquisition system for processing and analysis.

[0029] In a further embodiment, the quantitative analysis algorithm model includes an energy consumption detection module, a power factor detection module and a load characteristic index detection module. The energy consumption detection module divides the power consumption data according to time intervals by dividing the data into equal intervals. The energy consumption detection module analyzes the power consumption data within the time interval by linear integration and exponential integration to obtain the power consumption within the time interval. The energy consumption detection module then accumulates the power consumption within the time interval by an integral function to obtain the energy consumption of the electrical equipment. The energy consumption calculation formula of the electrical equipment is: (1) In formula (1), is the energy consumption of electrical equipment, is the time interval, is the power consumption in the time interval, is the output voltage of the electrical equipment, is the output current of the electrical equipment; The power factor detection module uses a principal component extraction calculation algorithm to extract active power and reactive power from the power consumption data. The principal component extraction calculation algorithm performs standardization processing on the power consumption data through principal component dimensionality reduction analysis. The principal component extraction calculation algorithm then calculates the active power and reactive power in the principal components of the power consumption data through covariance matrix and singular value decomposition. The power factor detection module calculates the power factor of the power fluctuation of the power consumption equipment during the power consumption time according to the active power and reactive power in the power consumption data through a linear regression function. The active power extraction calculation formula in the power consumption data is: (2) In formula (2), is the active power in the power consumption data, is the sampling frequency of the Hall sensor for current, is the covariance power matrix of electricity consumption data, is the product of current and voltage; The calculation formula for reactive power extraction in the power consumption data is: F (3) In formula (3), F is the reactive power in the power consumption data, is the sampling frequency of the voltage transformer for voltage, The power collected by the electrical equipment; The calculation formula of the power factor is: (4) In formula (4), is the power factor, is the linear regression function, The pulse signal frequency of the electrical equipment; The load characteristic index detection module uses a state filtering conversion method to convert the power consumption data into a load curve and perform quantitative analysis on the load curve. The state filtering conversion method accumulates the power values ​​of the power consumption data on the time axis according to time intervals through recursive conversion to obtain a load curve. The state filtering conversion method identifies the peak and trough of the load curve through a load curve fitting function and extracts the load characteristic index. The load characteristic index calculation formula is: (5) In formula (5), is the load characteristic index, is the peak value of the load curve, The trough of the load curve. is the load curve fitting function, The temperature of the electrical equipment The hardware carrier of the quantitative analysis algorithm model in the specific embodiment can be implemented with the help of a data processor. The data processor is a specific hardware device, usually a chip or module based on a computer architecture, used to perform various data processing tasks. The data processor as a hardware carrier can provide the following advantages: 1. High-performance computing: Data processors usually have powerful computing power and parallel processing capabilities, and can efficiently perform complex algorithms and large-scale data processing tasks; 2. Flexibility: Data processors can be programmed and configured as needed to adapt to different quantitative analysis algorithm models. They support a variety of programming languages ​​and development environments, allowing developers to freely choose the most suitable tools and methods; 3. Data storage and management: Data processors usually have a large memory capacity and cache, which can effectively store and manage large amounts of data that need to be quantitatively analyzed. In addition, they also support various data formats and storage methods, such as databases, file systems, etc.; 4. Data interaction and communication: Data processors usually have rich input and output interfaces, which can interact and communicate with other devices or systems, which makes it easy to receive, send and share relevant data during the quantitative analysis process; 5. Real-time performance: Some data processors have real-time processing capabilities and can complete quantitative analysis tasks in a shorter time, which is very important for applications that require fast response and real-time decision-making. In short, quantitative analysis algorithm models can be effectively implemented with the help of data processors as hardware carriers. They provide advantages such as high-performance computing, flexibility, data storage and management, data interaction and communication, and real-time performance, providing strong support for quantitative analysis.

[0030] In other embodiments, a quantitative analysis algorithm model application platform may be constructed. During the operation of the platform, a hardware platform may be constructed, such as by constructing the following components for processing, for example: Processor: The execution speed and parallel computing capability of an algorithm usually depend on the performance of the processor. A faster processor can speed up the execution of an algorithm, while a processor with multiple cores can provide better parallel computing capabilities.

[0031] Memory: Algorithms require sufficient memory to store and process data. If there is insufficient memory, the algorithm may not run properly or performance may degrade.

[0032] Memory: Algorithms may need to read and write large amounts of data, so larger memory capacity can better support the operation of the algorithm.

[0033] Graphics Cards: Algorithms can be accelerated by using a graphics processing unit (GPU). The performance and parallel computing capabilities of graphics cards have a significant impact on the execution speed of these algorithms.

[0034] Network connectivity: If the algorithm needs to obtain data from the network or communicate with other systems, a good network connection is necessary.

[0035] Other peripheral devices: Some algorithms may require specific peripheral devices for input and output, such as cameras, sensors, etc.

[0036] In short, the hardware conditions for algorithm operation include processor performance, memory capacity, storage capacity, graphics card performance, network connection and other peripheral devices. The quality of these hardware conditions will directly affect the performance and effect of the algorithm. By building the above platform, the hardware can be effectively implemented.

[0037] For the analysis of electricity consumption data, quantitative analysis algorithm models can be used to achieve energy consumption statistics, power factor calculation and load analysis. The following is a specific explanation of each aspect: 1. Energy consumption statistics: Through the quantitative analysis algorithm model, the electricity consumption data can be accumulated and summed, and statistics can be combined with the time dimension to obtain the energy consumption in different time periods, which can help users understand the overall energy consumption and carry out energy-saving management and optimization; 2. Power factor calculation: The power factor is an important indicator to measure the effective utilization of the power system. Through the quantitative analysis algorithm model, the active power and reactive power in the electricity consumption data can be calculated to obtain the power factor value, which helps to judge the operating status and load status of the power system and provide corresponding improvement measures; 3. Load analysis: Through the quantitative analysis algorithm model, the load characteristics of the electricity consumption data can be extracted and the load curve can be drawn. By analyzing the volatility, peak and valley changes and other characteristics of the load curve, the load change trend, peak demand and potential problems can be judged. This helps to reasonably plan the power supply strategy and improve the reliability of power supply. The statistical table of the energy consumption calculation results of the power equipment is shown in Table 1:

[0038] As shown in Table 1, four test groups are set up, and two methods are used to calculate the energy consumption of electrical equipment. Method 1 estimates the energy consumption of electrical equipment by drawing a load curve graph and calculating the area below it. Method 2 is a quantitative analysis algorithm model that uses an integral function to accumulate the power consumption in a time interval to obtain the energy consumption of the electrical equipment. The error of Method 1 is greater than the error of Method 2. It can be seen that the quantitative analysis algorithm model of the present invention uses an integral function to accumulate the power consumption in a time interval to obtain the energy consumption of the electrical equipment, which has outstanding technical effects.

[0039] In a further embodiment, the embedded acquisition control model includes a timing control module, a time-sharing acquisition control module and a data verification control module. The output end of the timing control module is connected to the input end of the time-sharing acquisition control module, and the output end of the time-sharing acquisition control module is connected to the input end of the data verification control module; the timing control module adopts an external crystal oscillator clock control method to generate a clock control signal to trigger the information acquisition module to collect power consumption data according to a sampling period. The external crystal oscillator clock control method configures the pre-division value and counting pulse value of the clock source to realize that the clock source generates a clock control signal according to the sampling period. When the pre-division value of the clock source is 7999, a counting pulse of 1ms is obtained. The clock control signal triggers the embedded information acquisition module to collect power consumption data through an external crystal oscillator pin.

[0040] In a further embodiment, the time-sharing collection control module adopts time-division multiplexing collection control to divide the task of collecting electricity consumption data into at least 7 sub-tasks, and completes all electricity consumption data collection within at least 7 sampling cycles, thereby reducing the burden on the electricity consumption information collection terminal and ensuring the correctness of electricity consumption data collection. The time-division multiplexing collection control controls the embedded information collection module through time-division multiplexing time and task allocation to only collect the sub-tasks that currently need to be collected in each sampling cycle, thereby avoiding the pressure and delay caused by collecting electricity consumption data tasks at the same time.

[0041] In a further embodiment, the data calibration control module uses a cyclic redundancy check method and a data error calibration method to check and correct the collected electricity consumption data, thereby improving the integrity and accuracy of the collected electricity consumption data. The cyclic redundancy check method uses a check code operation to perform an XOR operation on each bit of the electricity consumption data to generate a check code. The cyclic redundancy check method uses a CRC polynomial to check the electricity consumption data according to the check code to identify and mark abnormal data points. The data error calibration method uses a data interpolation algorithm to repair and reconstruct abnormal data points according to the marked abnormal data points, thereby ensuring the integrity of the electricity consumption data. The data interpolation algorithm derives the values ​​of missing data points according to known electricity consumption data through polynomial fitting. The data interpolation algorithm uses a spline difference fitting function to smoothly fit known abnormal data points according to the values ​​of missing data points, thereby correcting the electricity consumption data.

[0042] In a specific embodiment, the embedded acquisition control model consists of three parts: a timing control module, a time-sharing acquisition control module and a data verification control module. Their functions are as follows: Timing control module: manages and controls the time series of data acquisition to ensure that the data is collected in a predetermined time sequence. This module generally includes a high-precision timer or real-time clock, which can provide a reliable reference time. Time-sharing acquisition control module: divides the entire data acquisition process into multiple time periods, and performs corresponding data acquisition tasks in each time period. This module can prioritize different sensors or measuring devices and prevent conflicts between different devices. Data verification control module: is responsible for checking and verifying the collected raw data to ensure its accuracy and integrity. This module can use various algorithms and techniques to detect or correct abnormal values, omissions, misreporting and other problems, thereby improving data quality. These three parts work together to form a complete embedded acquisition control system. By reasonably designing and configuring these components, an efficient, accurate, stable and reliable data acquisition process can be achieved, providing a good foundation for subsequent data analysis and application.

[0043] The data calibration control module is an important component used to check and correct the collected power consumption data to improve the integrity and accuracy of the collected power consumption data. Among them, the cyclic redundancy check method and the data error calibration method are two common calibration methods. The cyclic redundancy check (CRC) method is a data verification method. It uses the principle of polynomial division to convert the data to be transmitted into a polynomial according to certain rules, and generates a check code of fixed length by calculation. After receiving the data, the receiving end also calculates and generates the check code according to the same rules, and compares it with the check code generated by the sending end. If the two check codes are inconsistent, it means that there is an error in the data. This method can quickly and efficiently detect multiple types of data errors. Another common data error calibration method is to detect and correct based on a standard reference source (such as standard resistance, standard voltage, etc.). This method first measures the true value generated by the standard reference source through a precision instrument, then compares the collected power consumption data with the standard reference source, calculates the error between the two, and calibrates the collected power consumption data accordingly. This method can effectively eliminate errors caused by factors such as sensors and circuits, and improve the accuracy and stability of data. To sum up, the data calibration control module uses a cyclic redundancy check method and a data error calibration method to check and correct the collected power consumption data, which can not only quickly and efficiently detect transmission errors, but also eliminate errors caused by various factors, thereby improving the integrity and accuracy of the collected power consumption data.

[0044] In a further embodiment, the data visualization interface configuration design method adopts a BI data visualization library to add real-time updated electricity consumption data in a visualization display screen. The BI data visualization library is connected to a blockchain centralized data storage library built into a power consumption information collection terminal through an application program interface to obtain electricity consumption data and electricity consumption data analysis and detection results. The BI data visualization library adopts visualization design to map the electricity consumption data analysis results into chart elements of energy consumption statistics, power factor and load analysis in real time.

[0045] In a specific embodiment, the BI data visualization library (Business Intelligence Data Visualization Library) is a tool or software library for displaying and presenting data. It provides various charts, dashboards, and reports, etc., which are used to convert data into a visual form that is easy to understand and analyze, helping users to better understand data, discover trends and patterns, and make decisions based on data. The BI data visualization library usually provides a variety of chart types, such as bar charts, line charts, pie charts, scatter charts, etc., and suitable charts can be selected for display according to different needs. It also supports operations such as filtering, sorting, and aggregation of data so that users can view and analyze data according to their needs. The visual display screen is a device or display device specifically used to display visual content. It usually has a large screen size and high resolution, and can clearly display complex charts and dashboards. The visual display screen can be a TV wall, a large-screen projector, or other equipment specially designed to display data visualization content. In the data display module, by combining the BI data visualization library with the visual display screen, it is possible to display the real-time updated power consumption data to the user in a clear and intuitive manner. Users can understand the power consumption in real time by observing the charts and dashboards on the visual display screen, and perform data analysis and decision-making.

[0046] Although the specific embodiments of the present invention are described above, it should be understood by those skilled in the art that these specific embodiments are only illustrative, and those skilled in the art may make various omissions, substitutions and changes to the details of the above methods and systems without departing from the principles and essence of the present invention. For example, merging the above method steps so as to perform substantially the same functions in substantially the same manner to achieve substantially the same results is within the scope of the present invention. Therefore, the scope of the present invention is limited only by the appended claims.

Claims

1. A power consumption information collection terminal detection system, characterized in that: The system includes a power module, a wireless data transmission module, a blockchain data storage module, an embedded information collection module, an automatic collection and control module, an electricity consumption information analysis and detection module, and a data visualization module; The power supply module uses an AC power grid to supply power to the power consumption information collection terminal detection system; The data wireless transmission module uses a wireless communication network with a blockchain interface to transmit the power consumption data to the blockchain data storage module; The blockchain data storage module uses the blockchain centralized data storage library built into the electricity consumption information collection terminal to centrally store the electricity consumption data and the electricity consumption data analysis and detection results; The embedded information acquisition module is used to collect power consumption data of the electrical equipment, and the power consumption data at least includes voltage, current, temperature, pressure, switch quantity state, power and pulse signal frequency. The embedded information acquisition module comprises an analog signal acquisition circuit, a digital-to-analog conversion module, a level matching circuit, a digital signal acquisition circuit and an information classification module; the output end of the analog signal acquisition circuit is connected to the input end of the digital-to-analog conversion module, the output end of the digital-to-analog conversion module is connected to the input end of the level matching circuit, the analog signal acquisition circuit, the level matching circuit and the digital signal acquisition circuit are connected in parallel, and the output end of the digital signal acquisition circuit is connected to the input end of the information classification module; The automatic collection control module is used to control the automatic collection of electricity consumption data. The automatic collection control module uses an embedded collection control model to control the embedded information collection module to collect electricity consumption data, thereby realizing the automation of electricity consumption data collection and improving the speed and quality of electricity consumption data collection; The power consumption information analysis and detection module is used to enable the power consumption information collection terminal to analyze and detect the energy consumption, power factor and load of the detected equipment. The power consumption information analysis and detection module uses a quantitative analysis algorithm model to analyze and calculate according to the power consumption data to obtain the energy consumption, power factor and load of the detected equipment; The data visualization module is used to display the power consumption data and the power consumption data analysis and detection results to the user in real time. The data visualization module realizes the visualization display of the power consumption data and the power consumption data analysis and detection results through the data visualization interface configuration design method; The output end of the automatic acquisition control module is connected to the input end of the embedded information acquisition module, the output end of the embedded information acquisition module is connected to the input end of the data wireless transmission module, the output end of the data wireless transmission module is connected to the input end of the blockchain data storage module, the output end of the blockchain data storage module is connected to the input end of the power consumption information analysis and detection module, the output end of the power consumption information analysis and detection module and the output end of the blockchain data storage module are connected to the input end of the data visualization module, and the output end of the power supply module is respectively connected to the input ends of the data wireless transmission module, the blockchain data storage module, the embedded information acquisition module, the automatic acquisition control module, the power consumption information analysis and detection module and the data visualization module.

2. The power consumption information collection terminal detection system according to claim 1 is characterized in that: The analog signal acquisition circuit adopts an integral approximation conversion method to linearize and filter the physical quantities of electrical equipment obtained by voltage transformers, Hall sensors, thermistors and pressure sensors to obtain accurate voltage, current, temperature and pressure analog signals. The integral approximation conversion method samples and discretizes continuous analog signals through random sampling to achieve signal mode conversion, and amplifies, filters and samples analog signals. The integral approximation conversion method adopts analog filtering to integrate analog signals through an integration circuit to achieve analog signal filtering. The integral approximation conversion method amplifies the analog signal to 5.5 times through an analog amplifier circuit to reduce the noise and interference of the analog signal. The integral approximation conversion method periodically samples from the analog signal through analog sampling processing to achieve equal-interval sampling of the analog signal.

3. The power consumption information collection terminal detection system according to claim 1 is characterized in that: The digital-to-analog conversion circuit adopts an analog-to-digital conversion quantization method to convert the analog signal collected by the analog signal acquisition circuit into a discrete digital signal. The analog-to-digital conversion quantization method adopts a sampling and holding circuit to perform discrete sampling processing on the collected continuously changing analog signal to obtain a series of equally spaced sampling points. The analog-to-digital conversion quantization method then quantizes each sample point through quantization coding to map the sampling points of voltage, current, temperature and pressure into digital quantities with fixed precision. The level matching circuit adopts a cascade feedback control loop to confirm that the sampling frequency and sampling precision of the sampling and holding circuit match the analog signal, so as to ensure the precision and quality of the digital quantity when converting the signal from analog to digital quantity. The cascade feedback control loop confirms that the sampling frequency of the sampling and holding circuit matches the analog signal according to Nyquist sampling. The cascade feedback control loop confirms that the sampling precision of the sampling and holding circuit matches the analog signal according to the quantization precision and the signal-to-noise ratio.

4. The power consumption information collection terminal detection system according to claim 1 is characterized in that: The digital signal acquisition module adopts a pulse recording and analysis method to record the switch state, power and pulse signal frequency without distortion. The pulse recording and analysis method adopts a programmable gate array to count and accurately record the time and number of switch state changes. The pulse recording and analysis method uses an analog-to-digital converter to discretely sample the input signal in time, and detects and identifies the sampling signal power through threshold comparison to achieve power extraction of the detected sampling signal. The pulse recording and analysis method uses a real-time sampling digital oscilloscope to continuously and stably record the pulse signal frequency to obtain a complete pulse signal frequency waveform; the information classification module uses an automatic execution smart contract to automatically classify, verify and transfer the collected electricity consumption data, so as to allocate the electricity consumption data to the blockchain data storage module for storage and subsequent analysis and processing.

5. The power consumption information collection terminal detection system according to claim 1 is characterized in that: The quantitative analysis algorithm model includes an energy consumption detection module, a power factor detection module and a load characteristic index detection module. The energy consumption detection module divides the power consumption data according to the time interval by dividing the data into equal intervals. The energy consumption detection module analyzes the power consumption data within the time interval by linear integration and exponential integration to obtain the power consumption within the time interval. The energy consumption detection module then accumulates the power consumption within the time interval by an integral function to obtain the energy consumption of the electrical equipment. The energy consumption calculation formula of the electrical equipment is: （1） In formula (1), is the energy consumption of electrical equipment, is the time interval, is the power consumption in the time interval, is the output voltage of the electrical equipment, is the output current of the electrical equipment; The power factor detection module uses a principal component extraction calculation algorithm to extract active power and reactive power from the power consumption data. The principal component extraction calculation algorithm performs standardization processing on the power consumption data through principal component dimensionality reduction analysis. The principal component extraction calculation algorithm then calculates the active power and reactive power in the principal components of the power consumption data through covariance matrix and singular value decomposition. The power factor detection module calculates the power factor of the power fluctuation of the power consumption equipment during the power consumption time according to the active power and reactive power in the power consumption data through a linear regression function. The active power extraction calculation formula in the power consumption data is: （2） In formula (2), is the active power in the power consumption data, is the sampling frequency of the Hall sensor for current, is the covariance power matrix of electricity consumption data, is the product of current and voltage; The calculation formula for reactive power extraction in the power consumption data is: F （3） In formula (3), F is the reactive power in the power consumption data, is the sampling frequency of the voltage transformer for voltage, The power collected by the electrical equipment; The calculation formula of the power factor is: （4） In formula (4), is the power factor, is the linear regression function, The pulse signal frequency of the electrical equipment; The load characteristic index detection module uses a state filtering conversion method to convert the power consumption data into a load curve and perform quantitative analysis on the load curve. The state filtering conversion method accumulates the power values ​​of the power consumption data on the time axis according to time intervals through recursive conversion to obtain a load curve. The state filtering conversion method identifies the peak and trough of the load curve through a load curve fitting function and extracts the load characteristic index. The load characteristic index calculation formula is: （5） In formula (5), is the load characteristic index, is the peak value of the load curve, The trough of the load curve. is the load curve fitting function, The temperature of the electrical equipment.

6. The power consumption information collection terminal detection system according to claim 1, characterized in that: The embedded acquisition control model includes a timing control module, a time-sharing acquisition control module and a data verification control module. The output end of the timing control module is connected to the input end of the time-sharing acquisition control module, and the output end of the time-sharing acquisition control module is connected to the input end of the data verification control module; the timing control module adopts an external crystal oscillator clock control method to generate a clock control signal to trigger the information acquisition module to collect power consumption data according to a sampling period. The external crystal oscillator clock control method configures the pre-division value and count pulse value of the clock source to realize that the clock source generates a clock control signal according to the sampling period. When the pre-division value of the clock source is 7999, a count pulse of 1ms is obtained. The clock control signal triggers the embedded information acquisition module to collect power consumption data through an external crystal oscillator pin.

7. The power consumption information collection terminal detection system according to claim 6 is characterized in that: The time-sharing collection control module adopts time-division multiplexing collection control to divide the task of collecting electricity consumption data into at least 7 sub-tasks, and completes all electricity consumption data collection within at least 7 sampling cycles, reducing the burden on the electricity consumption information collection terminal and ensuring the correctness of electricity consumption data collection. The time-division multiplexing collection control controls the embedded information collection module through time-division multiplexing time and task allocation to only collect the sub-tasks that currently need to be collected in each sampling cycle, avoiding the pressure and delay caused by collecting electricity consumption data tasks at the same time.

8. The power consumption information collection terminal detection system according to claim 6, characterized in that: The data calibration control module adopts a cyclic redundancy check method and a data error calibration method to check and correct the collected power consumption data, so as to improve the integrity and accuracy of the collected power consumption data. The cyclic redundancy check method adopts a check code operation to perform an XOR operation on each bit of the power consumption data to generate a check code. The cyclic redundancy check method adopts a CRC polynomial to check the power consumption data according to the check code, so as to identify and mark abnormal data points. The data error calibration method adopts a data interpolation algorithm to repair and reconstruct abnormal data points according to the marked abnormal data points, so as to ensure the integrity of the power consumption data. The data interpolation algorithm derives the value of the missing data point according to the known power consumption data through polynomial fitting. The data interpolation algorithm performs smooth fitting on the known abnormal data points according to the value of the missing data points through a spline difference fitting function, so as to correct the power consumption data.

9. The power consumption information collection terminal detection system according to claim 1, characterized in that: The data visualization interface configuration design method adopts a BI data visualization library to add real-time updated electricity consumption data in a visualization display screen. The BI data visualization library is connected to a blockchain centralized data storage library built into an electricity consumption information collection terminal through an application program interface to obtain electricity consumption data and electricity consumption data analysis and detection results. The BI data visualization library adopts visualization design to map the electricity consumption data analysis results to chart elements of energy consumption statistics, power factor and load analysis in real time.

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