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| Categories | Raman Analyzer Process Instruments |
|---|---|
| Model Number: | RS2000PAT |
| Operating temperature: | -20℃ ~ 50 ℃ |
| MOQ: | 1 |
| Delivery Time: | 50-60 working days |
| Communication protocols: | Modbus |
| Brand Name: | JINSP |
| Explosion Proof (Main Unit): | ExdbebibmbpxbIICT4Gb / ExtbibmbIIICT135℃Db |
| Packaging Details: | International Shipping Package |
| Payment Terms: | TT |
| Wavelength accuracy: | 0.2nm |
| Output Data format: | spc standard spectrum, prn, txt and other formats are optional |
| Price: | USD120000 - USD171500 |
| Wavelength stability: | 0.01nm |
| Supply Ability: | 20 Unit/70-90 days |
| Laser wavelength: | 785nm |
| Power supply: | 900 W (max)；500 W (typical running) |
| Certification: | CE ISO9001 |
| Connectivity interface: | USB 2.0 |
| Place of Origin: | CHINA |
| Pre-heating time: | ＜60 min |
| Company Info. |
| JINSP Company Ltd. |
| Verified Supplier |
| View Contact Details |
| Product List |
In PX production, process decisions depend on accurate information about the composition of C8 aromatic streams.
The challenge is timing.
When analytical results come from periodic laboratory chromatography, the process may already have changed by the time the result reaches the production team. For adsorption separation, where concentration profiles evolve continuously, this delay can limit process optimization.
JINSP RS2000PAT Online Raman Analyzer provides another approach: measure the process directly and continuously.
The Challenge in PX Production
PX is produced from C8 aromatic mixtures containing PX, MX, OX and EB. These components have closely spaced boiling points, making separation by conventional distillation difficult.
Simulated moving bed adsorption is therefore widely applied.
However, effective operation requires knowledge of composition at important process locations. Traditional offline analysis introduces a measurement delay and requires sample collection, laboratory analysis and result feedback.
RS2000PAT Approach
RS2000PAT uses laser Raman spectroscopy for in-situ liquid analysis.
Raman probes can be installed at different positions inside an adsorption tower to continuously monitor the C8 aromatic mixture. The system analyzes the Raman response and provides real-time concentration information.
This creates a continuous analytical layer between the physical separation process and the plant control system.
What the Analyzer Provides
Real-time PX concentration
The Raman model extracts the PX signal from the surrounding C8 aromatic components and provides quantitative measurement.
Multiple monitoring locations
Different probe positions can provide information about concentration distribution within the adsorption tower.
Automatic data transmission
Measurement results can be communicated to the DCS through industrial communication interfaces.
Continuous operation
The analyzer is designed for uninterrupted process monitoring rather than periodic laboratory measurement.
Measured Application Performance
For the demonstrated PX monitoring application, the quantitative deviation of PX is reported to be less than 0.07%.
Why Process Teams Use Online Raman
Online Raman measurement can transform analytical information from a delayed laboratory result into a continuously available process variable.
That information can support faster operating adjustments, improved adsorbent-cycle management and reduced manual sampling requirements.
Application: Online PX concentration monitoring in C8 aromatic adsorption separation systems.
Model number | RS2000PAT |
Number of detection channels | Single channel, monitoring 1 position only |
Device dimension | 800 mm(width)× 900 mm(depth)× 1300 mm(height) |
Operating temperature | -20 ~ 50 ℃ |
Explosion Proof (Main Unit) | ExdbebibmbpxbIICT4Gb / ExtbibmbIIICT135℃Db |
Thermostat | Three-level temperature control system design can operate stably for a long time in an environment of -20 ~ 50 ℃ , and is suitable for online monitoring environments in different factories |
Connectivity | RS485 and RJ45 network ports provide Mod Bus protocol, can be adapted to many types of industrial control systems and can feedback results to the control system. |
Probe | 1pc standard immerssion fiber optic probe and 1pc non-immersion probe |
Multi-component monitoring | Simultaneously obtain the content of multiple components during the reaction process, collect single-channel signals continuously in real-time, and the substance content and change trend can be given in real-time, enabling intelligent analysis of unknown components during the reaction process. |
Consistency | Patented algorithms for device calibration and model transfer ensure data consistency across multiple devices |
Smart modeling | Intelligent matching of optimal algorithms, or customize multiple machine learning models according to the needs of one-click automatic modeling |
Self-learning modeling | Equipped with self-learning modeling capabilities, it eliminates the need for sampling and manual modeling. It can intelligently select optimal collection parameters, monitor changes in various components within the system in real-time, automatically identify and assist in analysis. This aids in understanding and monitoring reactions without the need for manual intervention |
24h working | Built-in real-time automatic calibration and self-test, thermostatic control and positive pressure protection. Works well in high and low temperatures, explosive and corrosive environments. |
% Relative humidity | 0~90%RH |
Power supply | 900 W (max)；500 W (typical running) |
Pre-heating time | ＜60 min |
Company Introduction:
JINSP COMPANY LIMITED is a professional enterprise focusing on spectral analysis technology. Rooted in Tsinghua University, it has accumulated 19 years of technical expertise with over 200 patent applications. The company has participated in formulating 4 national standards for Raman spectroscopy and 1 international standard, and has won authoritative awards including China Patent Excellence Award, Geneva International Invention Award, and Zhu Liang-Yi Analytical Instrument “Innovation Achievement Award”.
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