Microcontroller is widely used in the intelligent life of modern society. Intelligent development based on Microcontroller to solve the actual needs of people's life, work, study and other fields is the core of Microcontroller application. Therefore, it is a task for researchers to understand the structure and performance of microcontroller, develop software, and be familiar with the method and process of intelligent development based on microcontroller. And with that in mind, this paper designs and produces a physical hardware system for indoor environment detection based on STM32 microcontroller. The system can detect the light intensity, temperature and humidity, and CO gas concentration in the indoor environment; and the data is integrated and processed by the STM32 microcontroller to display the current parameter values of each quantity in the indoor environment on a 3.5-inch resistive screen; at the same time, the PC can also log in to the OneNET cloud platform through the web page, and display the light intensity, temperature and humidity, and CO gas concentration values in the indoor environment in real time in the device created by OneNET for real-time viewing. The system can also display the light intensity, temperature and humidity, and CO gas concentration values in the indoor environment in real time. The hardware system has been tested and tested to achieve its function.
The most generally used technique of load power monitoring is non-intrusive load monitoring, which requires only one device to be mounted on the bus to monitor the current parameters and the working state of various types of appliances within the total load. It is required to investigate a cost-effective nonintrusive load monitoring and identification system that can perform a range of duties such as fault monitoring, energy monitoring, and fault analysis without requiring a significant number of sensing components. Measurement of electrical values of commonly used home appliances during stable operation, followed by feature extraction and electrical feature analysis to identify appliance types, can help residential users understand appliance habits and consciously reduce consumption and losses while enabling fault detection. The STM32F103RCT6 core control chip and the SUI-101 energy metering module are used in this system to monitor and evaluate load characteristics using the Modbus-RTU communication protocol. The active and reactive power of the load is measured and recorded in the learning mode; in the analysis and identification mode, the electrical parameters of the current appliance, such as current, voltage, active power, reactive power, frequency, and power factor, can be displayed in real-time, and the corresponding load can be deduced using binary simulation and the Euclidean distance matching method. The device has a short learning time and good identification accuracy for typical household appliances, according to the system test, and can satisfy the analysis and recognition of electrical appliances in a regular domestic setting. The current device design combines the advantage of cheap cost, low power consumption, and portability, making it a viable alternative for domestic appliance identification and monitoring.
The manuscript developed an optimal frequency band transmission system structure of QPSK. The software programming experiment of this complete QPSK optimal band transmission system is designed and realized based on Matlab. The experimental parameters used in the design are consistent with the requirements of the actual system parameters. The key code of the software design is given in each module of the system. The whole system is simulated. The simulation results show that the QPSK optimal band transmission system can achieve the best reception performance and realize its function.
This paper mainly studies the data characteristics of high order cumulants using digitally modulated signals, and constructs the identification feature parameters that can distinguish the signal modulation type by the high-order cumulants data of the digital modulation signal. Set the identification signal modulation type determination threshold based on the value of the identification feature parameter. The identification feature parameter value of the signal modulation type is compared with the set determination threshold, to realize the recognition of digital modulation signal. This identification method is implemented based on MATLAB design, with a 2ASK (2-ary Amplitude Shift Keying) signal, 4ASK (4-ary Amplitude Shift Keying) signal, 2PSK (2-ary Phase Shift Keying) signal, 4PSK (4-ary Phase Shift Keying) signal, 2FSK (2-ary Frequency Shift Keying) signal, 4FSK (4-ary Frequency Shift Keying) signal. The second, fourth and sixth order cumulants of the six signals were analyzed. Calculate the selected identification feature parameter value and the determination threshold to identify the six signals. The six signals have made MATLAB identification simulation. Simulation results show that this method is feasible and has high recognition rate. Simulation results verify that such recognition methods maintain a high recognition rate under conditions with low signal-to-noise ratio. This identification method can be extended to more MASK (M-ary Amplitude Shift Keying), MPSK (M-ary Phase Shift Keying), MFSK (M-ary Frequency Shift Keying), MQAM (M-ary Quadrature Amplitude Modulation) signal identification.
This paper designs a simulation experiment model of the overall structure of time-division multiplexing digital optimal frequency band transmission system based on MATLAB simulation platform. The parameters of each module in the simulation model are set. The working process and performance of the time-division multiplexing digital optimal band transmission system are simulated. The simulation results show that the digital optimal band transmission system achieves the best transmission receiving conditions and performance, and the designed time-division multiplexing optimal digital band transmission simulation system achieves its functions. The research in this paper will help to improve the level of digital communication technology and to understand the structure of time-division multiplexing digital optimal band transmission system.
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