The Heil Co.

Garrett J Eckerl

John Forrest Smith

Michael Dean Geary

Albert Xiaoxia Jiang

Anthony Romano

Thomas Leon Wilding

Alejandro De Leon

A refuse collection vehicle has various hydraulic actuators including at least one cylinder with an internal seal. A sensor is responsive to movement of the piston and sends a signal to a controller to indicate piston movement information during an associated vehicle body component movement. The controller is configured to determine a motion characteristic of the piston during a predetermined body component movement, compare the determined motion characteristic to a stored reference motion characteristic, and in response to determining that a difference between the determined motion characteristic and the reference motion characteristic is greater than a predetermined value, trigger an indication that the refuse collection vehicle is in need of service.

Hydraulic cylinder monitoring

A refuse vehicle includes a telescopic arm, a sensor, and a processor. The telescopic arm includes an outer boom defining a bore, an inner boom received in the bore of the outer boom, and a bearing pad received in the bore and located between an exterior surface of the inner boom and an interior surface of the outer boom. The sensor is configured to output data indicating a position of a load-bearing limb of the telescopic arm. The processor is configured to receive data output from the sensor and determine a wear-state of the bearing pad based on the position.

Bearing pad monitoring systems and methods

A computer-implemented method for analyzing refuse includes operations of receiving sensor data indicating an operational state of a vehicle body component of a refuse collection vehicle (RCV); analyzing the sensor data to detect a presence of a triggering condition based at least partly on a particular operational state of the vehicle body component, as indicated by the sensor data; in response to detecting the triggering condition, accessing image data indicating a physical state of refuse collected by the RCV; providing the image data as input to at least one contaminant detection model trained, using at least one machine learning (ML) algorithm, to output a classification of the image data, the classification indicating a degree of contamination of the refuse; and storing, in a machine-readable medium, the classification of the image data.

Growing community of inventors

Fort Payne, AL, United States of America

Garrett J Eckerl