Estimation of Flicker of Contemporary LED Lamps and Luminaires

Petrinska, Iva; Ivanov, Dilyan

doi:10.1109/bulef48056.2019.9030752

Cited by 6 publications

(4 citation statements)

References 3 publications

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“…CFFs for insects and birds are significantly higher than for other classes, and CFFs for fish and amphibians are significantly lower than for other classes. The CFF for humans is typically in the range of [35][36][37][38][39][40], but in some cases, it extends up to 90 Hz [28]. How do these CFF ranges compare to the flicker rates in actual light sources?…”

Section: Previous Studiesmentioning

confidence: 99%

“…This includes the "stroboscopic effect visibility measure" (SVM) [38] and PstLM (short term light modification), which predict the probability of flicker detection and strobe effects for an average human [39]. The calculations of SVM and PstLM are designed for individual luminaires with laboratory measurements and are not suitable for the outdoor measurements [40] presented in this study.…”

Section: Previous Studiesmentioning

confidence: 99%

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Exploring the Hidden World of Lighting Flicker with a High-Speed Camera

Elvidge,

Zhizhin,

Pipkin

et al. 2024

Atmosphere

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Alternating current can result in flickering—or pulsing—in the brightness of light emitted by luminaires. Lighting flicker typically occurs in the range of 100 to 140 cycles per second (Hz), which is too fast for visual perception by most organisms. However, evidence indicates that many organisms perceive flicker with non-visual photoreceptors present on the retinas. Exposure to flickering lights at night disrupts the circadian rhythm of organisms, leading to symptoms similar to blue light exposure at night. The traditional method for detecting flickering is with a flickermeter held near a single light. In this paper, we explore the use of high-speed camera data in the collection of temporal profiles for groups of luminaires simultaneously at distances ranging from several meters to several kilometers. Temporal profiles are extracted for individual lighting features and the full scene. The identification of luminaire types is based on their spectral signatures. With the camera data, it is possible to identify flickering and non-flickering lights, to determine the flicker frequency, to calculate percent flicker and the flicker index, and to identify groups of lights whose flickers are synchronized. Both flickering and non-flickering luminaires can be found for LED, metal halide, fluorescent, and compact fluorescent lights. To date, flickering has been detected in all of the incandescent, high-pressure sodium, and low-pressure sodium luminaires that we measured. We found that flicker synchronization is often present for lights installed within a single facility and also for strings of streetlights. We also found that flicker exposure can come from the light reflected off of the earth’s surface. Luminaires designed to illuminate large areas often saturate high-speed camera data collection. This saturation can be reduced or eliminated using neutral density filters on the camera. Published experimental data on the impacts of flicker on organisms remains sparse. Many studies have drawn inferences on the impacts of spectral and lighting brightness on organisms without controlling for flicker. Our conclusion is that lighting flicker is a type of light pollution. The use of high-speed camera data makes it easier to include flicker as a variable in studies regarding the impacts of lighting on organisms.

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Section: Previous Studiesmentioning

confidence: 99%

Section: Previous Studiesmentioning

confidence: 99%

Exploring the Hidden World of Lighting Flicker with a High-Speed Camera

Elvidge,

Zhizhin,

Pipkin

et al. 2024

Atmosphere

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“…Therefore, its measurement results are not referential. In [18][19][20][21], the response distribution of different types of LED lamps under the same interharmonic conditions was analyzed with the percent flicker and flicker index from the perspective of luminous flux as the bases for evaluating the quality of lighting products. These studies lack the quantitative analysis of the corresponding relationship between the light and dark changes of LED lights caused by interharmonics.…”

Section: Introductionmentioning

confidence: 99%

Experimental Interharmonic Sensitivity Evaluation of LED Lamps Based on the Luminous Flux Flicker Model

Song

Zhu

et al. 2022

Energies

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LED lamps have gradually replaced other lighting sources and have become mainstream in the lighting industry. The research on interharmonic sensitivity affecting their lighting quality cannot be ignored. By deconstructing the lamp-eye-brain module in the International Electrotechnical Commission (IEC) flicker model, a luminous flux flicker model without the constraints of a specific light source was proposed. The test system and corresponding analysis method of the interharmonic-luminous flux transfer coefficient in the model were described in detail, and the accuracy of the test results of the system was verified via incandescent lamp heat balance model simulations. Based on the test results, the conversion method of the interharmonic ratio of LED lamps under the flicker limit based on the interharmonic-flicker limit curve of incandescent lamps was deduced. By testing and comparing the differences in interharmonic-flicker limit curves of different driving types of LED lamps, the experimental evaluation of their sensitivity was completed, and the reference for LED lamp selection, driver design, and compatibility standard formulation in different application scenarios was provided.

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“…Incandescent and discharge light sources are the most sensitive to voltage fluctuations. However, research results from recent years show that LED lamps with builtin switching power supplies or supplied directly from the power grid are also sensitive to voltage fluctuations [9], which is also shown on the basis of a signal from a photodiode with a spectral sensitivity similar to that of the human eye [10,11]. Therefore, it is important to detect the voltage fluctuation [12][13][14], to locate voltage fluctuation sources [15] (e.g., by using histogram analysis for voltage fluctuation indices [16]; voltage fluctuation amplitude analysis [17]; kernel density estimation analysis for voltage fluctuation indices [18]; a multi-level perceptron neural network [19]; a Jacobian matrix for gradients of voltage amplitudes [20]; analysis of power of voltage fluctuations [21]; or analysis of active power changes [22]), and to eliminate disturbances caused by them [23].…”

Section: Introductionmentioning

confidence: 99%

Selective Identification and Localization of Voltage Fluctuation Sources in Power Grids

Kuwałek¹

2021

Energies

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The current study presents a novel approach to the selective identification and localization of voltage fluctuation sources in power grids, considering individual disturbing loads changing their state with a frequency of up to 150 Hz. The implementation of the proposed approach in the existing infrastructure of smart metering allows for the identification and localization of the individual sources of disturbances in real time. The proposed approach first performs the estimation of the modulation signal using a carrier signal estimator, which allows for a modulation signal with a frequency greater than the power frequency to be estimated. In the next step, the estimated modulating signal is decomposed into component signals associated with individual sources of voltage fluctuations using an enhanced empirical wavelet transform. In the last step, a statistical evaluation of the propagation of component signals with a comparable fundamental frequency is performed, which allows for the supply point of a particular disturbing load to be determined. The proposed approach is verified in numerical simulation studies using MATLAB/SIMULINK and in experimental studies carried out in a real low-voltage power grid. The research carried out shows that the proposed approach allows for the selective identification and localization of voltage fluctuation sources changing their state with a frequency of up to 150 Hz, unlike other methods currently used in practice.

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Estimation of Flicker of Contemporary LED Lamps and Luminaires

Cited by 6 publications

References 3 publications

Exploring the Hidden World of Lighting Flicker with a High-Speed Camera

Exploring the Hidden World of Lighting Flicker with a High-Speed Camera

Experimental Interharmonic Sensitivity Evaluation of LED Lamps Based on the Luminous Flux Flicker Model

Selective Identification and Localization of Voltage Fluctuation Sources in Power Grids

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