Sensor-based excavator performance measurement and optimization

[DIG-DOG]

1. Common sensor types for excavators
In practical applications, sensors in different parts undertake different measurement tasks. Common ones are:

Pressure sensor: used to measure the pressure change of the hydraulic system to ensure the stable operation of the hydraulic circuit, which is the basis for realizing "excavator hydraulic system sensor monitoring".

Displacement sensor: installed on the boom, dipper and bucket, real-time monitoring of the movement amplitude and position, providing data support for "excavator arm movement accuracy measurement".

Acceleration sensor: detects the vibration of the excavator during operation, which helps to "excavator vibration characteristic analysis and optimization".

Tilt sensor: used to detect the inclination angle of the whole machine and components to ensure operation safety, especially suitable for "excavator slope operation stability measurement".

Temperature sensor: monitors hydraulic oil temperature and engine temperature, detects abnormalities in time, and assists in "excavator hydraulic oil temperature intelligent monitoring".

Through the collaborative work of these sensors, a complete data chain can be formed to achieve a comprehensive evaluation of the various working performances of the excavator.

2. Sensor measurement method and data collection process
In order to ensure the accuracy of measurement, the sensors on the excavator generally adopt the following measurement and data collection methods:

Multi-point synchronous sampling
Use a high-frequency data collector to record the numerical changes from each sensor at the same time to ensure the time synchronization of different data sources, which is crucial for "real-time measurement of dynamic working parameters of excavators".

Wireless data transmission and remote monitoring
Through the wireless module, the collected data is uploaded to the back-end platform in real time to realize "excavator remote sensor data monitoring", which is especially suitable for large construction sites or remote areas.

Data preprocessing and filtering
In order to reduce the interference caused by environmental noise, the common filtering algorithm is used to preprocess the raw data, which is particularly important in the process of "excavator sensor measurement data cleaning and optimization".

Data fusion analysis
Combined with machine learning models to fuse multi-source data, explore potential correlations, such as calculating the operating load through pressure and displacement data, and realizing "excavator load identification technology based on sensor data".

3. Excavator performance optimization strategy
Only with accurate measurement data can targeted optimization be carried out. Generally includes the following aspects:

1. Operation path optimization
By analyzing the motion trajectory of the boom, dipper, and bucket, unnecessary actions and time waste can be found, so as to develop a more efficient operation path. This technology is usually called "excavator work cycle efficiency optimization".

2. Hydraulic system energy efficiency improvement
Monitoring the pressure and flow changes of the hydraulic system, optimizing the oil circuit design and control strategy, can effectively reduce energy consumption and extend the life of the equipment. It is a typical "excavator hydraulic energy efficiency optimization solution".

3. Fault warning and maintenance strategy
The sensor-based abnormal detection system can issue an early warning before a fault occurs. For example, when an abnormal fluctuation in hydraulic pressure is detected, the system will remind the operator to check according to the "excavator hydraulic sensor abnormal alarm rule", which greatly reduces the downtime loss.

4. Safe operation guarantee
The data of the inclination sensor and the acceleration sensor can be used to determine in real time whether the excavator is in a dangerous posture, especially when constructing on slopes or unstable ground. With the help of the "excavator operation safety intelligent monitoring system", timely intervention can be made to improve construction safety.

IV. Future Development Trends
With the advancement of technology, the sensor measurement and optimization system for excavators will develop in a more intelligent and integrated direction:

Self-learning and adaptive optimization: In the future, more artificial intelligence technology will be used to enable the system to automatically adjust parameters according to the working environment and task requirements, realizing "intelligent adaptive excavator performance optimization".

Low-power and miniaturized sensor application: The new generation of sensors will be more miniaturized and have lower energy consumption, which is convenient for large-scale deployment and promotes the "application of low-power wireless sensor networks in excavators".

Data interconnection and cloud platform management: Through the Internet of Things technology, all excavators are connected to the cloud platform for unified management and optimization, realizing "cloud-based excavator remote maintenance and optimization system".