The paper reports on a nonlinear frequency up-converting vibration energy harvester with enhanced broadband performance below 50 Hz, which is attained by leveraging vibro-impact interaction between two high-frequency piezoelectric generators and two low-frequency resonators with commensurate natural frequencies in the 2:1 ratio. Finite element model was implemented to assess the proposed concept by treating the harvester as a vibro-impact coupled piezoelectric-circuit system. The model accommodates multiple mechanical contact pairs defined by nonlinear dissipative Hunt–Crossley contact force formulation. Effective design principles were applied to maximize power output including near-optimal positioning of the neutral plane in the generators and rational adjustment of response settling time. The fabricated proof-of-concept device was tested in different clearance configurations and under varying harmonic excitation conditions to reveal rich nonlinear dynamics behavior. The measured hardening-type power frequency responses were examined to gain better insight into nonlinear resonance characteristics (instability jumps, frequency hysteresis, etc), which determine effectiveness of micro-power generation. It was demonstrated that the proposed dual-resonator energy harvester favorably harnesses nonlinear resonance amplification to deliver larger average power output (up to 37 μ W) and useable bandwidth (up to 9.5 Hz) in comparison to the conventional single-resonator counterparts (delivering up to 26 μ W and up to 7 Hz, respectively). The maximum normalized power density of the device is 41 μ W cm ⁻³ g ⁻² , while volume figure of merit and 3 dB or 1 dB bandwidth-based figures of merit reach 0.18%, 11 μ W cm ⁻³ g ⁻² and 1.5%, respectively. The latter value indicates superior broadband performance of the device. Adoption of mean performance index and coefficient of variation as complementary figures of merit proved to be valuable in identifying device configuration that yields the most effective and stable broadband operation in a targeted frequency range.

This work studies the influence of high-frequency excitation of a cutting tool during end milling of workpieces made of difficult-to-cut metallic alloys. It is demonstrated that high-frequency vibrations superimposed onto the continuous movement of the tool lead to milling process stabilization with superior surface finish in comparison to conventional machining. A finite element model of the vibration milling tool was built and verified experimentally. The model treats the tool as an elastic pre-twisted structure (mill cutter) characterised by its natural vibration modes. The resonance frequencies of the axial vibration mode of cutters of two different lengths were predicted numerically and subsequently used for excitation of the vibration milling tool during cutting experiments. Qualitative and quantitative characterization of the surface quality of the machined stainless steel and titanium alloys was performed. Measurement results have confirmed that excitation of a specific tool mode is a prerequisite for achieving maximal efficiency of the vibration milling process. Statistical analysis of the collected roughness measurement data identified factors that most significantly contribute to the improved surface finish of the workpieces

This paper presents a method of cutting tool vibration energy harvesting for wireless applications, the created devices and the results of the accomplished experiments. The proposed high frequency piezo generator assures energy harvesting, accumulation and appropriateness for wireless sensors applications. The proposed architecture composed from energy harvesting transducer, energy accumulating capacitor, sensors, microcontroller and RF link opens a way for wireless sensors networks in manufacturing technologies providing the effective integration of information, delivered by sensors of different nature, to achieve a wholesome description of the status of the monitored process. The elaborated algorithm and the created detector could reach no more than 100–150nA current consumption during capacitor charging. This method makes possible the accumulation of necessary energy during turning tool vibrations. According to the experimental results, the created wireless sensor energy harvester prototype satisfies the energy needs for sensors and is capable of transmitting the information at the distance of 20m. For cutting tool performance evaluation the limitary moment, when cutting tool starts manufacturing inappropriate quality parts, was defined experimentally and statistically

This paper proposes a method for extracting information from the parameters of a single point incremental forming (SPIF) process. The measurement of the forming force using this technology helps to avoid failures, identify optimal processes, and to implement routine control. Since forming forces are also dependent on the friction between the tool and the sheet metal, an innovative solution has been proposed to actively control the friction forces by modulating the vibrations that replace the environmentally unfriendly lubrication of contact surfaces. This study focuses on the influence of mechanical properties, process parameters and sheet thickness on the maximum forming force. Artificial Neural Network (ANN) and different machine learning (ML) algorithms have been applied to develop an efficient force prediction model. The predicted forces agreed reasonably well with the experimental results. Assuming that the variability of each input function is characterized by a normal distribution, sampling data were generated. The applicability of the models in an industrial environment is due to their relatively high performance and the ability to balance model bias and variance. The results indicate that ANN and Gaussian process regression (GPR) have been identified as the most efficient methods for developing forming force prediction models.

The piezoelectric transduction mechanism is a common vibration-to-electric energy harvesting approach. Piezoelectric energy harvesters are typically mounted on a vibrating host structure, whereby alternating voltage output is generated by a dynamic strain field. A design target in this case is to match the natural frequency of the harvester to the ambient excitation frequency for the device to operate in resonance mode, thus significantly increasing vibration amplitudes and, as a result, energy output. Other fundamental vibration modes have strain nodes, where the dynamic strain field changes sign in the direction of the cantilever length. The paper reports on a dimensionless numerical transient analysis of a cantilever of a constant cross-section and an optimally-shaped cantilever with the objective to accurately predict the position of a strain node. Total effective strain produced by both cantilevers segmented at the strain node is calculated via transient analysis and compared to the strain output produced by the cantilevers segmented at strain nodes obtained from modal analysis, demonstrating a 7% increase in energy output. Theoretical results were experimentally verified by using open-circuit voltage values measured for the cantilevers segmented at optimal and suboptimal segmentation lines.