GS Omni 分析仪
GS Omni 分析仪
GS Omni 分析仪
GS Omni 分析仪
GS Omni 分析仪
Thermo Scientific™

GS Omni 分析仪

Thermo Scientific™ GS Omni 分析仪是用于浆液工艺中独特的轻元素分析 。
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货号 GSOMNI
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Thermo Scientific™ GS Omni 分析仪用于浆液工艺中独特的轻元素分析

Thermo Scientific GS Omni 分析仪可对多个浆液流进行准确的、实时的轻和重元素分析。GS Omni 使用瞬发伽玛射线中子活化分析 (PGNAA) 技术,能够测量周期表上低于钙的元素,与使用 X 射线荧光的分析仪相比具有明显优势。此元素分析仪将可改进产品质量、提高回收率和降低生产成本。

Thermo Scientific GS Omni 是最新开发的、经过验证的、坚固耐用的分析仪,可直接同时分析浆液选矿工厂中的多种元素。该分析仪提供1至8个流的配置。最佳的流数通常取决于流浓度、目标元素、所需循环分析时间、工厂布局和过程控制考虑因素。

GS Omni 具有以下优点:

  • 与常见 XRF 技术不同,大多数轻元素都可以测量
  • PGNAA 技术不受粒径(高达 5 mm)变化的影响 - 由于中子和 γ 射线具有高穿透性
  • 闪烁检测器无需冷却
  • 工厂校准,仅需要使用提供的参比标准品进行不频繁的现场检查/维护
  • 当与代表性原始采样器(例如 SamStat-30C)配合使用时,多路器可用于接近冶金质量。这为重复采样系统提供了节约成本的机会
  • 使用可选多路器时可接受多个流
  • 进行工厂校准以用于浆液应用

分析以下一系列元素:

  • 铁矿石浮选和铁矿石湿法磁性分离 - S、Si 和 Al
  • 磷酸盐浮选 - P、Ca 和 Si 以及硫化金和基础金属浮选中的各种其他轻元素应用
规格
类型Analyzer - configurations 2 to 8 streams.
Unit SizeEach

常见问题解答 (FAQ)

Do you have any tips on determining ROI to justify an investment in online elemental analysis?

Justifying any decision around online analysis requires careful and fair consideration of the associated upside.

For a decision around dedicated sampling/analysis stations for a new build, we recommend making a conservative estimate of savings in materials and not underestimating the value of time. A few months' saving on the construction timeline translates directly into an earlier swing from expenditure to income, an inflection point that cannot come soon enough for most projects.

For process control, consider the current situation to determine the magnitude of possible gains. For example:

- What is a recovery improvement worth for your process?

- If you could reduce impurities in the concentrate, what would that mean for selling price?

- What’s the difference in flotation reagent consumption, best to worst current case? What would be the savings if you consistently hit the best case?

- How much are you overmilling over milling to avoid overly coarse material exiting the grinding circuit? What would be the energy savings if you weren’t? Online analysis should pay its way, and easily, so calculations such as these should readily highlight optimal areas for economic implementation and provide evidence to support investment.

How does real-time online elemental analysis data assist in stabilizing grinding circuit and flotation plant operations?

In the grinding circuit, under-grinding typically means poor metal recovery (mineral processing) or sub-standard product (cement). Over-grinding, on the other hand, drives up energy consumption and results in undesirable levels of fines. Milling just enough, balances these competing impacts. Online real-time particle sizing analysis makes it possible both to identify an optimal setpoint for particle size and then reliably maintain it.

In a flotation plant, there is an analogous balance to establish. Poor separation means excessive metal loss while excessive reagent addition is expensive and environmentally undesirable. Here, real-time elemental analysis can provide the information needed to identify the operational sweet spot and optimal control in the face of changes in particle size, ore mineralogy, and pulp density.

In both cases, with real-time data, changes tend to be more frequent but smaller, i.e., the plant stabilizes, with automated control minimizing variability.

Why is high availability of assay data necessary for effective process control in elemental analysis?

If you are aiming for automated process control, then that is only practical with high availability and 95% should be an absolute minimum. Otherwise, switching to and from manual process control will be arduous and problematic with respect to operational efficiency. If availability is not demonstrably high, then operators cannot rely on an analyzer, whether control is manual or automated, and it never becomes an integral part of the control architecture.

How important is measurement interval for process control with on-line elemental analyzer data? How can I determine how often to sample/measure?

When implementing online analysis, there are two key questions to consider: What can I measure? And what can I control to affect that measurement?

Let’s take grinding circuit control as an example. A measurable variable is the particle size of the exiting material, and it can be controlled by parameters such as mill throughput and speed of rotation. How often to measure is then the next question. With manual control, a large interval between measurements inhibits an operator’s ability to adjust the process effectively. There is a long lag between taking action and seeing the result. Increasing measurement frequency, to the limit of real-time measurement, improves feedback allowing the operator to learn how to 'steer' the circuit more effectively. The result will be steadier operation with an automated, well-tuned control loop, the best solution for driving variability to a minimum.

If you can measure and tightly control a vital characteristic of a key stream, in a grinding or flotation circuit, or elsewhere on the plant, then the rewards can be substantial. If you can’t influence a measurable parameter, then there is far less impetus to measure it at all, or with any frequency, though measurement may still be valuable for upset monitoring. Focus on how you would use data if you had it to identify the best places for investment and the frequency of measurement that will be most useful.

What are the operational pros and cons of multi-stream and dedicated analyzers for slurries?

Well-designed dedicated analyzers require only minimal cleaning and maintenance for reliable operation over the long-term. The sample transport associated with centralized systems, on the other hand, requires the addition of pumps and small-bore sample lines adding additional complexity and failure points to the system. These have potential to affect data availability and cost of ownership due to the maintenance, running costs, and emissions associated with pump operation. Such systems are often installed with good intentions and a sound understanding of the practice required to keep them in good working order, but over the years, enthusiasm and rigor have tended to dwindle. Abandoned lines are common with centralized analyzers, an important point to note when assessing upfront CAPEX.

The other significant difference between multi-stream and dedicated analyzers is measurement frequency. For streams that justify real-time measurement, or as close as is feasible, dedicated analyzers are unbeatable.