How to analyze data changes before and after chemical cleaning of reverse osmosis systems to evaluate cleaning effectiveness?

How to analyze data changes before and after chemical cleaning of reverse osmosis systems to evaluate cleaning effectiveness?

Chemical cleaning of reverse osmosis systems for industrial pure water, drinking water, wastewater reuse, and zero liquid discharge is a common operational procedure. Analyzing data before and after chemical cleaning is crucial for assessing cleaning effectiveness, identifying membrane fouling types, and guiding subsequent operations.

The objective of chemical cleaning is to remove contaminants from the membrane surface (such as scale, colloids, organic matter, and microorganisms), restoring the system to or near its initial (or post-previous cleaning) operational state. Therefore, the core of analysis lies in “comparison” and “recovery.”

Comparison: Contrasting stable post-cleaning operational data with pre-cleaning data (under identical or similar feed conditions).

Restoration: Observing whether key parameters recover in a “positive direction,” specifically: reduced operating pressure, restored flow rate, decreased pressure drop, and increased salt rejection rate.

I. Key Parameter Analysis Guide

For greater clarity, the following table illustrates what changes in each parameter signify:

Monitored Parameter

Pre-Cleaning State (Contaminated)

Ideal Post-Cleaning Change (Indicator of Effective Cleaning)

Physical Significance of Parameter Change

1. Inlet Pressure

Increase (to maintain product water flow)

Decrease

Contaminants clog membrane pores, requiring greater force to push water through. After cleaning, channels reopen and pressure naturally drops.

2. Inter-stage pressure differential/concentrate pressure

Significantly increased

Markedly decreased

One of the most critical indicators. Increased pressure differential primarily results from membrane channels (especially the first stage) being blocked by contaminants, increasing flow resistance. After cleaning, channels are unobstructed, and pressure differential decreases.

3. Product water flow rate

Decreased

Increased

Contaminants cover the membrane surface, hindering water permeation. After cleaning, membrane flux is restored, and product water flow increases.

4. Concentrate flow rate may decrease or remain stable. This is correlated with product water flow and system recovery rate.

5. Product water conductivity (salt rejection rate) increases (salt rejection rate decreases) or decreases (salt rejection rate recovers). Contaminants disrupt the membrane's dense separation layer or “salt ion channels” (e.g., sub-scale corrosion), allowing more salts to pass through. Cleaning restores the membrane's selective separation function.

Key Takeaways:

A successful chemical cleaning should demonstrate “two decreases and one increase”:

Two decreases: Lower feed pressure, reduced inter-stage pressure differential

One increase: Higher product water flow Additional benefit: Lower product water conductivity (higher salt rejection rate)

II. How to Quantitatively Assess Cleaning Effectiveness? (Specific Data Metrics) This is a highly practical question, but there is no universal numerical standard, as it heavily depends on each project's system design, contamination level, and pre-cleaning condition. However, the industry commonly uses performance recovery rate as a benchmark.

1. Core Evaluation Standard: Performance Recovery Rate

Ideally, post-cleaning parameters should return to the system's initial performance or the performance achieved after the last effective cleaning. We typically aim for a post-cleaning performance recovery rate exceeding 80%, with excellent results reaching 90%-95%. The calculation formula is as follows:

Performance Recovery Rate = (Pre-cleaning Value - Post-cleaning Value) / (Pre-cleaning Value - Initial Healthy Value) × 100% This formula applies to water production rate and salt rejection rate (adjustments are needed for pressure-related parameters). Example (Water Production Rate): Initial RO system water production rate: 100 m³/h Pre-cleaning rate reduced to: 70 m³/h due to fouling Post-chemical cleaning rate restored to: 90 m³/h Water Production Recovery Rate = (90 - 70) / (100 - 70) × 100% = 20 / 30 × 100% ≈ 66.7%

This result is considered average, possibly indicating severe fouling or room for optimization in the cleaning protocol.

2. Key quantitative observation points:

Inter-stage pressure difference: This is the most sensitive indicator. A successful cleaning should reduce the inter-stage pressure difference by 10%-25% or more. For example, if the pressure difference increased from 1.5 bar to 3.0 bar before cleaning, it should drop to around 1.8-2.0 bar after cleaning.

Feed water pressure: Under the same water production rate and temperature, the feed water pressure should decrease by 5%-15%. For instance, if pressure increased from 10 bar to 12 bar to maintain production rate, it should drop back to 10.5–11.0 bar post-cleaning.

Product Water Flow Rate: Under identical inlet pressure and temperature conditions, the flow rate should increase by 5%–15%.

Dissolved Solids Removal Rate: Product water conductivity should decrease by 10%–30%. For example, if the product water conductivity increases from 20 μS/cm to 50 μS/cm before cleaning, it should decrease to the range of 25-35 μS/cm after cleaning.

III. Comprehensive Analysis Case Scenario:

A RO system designed for 10 bar feed pressure, 1.5 bar inter-stage pressure difference, 100 m³/h permeate flow, and 10 μS/cm permeate conductivity. Fouling occurred after operational period.

Pre- and Post-Cleaning Data Comparison (at identical water temperature and recovery rate):

Parameter Pre-flushing (Contaminated) Post-flushing (Stable Operation) Change Analysis Effect Assessment Feed Pressure (bar) 12.0 10.5 Decreased by 1.5 bar Significant effect; reduced membrane channel resistance Inter-stage Pressure Difference (bar) 3.2 1.8 Decreased by 1.4 bar Very significant effect; flow channel blockage greatly alleviated Product Water Flow Rate (m³/h) 75 95 Increased by 20 m³/h Significant effect; Membrane flux substantially restored.

Product water conductivity (μS/cm)

45 → 15

Decrease of 30 μS/cm

Significant effect, membrane desalination performance well restored.

Conclusion:

This chemical cleaning was highly successful. All key parameters showed substantial recovery in favorable directions, indicating the cleaning agent and protocol effectively removed contaminants from the membrane surface. (The above examples are for reference only.)

IV. Special Cases and Precautions

Possible causes for poor post-cleaning results:

Misdiagnosis of contamination type: Acid cleaning used for organic fouling, or alkaline cleaning used for inorganic scaling.

Inappropriate cleaning protocol: Insufficient chemical concentration, temperature, flow rate, or soak time.

Irreversible fouling: Membrane elements have undergone irreversible clogging (e.g., aging, colloidal silica hardening, severe biofouling).

Untimely cleaning: Contamination is too severe for conventional cleaning to restore performance.

Post-cleaning data deterioration scenarios:

Temporary conductivity increase: Residual cleaning agents or dissolved contaminants in membrane pores may cause transiently elevated product water conductivity initially. This typically normalizes after several hours or one day of operation.

Membrane damage: If cleaning parameters exceed manufacturer limits (e.g., pH, temperature) or prohibited chemicals (e.g., cationic surfactants) are used, permanent membrane damage may occur, resulting in irreversible desalination rate decline.

Standardized Data Mandatory:

During actual operation, feedwater temperature, salt content, and recovery rate fluctuate. It is strongly recommended to use the RO system's built-in standardization software or correct data to standard conditions (e.g., 25°C) before comparison. Failure to do so may distort analysis results. To summarize and analyze chemical cleaning effectiveness, follow these steps:

1. Collect Data: Accurately record key operating parameters before and after cleaning.

2. Normalize conditions: Compare data under identical feedwater temperature, salinity, and recovery rate whenever possible, or use standardized data.

3. Comparative analysis: Focus on “two decreases and one increase” (pressure drop, differential pressure drop, and water flow increase) and conductivity reduction.

4. Quantitative assessment: Calculate recovery rates for key parameters (especially permeate flow and differential pressure), targeting 80% or higher as a good benchmark.

5. Comprehensive Judgment: Integrate trends across all parameters to provide a holistic evaluation of cleaning effectiveness, informing optimization for subsequent cleaning protocols.

Through this systematic analysis, you can scientifically and accurately assess the true efficacy of each chemical cleaning cycle, thereby enhancing the maintenance of your reverse osmosis system.

Alright, the above outlines my perspective on analyzing data changes before and after chemical cleaning to assess its effectiveness in reverse osmosis systems. How do you typically evaluate the results of chemical cleaning during routine operations? Feel free to share your thoughts in the comments section!