NIR/CS sorting technology application solutions

XRT Series Intelligent Sensor Sorting Machine

The intelligent sensor photoelectric sorting machine introduces artificial intelligence techniques such as deep convolutional neural networks (CNN) into the field of visible light photoelectric sorting for material image analysis and processing Through C

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Working Principle

Technological Advantages

◎ High Accuracy: The equipment is equipped with two sensor systems: near-infrared hyperspectral and visible light. The optimal sensor combination is selected based on the ore properties and beneficiation task to achieve accurate identification.

◎ High Speed: The near-infrared spectral probe can measure one million spectra per second, with wavelength resolution accurate to ten nanometers. The visible light sensor can detect up to 20,000 mineral particles per second. From sensor scanning to the final decision on whether to change the ore block's trajectory, only milliseconds are needed. The compressed air solenoid valve completes one ore block blowing and resetting in just 10-18 milliseconds.

◎ High Capacity: The equipment fully meets the requirements of modern large-scale mining equipment. Taking talc ore with a feed particle size of 20-60mm as an example, the processing capacity can reach 50t/h. The maximum on-site processing capacity is approximately 300t/h.

◎ Energy Saving and Environmentally Friendly: For example, a near-infrared hyperspectral and visible light composite intelligent sensor sorting machine with a belt width of 1200 mm consumes only 15 kW/h, and its fully sealed structure is equipped with a dust removal port, making dust controllable.

Technical Features

◎ Utilizing imported German technology, the material separation system employs a jet nozzle design and imported solenoid valves, ensuring stable performance and precise operation.

◎ High-precision identification is achieved through spectral analysis and a motion camera.

◎ The system is self-learning and can identify different minerals through batch mineral data acquisition.

Technical Parameters

Model	Belt Width mm	Sorting belt speed m/s	Infrared wavelength nm	Sorting accuracy %	Feed particle size mm	Processing capacity t/h
NIR-1000	1000	0 ～ 3.5	900-1700	≥ 90	10 ～ 30	15 ～ 20
					30 ～ 80	20 ～ 45
NIR-1200	1200				10 ～ 30	20 ～ 30
					30 ～ 80	30 ～ 65
NIR-1600	1600				10 ～ 30	30 ～ 45
					30 ～ 80	45 ～ 80
NIR-1800	1800				10 ～ 30	45 ～ 60
					30 ～ 80	60 ～ 80