Detection of K in soil using time-resolved laser-induced breakdown spectroscopy based on convolutional neural networks

One of the technical bottlenecks of traditional laser-induced breakdown spectroscopy(LIBS) is the difficulty in quantitative detection caused by the matrix effect. To troubleshoot this problem,this paper investigated a combination of time-resolved LIBS and convolutional neural networks(CNNs) to improve K determination in soil. The time-resolved LIBS contained the information of both wavelength and time dimension. The spectra of wavelength dimension showed the characteristic emission lines of elements, and those of time dimension presented the plasma decay trend. The one-dimensional data of LIBS intensity from the emission line at 766.49 nm were extracted and correlated with the K concentration, showing a poor correlation of R_c^2?=?0.0967, which is caused by the matrix effect of heterogeneous soil. For the wavelength dimension, the two-dimensional data of traditional integrated LIBS were extracted and analyzed by an artificial neural network(ANN), showing R_v^2?=?0.6318 and the root mean square error of validation(RMSEV)?=?0.6234. For the time dimension, the two-dimensional data of time-decay LIBS were extracted and analyzed by ANN, showing R_v^2?=?0.7366 and RMSEV?=?0.7855.These higher determination coefficients reveal that both the non-K emission lines of wavelength dimension and the spectral decay of time dimension could assist in quantitative detection of K.However, due to limited calibration samples, the two-dimensional models presented over-fitting.The three-dimensional data of time-resolved LIBS were analyzed by CNNs, which extracted and integrated the information of both the wavelength and time dimension, showing the R_v^2?=?0.9968 and RMSEV?=?0.0785. CNN analysis of time-resolved LIBS is capable of improving the determination of K in soil.

Design and parameters optimization of the curved sieve for an air suction jujube harvester

In order to improve the screening performance and cleaning effect of the jujube harvesting machinery cleaning device,a vibrating curved screen device was designed in this study.By analyzing the structure mechanism of the curved sieve body,it was obtained that the arc-shaped mesh hole spacing S was 15-25 mm and the curved mesh hole curvature U was 90°-150°.By exploring the movement state and stress of jujube and impurities on the curved sieve body,it was determined that the horizontal spacing L of the curved layer sieve was 30 mm and the vertical spacing H was 45-65 mm.Taking the vertical spacing H of the curved layer sieve,the curvature U of the curved mesh hole,and the spacing S of the curved mesh hole as the experimental factors,considering the screening efficiencyαand the impurity contentβof the jujube as the response values,the three-factor three-level quadratic regression orthogonal experiment was designed,establishing the regression mathematical model of each factor and response value,and the multiple target optimization algorithm of Design-expert software was used to optimize various factors.The results showed that the influence factors on the screening efficiency were in the descending order as:the arc screen spacing,the vertical spacing of the curved layer screen,and the curved screen hole curvature;The significant factors affecting the impurity content of jujube were in the descending order as:the arc screen spacing,the curved screen hole curvature,and the vertical spacing of the curved layer screen.The experimental results were verified by the optimized combination of parameters:when the vertical spacing H of the curved layer screen was 65 mm,the curved screen hole curvature U was 110°,and the arc screen spacing S was 23 mm,the average screening efficiencyαin the test was 91.09%.The relative error between the experimental verification value and the theoretical optimization value was 1.36%,which was less than 5%.The impurity content of jujubeβin the test was 1.02%.The relative error between the experimental verification value and the theoretical optimization value was 2.00%,which was also less than 5%.The test results can provide a reference for the research and optimization of the subsequent air-suction-type jujube harvester cleaning device.

Obstacle avoidance transplanting method on Kinect visual processing

In modern facility agriculture,to improve the quality and efficiency of transplanting,the application of transplanting robots based on visual processing is becoming more and more widespread.In order to reduce the damage to plants during the transplanting process and reduce the damage rate of plant stems,leaves and substrates,a transplanting method based on Kinect visual processing combined with an inclined transplanting manipulator was proposed.In the research,the Kinect visual processing was used to obtain and process the seedling height information and leaf edge information,and the working coordinate system of the transplanting manipulator was established and applied to plan the obstacle avoidance path.Combined with the oblique manipulator,the obstacle avoidance transplanting method was proposed.Through the structural design and force analysis of the seedling transplanting device,the key parameters that affect the transplanting quality were obtained,and the optimal transplanting performance parameters were obtained through experiments.In the experiment,with the aid of the Kinect vision processing system,the designed obstacle avoidance transplanting manipulator had a leaf damage degree of 4.70%,a stem bending rate of 16.67%,substrate integrity of 83.45%and a transplanting quality parameter of 87.36%.The time for a single seedling transplanting was(8.32±0.40)s.The experiment result proves that the obstacle avoidance transplanting method based on Kinect visual processing can effectively reduce the damage to seedlings when ensuring the transplanting efficiency.

Design and optimization of an automatic hydraulic steer-by-wire system for an agricultural chassis

To meet the requirements of fast steering at low vehicle speed and slow steering at high vehicle speed,the automatic steering of agricultural chassis must control both the wheel steering angle and the steering angle’s angular speed.This study applied hydraulic steer-by-wire technology to the automatic steering control of agricultural chassis.First,the transmission mechanism of the designed steering system was optimized.According to the rule of least squares,aiming at the minimum sum of squares of errors between 10 ideal outer wheel angles and real outer wheel angles,the optimal solution of hole spacing on both sides of the steering hydraulic cylinder piston rod was 925 mm.The outer wheel angle error of the optimized steering mechanism throughout the steering stroke was less than 0.15°.Additionally,a hydraulic steer-by-wire system was developed,and the parameters of its critical components were calculated.Then,the compound control strategy of the steering cylinder piston rod displacement and moving speed was formulated for this automatic steering system.The entire control system included a valve control signal calculation model,an initial velocity calculation model,a correction velocity calculation model,and an attenuation velocity calculation model,and the formulae of each model were deduced.Based on the optimized parameters and the developed control strategy,a simulation model was built in AMESim,and simulation results showed that the proposed control strategy could achieve simultaneous controls of piston rod displacement and speed at different vehicle speeds and loads.The horizontal and vertical displacements of the right wheel center were plotted for typical vehicle speeds and steering commands.The results of this study provided a new idea for the application of hydraulic steer-by-wire technology in the automatic steering of agricultural chassis.

Finite element modal analysis and experiment of rice transplanter chassis

The vibration problem during the operation of rice transplanters is the most common phenomenon.In order that the static and dynamic characteristics of the rice transplanter chassis can meet the requirements of more stable operation,the research took the 2ZG-6DK rice transplanter as the research object to carry out a vibration reduction optimization study.In the research,the Pro/Engineer 5.0 software was first used to model the chassis of the rice transplanter.The constructed finite element model was revised by using the structural parameter revision method and the mixed penalty function method.The model was imported into ANSYS Workbench to solve the modal frequency and vibration shape of the rice transplanter chassis.Based on the MAC(modal assurance criterion)criterion,modal tests were carried out to verify the accuracy of the finite element theoretical analysis.Through the analysis of the characteristics of the external excitation frequency,the chassis is structurally optimized to avoid resonance caused by the natural frequency of the chassis falling within the road excitation frequency range.The final optimization results showed that the first four orders of modal frequencies of the chassis were adjusted to 32.083 Hz,33.751 Hz,42.517 Hz,and 50.362 Hz,respectively,in the case that the chassis mass was increased by 6.714 kg(8.8%).They all avoid the range of road excitation frequency(10-30 Hz)so that the rice transplanter can effectively avoid the resonance phenomenon during operation.This study can provide a reference for the design and optimization of the chassis structure of transplanter.