Abstract Water and wastewater processing (cooling tower, heat exchanger, treatment, etc.) generate desirable or undesirable biofouling (mineral, organic, biological) which may affect equipment or process performances. Fouling magnitude and nature stand as critical parameters to be evaluated in-situ and on-line to control and optimize the operation (production, cleaning). A fouling sensor based on a Micro-Electro-Mechanical Systems (MEMS) structure generating a local in-situ periodic thermal excitation (PTR) was studied in order to quantify and qualify fouling. At lab scale, model deposit (PVC) were used to simulate fouling conditions. Limits of detection (LOD) and quantification (LOQ) under steady and periodic thermal regimes were compared. Transposition to industrial conditions was investigated at pilot-plant scale. A continuous bioprocess (PropellaTM reactor) was fed with diluted wastewater under controlled operating condition (temperature, mixing rate, flow rates, residence time) in order to mimic realistic industrial conditions and to generate a complex biofouling over six weeks. Thermal diffusivity, capacitive and resistive components are extracted from thermal spectrum response and a final fouling factor is introduced. Results demonstrate the ability to quantify and qualify a complex biofouling with in-situ and on-line information.

中文翻译：

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基于局部热和周期性激励的 MEMS 传感器在线生物污垢监测和鉴定

摘要 水和废水处理（冷却塔、热交换器、处理等）会产生可能影响设备或工艺性能的理想或不良生物污垢（矿物、有机、生物）。污染程度和性质是现场和在线评估的关键参数，以控制和优化操作（生产、清洁）。研究了基于微机电系统 (MEMS) 结构的污垢传感器，该结构可产生局部原位周期性热激发 (PTR)，以量化和限定污垢。在实验室规模，模型沉积物 (PVC) 用于模拟结垢条件。比较了稳定和周期性热状态下的检测限 (LOD) 和定量 (LOQ)。以中试规模研究了向工业条件的转移。连续生物工艺（PropellaTM 反应器）在受控操作条件（温度、混合速率、流速、停留时间）下加入稀释的废水，以模拟真实的工业条件并在六周内产生复杂的生物污垢。从热谱响应中提取热扩散率、电容和电阻分量，并引入最终的污染因子。结果证明了使用原位和在线信息量化和鉴定复杂生物污垢的能力。从热谱响应中提取电容和电阻分量，并引入最终污染因子。结果证明了使用原位和在线信息量化和鉴定复杂生物污垢的能力。从热谱响应中提取电容和电阻分量，并引入最终污染因子。结果证明了使用原位和在线信息量化和鉴定复杂生物污垢的能力。