Roadheader Model Weight Class Total Power (kW) Cutter Transmission Power (kW) AQM 50: 18 tons: 78.5 163: 33/110: AQM 100L: 24 tons: 135 186: 110: AQM 100: 27 tons: 135 220: 110: AQM 150: 35 tons: 205 264: 132/150: AQM 150HR: 36 tons: 205 264: 150/160: AQM 175: 65 tons: 300 389: 186: AQM 200: 70 tons: 394: 200: AQM 260: 90 tons: 340 464: 260
Strong power Mining Crawler Roadheader machine EBZ230 core drilling rig for sale Shanghai Canmax Electronic & Mechanical Equipment Co., Ltd. US $260000-$660000 / Unit
2020-1-1 The roadheader is a machine for excavating rock in mining and civil construction projects. It is a hybrid machine, with better manoeuvrability than that of tunnel boring machines. It can cut rocks even up to 160 MPa, if laminated or fractured, in different tunnel profiles and adapts easily to changing operational conditions.
Cutting Motor Power: 75 318kW
TON MR520 is an electrically powered, crawler-mounted roadheader designed for the production of potash and salt, with compressive strengths of 20–40 MPa (UCS).
2010-1-12 Roadheader performance and related parameters are reviewed and their effects on the production and which require high machine power and mass to react to these forces. Therefore, heavy duty hard rock machines with higher power and more mass have been developed and introduced into the market by manufacturers in recent years. The performance of a
A critical issue in successful roadheader application is the ability to evaluate and predict the machine performance named instantaneous (net) cutting rate. Although there are several prediction...
where RPI is the roadheader penetration index, P is machine power in kW, W is the roadheader weight in tons, UCS is unconfined compressive strength of rock in MPa and e is the base of natural...
Non-coal Seam. Working Conditions. 200 520kW. Cutting Motor Power. Home Products Mining & Tunneling Roadheader. SCR Series Roadheader. A Hard Worker For Non-Coal Seam. Total Power. 420
2017-7-11 This paper focuses on roadheader performance prediction using six different machine learning algorithms and a combination of various machine learning algorithms via ensemble techniques. Algorithms are ZeroR, random forest (RF), Gaussian process, linear regression, logistic regression and multi-layer perceptron (MLP).