A method of determining a fouling location of a shell and tube heat exchanger is provided. Under the method, a simulation model of the heat exchanger is partitioned into multiple segments. Each segment corresponds to a different one of multiple operating scenarios of the heat exchanger. For each operating scenario, temperature data and pressure drop data are generated from the simulation model of the heat exchanger. The fouling location of the heat exchanger corresponds to a respective segment in each of the multiple operating scenarios. The temperature data and the pressure drop data are classified based on the multiple segments of the simulation model by inputting the temperature data and the pressure drop data to one or more machine learning classification algorithms. The fouling location and a value of accumulated fouling at the fouling location are determined based on the classified temperature data and the classified pressure drop data.

A corrosive environment monitoring device that suppresses a decline in measurement precision in an initial period of monitoring the corrosivity of an environment and measures the corrosivity of the environment continuously and with high precision over a long period of time. The corrosive environment monitoring device includes: a layered body having an insulating plate, a base metal thin film that is formed on the insulating plate and is corrosion resistant with respect to a corrosive substance, and a sensing metal thin film that is formed on the base metal thin film and is corrosion susceptible with respect to the corrosive substance; and a housing that encloses the layered body, has an opening oriented in a side face direction, and forms a gas passage inside for the corrosive substance, wherein the sensing metal thin film is formed in a limited region on the base metal thin film.

Methods of detecting, quantifying and/or characterizing the fouling of a device from a combination of pressure and spectroscopic data are provided. The device can be any device containing components susceptible to fouling. Components can include membranes, pipes, or reactors. Suitable devices include membrane devices, heat exchangers, and chemical or bio-reactors. Membrane devices can include, for example, microfiltration devices, ultrafiltration devices, nanofiltration devices, reverse osmosis, forward osmosis, osmosis, reverse electrodialysis, electro-deionisation or membrane distillation devices. The methods can be applied to any type of membrane, including tubular, spiral, hollow fiber, flat sheet, and capillary membranes. The spectroscopic characterization can include measuring one or more of the absorption, fluorescence, or raman spectroscopic data of one or more foulants. The methods can allow for the early detection and/or characterization of fouling. The characterization can include determining the specific foulant(s) or type of foulant(s) present. The characterization of fouling can allow for the selection of an appropriate de-fouling method and timing.

A thermal sensor comprises an active element (41), e.g., a heater or cooler, at least one temperature sensor (31), and processing circuitry (50). The processing circuitry causes a change of power supplied to the active element (41). It then determines, at a plurality of times, a thermal parameter based on an output signal of the temperature sensors and analyzes the transient behavior of the thermal parameter. Based on this analysis, the processing circuitry determines a contamination signal that is indicative of a contamination on a sensing surface of the thermal sensor. If the thermal sensor comprises a plurality of temperature sensors arranged in different sectors of the sensing surface, a multi-sector thermal signal can be derived from the outputs of the sensors, and determination of the contamination signal can be based on the multi-sector thermal signal.

The following provides a system and method to predict an indicator of tube fouling in a fired apparatus such as a boiler. Historical data can be collected when the tubing is still considered to be clean, and used to build a first model between an indicator of fouling, such as tube skin temperature, and boiler load. The actual measurement of that indicator of fouling can then be compared against the model output, such that the error between the model and measurement is considered an indication of the tube fouling. Moreover, the rate of change of the model error can be used to measure the fouling rate. Next, historical data on the fluid feed quality can be collected and together with the historical error rate change data can be combined to develop a second model. This second model reflects how fluid feed quality variables may affect the fouling rate over time.

Calibration of a valve in a vacuum system and providing a diagnostic indication in the vacuum system using the calibration includes measuring conductance of the valve as a function of angular valve position and generating a conductance calibration map or function for use during operation of the valve. An actual angular valve position is set based on the received set point angular valve position and a difference between the measured valve conductance and a predefined metric of conductance versus angular valve position. An actual system conductance and a difference between the actual system conductance and a reference system conductance for the system are determined. The diagnostic indication of a fault in the system is generated based on the actual angular valve position of the valve and the difference between the actual system conductance and the reference system conductance for the system.

A method of controlling cooling water treatment may involve measuring operating data of one or more downstream heat exchangers that receive cooling water from the cooling tower. For example, the inlet and outlet temperatures of both the hot and cold streams of a downstream heat exchanger may be measured. Data from the streams passing through the heat exchanger may be used to determine a heat transfer efficiency for the heat exchanger. The heat transfer efficiency can be trended over a period of time and changes in the trend detected to identify cooling waterfouling issues. Multiple potential causes of the perceived fouling issues can be evaluated to determine a predicted cause. A chemical additive selected to reduce, eliminate, or otherwise control the cooling water fouling can be controlled based on the predicted cause of the fouling.

A method of measuring a flow line deposit comprising: providing a pipe comprising the flow line deposit; measuring unattenuated photon counts across the pipe; and analyzing the measured unattenuated photon counts to determine the thickness of the flow line deposit and associated systems.

The present invention relates to a method and device for detecting and analyzing deposits in liquid-bearing systems. More particularly, the device relates to being able to detect and analyze deposits in a liquid-bearing systems such as industrial plants that use and store fluids. The method relates to being able to determine a distribution of the run time of a detected ultrasonic reflection signal and analyzing the distribution to determine if deposits are deposited onto a heated reflecting area.

In one embodiment, the method begins by flowing a product stream through an upstream pipeline comprising a first product stream. The product stream is then continuously analyzed with an automated analyze to produce data. The first product stream downstream is then directed downstream of the automated analyzer to a downstream first product stream pipeline. The method then changes the product stream flowing through the upstream pipeline from the first product stream to a second product stream without purging the first product stream from the upstream pipeline, thereby creating a transmix product stream within the upstream pipeline wherein the transmix product stream comprises a mixture of the first product stream and the second product stream. The data from the automated analyzer is then analyzed with an automatic splitter, wherein the product stream flowing through the upstream pipeline no longer matches the physical and/or chemical characteristics of the first product stream. The automatic splitter then directs the transmix product stream downstream of the automatic splitter to a downstream transmix pipeline. As the data from the automated analyzer is still analyzed by the automatic splitter the product stream flowing through the upstream pipeline matches the physical and/or chemical characteristics of the second product stream. The automatic splitter then directs the second product stream downstream of the automatic splitter to a downstream second product stream pipeline.