Accurate diagnosis of incipient faults in wind turbine (WT) assets will provide sufficient lead time to apply an optimal maintenance for the expensive WT assets which often are located in a remote and harsh environment and their maintenance usually needs heavy equipment and highly skilled engineers. This paper presents an online bearing clearance monitoring approach to diagnose the change of bearing clearance, providing an early and interpretable indication of bearing health conditions. A novel dynamic load distribution method is developed to efficiently gain the general characteristics of vibration response of bearings without local defects but with small geometric errors. It shows that the ball pass frequency of outer race (BPFO) is the primary exciting source due to biased load distribution relating to bearing clearance. The geometric errors, including various orders of runouts on different bearing parts, can be the secondary excitation source. Both sources lead to compound modulation responses with very low amplitudes, being more than 20 dB lower than that of a small local defect on raceways and often buried by background noise. Then, Modulation Signal Bispectrum (MSB) is identified to purify the noisy signal and Gini index is introduced to represent the peakness of MSB results, thereby an interpretable indicator bounded between 0 and 1 is established to show bearing clearance status. Datasets from both a dedicated bearing test and a run-to-failure gearbox test are employed to verify the performance and reliability of the proposed approach. Results show that the proposed method is capable to indicate a change of about 20 µm in bearing clearance online, which provides a significantly long lead time compared to the diagnosis method that focuses only on local defects. Therefore, this method provides a big opportunity to implement more cost-effective maintenance works or carry out timely remedial actions to prolong the lifespan of bearings. Obviously, it is applicable to not only WT assets, but also most rotating machines.

This paper investigates the performance of the conventional bispectrum (CB) method and its new variant, the modulation signal bispectrum (MSB) method, in analysing the electrical current signals of induction machines for the condition monitoring of rotor systems driven by electrical motors. Current signal models which include the phases of the various electrical and magnetic quantities are explained first to show the theoretical relationships of spectral sidebands and their associated phases due to rotor faults. It then discusses the inefficiency of CB and the proficiency of MSB in characterising the sidebands based on simulated signals. Finally, these two methods are applied to analyse current signals measured from different rotor faults, including broken rotor bar (BRB), downstream gearbox wear progressions and various compressor faults, and the diagnostic results show that the MSB outperforms the CB method significantly in that it provides more accurate and sparse diagnostics, thanks to its unique capability of nonlinear modulation detection and random noise suppression.

A two-step method involving continuous screw-extrusion steam explosion (CSESE) pretreatment and esterification in supercritical carbon dioxide (scCO₂) is used to prepare long-chain fatty acid-modified jute fiber. The weight gain percentage (WG %) of CSESE-pretreated jute laurate (JL) was 110.7% when esterification was carried out in scCO₂ at 14 MPa and 100 °C for 2 h. The corresponding WG % was 105.5% when esterification was instead carried out in pyridine at 100 °C for 2 h. Scanning electron microscopy and X-ray diffraction indicated that CSESE pretreatment enhanced the reactivity of jute fiber, with esterification in scCO₂ simultaneously occurring on the fibers surface and internal walls. The glass transition temperature of esterified jute was approximately 119 °C, indicating that it could be hot processed over a wide temperature range. The esterified jute had an oil absorption ratio of 17.01 g/g, so it can be used as an oil absorption material.

Belt transmission is one of the most common forms of transmission on CNC lathes. To assess the impact of belt performance on monitoring machining conditions using motor current signal analysis, we developed a dynamic model for belt-driven electromechanical spindle systems. This model enables the coupling of multi-physics variables including mechanical dynamics, particularly the dynamic axil and belt bending motions of belt transmissions and electromagnetic effects. Thus, various changes in belt transmission, including different degrees of belt tension and defects with inherent motor and spindle errors, can be investigated. The modulation characteristics of the current and speed signals revealed that belt transmission can cause a high degree of modulation, reflected by the rich harmonic sidebands at the belt-passing frequency in the motor current spectrum. The rate and extent of belt wear worsened with excessive wear and inadequate tension. It was confirmed that the sideband at the spindle rotating frequency was slightly impacted by changes in the belt conditions. This model was verified based on a CNC lathe induced with different degrees of belt looseness. These conclusions drawn from the numerical analyses can be used for motor current signal analysis, providing reliable and accurate results for machining monitoring.

The design of good performance and long service life, crankshaft affects the engine performance and fuel economy. It can reduce the consumption of materials and manufacturing cost. Thermodynamic calculation of mixed gas cylinder is analysised based on P-V diagram drawing, It compared with theory and practice to optimize the design of the crankshaft...

To monitor online the operational condition and quality of a desktop fused deposition modeling (FDM) printer, the dynamics of vibro-acoustics must be accurately understood. In this paper, an electromechanical coupling (EMT) framework is established to relate the dynamics of stepper actuation, the transmission chain, and machine motion, deriving a steady-state frequency–velocity mapping for steady or near steady printing segments. The mapping is evaluated by numerical calculation to obtain a theoretical drive frequency for different toolpath directions and commanded printing velocities. Validation is performed on the experiment platform I. Drive-side vibration is measured by an accelerometer mounted on the x-axis beam near the motor end. An acoustic channel is recorded as an auxiliary qualitative cross-check rather than for quantitative error evaluation. For steady printing segments, the dominant frequency in drive-side vibration is compared with the theoretical drive frequency. In the tested steady segments and toolpath directions, the relative error remained below 3%. In a further case study, the G-code is modified to introduce two constant printing velocity segments (40 mm/s and 80 mm/s) within the same continuous record, enabling a direct comparison of dominant frequencies between two steady segments. The results show that, under open-loop stepper drive and within the steady/near steady scope adopted here, a drive-related dominant frequency can be observed stably in the x-axis beam vibration response and matches the theoretical drive frequency. When the commanded constant printing velocity is doubled, the dominant frequency in drive-side vibration in the corresponding steady segment changes by approximately a proportional factor. This study provides a verifiable drive referenced frequency–velocity mapping for steady segments under the tested configuration and a traceable frequency reference for steady segment comparisons within the same print record in subsequent case studies.