Filter life determination

Abstract

Embodiments provide a method for determining filter life, comprising: introducing an aqueous sample into a filtration apparatus, the filtration apparatus comprising at least one filter and one or more sensors positioned upstream of the at least one filter, wherein the one or more sensors are capable of measuring a component of the aqueous sample; using the one or more sensors to measure the component of the aqueous sample; identifying a loading on the at least one filter based on the measurement of the component of the aqueous sample and at least one filtration characteristic; and determining a filter life of the at least one filter based on the identification. Other aspects are described and claimed.

Description

[0001] Case Analysis

[0002] This application is a divisional application of the invention patent application filed on November 30, 2021, with application number 202180081106.7 and invention title "Determining the Lifespan of a Filter".

[0003] Cross-references to related applications

[0004] This application claims priority to U.S. Patent Application No. 17 / 108,629, filed on December 1, 2020, entitled “FILTER LIFE DETERMINATION”, the contents of which are incorporated herein by reference. Technical Field

[0005] This application generally relates to determining the lifespan of a filter, and more specifically, to measuring the components in an aqueous sample and determining the filter lifespan. Background Technology

[0006] Ensuring water quality is crucial in many industries, such as drinking water, pharmaceuticals, industrial processes, and other manufacturing sectors. Additionally, ensuring water quality is essential for the health and well-being of humans, animals, and plants that depend on water for survival. One element commonly measured is chlorine. In industrial processes, excessive chlorine in water can damage turbines, heat exchangers, and other components. Chlorine can also damage filters in filtration systems. For example, chlorine can corrode materials in turbines, etc. Furthermore, when chlorine damages filters, they may fail to effectively remove dissolved solids or other components, leading to damage in turbines and heat exchangers. In other words, components may become coated, reducing heat transfer, generating friction, etc. Chlorine can be present from natural sources or human activities such as disinfection. Measuring and mitigating chlorine can lead to higher water treatment costs because chlorine can damage expensive equipment and shorten filter life. Therefore, detecting the presence and concentration of chlorine in water or other liquid solutions is essential. Summary of the Invention

[0007] In summary, one embodiment provides a method for determining filter life, comprising: introducing an aqueous sample into a filtration device including at least one filter and one or more sensors located upstream of the at least one filter, wherein the one or more sensors are capable of measuring the components of the aqueous sample; using the one or more sensors to measure the components of the aqueous sample; identifying the load on the at least one filter based on the measurement of the components of the aqueous sample and at least one filtration characteristic; and determining the filter life of the at least one filter based on the identification.

[0008] Another embodiment provides a measuring device for determining filter life, comprising: at least one filter; one or more sensors located upstream of the at least one filter; a processor; and a storage device storing instructions executable by the processor to: introduce an aqueous sample into the filtration device, the filtration device including at least one filter and one or more sensors located upstream of the at least one filter, wherein the one or more sensors are capable of measuring the components of the aqueous sample; using the one or more sensors to measure the components of the aqueous sample; identifying the load on the at least one filter based on the measurement of the components of the aqueous sample and at least one filtration characteristic; and determining the filter life of the at least one filter based on the identification.

[0009] Another embodiment provides a product for determining filter life, comprising: a storage device storing code executable by a processor, and including: code for introducing an aqueous sample into a filtration device including at least one filter and one or more sensors located upstream of the at least one filter, wherein the one or more sensors are capable of measuring the composition of the aqueous sample; code for measuring the composition of the aqueous sample; code for identifying the load on the at least one filter based on the measurement of the composition of the aqueous sample and at least one filtration characteristic; and code for determining the filter life of the at least one filter based on the identification.

[0010] The above is an overview and may therefore contain simplifications, generalizations and omissions of details; therefore, those skilled in the art will understand that the overview is illustrative only and is not intended to be limiting in any way.

[0011] To better understand the embodiments, as well as other and additional features and advantages of the embodiments, reference is made to the following description in conjunction with the accompanying drawings. The scope of the invention will be set forth in the appended claims. Attached Figure Description

[0012] Figure 1 A flowchart of an example filter lifetime determination system is shown.

[0013] Figure 2 A flowchart of an example operation for cumulative chlorine measurement is shown.

[0014] Figure 3 A flowchart of a sample cumulative chlorine data interface is shown.

[0015] Figure 4 Example data is shown for providing confidence levels for cumulative chlorine counters and extrapolated predictions.

[0016] Figure 5 An example of a computer circuit system is shown. Detailed Implementation

[0017] It will be readily understood that, in addition to the exemplary embodiments described herein, the components of the embodiments generally described and illustrated in the accompanying drawings can be arranged and designed in a variety of different configurations. Therefore, the more detailed description of the exemplary embodiments shown below is not intended to limit the scope of the claimed embodiments, but is merely illustrative of exemplary embodiments.

[0018] Throughout this specification, references to "an embodiment" or "an embodiment" (etc.) mean that a particular feature, structure, or characteristic described in connection with an embodiment is included in at least one embodiment. Therefore, phrases such as "in one embodiment" or "in an embodiment" appearing in various places throughout this specification do not necessarily all refer to the same embodiment.

[0019] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a complete understanding of the embodiments. However, those skilled in the art will recognize that various embodiments can be practiced without one or more of these specific details, or using other methods, components, materials, etc. In other instances, well-known structures, materials, or operations have not been shown or described in detail. The following description is intended only as an example and simply illustrates some exemplary embodiments.

[0020] Removing chlorine from water sources or water samples can be a crucial step in water filtration. For example, chlorine can be filtered for use in drinking water, the food / beverage industry, pharmaceuticals, and water supply for industrial processes. Improperly treated water supply for industrial processes can damage industrial installations. As another example, a user or entity may want the chlorine level in water to be below a specific threshold; therefore, the user can measure and filter or remove chlorine to determine if the amount is below that threshold. Chlorine can be naturally present in water bodies or can originate from human activities such as manufacturing, storage, or treatment conditions. Higher levels of chlorine can provide unpleasant odors, contaminate or degrade pipes or filters, interfere with measurements, and so on.

[0021] Filtration represents a significant cost for any facility. For example, a facility may have a large number of filters. Replacing filters involves the cost of the filters themselves, the manpower and time required for replacement, and the downtime. Replacing filters too early means they haven't reached their full filtration life. Replacing filters too late can result in poor performance, flow limitations, perforation, and malfunctions.

[0022] Conventional methods for determining filter lifespan may have the limitations discussed in this article. Conventional methods can be based on the length of time the filter has been used. For example, filter replacement logs or records can be written or entered. As another example, a facility may simply write the date on the filter when it was installed. The facility may have to visually inspect the filter, look for the service date on the filter, etc. Conventional methods present a “reactive” approach to filter lifespan. What is needed is a “proactive” approach that monitors the efficiency of the filter to determine when its lifespan has ended or is nearing its end.

[0023] Other facilities can wait for a failure to replace the filter. This may not allow for preventative maintenance of the filter. In the event of a failure, the facility may replace several filters that do not necessarily need replacement. This technique increases the cost, time, and inefficiency of the filtration system within the facility.

[0024] Industrial facilities, food / beverage, pharmaceutical, and water treatment industries require clean water for their processes. Some facilities use reverse osmosis (RO) filters in their filter arrays, which can cost approximately $50,000 to $200,000. Facilities may purchase filters or have contracts for filter replacement. A facility's profitability can be based on the projected lifespan of the RO membrane and the associated costs of the filter, as well as the man-hours required for filter replacement / maintenance. For example, before replacement, an RO membrane can be assessed for 1,000 ppm-hrs (parts per million-hours) of chlorine exposure. This example would be an expected continuous chlorine exposure of approximately 38 ppb (parts per billion) over 3 years. For simplicity, this disclosure may use the term "filter" to refer to a unit that may include a membrane and other associated components for filtering aqueous samples.

[0025] Therefore, facilities can filter water using expensive membrane modules via reverse osmosis. Facilities can plan and budget for membrane use for approximately 3 years, although this timeframe may vary based on filter and conditions. Membranes can deteriorate for several reasons, with chemical corrosion by chlorine being a primary cause. Membrane manufacturers can rate membranes for 1,000 ppm-hrs of chlorine contact, which may vary based on filtration conditions. For example, this could be equivalent to continuous flow through the membrane over 3 years at an average of 38 ppb (parts per billion) or 0.038 ppm (parts per million). This example falls within the realm of ultra-low chlorine levels.

[0026] Currently, there is no reliable method for continuously measuring ultra-low levels of chlorine exposure. Because low levels may be unmeasurable, facilities may overuse sodium bisulfite to remove chlorine. Overuse of sodium bisulfite can damage filter membranes and lead to premature failure. In this embodiment, an ultra-low chlorine analyzer capable of measuring chlorine in the range of 38 ppb can be used to measure the components. For example, by multiplying each measurement result by the product of the measurement intervals and then summing them, a reasonable estimate of the magnitude of the chlorine exposure experienced by the membrane in ppm-hrs can be determined. This can provide a leading indicator to the facility if the membrane continues as planned for the expected time. The measurement interval can be selected as a time “snapshot” associated with filter use or the entire filter lifecycle.

[0027] Reverse osmosis (RO) filters can remove dissolved solids from aqueous samples. Chlorine can be removed from the water upstream of the filter because it can damage the membrane in the RO system by increasing the size of the pores in the filter. Chlorine can be measured as a component in an aqueous sample and may not be physically filtered out of the water. Chlorine can be removed by chemically binding chlorine to carbon, reacting chlorine with sodium bisulfite, or other methods. In this way, the measured component, such as chlorine, may be different from the component filtered by the RO system, but the portion of chlorine that passes through the filter can degrade the filter by enlarging the pores to allow more dissolved solids to pass through. The systems and methods described herein can protect expensive industrial components or parts, such as turbines, heat exchangers, etc.

[0028] Therefore, embodiments provide systems and methods for determining the filter life of a filtration device. This determination can be similar to an estimate of filter life; however, the determination may take into account additional parameters discussed herein. In embodiments, filter life may be the remaining filter life. In embodiments, the method and system may have one or more sensors. The one or more sensors may be located upstream of at least one filter. The one or more sensors may measure a component in an aqueous sample. This component may be chlorine. At least one filter may filter this component or another component from the aqueous sample. The method and system may measure the component and / or filtration characteristics to identify the load on the filter. In embodiments, the system and method may determine filter life. In embodiments, filter life may be determined by calculating the accumulated chlorine through the filter or membrane. In another embodiment, the system and method may extrapolate trends to predict or determine when the filter will reach the end of its life. In yet another embodiment, the system and method may monitor the consistency of data to provide a confidence level for the prediction or determination of filter life. In embodiments, a user or system may select a time period for determining filter life. The determined filter life may be compared to an expected filter life. In embodiments, a notification or alarm may indicate that the filter is approaching or has reached its usable time limit. In an embodiment, a notification or alarm may indicate that the cumulative chlorine limit has been reached, is approaching, or has been exceeded.

[0029] The illustrated exemplary embodiments will be best understood by referring to the accompanying drawings. The following description is intended to be illustrative only and simply illustrates some exemplary embodiments.

[0030] refer to Figure 1 An example system and method for determining filter life are shown. The filtration device may have one or more filters. The filter can filter a measured component or another component from an aqueous sample. In an embodiment, the component may be chlorine. In an embodiment, the filtration device may have at least one filter. The filtration device may have one or more sensors. The aqueous sample may be a fluid such as drinking water, a fluid for food / beverage, a pharmaceutical product, or feedwater for industrial process water.

[0031] At point 101, in an embodiment, an aqueous sample may be introduced into the filtration device. The aqueous sample may contain a certain amount of a component. In an embodiment, the component may be chlorine. The component may be another substance; chlorine is used as an example for simplicity of this disclosure. The filtration device may have at least one filter capable of filtering the component or another component from the aqueous sample. The filtration device may have one or more sensors. The one or more sensors may be capable of measuring the components of the aqueous sample. The one or more sensors may be located upstream of or before at least one filter. In this way, the sensors can measure the components passing through at least one filter.

[0032] The aqueous sample can be a sample from a natural water body, storage tank, treatment tank, pipeline, etc. The aqueous sample can be a continuous flow, a fixed volume of liquid, or any combination thereof. In one embodiment, the solution can be introduced into one or more chambers, containers, or pipelines, such as the measurement chamber of a filtration device. Introducing the aqueous sample into the filtration device can include placing or introducing the solution into the filtration device manually or mechanically (e.g., gravity flow, pump, pressure, fluid flow, etc.). For example, a pump can be used to introduce a water sample for filtration into a measurement chamber or test chamber. In embodiments, valves, etc., can control the flow of the solution into or out of one or more chambers, containers, or pipelines (if present).

[0033] Additionally or alternatively, the filtration device may be present in or introduced into a volume of aqueous sample. The filtration device is then exposed to that volume of aqueous sample. The system and associated measurements may be an automated flow system for mixing and measuring solutions and / or reagents. Once the sample comes into contact with the filtration or measurement system, the system can measure the components of the sample, as discussed in further detail herein. In embodiments, the filtration or measurement device may include one or more chambers in which one or more method steps may be performed.

[0034] At point 102, in an embodiment, the method and system can measure the components of an aqueous sample. This measurement can be performed by one or more sensors. The sensors can be capable of measuring components in the aqueous sample. In an embodiment, the component being measured can be chlorine. Other components, such as dissolved solids, can be measured and disclosed. The measurement of the component can be performed by one or more sensors capable of measuring that component or another component filtered by at least one filter.

[0035] The measurement of chlorine can be performed using various methods. For example, one or more sensors may be components or parts of a colorimeter, ammeter, optical, or similar system. The measurement may be a measurement of free chlorine or total chlorine. The measurement can be performed using the method described in U.S. Patent Application No. 16 / 433,752, filed June 6, 2019, entitled “ULTRA LOW RANGE FREE CHLORIDE MEASUREMENT,” the entire contents of which are incorporated herein by reference. Briefly, the described system and method can measure ultra-low range (ULR) concentrations of chlorine under ambient conditions with improved reagent stability. In embodiments, the method may not use conventional DPD chemistry. In embodiments, the method can detect free chlorine at concentrations below 20 parts per billion (ppb) and can produce accurate concentration measurements of free chlorine down to or below 1 ppb. In embodiments, the method may use fluorescence. The indicator that provides the fluorescent signal may be a thiocarbamate derivative. The thiocarbamate derivative may be a coumarin-based fluorophore. The thiocarbamate-based indicator could be methyl umbelliferone thiocarbamate. In the examples, the fluorescence intensity can be correlated with the detection of ULR in free chlorine. In the examples, the pH of the solution can be adjusted to activate the reporter molecule or indicator molecule.

[0036] This system and method can determine whether the concentration of free chlorine can be measured. In an example, the presence of free chlorine in an aqueous solution can lead to an increase in the fluorescence intensity of a thiocarbamate-based indicator. In an example, the thiocarbamate derivative can be selective for free chlorine and react with free chlorine in an aqueous environment to release fluorescently active molecules. Therefore, the fluorescence intensity of a solution containing free chlorine can be correlated with the concentration of free chlorine in the aqueous solution. Fluorescence curves can be generated for a range of free chlorine concentrations, for different thiocarbamate-based indicators, and for any different conditions that can affect the absorption or fluorescence value (e.g., temperature, sample content, turbidity, viscosity, measuring device, aqueous sample chamber, etc.).

[0037] Alternatively or additionally, free chlorine concentration can be measured at user-defined periodic intervals or at pre-programmed frequencies within the device. Measuring free chlorine via the device allows for real-time data acquisition with minimal human intervention during the measurement process. Cleaning of the fluorescence chamber may be required at unspecified time intervals. Programmed calibration curves can be input into the device.

[0038] Chambers, containers, units, rooms, pipes, etc., may contain an aqueous sample, at least one thiocarbamate-based indicator, and associated reagents (e.g., buffers and / or additives). The device may include one or more reagent bottles containing the necessary reagents. The reagents contained in the one or more bottles may be pump-supplyed or gravity-supplyed. The flow rate of the reagents can be metered to ensure an appropriate volume is delivered to the measuring unit. The aqueous sample may be supplied via a pressurized inlet, container, etc. The aqueous sample may be introduced into the measuring chamber by pump or gravity supply. The sampling device may be connected in series or parallel with the water flow. The device may have a system to ensure proper mixing of the aqueous sample with, as an example, the thiocarbamate-based indicator and associated reagents.

[0039] Fluorescence intensity or free chlorine concentration can be output on the device in the form of display, printing, storage, audio, haptic feedback, etc. Alternatively or additionally, this output can be transmitted to another device via wired, wireless, fiber optic, Bluetooth®, near-field communication, etc. Examples can use alarms to warn of measurement results or concentrations outside acceptable levels. Examples can use the system to shut off water output or divert water from sources with unacceptable component levels. For example, component measurement devices or sensors can use relays coupled to electrically actuated valves, etc.

[0040] At point 103, in an embodiment, the system and method can identify the load on at least one filter. This identification can be based on measurements of components in an aqueous sample. The identification can be based on at least one filtration characteristic. Filtration characteristics can be registered or recorded to the system. Filtration characteristics may include time, date, filter service length, manufacturer-expected filter life, filtration pressure, volume, initial concentration of the filtered component in the aqueous sample, filter type, filter media, filter size, filter efficiency, number of filters in a larger filtration unit, temperature, aqueous sample content, turbidity, viscosity, etc. In an embodiment, the method and system can use one or a combination of filtration characteristics to determine filter life. In an embodiment, measuring components and / or using filtration characteristics can determine the “load” on the filter. Filtration characteristics include any data related to the filtration of said component or another component in the system. In an embodiment, filtration characteristics can be used in combination with component measurements to determine filter life.

[0041] At 104, in an embodiment, the system and method can determine the filter life of at least one filter based on this identification. In an embodiment, the filter life can be determined based on measurements of components and / or filtration characteristics. For example, the system and method can use measurements of components in an aqueous sample and can combine the filtration characteristics described herein to predict or determine filter life. The facility can use filter banks. Filter life can be determined for filter banks, subsets of filter banks, individual filters, etc. In an embodiment, the aqueous sample can be a homogeneous sample in which one or more sensors can be placed upstream of all filters or only upstream of a subset of filters. The system and method can be able to distinguish filtration zones even when the aqueous sample is heterogeneous. The system and method can use different methods to determine filter life.

[0042] In an embodiment, filter life can be determined by calculating the accumulated chlorine through the filter or membrane. See also Figure 2 In other words, the system and method can keep track of the total amount of components, such as chlorine, passing through a filter over time. The time period can be set by the user or the system. This time period can be the entire time the filter has been used, a snapshot of time, or any length of time. For example, the user or the system can set a start date and time. The start point could be when the filter is installed, when a specific batch of aqueous samples is run through the filter, or when the system is reset by the user or system, etc. The system can then calculate incremental exposure. For example, the system can multiply the measured component concentration by a constant. Specifically, for a filter with a projected lifespan of 3 years, the system can multiply the concentration in ppm by 0.0417 hours. The system can then add each incremental value to the sum of exposures from the start date and the time following each measurement cycle. In other words, the method and system keep track of the cumulative amount of components filtered by the filter or exposed to the filter over time. See also Figure 3 An increase in the measured amount of a component can shorten the filter's lifespan. Conversely, a decrease in the measured amount of a component can increase the filter's lifespan. In an embodiment, an alarm or warning may indicate that the filter is approaching or has reached the end of its expected lifespan.

[0043] In another embodiment, the system and method can extrapolate trends to predict or determine when the filter will reach the end of its lifespan. For example, the system can plot component concentrations over time or measurement periods. A trend can be fitted to this plot. In one embodiment, a simple linear extrapolation can be used, employing a slope from a start date / time to the current date / time. This method can be most useful if an aqueous sample containing the component maintains a similar component concentration over filtration time. In another embodiment, nonlinear extrapolation can be used to fit the plot. This method can be useful when component concentrations vary over filtration time. The extrapolation can be used to determine how much of the filter's lifespan has been used and the expected time to the end of the filter's lifespan.

[0044] Extrapolation can be performed on cumulative values ​​to determine when a membrane might reach, for example, a limit of 1000 ppm-hrs. The system can predict the date when a facility will need to replace / maintain its membrane. This extrapolation can be based on trends from the installation date to the present, only the most recent X months, only the last month, etc. The user or system can switch between different alternatives or monitor multiple alternatives to see how the predicted end date changes. This can have the added benefit of allowing facilities moving towards earlier filter or membrane replacement to see how recent improvements (through reductions in chlorine in the membrane) can alter their anticipated replacement date, not only in terms of the predicted replacement date. The system can help determine how recent spikes may have shortened the expected lifespan. Based on trends over a selected time period, the extrapolation can be a simple linear addition of the currently known cumulative sum of chlorine ppm-hrs. Additionally, a second-order polynomial can be adapted to more accurately determine filter lifespan. Other mathematical fits to the data curves are available and publicly available.

[0045] In yet another embodiment, the system and method can monitor data consistency to provide a predicted or determined confidence level for filter lifetime. See also Figure 4 For example, the measured component concentrations can be plotted over time. For a given plot, the standard deviation of the plot can be used to determine a confidence score. As an example, a plot with a high standard deviation can produce a low confidence score. As another example, a low standard deviation can produce a high confidence score. In other words, because the component amount varies over a given time, a large change in component concentration gives a lower confidence level in determining filter life. Conversely, because the component amount remains more consistent over time, a small change or no change in component concentration gives a higher confidence level in determining filter life.

[0046] At point 105, in this embodiment, if the filter lifespan cannot be determined, the system can continue measuring the composition of the aqueous sample. Alternatively or additionally, the system can output alarms, register events, etc. If the filter lifespan can be determined, at point 106, the system can provide a filter lifespan determination. The filter lifespan determination can be provided to the device as an output in the form of display, printing, storage, audio, haptic feedback, etc. Alternatively or additionally, this output can be transmitted to another device via wired, wireless, fiber optic, Bluetooth®, near-field communication, etc.

[0047] Examples can use alarms to warn of measurement results or determinations outside acceptable levels. Examples can use systems to shut off water output or divert water from sources with unacceptable remaining filter life. For example, the device can use relays coupled to electrically actuated valves. The system can connect to a communication network. The system can alert a user or network. The alert can occur regardless of whether filter life is determined. The alert can take the form of audio, visual, data, data stored in a storage device, output sent via a connected system or wireless system, printout, etc. The system can register information such as measurement location, calibration action, geographic location, time, date, number of measurement cycles, etc. The alert or registration can be automatic, meaning the system can automatically output whether calibration is needed. The system can also have associated alarms, limits, or predetermined thresholds. For example, if filter life reaches a threshold or set point, an alarm or log can be analyzed in real time, stored for later use, or any combination thereof. For example, an alarm can indicate that the current concentration of a component is higher than a desired threshold.

[0048] The various embodiments described herein represent a technical improvement over conventional methods for determining filter life. Using the techniques described herein, embodiments can employ systems and methods to measure ultra-low range concentrations of components in aqueous samples to determine filter life.

[0049] While various other circuits, circuit systems, or components can be utilized in information processing devices, the instrument for determining filter life according to any of the various embodiments described herein... Figure 5An example is shown. Device circuitry 10' may include a measurement system on a chip design basis (e.g., a specific computing platform (e.g., mobile computing, desktop computing, etc.)). Software and processor are combined in a single chip 11'. The processor includes internal arithmetic units, registers, cache memory, buses, I / O ports, etc., as are known in the art. Internal buses, etc., vary depending on the vendor, but essentially all peripherals (12') can be attached to a single chip 11'. Circuitry 10' combines the processor, memory control, and I / O controller hub all into a single chip 11'. Furthermore, this type of system 10' typically does not use SATA, PCI, or LPC. For example, common interfaces include SDIO and I2C.

[0050] A power management chip 13' (e.g., a battery management unit, BMU) is present, which manages power supplied, for example, via a rechargeable battery 14', which can be charged by connection to a power source (not shown). In at least one design, a single chip such as 11' is used to provide BIOS-like functionality and DRAM memory.

[0051] System 10' typically includes one or more of a WWAN transceiver 15' and a WLAN transceiver 16' for connecting to various networks such as telecommunications networks and wireless internet devices (e.g., access points). Additionally, it typically includes devices 12', such as transmitting and receiving antennas, oscillators, PLLs, etc. System 10' includes input / output devices 17' for data input and display / rendering (e.g., located in a user-accessible computing location away from the single-beam system). System 10' also typically includes various storage devices, such as flash memory 18' and SDRAM 19'.

[0052] As understood from the foregoing, the electronic components of one or more systems or devices may include, but are not limited to, at least one processing unit, memory, and a communication bus or communication method coupling various components, including memory, to the processing unit. The system or device may include or access various device-readable media. System memory may include device-readable storage media in the form of volatile and / or non-volatile memory, such as read-only memory (ROM) and / or random access memory (RAM). By way of example and not limitation, system memory may also include an operating system, application programs, other program modules, and program data. The disclosed system may be used in embodiments to perform filter lifetime determination.

[0053] As those skilled in the art will understand, the aspects may be embodied as a system, method, or device program product. Therefore, the aspects may take the form of a fully hardware embodiment or an embodiment including software, which may be collectively referred to herein as a “circuit,” “module,” or “system.” Furthermore, the aspects may take the form of a device program product embodied in one or more device-readable media having device-readable program code embodied therein.

[0054] It should be noted that the various functions described herein can be implemented using instructions stored on a device-readable storage medium, such as a non-signal storage device, which are executed by a processor. In the context of this document, storage devices are not signals, and "non-transitory" includes all media except signal media.

[0055] Program code for performing operations can be written using any combination of one or more programming languages. The program code can execute entirely on a single device, partially on a single device, as a standalone software package, partially on one device and partially on another, or entirely on other devices. In some cases, devices can be connected via any type of connection or network, including local area networks (LANs) or wide area networks (WANs), or via other devices (e.g., through the internet provided by an internet service provider), via wireless connections (e.g., near-field communication), or via hard-wired connections (e.g., via USB connections).

[0056] Example embodiments are described herein with reference to the accompanying drawings, which illustrate example methods, apparatuses, and products according to various example embodiments. It should be understood that these actions and functions can be implemented, at least in part, via program instructions. These program instructions can be provided to the processor of a device (e.g., a handheld measuring device or other programmable data processing device for generating machines) such that the instructions, executed via the device's processor, perform the specified functions / actions.

[0057] Note that the values ​​provided herein should be interpreted to include equivalent values ​​as indicated by the use of the term "about". Such equivalent values ​​will be obvious to those skilled in the art, but include at least the values ​​obtained by ordinary rounding of the last significant number.

[0058] This disclosure has been presented for purposes of illustration and description, but is not intended to be exhaustive or limited to. Many modifications and variations will be apparent to those skilled in the art. Example embodiments have been chosen and described to explain the principles and practical applications, and to enable those skilled in the art to understand various embodiments of this disclosure with various modifications suitable for the particular intended use.

[0059] Therefore, although illustrative example embodiments have been described herein with reference to the accompanying drawings, it should be understood that the description is not limited and various other changes and modifications can be made therein by those skilled in the art without departing from the scope or spirit of this disclosure.

Claims

1. A method for determining filter life, comprising: An aqueous sample and a thiocarbamate-based indicator are introduced into a filtration device, the filtration device comprising at least one filter and one or more sensors located upstream of the at least one filter, wherein the one or more sensors are capable of measuring the components of the aqueous sample, and wherein the components include free chlorine; The one or more sensors are used to measure the components of the aqueous sample, wherein the one or more sensors include a fluorescence sensor, wherein the fluorescence sensor measures the fluorescence intensity of the thiocarbamate-based indicator as it flows through the at least one filter with the aqueous sample, without the addition of an additive that converts monochloramine into a substance capable of activating the thiocarbamate-based indicator, and wherein the fluorescence intensity is correlated with the concentration of free chlorine in the aqueous sample; The load on the at least one filter is identified based on the measurements of the components of the aqueous sample and at least one filtration characteristic; and The filter lifespan of the at least one filter is determined based on the identification. The method further includes: plotting the component concentration over time and fitting a trend to the plotted value. The method further includes: extrapolating the trend to predict or determine when the at least one filter reaches the end of its lifespan, wherein the extrapolation is a linear extrapolation or a nonlinear extrapolation.

2. The method according to claim 1, wherein, The measured components were associated with the deterioration of at least one filter.

3. The method according to claim 1, wherein, The determination also includes the known expected lifespan of the filter.

4. The method according to claim 1, wherein, The at least one filtering feature includes a time period, wherein the time period corresponds to the time during which the filter is used.

5. The method according to claim 1, wherein, The at least one filtration feature includes a cumulative counter, wherein the cumulative counter corresponds to the total amount of the component passing through the at least one filter.

6. The method according to claim 1, wherein the determination further comprises: Assign a confidence score to the filter lifetime.

7. The method according to claim 1, further comprising: The filter lifespan is determined based on a user-selected time range.

8. The method according to claim 1, wherein, The aqueous samples include feedwater from industrial processes.

9. A measuring device for determining filter life, comprising: At least one filter; One or more sensors located upstream of the at least one filter; processor; as well as A storage device that stores instructions executable by the processor, such that: An aqueous sample and a thiocarbamate-based indicator are introduced into a filtration device, the filtration device including at least one filter and one or more sensors located upstream of the at least one filter, wherein the one or more sensors are capable of measuring the components of the aqueous sample, and wherein the components include free chlorine; The one or more sensors are used to measure the components of the aqueous sample, wherein the one or more sensors include a fluorescence sensor configured to directly measure free chlorine without the need for a monochloramine conversion additive, wherein the fluorescence sensor measures the fluorescence intensity of the thiocarbamate-based indicator as it flows through the at least one filter with the aqueous sample, and wherein the fluorescence intensity is correlated with the concentration of free chlorine in the aqueous sample. The load on the at least one filter is identified based on the measurements of the components of the aqueous sample and at least one filtration characteristic; and The filter lifespan of the at least one filter is determined based on the identification. The storage device also stores instructions executable by the processor to: plot component concentrations over time and fit a trend to the plot. The storage device also stores instructions executable by the processor to: extrapolate the trend to predict or determine when the at least one filter reaches the end of its lifetime, wherein the extrapolation is a linear extrapolation or a nonlinear extrapolation.

10. The device according to claim 9, wherein, The measured components were associated with the deterioration of at least one filter.

11. The device according to claim 9, wherein, The determination also includes the known expected lifespan of the filter.

12. The device according to claim 9, wherein, The at least one filtering feature includes a time period, wherein the time period corresponds to the time during which the filter is used.

13. The device according to claim 9, wherein, The at least one filtration feature includes a cumulative counter, wherein the cumulative counter corresponds to the total amount of the component passing through the at least one filter.

14. The device according to claim 9, wherein the determination further includes: Assign a confidence score to the filter lifetime.

15. The device according to claim 9, further comprising: The filter lifespan is determined based on a user-selected time range.

16. A product for determining filter life, comprising: A storage device storing code that can be executed by a processor, and comprising: Code for introducing an aqueous sample and a thiocarbamate-based indicator into a filtration device, the filtration device comprising at least one filter and one or more sensors located upstream of the at least one filter, wherein the one or more sensors are capable of measuring the components of the aqueous sample, and wherein the components include free chlorine; The code for measuring the components of the aqueous sample, wherein the one or more sensors include a fluorescence sensor configured to directly measure free chlorine without the need for a monochloramine conversion additive, wherein the fluorescence sensor measures the fluorescence intensity of the thiocarbamate-based indicator as it flows through the at least one filter with the aqueous sample, and wherein the fluorescence intensity is correlated with the concentration of free chlorine in the aqueous sample; A code identifying the load on the at least one filter based on the measurements of the components of the aqueous sample and at least one filtration characteristic; and The code that determines the filter lifespan of the at least one filter based on the identification. The code also includes code for plotting component concentrations over time and fitting trends to the plotted values. The code also includes: code for extrapolating the trend to predict or determine when the at least one filter reaches the end of its lifetime, wherein the extrapolation is a linear extrapolation or a nonlinear extrapolation.

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