| Duty: | Assistant of Departmental Lab Center |
| Email： | Mr.Alex.Hua@outlook.com |
| Department： | Department of Computer Science, North China Electric Power University |
| Major Area of Study： | Software Engineering |
| Title of Award: | Bachelor of Engineering |
| Minor Area(s) of Study: | Sensor network, Software-Hardware programme, Embedded system |
Lei Hua, a passionate and curious student studying Software Engineering at NCEPU.
My website showcases a wide range of interests and research in various fields, spanning software and hardware, computing and communications, design and production. These demonstrate my ability to provide innovative solutions to real-world problems.
My goal is to explore interdisciplinary intersections and contribute to scientific and societal progress.
Selected Awards
- First Class University Scholarship (2023-2024)
- Second Class University Scholarship (2022-2023)
- Merit Student (2023-2024)
- Merit Student (2022-2023)
- National Undergraduate Electronics Design Contest – Ti Cup (provincial level second placer) 2023.8
- Head of Hebei Provincial Student Innovation and Entrepreneurship Programme (Excellent level) 2024.5
- Second Prize Lanqiao Cup National Software and Information Technology Professional Talent Competition 2024.05
- Shenzhen Junior Technology Prodigy Nomination 2020
- The 10th Zayed Future Energy Prize – Global High School Finalist (Shenzhen Yadi School Project Leader) (2018)
Some Products made by me
Edge Gateway (BKGW-01)
Bolt Tightening force Sensor (BKPR-01)
The BKPR-01 is a high-precision pressure sensor with 433MHz radio frequency communication. It is a maintenance-free device that uses a disposable battery and is suitable for use in a wide range of industrial environments. The low-power design with a quiescent current as low as 30uA and the 5-year battery life with dual-acting Li/SOCl₂ batteries in the battery compartment are two of the key features of this product. A cross-platform application is available for receiving sensor data (with the BKGW-01 Edge Gateway), and various battery sizes can be adapted to suit different endurance requirements. By default, 3*M12 screws are used for mounting.
Infrared Image Sensor(BKTMP-1G)
The BKTMP-1G is a temperature image sensor with 433MHz radio frequency communication.The BKTMP-1G is a temperature image sensor that communicates with a 433MHz wireless radio frequency. It uses a disposable battery, which is maintenance-free and can be used in a wide range of industrial environments.The low-power consumption design, with quiescent current as low as 0.02mA, and the BR34615 Li/SOCl₂ battery in the battery compartment can last for several years.A cross-platform application is available for receiving sensor data (with the ND-01 grid).Various battery sizes can be adapted to suit different endurance requirements.The base is mounted with M3 screw holes.
Water Leaking Sensor (BKWL-01)
The BKWL-01 is a water leakage sensor with 433MHz radio frequency communication. It has a simple design and compact size, and is easy to install in specific pipe joints. The Sensirion sensor is characterized by high accuracy and reliability. Low power consumption and stable continuous detection of water leakage. Up to 3 years battery life with replaceable long-life batteries in the battery compartment. A cross-platform application is available for receiving sensor data (in conjunction with the gateway ND-01).
Partial Discharge Sensor (BKEE-01)
The BKEE-01 is a partial discharge sensor that communicates with 433MHz radio frequency. Its compact design and ease of mounting are enhanced by M3 screw holes. The UHF sensor boasts high sensitivity, high noise immunity and a wide bandwidth. The adjustable triggering design ensures stable and continuous detection of abnormal discharge signals under different operating conditions. The dual rechargeable 18650 batteries in the battery compartment have a lifespan of up to two years. A cross-platform application is available for receiving sensor data (with the grid ND-01). A range of battery sizes is available to suit different endurance requirements.
Recent works
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Dataset: Transient dataset of household appliances with Intensive switching events
Authors Dongyang Zhang1,2, Xiaohu Zhang1 ,Lei Hua1 ,Jian Di1 , Wenqing Zhao1,3 , Yumei Ma1 Affiliations Abstract: With the development of Non-Intrusive Load Monitoring (NILM), it has become feasible to perform device identification, energy consumption decomposition, and load switching detection using Deep Learning (DL) methods. Similar to other machine learning…
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