Variable Speed Research Articles

A Two-step Bearing Fault Diagnosis Strategy under Variable Speed based on Symplectic Geometry Modal Decomposition and Practical Fault Feature Extraction Framework

Abstract Strong noise interference can lead to failure of bearing fault diagnosis techniques. This paper proposes a two-step fault diagnosis strategy to address the challenge of weak fault feature extraction in bearing fault diagnosis using acoustic or vibration data at varying speed. Firstly, the paper introduces a short-time symplectic modal decomposition (stSGMD) method that utilizes fractional Fourier transform. This method involves signal processing with short-time windowing to extract fault-sensitive components. The window is then expanded to obtain the complete component through fractional Fourier narrow-band filtering based on energy concentration in the fractional Fourier domain. A novel entropy index, standard deviation discrete entropy, is introduced to quantify the intensity of fault shocks in non-stationary signal and is used to select components in the stSGMD. Subsequently, a fault feature extraction framework called global objective deconvolution (GOD) is presented for extracting instantaneous fault features at varying speed. This method establishes a global objective matrix for the extraction process. The GOD is utilized to deconvolute the complete fault-sensitive component, followed by envelope order analysis for demodulating the fault feature order. Numerical simulations and experimental studies on acoustics and vibration are performed. The results demonstrate that stSGMD improves the demodulation capability of SGMD, while GOD effectively extracts fault features. It is expected that the presented method will be effectively utilized for fault feature extractions in bearings operating under linear variable speed conditions.

Optimal control for helicopter/turboshaft engine system based on hybrid variable speed

Optimal control for helicopter/turboshaft engine system based on hybrid variable speed

Deep Learning–Assisted Two-Dimensional Transperineal Ultrasound for Analyzing Bladder Neck Motion in Women With Stress Urinary Incontinence

BACKGROUNDNo universally recognized transperineal ultrasound parameters are available for evaluating stress urinary incontinence. The information captured by commonly used perineal ultrasound parameters is limited and insufficient for a comprehensive assessment of stress urinary incontinence. Although bladder neck motion plays a major role in stress urinary incontinence, objective and visual methods to evaluate its impact on stress urinary incontinence remain lacking. OBJECTIVETo use a deep learning–based system to evaluate bladder neck motion using two-dimensional transperineal ultrasound videos, exploring motion parameters for diagnosing and evaluating stress urinary incontinence. We hypothesized that bladder neck motion parameters are associated with stress urinary incontinence and are useful for stress urinary incontinence diagnosis and evaluation. STUDY DESIGNThis retrospective study including 217 women involved the following parameters: maximum and average speeds of bladder neck descent, β angle, urethral rotation angle, and duration of the Valsalva maneuver. The fitted curves were derived to visualize bladder neck motion trajectories. Comparative analyses were conducted to assess these parameters between stress urinary incontinence and control groups. Logistic regression and receiver operating characteristic curve analyses were employed to evaluate the diagnostic performance of each motion parameter and their combinations for stress urinary incontinence. RESULTSOverall, 173 women were enrolled in this study (82, stress urinary incontinence group; 91, control group). No significant differences were observed in the maximum and average speeds of bladder neck descent and in the speed variance of bladder neck descent. The maximum and average speed of the β and urethral rotation angles were faster in the stress urinary incontinence group than in the control group (151.2 vs 109.0 mm/s, P=0.001; 6.0 vs 3.1 mm/s, P <0.001; 105.5 vs 69.6 mm/s, P <0.001; 10.1 vs 7.9 mm/s, P=0.011, respectively). The speed variance of the β and urethral rotation angles were higher in the stress urinary incontinence group (844.8 vs 336.4, P <0.001; 347.6 vs 131.1, P <0.001, respectively). The combination of the average speed of the β angle, maximum speed of the urethral rotation angle, and duration of the Valsalva maneuver demonstrated a strong diagnostic performance (area under the curve, 0.87). When 0.481*β anglea + 0.013*URAm + 0.483*Dval = 7.405, the diagnostic sensitivity was 70% and specificity was 92%, highlighting the significant role of bladder neck motion in stress urinary incontinence, particularly changes in the speed of the β and urethral rotation angles. CONCLUSIONSA system utilizing deep learning can describe the motion of the bladder neck in women with stress urinary incontinence during the Valsalva maneuver, making it possible to visualize and quantify bladder neck motion on transperineal ultrasound. The speeds of the β and urethral rotation angles and duration of the Valsalva maneuver were relatively reliable diagnostic parameters.

Power regulation of variable speed multi rotor wind systems using fuzzy cascaded control

Power quality is a crucial determinant for integrating wind energy into the electrical grid. This integration necessitates compliance with certain standards and levels. This study presents cascadedfuzzy power control (CFPC) for a variable-speed multi-rotor wind turbine (MRWT) system. Fuzzy logic is a type of smart control system already recognized for its robustness, making it highly suited and reliable for generating electrical energy from the wind. Therefore, the CFPC technique is proposed in this work to control the doubly-fed induction generator (DFIG)-based MRWT system. This proposed strategy is applied to the rotor side converter of a DFIG to improve the current/power quality. The proposed control has the advantage of being model-independent, as it relies on empirical knowledge rather than the specific characteristics of the DFIG or turbine. Moreover, the proposed control system is characterized by its simplicity, high performance, robustness, and ease of application. The implementation of CFPC management for 1.5 MW DFIG-MRWT was carried out in MATLAB environment considering a variable wind speed. The obtained results were compared with the direct power control (DPC) technique based on proportional-integral (PI) controllers (DPC-PI), highlighting that the CFPC technique reduced total harmonic distortion by high ratios in the three tests performed (25%, 30.18%, and 47.22%). The proposed CFPC technique reduced the response time of reactive power in all tests by ratios estimated at 83.76%, 65.02%, and 91.42% compared to the DPC-PI strategy. Also, the active power ripples were reduced by satisfactory proportions (37.50%, 32.20%, and 38.46%) compared to the DPC-PI strategy. The steady-state error value of reactive power in the tests was low when using the CFPC technique by 86.60%, 57.33%, and 72.26%, which indicates the effectiveness and efficiency of the proposed CFPC technique in improving the characteristics of the system. Thus this control can be relied upon in the future.

Model predictive path tracking control of intelligent vehicles based on dual-stage disturbance observer under multi-channel disturbances

Abstract Parameter fluctuations, unmodeled dynamics, speed variation, steering actuator faults, and other multi-channel uncertain disturbances are the key challenges faced by the path tracking control of intelligent vehicles, which will affect the accuracy and stability of the path tracking. Therefore, a model predictive control (MPC) method based on a dual-stage disturbance observer (DDOB) is proposed in this paper. First, a tracking error dynamics model considering multi-channel uncertain disturbances is constructed, based on which a model predictive controller is designed to obtain the nominal front wheel steering angle by the Karush–Kuhn–Tucker (KKT) condition. Furthermore, the DDOB is designed to enable real-time estimation of the system disturbances, and then the estimated disturbances are used as the compensation for the nominal front wheel steering angle, which establishes the MPC control law with parallel compensation of the DDOB. Finally, the error boundedness of the DDOB and the global stability of the model predictive controller are analyzed. The effectiveness and superiority of the proposed algorithm are verified through Carsim–Simulink simulation and hardware-in-the-loop experiments.

Stochastic Model Predictive Control Based on Polynomial Chaos Expansion With Application to Wind Energy Conversion Systems

The wind energy conversion system (WECS) has a complex structure, and its state space model is highly nonlinear. Due to the random uncertainty of wind speed, it poses a huge challenge to achieve optimal control tasks and ensure the safe and stable operation of the system. Therefore, this article proposes a stochastic model predictive control strategy based on Polynomial Chaotic Expansion (PCE), which achieves the control tasks of MPPT and constant power regions in wind energy conversion systems. Firstly, a simple algorithm is proposed to obtain a set of basis functions that are suitable for the stochastic variable wind speed. Then, the obtained basis functions are used to propagate the uncertainty of the original uncertain differential equation of the wind energy conversion system through polynomial chaotic expansion. Combining the operating region and constraint conditions of the wind energy conversion system, the original stochastic uncertainty problem is transformed into a deterministic convex optimization problem. Using NREL 5MW wind turbine as the research object for simulation, the task of capturing maximum wind energy in MPPT area and tracking rated power points in constant power area was achieved. The experimental results show that the proposed control method can effectively improve the wind energy capture capability and achieve accurate tracking of output power to rated power.

Application of uncertainty quantification techniques in the framework of process safety studies: Advanced dispersion simulations

AbstractIn the framework of process safety studies, consequence assessment of accidental scenarios is a crucial step affecting the eventual risk profile associated with the facilities under analysis. Conventional models used for consequence assessment are based on integral models, and may not be adequate to cope with the dynamic evolution of accidental scenarios and their three‐dimensional features. On the other hand, consequence assessment models based on computational fluid dynamics (CFD) approaches are promising to cope with complex scenarios and environments, but setting the simulation introduces relevant uncertainties associated with both the input data, assumptions, and with the modelling of physical effects involved. In the present study, uncertainty quantification (UQ) techniques are applied to support advanced safety studies based on CFD simulations of hazardous gas dispersion. Firstly, the accidental scenarios are characterized by defining release scenarios and conditions and quantifying source terms using integral models. At the same time, input meteorological data are gathered. This enables the development of high‐fidelity CFD simulations of gas dispersion based on different input sets and eventually the implementation of UQ techniques. The generalized polynomial chaos (gPC) expansion is employed to obtain hazardous gas concentration based on the variation of wind direction and speed. The present method is applied for the analysis of a real plant featuring a complex layout. The results show the advantages of the present approach by quantifying the influence of meteorological conditions and providing indications for supporting the development of protection systems and emergency measures.

Spatial Distribution and Variation in Debris Cover and Flow Velocities of Glaciers during 1989–2022 in Tomur Peak Region, Tianshan Mountains

In this study, we utilized a feature optimization method combining texture and topographical factors with the random forest (RF) approach to identify changes in the extent of the debris cover around the Tianshan Tomur Peak between 1989 and 2022. Based on Sentinel-1 image data, we extracted glacier flow velocities using an offset tracking method and conducted a long-term analysis of flow velocities in combination with existing datasets. The debris identification results for 2022 showed that the debris-covered area in the study region was 409.2 km2, constituting 22.8% of the total glacier area. Over 34 years, the area of debris cover expanded by 69.4 km2, reflecting a growth rate of 20.0%. Analysis revealed that glaciers in the Tomur Peak area have been decelerating at an overall rate of −4.0% per decade, with the complexity of the glacier bed environment and the instability of the glacier’s internal structure contributing to significant seasonal and interannual variability in the movement speeds of individual glaciers.

Abnormal Pavement Condition Detection with Vehicle Posture Data Considering Speed Variations.

Pavement condition monitoring is an important task in road asset management and efficient abnormal pavement condition detection is critical for timely conservation management decisions. The present work introduces a mobile pavement condition monitoring approach utilizing low-cost sensor technology and machine-learning-based methodologies. Specifically, an on-board unit (OBU) embedded with an inertial measurement unit (IMU) and global positioning system (GPS) is applied to collect vehicle posture data in real time. Through a comprehensive analysis of both time domain and frequency domain data features for both normal and abnormal pavement conditions, feature engineering is conducted to identify how the most important features affect abnormal pavement condition recognition. Six machine learning models are then developed to identify different types of pavement conditions. The performance of different algorithms and the significance of different features are then analyzed. Moreover, the influence of vehicle speed on pavement condition assessment is further examined and classification models for different speed intervals are developed. The results indicate that the random forest (RF) model that considers vehicle speed achieves the best performance in pavement condition monitoring. The outcomes of the present work would contribute to cost-effective pavement condition monitoring and provide an important reference for pavement maintenance sectors.

The stability and morphology of laminar premixed hydrogen/air flames under various gravity conditions

In the present work, direct numerical simulations (DNS) were employed to understand the stability and morphology of laminar lean premixed hydrogen/air flames under various gravity conditions. The combined effect of Darrieus–Landau (DL) instability, thermal-diffusive (TD) instability and Rayleigh–Taylor (RT) instability was studied quantitatively for both the initial linear regime and the long-term nonlinear regime, with a particular focus on the effect of RT instability. In the linear regime, it was found that the RT instability has a negligible effect on the linear growth rate of flames with an equivalence ratio of 0.4, but the effect is significant when the equivalence ratio decreases to 0.3. The performance of various models for the dispersion relation was discussed, including a theoretical model considering the effects of all instabilities, which captures well the trend of the simulated results in the cases with unity Lewis numbers. The hydrogen/air flames with an equivalence ratio of 0.3 was investigated comprehensively in the nonlinear regime. For the cases with unity Lewis numbers, the RT-unstable flame exhibits a similar single-cusp structure as the RT-neutral flame, but with a deeper cusp and larger consumption speed as a result of the destabilizing effect of RT instability. The RT-stable flame gradually returns to a planar flame shape owing to the stabilizing effect of RT instability. For the cases with non-unity Lewis numbers, the effect of domain size on the flame evolution was investigated, showing a domain width of 200δT is enough to obtain a domain-independent result, where δT is the laminar flame thickness. It was found that the cases initialized with multimode perturbations reach the quasi-steady state faster, while the flame statistics are consistent with those of the cases initialized with single mode perturbations. The effect of RT instability was explored by comparing the results from various gravity conditions. The flame consumption speed is the largest in RT-unstable flames, and the smallest in RT-stable flames. The variation in flame consumption speed is due to the difference in the flame surface area, while the local reactivity and flame structure are not influenced by the RT instability. Further fractal analysis reveals that although the RT instability causes significant differences in flame surface area, the characteristic fractal dimension remains constant for flames under different gravity conditions.Novelty and significanceIn the present work, direct numerical simulations were employed to understand the stability and morphology of RT-unstable, RT-neutral and RT-stable laminar lean premixed hydrogen/air flames. For the first time, the effect of DL, TD and RT instabilities was quantitatively examined for both the linear regime and the nonlinear regime. A theoretical model considering various instabilities was compared with the simulated dispersion relations in the linear regime. In the non-linear regime, the flame surface area and corresponding flame consumption speed are influenced by the RT instability, while the flame stretch factor remains unaffected. A fractal analysis was conducted in laminar premixed hydrogen/air flames under the influence of various instabilities. Remarkably, it was discovered that the characteristic fractal dimension remains constant for the cases with and without the RT instability.

The Effect of Total Body Resistance Exercise Variations on the Speed of Youth Pencak Silat Scythe Kicks

The magnitude of the sickle strike directly influences the number of match points that can be achieved in the martial art of Pencak Silat. The aim of this study is to undertake a comprehensive analysis of the impact of different types of Total Body Resistance Exercise training on the speed of Pencak silat sickle kicks performed by teenagers. This research methodology utilises a hypothetical inquiry that consists of two distinct groups: an experimental group and a control group. The subjects of this study were combatants who had engaged in the practice of Pencak silat at State Vocational High School (SMK) Negeri 1 Stabat. There were a total of 52 participants who met the requirements for this inquiry. The sample was gathered using purposive sampling, which followed the specified criteria. To participate, one must have attended Pencak silat training sessions at SMK N 1 Stabat, have a high level of skill in the fundamental methods of the sickle kick, be between the ages of 17 and 19, and be willing to serve as a study sample. The confirmation of eligibility for a group of 33 individuals, consisting of 17 girls and 16 males, resulted from the assessment of these specific criteria. This research apparatus is utilised to assess the speed of Pencak silat kicks and estimate the impact of sickle blows. Consequently, Total Body Resistance Exercise training affects the speed of sickle kicks. However, there is no noticeable statistically significant variation in sickle kick speed among adolescent Pencak Silat practitioners.

Antipsychotic-induced prolactin elevation in premenopausal women with schizophrenia: associations with estrogen, disease severity and cognition.

Antipsychotic-induced prolactin elevation may impede protective effects of estrogens in women with schizophrenia-spectrum disorders (SSD). Our study sought to confirm whether the use of prolactin-raising antipsychotics is associated with lower estrogen levels, and to investigate how estrogen and prolactin levels relate to symptom severity and cognition in premenopausal women with SSD. This cross-sectional study included 79 premenopausal women, divided in three groups of women with SSD treated with prolactin-sparing antipsychotics (n = 21) or prolactin-raising antipsychotics (n = 27), and age-matched women without SSD (n = 31). Circulating 17β-estradiol was compared among groups. In patients, we assessed the relationship between prolactin and 17β-estradiol, and the relationships of these hormones to symptom severity and cognition, using correlation analyses and backward regression models. In women receiving prolactin-raising antipsychotics, 17β-estradiol levels were lower as compared to both other groups (H(2) = 8.34; p = 0.015), and prolactin was inversely correlated with 17β-estradiol (r=-0.42, p = 0.030). In the prolactin-raising group, 17β-estradiol correlated positively with verbal fluency (r = 0.52, p = 0.009), and 17β-estradiol and prolactin together explained 29% of the variation in processing speed (β17β-estradiol = 0.24, βprolactin=-0.45, F(2,25) = 5.98, p = 0.008). In the prolactin-sparing group, 17β-estradiol correlated negatively with depression/anxiety (r=-0.57, p = 0.014), and together with prolactin explained 26% of the variation in total symptoms (β17β-estradiol=-0.41, βprolactin = 0.32, F(2,18) = 4.44, p = 0.027). In women with SSD, antipsychotic-induced prolactin elevation was related to lower estrogen levels. Further, estrogens negatively correlated with symptom severity and positively with cognition, whereas prolactin levels correlated negatively with cognition. Our findings stress the clinical importance of maintaining healthy levels of prolactin and estrogens in women with SSD.

Effect of bridge height on airflow and aeolian sand flux near surface along the Qinghai-Tibet Railway, China

In this work, we studied the near-surface flow field structure of railway bridges with different heights through field investigation and wind tunnel simulation experiments. Meanwhile, we simulated the distribution of sand accumulation around a bridge via CFD software based on the sand accumulation around the Basuoqu bridge in the Cuona Lake section of the Qinghai–Tibet Railway. Results show that the sand around this railway bridge is mainly from the lake sediment on the west side of the railway and the weathered detritus on the east side. The height of the railway bridge in the sandy area affects the distribution of the near-surface flow field and the variation in speed on both sides of the bridge. The wind speed trough on both sides of the 6 m high bridge is higher, and the horizontal distance between the wind speed trough and the bridge section is 1.5 times that of the 3 m high bridge. Wind speed attenuates in a certain range on the windward and leeward sides of the bridge, forming an aeolian area; under the beam body, it is affected by the narrow tube effect, forming a wind erosion area. The height of the bridge determines its sand transport capacity. Under certain wind conditions, the overhead area at the bottom of the 3 m high bridge and its two sides do not have the sand transport capacity, so sand accumulates easily. Nevertheless, the sand accumulation phenomenon gradually disappears with the increase in bridge clearance height. The objectives of this study are to reveal the formation mechanism of sand damage for railway bridges, provide theoretical support for the scientific design of railway bridges in sandy areas, and formulate reasonable railway sand prevention measures to ensure the safety of railway running, which have certain theoretical significance and practical value.

Magneto-elastic vibration of axially moving graphene nanocomposite current-carrying beam with variable speed and axial force

Magneto-elastic vibration of axially moving graphene nanocomposite current-carrying beam with variable speed and axial force

Design and implementation of an innovative single-phase direct AC-AC bipolar voltage buck converter with enhanced control topology

Direct AC–AC converters are strong candidates in the power converting system to regulate grid voltage against the perturbation in the line voltage and to acquire frequency regulation at discrete step levels in variable speed drivers for industrial systems. All such applications require the inverted and non-inverted form of the input voltage across the output with voltage-regulating capabilities. The required value of the output frequency is gained with the proper arrangement of the number of positive and negative pulses of the input voltage across the output terminals. The period of each such pulse for low-frequency operation is almost the same as the half period of the input grid or utility voltage. These output pulses are generated by converting the positive and negative input half cycles in noninverting and inverting forms as per requirement. There is no control complication to generate control signals used to adjust the load frequency as the operating period of the switching devices is normally greater than the period of the source voltage. However, high-frequency pulse width modulated (PWM) control signals are used to regulate the output voltage. The size of the inductor and capacitor is inversely related to the value of the switching frequency. Similarly, the ripple contents of voltage and currents in these filtering components are also inversely linked with PWM frequency. These constraints motivate the circuit designer to select high PWM frequency. However, the alignment of the high-frequency control input with the variation in the input source voltage is a big challenge for a design engineer as the switching period of a high-frequency signal normally lies in the microsecond. It is also required to operate some high-frequency devices for various half cycles of the source voltage, creating control complications as the polarities of the half cycles are continuously changing. This requires at least the generation of two high-frequency signals for different intervals. The interruption of the filtering inductor current is a big source of high voltage surges in circuits where the high-frequency transistors operate in a complementary way. This may be due to internal defects in the switching transistors or some unnecessary inherent delay in their control signals. In this research work, a simplified AC–AC converter is developed that does not need alignment of high-frequency control with the polarity of the source voltage. With this approach, high-frequency signals can be generated with the help of any analog or digital control system. By applying this technique, only one high-frequency control signal is generated and applied in AC circuits, as in a DC converter, without applying a highly sensitive polarity sensing circuit. So, controlling complications is drastically simplified. The circuit and configuration always avoid the current interruption problem of filtering the inductor. The proposed control and circuit topology are tested both in computer-based simulation and practically developed circuits. The results obtained from these platforms endorse the effectiveness and validation of the proposed work.

Validation of the Norwegian International Reading Speed Texts (IReST) in adult readers with normal vision

There is a lack of standardised reading tests in Norwegian suitable for adults and persons with visual impairment (VI). The International Reading Speed Texts (IReST) measure reading performance of longer paragraphs. The aim of this project was to translate and validate the IReST in Norwegian. Each of the German, English and Swedish IReST were translated into Norwegian. The translations were matched for length, linguistic difficulty, and structure, and piloted in five adults. Reading speed was assessed in 25 readers (41 years, SD = 10) with normal vision and the readings were recorded. Reading speeds were analysed for variability between texts and participants. There were no statistically significant differences between the ten texts (135 words, 765 characters [SD=18], word variation index 91.8% [SD = 0.9%]). Reading speed in adult readers was 204 (SD=31) words/min. There was no difference across texts for any of the participants (p&gt;0.05). Reading speed variance was 77.4% between subjects and 22.6% between texts. The Norwegian IReST is standardised and comparable to the international IReST tests. Reading speed falls within normative values in adult readers. The Norwegian IReST will be a valuable tool in assessing reading in clinical health care, rehabilitation and educational practice of adult and visually impaired readers and in reading research.

Control of dual star induction generator based on multi-level inverter used in wind energy conversion system

This paper presents vector control of dual star induction generator (DSIG) integrated into variable speed wind energy and supplied by three-level NPC converters. Now the DSIG is the most common among multiphase machines when used in high power generation systems, which is associated with two converters. Maximum power point tracking (MPPT) for extracting a maximum of power fluctuating wind speed is illustrated. In order to decrease the fluctuations that appear in the currents generated by DSIG to the electrical network, we propose the NPC structure three-level inverter. Simulation results of a 1.5 MW Wind turbine are presented to illustrate the validity of this application.

Research on Variable Speed Variable Displacement Power Unit with High Efficiency and High Dynamic Optimized Matching

For the variable speed variable displacement power unit (VSVDPU), achieving power matching between the permanent magnet synchronous motor (PMSM) and the variable displacement plunger pump (VDPP) is the key to reducing system energy consumption. The control method of adjusting the speed of the PMSM and the displacement of the VDPP is the mainstay of current research and application of the VSVDPU. However, the dynamic properties of the PMSM and VDPP have not been balanced, which affects the control effect of the VSVDPU. This paper proposes a control method of variable speed and variable displacement with low energy consumption and high dynamics. The main idea is based on the efficiency model and dynamic response model of the PMSM and VDPP, and the factors that affect the efficiency and dynamic characteristics of the VSVDPU are analyzed. Guided by the multi-objective optimization algorithm, the optimal combination of speed and displacement under specific working conditions is derived. Simulation and experiment results show that the proposed control method is feasible to improve the efficiency and dynamic characteristics of the VSVDPU.

Design and test of a novel converging groove-guided seed tube for precision seeding of maize

In precision seeding operations, the irregular shapes of maize seed particles and the suboptimal geometric structure of the seed tube contribute to the rolling and bouncing of seeds upon falling into the furrow, ultimately compromising seeding uniformity. To address this issue, a convergent groove-guided (CGG) seed tube was proposed based on the principle of brachistochrone curve considering friction (BCCF). The discrete element method (DEM) was employed to conduct a comprehensive phenomenological analysis and numerical investigation of particle guide characteristics. Bench tests and field experiments were designed to verify the simulation results. Through response surface analysis, the optimal seeding performance was achieved at a groove angle of 111.34°, tube incline angle of 1.56°, and ground speed of 7.2 km h−1, resulting in a lateral dispersion landing range of 11.10 mm, angular velocity of 17.38 rad s−1, seed landing speed variation coefficient of 2.29%, and plant spacing variation coefficient of 6.04%. Bench test results unveiled that, under a ground speed of 7.2 km h−1, the variation coefficient of plant spacing for CGG seed tubes was measured at 7.63%, with a deviation of 1.59% from the simulation results. At high ground speeds of 9.0–14.4 km h−1, the seed guiding performance was also better than traditional seed tubes. Consistent results were also verified through field experiments. Therefore, the CGG seed tube manifested superior seed guidance efficacy when juxtaposed with its conventional counterpart, and this design can provide technical support for the realization of seed-to-ground positioning technology.

Addressing variability in cell electrorotation through holographic imaging and correction factors

This study addresses the variations observed in electrorotation measurements due to cell positioning and movement. Electrorotation provides a non-disruptive method for inferring the electrical properties of individual cells. However, its widespread adoption is hindered by significant variation in the observed speed. By mitigating the impact of positional dependencies and other influencing factors, our methodology opens avenues for broader applications of electrorotation in single-cell analysis without the need for complex setups to trap and retain the cell in place. Our novel approach combines multi-plane imaging with mathematical treatment of rotation data. This method uses a conventional quadrupole chip and lens-free imaging to track cell movement, resulting in a simpler design and set-up. Through numerical simulations incorporating cell coordinates, chip design, and experimental parameters, we calculate the variation in torque for each position. These values serve as the basis for the correction factors. Validation experiments with T-lymphocytes and fibroblasts show that the correction factors reduce electrorotation speed variation due to cell movement, with an average reduction to 21% and 18%, respectively. These corrections also revealed previously concealed changes in cell properties, in response to external stimuli, thereby enhancing the reliability of measurements and enabling broader applications in single-cell analysis.