A Torque-Sensorless Viscometer for Food Processing Applications

2019 ◽  
Vol 888 ◽  
pp. 66-71
Author(s):  
Y. Jiang ◽  
S. Hashimoto ◽  
Y. Yamakoshi ◽  
Takashi Otomo

Our study aims to develop a small handy low-cost viscometer for nursing care food management. There are many methods to measure the viscosity of a fluid. In this research, the rotational viscometer employing the observer-based method instead of the actual torque transducer has been developed. The digitally controlled motor has been used to estimate the viscosity in real time with high accuracy. In order to verify the effectiveness of the developed viscosity estimation method, a prototype viscometer has been constructed and tested the viscosity estimation accuracy with standard liquids. As a result, the viscosity accuracy is equivalent to that of the conventional torque transducer-equipped viscometer.

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3250 ◽  
Author(s):  
Aleš Hace ◽  
Milan Čurkovič

Velocity measurement by an incremental encoder is an important issue for advanced motion control applications such as robotics. In this paper, we deal with a kind of MT-type velocity estimation method. Though the conventional MT method is well known and has been well proven in practice, it requires execution of an arithmetic division operation that prevents an efficient implementation on low-cost FPGA-based control platforms. Thus, we propose a divisionless MT-type algorithm, which can provide a similar performance in velocity estimation accuracy as the conventional method, but requiring significantly less FPGA resources, since it implements only simple arithmetic operations such as addition, subtraction, and multiplication, that can be implemented more easily on the processing hardware. Furthermore, the algorithm is fast in execution, thus, it provides the output in only a few clock cycles. Though the proposed algorithm can be described in a recursive form, the stability of the estimation process is not jeopardized, although it is an important issue in this case. Hence, the algorithm is introduced in a form which assures stability in a wide speed range. We show the implementation of the algorithm on the experimental FPGA platform. The experimental results validated the proposed divisionless MT-type algorithm fully for accurate velocity estimation.


Author(s):  
Xiao Chen ◽  
Zaichen Zhang ◽  
Liang Wu ◽  
Jian Dang

Abstract In this journal, we investigate the beam-domain channel estimation and power allocation in hybrid architecture massive multiple-input and multiple-output (MIMO) communication systems. First, we propose a low-complexity channel estimation method, which utilizes the beam steering vectors achieved from the direction-of-arrival (DOA) estimation and beam gains estimated by low-overhead pilots. Based on the estimated beam information, a purely analog precoding strategy is also designed. Then, the optimal power allocation among multiple beams is derived to maximize spectral efficiency. Finally, simulation results show that the proposed schemes can achieve high channel estimation accuracy and spectral efficiency.


2021 ◽  
Vol 13 (4) ◽  
pp. 803
Author(s):  
Lingchen Lin ◽  
Kunyong Yu ◽  
Xiong Yao ◽  
Yangbo Deng ◽  
Zhenbang Hao ◽  
...  

As a key canopy structure parameter, the estimation method of the Leaf Area Index (LAI) has always attracted attention. To explore a potential method to estimate forest LAI from 3D point cloud at low cost, we took photos from different angles of the drone and set five schemes (O (0°), T15 (15°), T30 (30°), OT15 (0° and 15°) and OT30 (0° and 30°)), which were used to reconstruct 3D point cloud of forest canopy based on photogrammetry. Subsequently, the LAI values and the leaf area distribution in the vertical direction derived from five schemes were calculated based on the voxelized model. Our results show that the serious lack of leaf area in the middle and lower layers determines that the LAI estimate of O is inaccurate. For oblique photogrammetry, schemes with 30° photos always provided better LAI estimates than schemes with 15° photos (T30 better than T15, OT30 better than OT15), mainly reflected in the lower part of the canopy, which is particularly obvious in low-LAI areas. The overall structure of the single-tilt angle scheme (T15, T30) was relatively complete, but the rough point cloud details could not reflect the actual situation of LAI well. Multi-angle schemes (OT15, OT30) provided excellent leaf area estimation (OT15: R2 = 0.8225, RMSE = 0.3334 m2/m2; OT30: R2 = 0.9119, RMSE = 0.1790 m2/m2). OT30 provided the best LAI estimation accuracy at a sub-voxel size of 0.09 m and the best checkpoint accuracy (OT30: RMSE [H] = 0.2917 m, RMSE [V] = 0.1797 m). The results highlight that coupling oblique photography and nadiral photography can be an effective solution to estimate forest LAI.


2020 ◽  
Author(s):  
Derek Schulte ◽  
Kyam Krieger ◽  
Carl W. Chin ◽  
Alexander Sonn
Keyword(s):  
Low Cost ◽  

2019 ◽  
Vol 61 (2) ◽  
pp. 253-259
Author(s):  
Iroshani Kodikara ◽  
Iroshini Abeysekara ◽  
Dhanusha Gamage ◽  
Isurani Ilayperuma

Background Volume estimation of organs using two-dimensional (2D) ultrasonography is frequently warranted. Considering the influence of estimated volume on patient management, maintenance of its high accuracy is empirical. However, data are scarce regarding the accuracy of estimated volume of non-globular shaped objects of different volumes. Purpose To evaluate the volume estimation accuracy of different shaped and sized objects using high-end 2D ultrasound scanners. Material and Methods Globular (n=5); non-globular elongated (n=5), and non-globular near-spherical shaped (n=4) hollow plastic objects were scanned to estimate the volumes; actual volumes were compared with estimated volumes. T-test and one-way ANOVA were used to compare means; P<0.05 was considered significant. Results The actual volumes of the objects were in the range of 10–445 mL; estimated volumes ranged from 6.4–425 mL ( P=0.067). The estimated volume was lower than the actual volume; such volume underestimation was marked for non-globular elongated objects. Regardless of the scanner, the highest volume estimation error was for non-globular elongated objects (<40%) followed by non-globular near-spherical shaped objects (<23.88%); the lowest was for globular objects (<3.6%). Irrespective of the shape or the volume of the object, volume estimation difference among the scanners was not significant: globular (F=0.430, P=0.66); non-globular elongated (F=3.69, P=0.064); and non-globular near-spherical (F=4.00, P=0.06). A good inter-rater agreement (R=0.99, P<0.001) and a good correlation between actual versus estimated volumes (R=0.98, P<0.001) were noted. Conclusion The 2D ultrasonography can be recommended for volume estimation purposes of different shaped and different sized objects, regardless the type of the high-end scanner used.


Author(s):  
Jonas Austerjost ◽  
Robert Söldner ◽  
Christoffer Edlund ◽  
Johan Trygg ◽  
David Pollard ◽  
...  

Machine vision is a powerful technology that has become increasingly popular and accurate during the last decade due to rapid advances in the field of machine learning. The majority of machine vision applications are currently found in consumer electronics, automotive applications, and quality control, yet the potential for bioprocessing applications is tremendous. For instance, detecting and controlling foam emergence is important for all upstream bioprocesses, but the lack of robust foam sensing often leads to batch failures from foam-outs or overaddition of antifoam agents. Here, we report a new low-cost, flexible, and reliable foam sensor concept for bioreactor applications. The concept applies convolutional neural networks (CNNs), a state-of-the-art machine learning system for image processing. The implemented method shows high accuracy for both binary foam detection (foam/no foam) and fine-grained classification of foam levels.


Author(s):  
Jong-Hwa Yoon ◽  
Huei Peng

Knowing vehicle sideslip angle accurately is critical for active safety systems such as Electronic Stability Control (ESC). Vehicle sideslip angle can be measured through optical speed sensors, or dual-antenna GPS. These measurement systems are costly (∼$5k to $100k), which prohibits wide adoption of such systems. This paper demonstrates that the vehicle sideslip angle can be estimated in real-time by using two low-cost single-antenna GPS receivers. Fast sampled signals from an Inertial Measurement Unit (IMU) compensate for the slow update rate of the GPS receivers through an Extended Kalman Filter (EKF). Bias errors of the IMU measurements are estimated through an EKF to improve the sideslip estimation accuracy. A key challenge of the proposed method lies in the synchronization of the two GPS receivers, which is achieved through an extrapolated update method. Analysis reveals that the estimation accuracy of the proposed method relies mainly on vehicle yaw rate and longitudinal velocity. Experimental results confirm the feasibility of the proposed method.


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