Basic Send-on-Delta Sampling for Signal Tracking-Error Reduction

Díaz-Cacho, Miguel; Delgado, Emma; Barreiro, Antonio; Falcon, Pablo

doi:10.3390/s17020312

Cited by 16 publications

(14 citation statements)

References 17 publications

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“…In sensor networks literature, [12] SoD event-based approaches are proposed in order to provide a trade-off between the effectiveness and resource utilization/energy efficiency. Diaz et al, in Reference [13], introduced a dynamic SoD by using a network adaptive scheme over network transport protocols for remote controlled sensors.…”

Section: Opc Deadband and Event-based Reporting Strategymentioning

confidence: 99%

Statistical Deadband: A Novel Approach for Event-Based Data Reporting

Torrisi

2019

Informatics

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Deadband algorithms are implemented inside industrial gateways to reduce the volume of data sent across different networks. By tuning the deadband sampling resolution by a preset interval ∆, it is possible to estimate the balance between the traffic rates of networks connected by industrial SCADA gateways. This work describes the design and implementation of two original deadband algorithms based on statistical concepts derived by John Bollinger in his financial technical analysis. The statistical algorithms proposed do not require the setup of a preset interval-this is required by non-statistical algorithms. All algorithms were evaluated and compared by computing the effectiveness and fidelity over a public collection of random pseudo-periodic signals. The overall performance measured in the simulations showed better results, in terms of effectiveness and fidelity, for the statistical algorithms, while the measured computing resources were not as efficient as for the non-statistical deadband algorithms.The objective of this work is to implement statistical algorithms based on Bollinger's theory as alternatives to the conventional SoD sampling scheme, which is an event-based data-reporting strategy.The experimental results showed a performance enhancement of the statistical deadband algorithms over the non-statistical send-on-delta schema. In order to reproduce the algorithms comparison in R [10], the pseudo-code of all of the algorithms in this paper have a corresponding function in the deadband package [11]. The algorithms described in the pseudo-code represent the concept to obtain the algorithm output, sample by sample, as in the online working mode. The corresponding functions in the package process the collection of all outputs for all input samples in a finite time period. The functions in the package have been developed to compare the overall performance of a hypothetical device that embeds a hardware or software implementation of the corresponding pseudo-code algorithms.This paper is organized as follows. Section 2 presents an introduction to the OPC deadband concepts that are related to the data collection process and the algorithms. Section 3 presents Bollinger's technical analysis. Section 4 presents the two original deadband algorithms. Section 5 provides the simulation results developed by using the deadband package. Finally, Section 6 draws some conclusions.

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Section: Opc Deadband and Event-based Reporting Strategymentioning

confidence: 99%

Statistical Deadband: A Novel Approach for Event-Based Data Reporting

Torrisi

2019

Informatics

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“…In change detection, using a threshold is known as a send-on-delta (SoD) technique [18][19][20][21][22][23]. After a SoD-enabled system uses the predefined thresholds, referred to as delta, to detect significant changes for measurement, it reports the detected event.…”

Section: Threshold-based Approachmentioning

confidence: 99%

“…On the contrary, a higher threshold indicates an increase in adaptability to changes, but the detectability and the reporting rate of the system may decrease. According to the average event reporting rate acceptable to the system, the threshold is dynamically adjusted in order to provide the higher sensitivity and satisfy the performance level (i.e., the average event reporting rate) required [21]. The threshold is determined by using the relationship between the performance level and the average variation of the continuous signal.…”

Section: Threshold-based Approachmentioning

confidence: 99%

Adaptive Threshold Generation for Fault Detection with High Dependability for Cyber-Physical Systems

Baek

2018

Applied Sciences

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Cyber-physical systems (CPS) applied to safety-critical or mission-critical domains require high dependability including safety, security, and reliability. However, the safety of CPS can be significantly threatened by increased security vulnerabilities and the lack of flexibility in accepting various normal environments or conditions. To enhance safety and security in CPS, a common and cost-effective strategy is to employ the model-based detection technique; however, detecting faults in practice is challenging due to model and environment uncertainties. In this paper, we present a novel generation method of the adaptive threshold required for providing dependability for the model-based fault detection system. In particular, we focus on statistical and information theoretic analysis to consider the model and environment uncertainties, and non-linear programming to determine an adaptive threshold as an equilibrium point in terms of adaptability and sensitivity. To do this, we assess the normality of the data obtained from real sensors, define performance measures representing the system requirements, and formulate the optimal threshold problem. In addition, in order to efficiently exploit the adaptive thresholds, we design the storage so that it is added to the basic structure of the model-based detection system. By executing the performance evaluation with various fault scenarios by varying intensities, duration and types of faults injected, we prove that the proposed method is well designed to cope with uncertainties. In particular, against noise faults, the proposed method shows nearly 100% accuracy, recall, and precision at each of the operation, regardless of the intensity and duration of faults. Under the constant faults, it achieves the accuracy from 85.4% to 100%, the recall of 100% from the lowest 54.2%, and the precision of 100%. It also gives the accuracy of 100% from the lowest 83.2%, the recall of 100% from the lowest 43.8%, and the precision of 100% against random faults. These results indicate that the proposed method achieves a significantly better performance than existing dynamic threshold methods. Consequently, an extensive performance evaluation demonstrates that the proposed method is able to accurately and reliably detect the faults and achieve high levels of adaptability and sensitivity, compared with other dynamic thresholds.

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“…For a given state x, z c can be easily obtained by solving the polynomial in Equation (18). Thus, under the constraint of σ(x) ∈ [τ min , τ max ], the maximal triggering interval can be obtained by Theorem 3.…”

Section: Proof See Appendix Bmentioning

confidence: 99%

Frequency Regulation of Power Systems with Self-Triggered Control under the Consideration of Communication Costs

Zhu

Sun

et al. 2017

Applied Sciences

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Abstract:In control systems of power grids, conveying observations to controllers and obtaining control outputs depend greatly on communication and computation resources. Particularly for large-scale systems, the costs of computation and communication (cyber costs) should not be neglected. This paper proposes a self-triggered frequency control system for a power grid to reduce communication costs. An equation for obtaining the triggering time is derived, and an approximation method is proposed to reduce the computation cost of triggering time. In addition, the communication cost of frequency triggering is measured quantitatively and proportionally. The defined cost function considers both physical cost (electricity transmission cost) and communication cost (control signal transmission cost). The upper bound of cost is estimated. According to the estimated upper bound of cost, parameters of the controller are investigated by using the proposed optimization algorithm to guarantee the high performance of the system. Finally, the proposed self-triggered power system is simulated to verify its efficiency and effectiveness.

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Basic Send-on-Delta Sampling for Signal Tracking-Error Reduction

Cited by 16 publications

References 17 publications

Statistical Deadband: A Novel Approach for Event-Based Data Reporting

Statistical Deadband: A Novel Approach for Event-Based Data Reporting

Adaptive Threshold Generation for Fault Detection with High Dependability for Cyber-Physical Systems

Frequency Regulation of Power Systems with Self-Triggered Control under the Consideration of Communication Costs

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