Assessment of power consumption of electric machinery in agricultural tasks for enhancing the route planning problem

Schmidt, Javier Romero; Cheein, Fernando Auat

doi:10.1016/j.compag.2019.104868

Cited by 10 publications

(2 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This implies that it is possible to carry out maintenance between several regions without leaving that particular location [35]. In a study by [36], it was established that one of the major problems of agricultural machinery industry lies in the electrification and maintenance network during operations. These problems have contributed to increase in the cost of production as well as safety problems.…”

Section: Maintenance Management Strategy Of Agricultural Machinerymentioning

confidence: 99%

Condition Monitoring of Farm Machinery, a Maintenance Strategy for a Sustainable Livestock Production: A Review

Salawu,

Airewa,

Akerekan

et al. 2023

E3S Web Conf.

View full text Add to dashboard Cite

The agricultural industry is crucial to the development of the national economy. Inadequate agricultural equipment maintenance could result to a huge economic impact, especially during the harvest period. Thus, this study highlighted on the importance of condition monitoring of agricultural machinery/equipment for enhanced agricultural productions. The study established that adequate condition monitoring of agricultural machineries provides reliability data that will help in the implementation of the integrity of maintenance strategies. Additionally, adequate health monitoring of the advanced machineries will help in improving the efficiency of the machines as well as improving the overall agricultural productivity. This study provides great insight to farmers on the way to monitor and maintain the health of their agricultural machineries.

show abstract

Section: Maintenance Management Strategy Of Agricultural Machinerymentioning

confidence: 99%

Condition Monitoring of Farm Machinery, a Maintenance Strategy for a Sustainable Livestock Production: A Review

Salawu,

Airewa,

Akerekan

et al. 2023

E3S Web Conf.

View full text Add to dashboard Cite

show abstract

“…Aerial spraying is essential to modern forestry and plays an increasingly important role in pest and disease control and in other applications [11,12]. Route planning is crucial for aerial applications in forestry to reduce the amount of applied pesticide and aviation fuel consumption and to improve the accuracy of the aircraft when following the track [13,14].…”

Section: Introductionmentioning

confidence: 99%

Route Planning of Helicopters Spraying Operations in Multiple Forest Areas

Fang

Liu

et al. 2021

Forests

View full text Add to dashboard Cite

It is of great value to research the problem of forest pest and disease control. Currently, helicopters play an important role in dealing with this problem. However, the spraying route planning still depends on the pilot’s driving experience, which leads to low efficiency and less accurate coverage. For this reason, this paper attempts to use intelligent algorithms to plan the pesticide spraying route for helicopters. When the helicopter is conducting spraying operations in multiple forest areas, the routes are divided into two parts: pesticide spraying routes for individual forest areas and dispatch routes between multiple forest areas. First, the shorter spraying route with fewer turnarounds for individual forest areas was determined. Then a two-layer intelligent algorithm, a combination of a genetic algorithm (GA) and ant colony optimization algorithm (ACO), was designed to determine the dispatch route between multiple forest areas, which is referred to as GAACO-GA. The performance was evaluated in self-created multiple forest areas and compared with other two-layer intelligent algorithms. The results show that the GAACO-GA algorithm found the shortest dispatch route (5032.75 m), which was 5.60%, 5.45%, 6.54%, and 4.07% shorter than that of GA-GA algorithm, simulated annealing-GA (SA-GA) algorithm, ACO-GA algorithm, and particle swarm optimization-GA (PSO-GA) algorithm, respectively. A spraying experiment with a helicopter was conducted near Pigzui Mountain, Huai’an City, Jiangsu Province, China. It was found that the flight path obtained from the proposed algorithm was 5.43% shorter than that derived from a manual planning method. The dispatch route length was reduced by 16.93%, the number of turnarounds was reduced by 11 times, and the redundant coverage was reduced by 17.87%. Moreover, helicopter fuel consumption and pesticide consumption decreased by 10.56% and 5.43%, respectively. The proposed algorithm can shorten the application route, reduce the number of turnarounds and the cost of spraying operations, and has the potential for use in spraying operations in smart forestry and agriculture.

show abstract