Abstract: An electric riding lawn mower includes a seat for a user to ride, a main frame to support the seat, a power output assembly including a mowing element to output power to realize mowing function and a first motor to drive the mowing element, a walking assembly to at least drive the electric riding lawn mower to travel in the direction of a first straight line on the ground and a second motor to drive the walking assembly, and a power supply device to power the electric riding lawn mower with a first battery pack, which includes a first battery pack housing and a plurality of battery cells disposed therein. The power supply device is mounted to the main frame. At least one of the first battery packs of the power supply device forms a pluggable connection with the main frame. The battery cells are lithium batteries.

Abstract: An electric riding lawn mower includes a seat for a user to ride, a main frame to support the seat, a power output assembly including a mowing element to output power to realize mowing function and a first motor to drive the mowing element, a walking assembly to at least drive the electric riding lawn mower to travel in the direction of a first straight line on the ground and a second motor to drive the walking assembly, and a power supply device to power the electric riding lawn mower with a first battery pack, which includes a first battery pack housing and a plurality of battery cells disposed therein. The power supply device is mounted to the main frame. At least one of the first battery packs of the power supply device forms a pluggable connection with the main frame. The battery cells are lithium batteries.

Abstract: A hard disk failure prediction method, a hard disk failure prediction system, a device and a medium are provided. The method includes: acquiring SMART attribute values of a hard disk; performing data standardization processing on the SMART attribute values, and filtering the processed SMART attribute values to obtain filtered SMART attribute values; constructing a hard disk failure prediction key database according to the filtered SMART attribute values, a warning value and a rating value corresponding to the filtered SMART attribute values; optimizing a decision tree-based hard disk failure prediction model by using the hard disk failure prediction key database to obtain an optimized decision tree-based hard disk failure prediction model; and acquiring SMART attribute values of a target hard disk hard disk, and predicting a health of the target hard disk to obtain a prediction result. The present disclosure improves the accuracy of failure prediction.

Abstract: An electric riding lawn mower includes a seat for a user to ride, a main frame to support the seat, a power output assembly including a mowing element to output power to realize mowing function and a first motor to drive the mowing element, a walking assembly to at least drive the electric riding lawn mower to travel in the direction of a first straight line on the ground and a second motor to drive the walking assembly, and a power supply device to power the electric riding lawn mower with a first battery pack, which includes a first battery pack housing and a plurality of battery cells disposed therein. The power supply device is mounted to the main frame. At least one of the first battery packs of the power supply device forms a pluggable connection with the main frame. The battery cells are lithium batteries.

Abstract: A grass trimming head includes a housing assembly and a spool. The housing assembly is formed with a housing cavity and an outer aperture for allowing a cutting line to be inserted from an outside of the housing assembly into the housing cavity. At least a portion of the spool is arranged inside the housing cavity, and the spool is rotatable with respect to the housing assembly about a central axis. The spool is formed with an inner aperture for allowing the cutting line to be inserted into the spool or a clamping portion configured to fix the cutting line.

Abstract: Described are an intelligence system and process for material blending in the gasification. The system includes a subsystem for material blending in the gasification, wherein the subsystem for material blending in the gasification includes a raw material property rapid analysis module, for obtaining raw material property parameters of raw materials according to characteristic spectral line intensities of in-furnace raw materials; a blended material property prediction module, for establishing a prediction model, and predicting blended material property parameters by means of the prediction model according to raw material property parameters and raw material proportions; a blending scheme optimization module, for establishing an optimization model, and obtaining an optimized blending scheme by means of the optimization model according to blended material property parameters; a blending scheme economy evaluation module, for outputting a blending scheme with the optimum technical economy.