scholarly journals Research on an invasive and low-frequency power consumption data acquisition method

2021 ◽  
Vol 2078 (1) ◽  
pp. 012059
Author(s):  
Weijia Sun ◽  
Hui Wang ◽  
Yongfeng Liu
Keyword(s):  
Power Consumption ◽  
Data Acquisition ◽  
Large Scale ◽  
Time Synchronization ◽  
Low Frequency ◽  
Acquisition Scheme ◽  
Reliability Issue ◽  
Local Storage ◽  
Scale Compatibility ◽  
Low Frequency Power

Abstract Aiming at the large-scale, compatibility and reliability problems faced by the data acquisition engineering for power consumption in the industrial field, for reducing the complexity and cost of the data acquisition engineering, and improving the quality, maintainability, scalability and manageability of the data acquisition, an engineering-oriented, intrusive, low-frequency data acquisition scheme for power consumption is proposed. The scheme leverages multi-agent networking technology to solve the large-scale problem, utilizes the communication driver of the dynamic loading adapter mode to tackle the compatibility trouble. Furthermore, the local storage, breakpoint retransmission, flow control, automatic recovery, automatic connection, and time synchronization are combined to solve the reliability issue. Engineering tests show that the proposed scheme possesses the significant backward compatibility characteristics, which can effectively reduce the complexity and cost of data acquisition engineering for power consumption, and significantly improve the quality, maintainability, scalability and manageability of data acquisition.

scholarly journals Application and Evolution for Neural Network and Signal Processing in Large-Scale Systems

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Dongbao Jia ◽  
Cunhua Li ◽  
Qun Liu ◽  
Qin Yu ◽  
Xiangsheng Meng ◽  
...  
Keyword(s):  
Signal Processing ◽  
Large Scale ◽  
Brain Activity ◽  
Low Frequency ◽  
Frequency Characteristics ◽  
Brain Diseases ◽  
Time Dimension ◽  
Frequency Oscillation ◽  
Low Frequency Oscillation ◽  
Low Frequency Power

Low frequency oscillation is an important attribute of human brain activity, and the amplitude of low frequency fluctuation (ALFF) is an effective method to reflect the characteristics of low frequency oscillation, which has been widely used in the treatment of brain diseases and other fields. However, due to the low accuracy of the current analysis methods for low frequency signal extraction of ALFF, we propose the Fourier-based synchrosqueezing transform (FSST), which is often used in the field of signal processing to extract the ALFF of the low frequency power spectrum of the whole-time dimension. The low frequency characteristics of the extracted signal are compared with those of FSST and fast Fourier transform (FFT) through the resting-state data. It is clear that the signal extracted by FSST has more low frequency characteristics, which is significantly different from FFT.

scholarly journals An Optimal Load Disaggregation Method Based on Power Consumption Pattern for Low Sampling Data

2019 ◽  
Vol 11 (1) ◽  
pp. 251 ◽  
Author(s):  
Huijuan Wang ◽  
Wenrong Yang ◽  
Tingyu Chen ◽  
Qingxin Yang
Keyword(s):  
Power Consumption ◽  
Optimization Model ◽  
Smart Grids ◽  
Large Scale ◽  
Reactive Power ◽  
Low Frequency ◽  
Performance Comparison ◽  
Consumption Pattern ◽  
Frequency Data ◽  
Load Disaggregation

In recent years, Smart Grids have been developing globally. Since smart meters only acquire low-frequency data, non-intrusive load monitoring technology using the signature extracted from high-frequency data needs an additional measurement device to be installed, so it is not suitable for promotion to the smart grid environment. However, methods using low-frequency features are poorly-suited when several appliances are switched on at the same time, or devices with similar power values are used. In response to these problems, this paper proposes a load disaggregation method based on the power consumption patterns of appliances, combining an improved mathematical optimization model and optimized bird swarm algorithm (OBSA) for load disaggregation. Experiments show that the method can effectively identify the operating states of appliances, and deal with situations in which multiple instruments have similar power characteristics or are simultaneously switching. The performance comparison proves that the improved model is more efficient than the traditional active and reactive power (PQ) optimization model in load disaggregation performance and computation time, and also verifies the robustness of the proposed method and the convergence of OBSA. As an inexpensive method without extra measurement hardware installed, the process is suitable for large-scale applications in smart grids.

scholarly journals Bridging the gap – Spontaneous fluctuations shape stimulus-evoked spectral power

2020 ◽  
Author(s):  
Soren Wainio-Theberge ◽  
Annemarie Wolff ◽  
Georg Northoff
Keyword(s):  
Neural Activity ◽  
Large Scale ◽  
Spectral Power ◽  
Low Frequency ◽  
Positive Interaction ◽  
Scale Free ◽  
The Time Domain ◽  
Low Frequency Power ◽  
Spontaneous Fluctuations ◽  
Frequency Power

AbstractSpontaneous fluctuations of neural activity have been shown to influence trial-by-trial variation in perceptual, cognitive, and behavioural outcomes. This implies that these fluctuations affect stimulus-related neural processes, and hence should affect stimulus-evoked neural activity. However, the mechanisms by which spontaneous neural activity shapes stimulus-evoked neural activity have rarely been examined. Employing a large-scale magnetoencephalographic dataset, as well as an electroencephalographic replication dataset, we observed that for high-frequency power, high pre-stimulus activity leads to greater evoked desynchronization (negative interaction); in contrast, for low-frequency power, high pre-stimulus activity induces greater event-related synchronization (positive interaction). We show that both positive and negative interactions are manifest primarily in cortical oscillations, rather than scale-free activity, and can also be observed in the time domain. In summary, we demonstrate positive and negative spontaneous-evoked interaction in multiple electrophysiological processes; these mechanisms “bridge the gap” between spontaneous and evoked activity and provide novel insights into how spontaneous activity influences behaviour and cognition.

Survey of Ambient Excitation Based Power Oscillation Analysis Methods

2012 ◽  
Vol 614-615 ◽  
pp. 1013-1018
Author(s):  
Chang Liu ◽  
Chang Song Li ◽  
Hua Qiang Li
Keyword(s):  
Power System ◽  
Large Scale ◽  
Low Frequency ◽  
Fundamental Principle ◽  
Low Frequency Oscillation ◽  
Operation Analysis ◽  
Power Oscillation ◽  
Oscillation Analysis ◽  
Low Frequency Power ◽  
Ambient Excitation

In large-scale power system, low frequency power oscillation is becoming a serious threat to the power system operation. Analysis of low frequency oscillation includes model-based method and ambient-excitation-based method. Based on the investigation of the related recently-published papers, this paper presents a survey of ambient-excitation-based method. Firstly, the fundamental principle and underlying theory of ambient-excitation-based method are summarized. Furthermore, several ambient-excitation-based methods are categorized and their characteristics are introduced.

scholarly journals Distributed Data Acquisition System for Condition Monitoring of Low-speed Machines Using Wireless Sensor Networks

2016 ◽  
Vol 12 (1) ◽  
pp. 17 ◽  
Author(s):  
Kai Zheng ◽  
Yun Zhang ◽  
Lei Liu ◽  
Chen Zhao
Keyword(s):  
Power Consumption ◽  
Data Acquisition ◽  
Condition Monitoring ◽  
Low Frequency ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Signal Acquisition ◽  
Actual Measurement ◽  
Low Speed ◽  
Measurement Results

Low-speed machines play an important role in industrial production, and the condition monitoring of these machines is of great importance. Monitoring with wireless sensor network (WSN) has many advantages. To monitor the condition of low-speed machines, we need to acquire low-frequency, weak and hardly-varying physical signals. As such, we designed a WSN system for high-precision signal acquisition. Actual measurement results showed that the acquisition precision of nodes could reach 0.01 mV. When the sensor nodes continuously acquired and sent data, the energy conversion efficiency was higher than 90% and the nodes’ power consumption came to about 110mW. The WSN system was designed based on the low-power consumption 802.15.4 MAC/Zigbee, and the WSN was built through MESH topology. Data transmission was stable and the PER was lower than 1%. The measurement results under laboratory and industrial field conditions showed that the WSN system designed met the requirements for on-site data acquisition and monitoring of low-speed machines.

Development of a Low Frequency Electric Field Probe Integrating Data Acquisition and Storage

2020 ◽  
Vol E103.C (8) ◽  
pp. 345-352
Author(s):  
Zhongyuan ZHOU ◽  
Mingjie SHENG ◽  
Peng LI ◽  
Peng HU ◽  
Qi ZHOU
Keyword(s):  
Electric Field ◽  
Data Acquisition ◽  
Low Frequency ◽  
Frequency Electric Field ◽  
Electric Field Probe ◽  
And Storage

scholarly journals Toward asleep DBS: cortico-basal ganglia spectral and coherence activity during interleaved propofol/ketamine sedation mimics NREM/REM sleep activity

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Jing Guang ◽  
Halen Baker ◽  
Orilia Ben-Yishay Nizri ◽  
Shimon Firman ◽  
Uri Werner-Reiss ◽  
...  
Keyword(s):  
Basal Ganglia ◽  
Rem Sleep ◽  
Standard Procedure ◽  
Low Frequency ◽  
Nrem Sleep ◽  
Sleep Cycle ◽  
Advanced Parkinson’S Disease ◽  
Low Frequency Power ◽  
The Brain ◽  
Frequency Power

AbstractDeep brain stimulation (DBS) is currently a standard procedure for advanced Parkinson’s disease. Many centers employ awake physiological navigation and stimulation assessment to optimize DBS localization and outcome. To enable DBS under sedation, asleep DBS, we characterized the cortico-basal ganglia neuronal network of two nonhuman primates under propofol, ketamine, and interleaved propofol-ketamine (IPK) sedation. Further, we compared these sedation states in the healthy and Parkinsonian condition to those of healthy sleep. Ketamine increases high-frequency power and synchronization while propofol increases low-frequency power and synchronization in polysomnography and neuronal activity recordings. Thus, ketamine does not mask the low-frequency oscillations used for physiological navigation toward the basal ganglia DBS targets. The brain spectral state under ketamine and propofol mimicked rapid eye movement (REM) and Non-REM (NREM) sleep activity, respectively, and the IPK protocol resembles the NREM-REM sleep cycle. These promising results are a meaningful step toward asleep DBS with nondistorted physiological navigation.

scholarly journals Experiment Investigation of Bistable Vibration Energy Harvesting with Random Wave Environment

2021 ◽  
Vol 11 (9) ◽  
pp. 3868
Author(s):  
Qiong Wu ◽  
Hairui Zhang ◽  
Jie Lian ◽  
Wei Zhao ◽  
Shijie Zhou ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Energy Harvesting ◽  
Cantilever Beam ◽  
Large Scale ◽  
Low Frequency ◽  
Vibration Energy ◽  
Random Wave ◽  
Periodic Signal ◽  
Vibration Energy Harvesting ◽  
Motion Activity

The energy harvested from the renewable energy has been attracting a great potential as a source of electricity for many years; however, several challenges still exist limiting output performance, such as the package and low frequency of the wave. Here, this paper proposed a bistable vibration system for harvesting low-frequency renewable energy, the bistable vibration model consisting of an inverted cantilever beam with a mass block at the tip in a random wave environment and also develop a vibration energy harvesting system with a piezoelectric element attached to the surface of a cantilever beam. The experiment was carried out by simulating the random wave environment using the experimental equipment. The experiment result showed a mass block’s response vibration was indeed changed from a single stable vibration to a bistable oscillation when a random wave signal and a periodic signal were co-excited. It was shown that stochastic resonance phenomena can be activated reliably using the proposed bistable motion system, and, correspondingly, large-scale bistable responses can be generated to realize effective amplitude enlargement after input signals are received. Furthermore, as an important design factor, the influence of periodic excitation signals on the large-scale bistable motion activity was carefully discussed, and a solid foundation was laid for further practical energy harvesting applications.

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