The paper presents a computationally efficient and accurate numerical approach to evaluating RF–DC power conversion efficiency (PCE) for energy harvesting circuits in the case of multi-tone power-carrying signal with periodic envelopes. This type of signal has recently received considerable attention in the literature. It has been shown that their use may result in a higher PCE than the conventional sine wave signal for low to medium input power levels. This reason motivated the authors to develop a fast and accurate two-frequency harmonic balance method (2F-HB), as fast PCE calculation might appreciably expedite the converter circuit optimization process. In order to demonstrate the computational efficiency of the 2F-HB, a comparative study is performed. The results of this study show that the 2F-HB significantly outperforms such extensively used methods as the transient analysis (TA), the harmonic balance method (HB), and the multidimensional harmonic balance method (MHB). The method also outperforms the commercially available non-linear circuit simulator Keysight ADS employing both HB and MHB. Furthermore, the proposed method can be readily integrated into commonly used commercially available non-linear circuit simulation software, including the Keysight ADS, Ansys HFSS, just to name a few—minor modifications are required. In addition, to increase the correctness and reliability of the proposed method, the influence of PCB is considered by calculating Y parameters of its 3D model. The widely employed voltage doubler-based RF–DC converter for energy harvesting and wireless power transfer (WPT) in sub-GHz diapason is chosen to validate the proposed method experimentally. This RF–DC converter is chosen for its simplicity and capability to provide sufficiently high PCE. The measurements of the PCE for a voltage doubler prototype employing different multi-tone waveform signals were performed in laboratory conditions. Various combinations of the matching circuit element values were considered to find the optimal one in both—theoretical model and experimental prototype. The measured PCE is in very good agreement with the PCE calculated numerically, which attests to the validity of the proposed approach. The proposed PCE estimation method is not limited to one selected RF–DC conversion circuit and can also be applied to other circuits and frequency bands. The comparison of the PCE obtained by means of the proposed approach and the measured one shows very good agreement between them. The PCE estimation error reaches as low as 0.37%, and the maximal estimation error is 32.65%.

While predictive maintenance increasingly relies on artificial intelligence, strict dependence on cloud computing introduces network latency and demands continuous connectivity, creating critical bottlenecks for time-sensitive industrial applications. To overcome this, we introduce a novel hybrid edge-cloud architecture, which allows deploying an ultra-low-power microcontroller (ESP32-S3) without dedicated AI acceleration hardware to perform complete, operational, predictive maintenance on ultra-constrained embedded hardware. The edge model is optimized to be very small to ensure that increasing model complexity does not cause inference latency to exceed 100 ms or make real-time operation infeasible. We created a very compact INT8-quantized neural network to perform the simultaneous classification of faults and estimation of Time-to-Failure (TTF) with a deterministic mean inference time of 42.3 ms. It dynamically estimates prediction confidence, processes high-confidence predictions locally, and offloads uncertain predictions to a higher-capacity cloud model, and recovers 97.3% of the cloud accuracy gain at 92% of the cloud latency budget. An asymmetric loss function penalizes over-prediction of the remaining useful life, and thus it provides conservative and safe warnings of fault. Operators’ interpretability is improved with Shapley Additive exPlanations (SHAP) and natural-language recommendations. Network outages of up to 50% have not influenced the safety-critical fault recall (above 0.924), so graceful degradation is reached when the network is used in real time in industrial applications. The edge-first with adaptive cloud fallback approach is demonstrated to be technically feasible for a full predictive maintenance workflow—including inference, confidence fusion, and explainability on a low-cost commercial microcontroller.

In the present work, a fast and robust method to analyze multiple cylindrical posts with multiple cylindrical inclusions is developed and discussed. The cylindrical posts are located in a rectangular waveguide. The method employed herein is a boundary integral method discretized by entire domain basis functions. The resulting surface integrals can be evaluated in closed form, except those over the outer surfaces, which result in very slowly converging series of cylindrical functions. A considerable speed-up in the convergence of these series is achieved by means of well-established Ewald’s summation technique. To verify the efficiency of the developed method numerical studies were performed. The calculated results for several different configurations are compared with the data obtained using Ansys HFSS. Owing to its semi-analytical nature, the method requires several orders of magnitude less CPU time than FEM based Ansys HFSS.

The energy efficiency of a communication system using pulse position modulation (PPM) can be increased by reducing the duration of the pulses transmitted over the communication channel to several tens of picoseconds. The employment of an event timer device as a time-to-digital converter (TDC) for demodulation allows the use of PPM with many pulse positions and achieves competitive data transfer speeds. However, along with several-picosecond accuracy of modern event timers, they require a pulse duration of several hundred picoseconds for precise detection. This research is devoted to developing passive techniques for precise pulse expansion from tens of picoseconds to hundreds of picoseconds. We propose two methods: the electrical method, which employs a microstrip low-pass filter (LPF), and the optical method, which uses fiber Bragg grating (FBG). This research offers a detailed analysis of distortion-free pulse expansion requirements, the design of prototypes meeting these requirements, and experimental design verification. Theoretical background, mathematical models, and results of experimental validation of the proposed pulse expansion methods within the laboratory transmitted reference pulse-position modulation (TR-PPM) communication system are provided.

An accelerated boundary integral method for the analysis of scattering of the dominant mode by multiple multi-layered full-height circular cylindrical posts in a rectangular waveguide is presented. After some transformations the surface integral equation is converted to a system of equations whose entries can be evaluated analytically yielding Schlämilch series. Slow convergence of these series is accelerated using the Ewald technique. The proposed method gives results that are comparable in terms of accuracy with other approaches, including those incorporated in solvers HFSS and CST Studio and outperforms them in terms of computation time, especially for posts with large electrical sizes. The efficiency of the proposed method is confirmed by the examples of H-plane cylinder bandpass filters design.

A novel and efficient methodology is proposed for reducing measurement uncertainty associated with the dielectric constant of low-loss materials. The experimental setup consists of two H-plane cylindrical rods located in a rectangular waveguide. One of the rods has the unknown dielectric constant to be extracted, while the other dielectric rod whose dielectric constant is known in advance and serves as a tool for altering the shape of the dependence of the absolute value of the reflection coefficient on the dielectric constant in such a way that the resulting curve exhibits more rapid variations in the range of possible values of the dielectric constant of the post being characterized. The distance between the rods, radius of the optimizing rod, and position offset of the optimizing post serve as optimization parameters to be adjusted so that measurement uncertainty could be reduced which is confirmed by the results of numerical modeling. However, in the vicinity of the resonances, the method cannot be applied.