Real-time Power Measurement Research Articles

Automatic real-time fire distance, size and power measurement driven by stereo camera and deep learning

Automatic real-time fire characterization is a crucial requirement of future smart firefighting. This work proposes a novel computer vision method to automatically measure the fire heat release rate, even when the camera is moving in real-time. Firstly, a portable binocular stereo camera is used to capture the real-time fire video stream that is fed into a pre-trained computer-vision model frame-by-frame to detect the fire region. By identifying the fire location inside the image, the real-time distance between the camera and the fire source is determined. This fire distance helps re-scale the images to match the input scale of the AI-image Fire Calorimetry. Then, the deep learning model can automatically output the transient fire power in real time. Results show that the stereo vision system is capable of accurately measuring the distance between the camera and the fire source, flame height, and power, with a relative error of less than 20%. This work provides an automatic and flexible way to measure the distance, power and hazard of fire in real-time, and such a method has broad applications in firefighting operations and decision-making.

Model-based feed rate optimization for cycle time reduction in milling

Feed rate is an important determinant of the cutting force and cycle time. Selection of an appropriate feed rate can increase the processing quality and production efficiency. To determine an optimized feed rate, many methods have been developed to maintain a constant cutting force by applying a real-time feedback system constructed with data such as the tool condition, temperature, and cutting load of the spindle. However, these methods have low reliability because of difficulty in accurately measuring the spindle load. Moreover, real-time changes in the feed rate alter the cycle time. This study optimized the feed rate to a value that maintains the cutting force based on a cutting force prediction model and an algorithm to extract the cutting conditions from each line of the G-code. The feed rate optimization was applied to a flat end mill and ball end mill. An interpreter for the G-code was configured to calculate the tool center point and cutting condition. A real-time spindle power measurement system was constructed to measure the cutting force in each line of the G-code by identifying the parameters of the cutting force prediction model. The cutting force criterion was selected as the highest value among the predicted cutting forces. The optimized feed rate that maintains the cutting force was extracted based on the cutting conditions in other lines and the cutting force prediction model. The extracted feed rate was applied to the G-code by modifying only the feed rate command. Experimental results obtained with a commercial machining tool show that the proposed feed rate optimization significantly reduces the overall cycle time and effectively maintains the cutting force.

A study on the energy saving of lighting through the development of integrated control of multifunctional shading system

Recently, interest in integrated shading and lighting control, which are building components, is increasing to reduce the energy used in buildings. However, the multi-functional shading system, which has recently been distributed, has a natural lighting function through ceiling reflection by introducing sunlight into the room, but it is difficult to control interworking with surrounding electric lighting and integrated control is impossible due to solar reflection or acquisition. In order to solve this problem, we intend to design and implement an integrated control system for multifunctional shading devices that affect the indoor light environment and thermal environment and are effective in reducing lighting energy. This study can reduce energy in buildings by controlling the temperature through an internally integrated control system for the inflow of sunlight into the room. In addition, integrated monitoring control is possible through real-time power and energy measurement and on-site sensor data management. As a result of this study, 34.5% of lighting energy could be saved through the study of the automated system of integrated control of multifunctional shading devices.

Systematic and Random Errors in the Net Power Measurement Using a Reflectometer

Net power delivered to a device is one of the important quantities to obtain various free field parameters in the radio frequency band, such as electric field strength, and a reflectometer is one practical choice for the real-time net power measurement. In carrying out the net power measurement, a pair of reflectometer calibration coefficients obtained by assuming the coupler idealities is used to estimate the forward and reverse traveling powers at the test port. In this article, the systematic and random errors of the measured net power by using the reflectometer are thoroughly discussed in terms of the terminal condition at the test port. In addition, useful parameters to evaluate the quality of the dual-directional coupler as a component of the reflectometer are proposed.

Real-Time Power Measurement Using the Maximal Overlap Discrete Wavelet-Packet Transform

This paper proposes the real-time estimation of the root-mean-square (rms) values, primary power quantities (active, total apparent, nonactive power, and power factor), and distortion power using the maximal overlap wavelet packet transform (MODWPT). The MODWPT provides a uniform frequency band and possesses the time-invariance property, which is ideal for the real-time power estimation. The performance of the proposed wavelet-based power measurement was assessed and compared to the IEEE Standard 1459-2010 in different case studies including stationary synthetic waveforms and power quality disturbances in experimental setup. The proposed method presented good results in the estimation of rms values and primary power quantities by using compact mother wavelets, whereas the estimation of distortion power was better with long mother wavelets.

Marcher: A Heterogeneous System Supporting Energy-Aware High Performance Computing and Big Data Analytics

Abstract Excessive energy consumption is a major constraint in designing and deploying the next generation of supercomputers. Minimizing energy consumption of high performance computing and big data applications requires novel energy-conscious technologies (both hardware and software) at multiple layers from architecture, system support, and applications. In the past decade, we have witnessed the significant progress toward developing more energy-efficient hardware and facility infrastructure. However, the energy efficiency of software has not been improved much. One obstacle that hinders the exploration of green software technologies is the lack of tools and systems that can provide accurate, fine-grained, and real-time power and energy measurement for technology evaluation and verification. Marcher, a heterogeneous high performance computing infrastructure, is built to fill the gap by providing support to research in energy-aware high performance computing and big data analytics. The Marcher system is equipped with Intel Xeon CPUs, Intel Many Integrated Cores (Xeon Phi), Nvidia GPUs, power-aware memory systems and hybrid storage with Hard Disk Drives (HDDs) and Solid State Disks (SSDs). It provides easy-to-use tools and interfaces for researchers to obtain decomposed and fine-grained power consumption data of these primary computing components. This paper presents the design of the Marcher system and demonstrates the usage of Marcher power measurement tools to obtain detailed power consumption data in various research projects.

Self-adjusted multi-sensor information fusion electric energy measuring based on neural networks

In this article, self-adjusted Multi-sensor Information Fusion measuring method of electric energy based on neural networks has been thoroughly given. This paper studies the method of automatic error correction of electric power measurement also. The effective learning algorithm of the neural network based on gradient algorithm and Newton algorithm is combined with the LEA discriminant method.The results show that the method can improve the learning efficiency. The hardware model of adaptive real-time fast power measurement is constructed by using DSP device. The experimental results show that the adaptive power measurement model is better than the traditional power meter.

Energy Efficiency of Parallel Multicore Programs

The increasing energy consumption of large-scale high performance resources raises technical and economical concerns. A reduction of consumed energy in multicore systems is possible to some extent with an optimized usage of computing and memory resources that is tailored to specific HPC applications. The essential step towards more sustainable consumption of energy is its reliable measurements for each component of the system and selection of optimally configured resources for specific applications. This paper briefly surveys the current approaches for measuring and profiling power consumption in large scale systems. Then, a practical case study of a real-time power measurement of multicore computing system is presented on two real HPC applications: maximum clique algorithm and numerical weather prediction model. We assume that the computing resources are allocated in a HPC cloud on a pay-per-use basis. The measurements demonstrate that the minimal energy is consumed when all available cores (up to the scaling limit for a particular application) are used on their maximal frequencies and with threads binded to the cores.

Direct Real-Time Power Measurement of a High-Power Electron Cyclotron Maser by a Simple One-Point Schottky Detector Signal

Measurements of the absolute power of high-power millimeter/THz wave generators have been considered to be highly variable and to occasionally produce faulty results owing to experimental difficulty. In this study, we propose a calibration-free method for real-time power measurement of an electron cyclotron maser system, a so-called gyrotron. We demonstrate the feasibility of the method by using a recently developed W-band gyrotron with a peak power of tens of kilowatts. The technique is based on transmitter antenna power measurement by using the Friis transmission equation with a defined gyrotron antenna gain. The new technique will allow extremely simple and accurate real-time measurement of output power over a wide dynamic range ( ${>} {\hbox{50}}$ dB) for continuous wave sources to high-power millimeter/THz wave sources with nanosecond pulse lengths.

An investigation on energy-related occupancy behavior for low-income residential buildings

Previous studies show that individuals’ energy consumption tends to outweigh the technical efficiency gains. Occupancy behavior accounts for about 30% of the variance in overall heating consumption and 50% in cooling consumption. In addition, overall energy savings of 10%–20% due to simple behavioral adjustments are a reasonable expectation. Unfortunately, few studies have focused on the specific cases of behavior in low-income houses, where unique individual energy behavior, demographic, and socio-economic factors come into play. This article investigates energy-related occupancy behavior in low-income families through real-time power, indoor environment, and occupancy presence measurement. Four residential houses with different building envelope materials are used as test-beds. Occupancy behavior includes thermostat schedules, occupancy presence, and major appliance usages. A simulation study is further conducted to show the energy impact of occupancy behavior.

Research on Intelligent Power Management System Based on CAN Bus

This paper analyzes the actual situation of the electricity management about student apartments, and design intelligent energy student housing management system based on CAN bus. The system uses the field level, the underlying management level and upper management level three management systems. Field level with a dedicated energy metering chip AD7755 and STM32F103 microcontroller with A/D conversion function as the core, to achieve real-time power measurement; via CAN bus timing or random read live energy data for monitoring electricity consumption of the apartment, investigate abnormal electricity, thus effectively limiting the students to use electrical power to achieve the modernization and automation of power management solutions student apartments.

Design and implementation of real-time power measurement system for server’s key energy components

In view of the high energy consumption and the lack of real-time monitoring system,a power measurement system based on atmegal16 was designed and implemented to survey server's key power components.Consumption of server machine,hard disk,CPU and memory were separately gauged in real-time and displayed in curves.The system used perforated-type external components,without insertion loss,so as to achieve the purpose of measuring non-destructively.The experimental results show that this system is lossless and stable,and the measurement result is consistent with the standard power valuation,which can reflect power change of server's key components in real-time.