Methods for monitoring the condition of piping systems for buildup, wear, or corrosion damage.

Abstract

This invention relates to a method for monitoring the condition within a piping system regarding accumulation, wear, or corrosion damage. It includes: installing a measuring device susceptible to damage corresponding to the condition within the piping system and measuring variables indicating damage; at least two variables exhibiting different dependencies on the damage; continuously recording data, including time series of variable measurements; determining a dynamic reference state of the variables based on training data in the data, corresponding to a time-related distribution of expected variable values ​​when the measuring device is undamaged; repeatedly determining the deviation between the monitoring state and the reference state of the variable measurements; and, based on the deviation, determining and providing monitoring results by at least one of the following, at least once or repeatedly: a) detecting damage when the deviation exceeds a first deviation range, and b) determining the remaining time until the degree of damage exceeds a predetermined limit by predicting a time series of the remaining time until the deviation exceeds a second deviation range corresponding to a predetermined limit.

Description

Technical Field

[0001] The present invention relates to a method for monitoring the dominant condition within a piping system caused by buildup, wear, or corrosion resulting from one or more fluids flowing through a piping system comprising at least one pipe. Background Technology

[0002] Piping systems are used in various types of industries, such as the food and beverage industry, the chemical industry, and the oil and gas industry, to transport various types of fluids (e.g., liquids or gases) from one location to another. As an example, they are used in industrial plants or facilities that perform production processes.

[0003] During the operation of a piping system, its inner surfaces are exposed to one or more fluids flowing through the system. Due to this exposure, damage to the dominant condition within the piping system can develop over time due to buildup, abrasion, or corrosion. Buildup is caused by deposits of fluids that tend to adhere to one or more surfaces exposed to these fluids. The buildup layer that forms inside the pipe reduces its inner diameter, thereby increasing flow resistance. Continuously growing buildup layers can eventually lead to pipe blockage. Countermeasures include, for example, regular pipe cleaning. Abrasion is caused by abrasive fluids (e.g., fluids containing sand or other abrasive particles). Corrosion is caused by corrosive fluids (e.g., salt or acidic liquids) that corrode surfaces exposed to these fluids. Abrasion and corrosion reduce the wall thickness of pipes, thereby reducing their mechanical stability. Therefore, pipes exposed to corrosive or abrasive fluids should be replaced periodically. Cleaning and replacement of pipes incurs costs and often requires interrupting processes performed on-site, including the piping system.

[0004] Because visual inspection of the dominant conditions within a piping system is typically impossible during operation, the intervals between continuous cleaning or replacement should be kept short to ensure safe operation. Consequently, these intervals are often performed well in advance of the actual conditions of the piping system. However, applying longer intervals can result in cleaning or replacement being performed too late. This can have serious consequences regarding the safety and operability of the piping system, potentially causing harm to people and / or the environment, leading to high additional costs and / or prolonged downtime. Therefore, in industry, it is necessary to monitor the dominant conditions within the piping system during operation, for example, by optimizing the intervals between continuous cleaning or replacement.

[0005] In many applications, piping systems are equipped with measuring devices that measure the physical and / or chemical properties of one or more fluids, and / or process parameters required to regulate and / or control processes performed in the field, including the piping system. Many of these measuring devices are susceptible to damage due to buildup, wear, or corrosion, which can negatively impact their measuring properties.

[0006] Examples include vibration measurement devices, such as density measuring devices, which measure the density of a fluid based on the resonant frequency of an oscillating element immersed in the fluid, and level switches, which monitor whether the fluid level exceeds a predetermined level corresponding to the position of the level switch based on changes in the resonant frequency of the oscillating element that occur when it is immersed in the fluid. Deposits on the oscillating element enhance the oscillation mass and thus reduce the frequency, while corrosion or wear of the oscillating element reduces the oscillation mass and thus increases the frequency. Therefore, changes in oscillation mass caused by deposits, corrosion, or wear impair the measurement and / or monitoring capabilities of the vibration measurement device.

[0007] This problem is addressed in US 7,665,357B2, which describes a vibrating device designed to issue a buildup alarm when the oscillation frequency of an oscillating element drops below an adjustable limit, the adjustable limit being determined based on the dependence of the oscillation frequency on process conditions and / or process variables to be monitored and / or determined by the vibrating device. DE 102017102550 A1 describes a method for detecting corrosion or buildup on an oscillating element based on its resonant frequency.

[0008] Another example is a Coriolis measuring device, which includes a tube connected to or inserted into a pipe, such that at least a portion of one or more fluids flowing through the pipe system passes through the tube, and a drive system for vibrating the tube. Coriolis measuring devices are used, for example, to measure the flow rate through a pipe based on the phase difference between vibrations occurring near the inlet and outlet of the pipe during vibration. Furthermore, the density of the fluid can be measured based on the resonant frequency of the tube, and the viscosity of the fluid can be determined based on the power required to vibrate the tube. As with the previous examples, variations in the oscillatory quality of the tube caused by buildup, corrosion, or wear impair the measuring capability of the Coriolis measuring device.

[0009] In this context, DE 102005050898 A1 describes a method for detecting buildup inside a straight pipe of a Coriolis measuring device by at least temporarily exciting torsional vibration of the straight pipe and detecting buildup based on the frequency of the torsional vibration. DE 102005050898 A1 further discloses the use of this buildup detection method to monitor the condition within a pipe connected to a Coriolis measuring device relative to the predominance of damage caused by buildup.

[0010] WO 2014 / 056709 A1 describes a system for measuring the volumetric flow rate of fluid flowing through a pipe. In one embodiment, the system includes two vibrating elements, such as a pipe connected to the pipe through which at least some fluid flows, and an oscillating element immersed in the fluid. The system can operate in a self-diagnostic mode, wherein when the difference between the resonant frequencies of the two vibrating elements exceeds a predetermined limit, the system issues an alarm indicating irreversible damage to at least one of the two vibrating elements due to wear, corrosion, plastic deformation, or fracture. Furthermore, when the deviation between the average power of the drive signals causing the vibrating elements to vibrate exceeds a given limit, the system, for example, issues an alarm indicating irreversible damage to at least one of the two vibrating elements due to wear, corrosion, plastic deformation, or fracture.

[0011] US 8,046,194 B2 describes a magnetic induction flow meter that measures the flow rate of a fluid based on the voltage induced between measuring electrodes by the fluid flowing through the measuring tube during the application of a magnetic field. The flow meter is further configured to determine the conductivity of the fluid and / or the surface variation of the measuring electrodes based on the impedance measured between the measuring electrodes and a reference electrode.

[0012] DE 102009002539 A1 describes a magnetic induction flowmeter configured to measure the conductivity of a fluid flowing through its measuring tube, which can be used to detect conductive deposits formed within the measuring tube.

[0013] Damage to measuring equipment caused by buildup, corrosion, or wear is due to their exposure to one or more fluids. Therefore, variables measured by measuring equipment suitable for detecting damage are at least partially affected by other influencing factors. These factors include, for example, the density, viscosity, flow rate, conductivity, and / or other properties of the fluid(s), the pressure and / or temperature to which the measuring equipment is exposed, and / or other influencing factors, such as those associated with dynamic processes performed at the measurement site. Each of these factors makes it more difficult to distinguish between changes in variables caused by damage and changes in variables caused by other influencing factors. Therefore, the extent of damage must exceed a certain size before damage can be detected based on variables. Regarding influencing factors that can be measured by the measuring equipment, some improvements can be obtained by applying compensation methods. As an example, DE 102005050898 A1 described above describes a method for compensating for the dependence of the frequency of torsional vibration on the density and / or viscosity of the fluid based on the density and / or viscosity measured by a Coriolis measuring device during lateral vibration of a straight pipe. Nevertheless, numerous influencing factors remain that affect the variables being measured to detect damage. These factors cannot be eliminated, for example, because they are unknown and / or because their measurement is impossible or unavailable. Therefore, the influence of these factors on the variables being measured reduces the ability of the detection method to detect minor damage and may also lead to a large number of false detections. Summary of the Invention

[0014] Therefore, the object of the present invention is to provide a method for monitoring the dominant condition within a pipeline system during operation, the method exhibiting improved detection capability, particularly regarding the detection of damage at an early stage when the degree of damage is small, and / or regarding the reliability of the detection.

[0015] Therefore, the present invention includes a method, particularly a computer-implemented method, for monitoring the dominant condition within a piping system comprising at least one pipe, regarding damage caused by deposits, abrasion, or corrosion resulting from one or more fluids flowing through the piping system; the method includes the following steps:

[0016] At least two measuring devices are installed on the piping system; wherein each measuring device is configured to measure one or more variables indicating the damage, for different types of damage corresponding to the predominant condition within the piping system; and wherein the variables measured by the different measuring devices include at least two or at least three variables, each exhibiting a different dependence on the damage.

[0017] During the operation of the piping system, data is continuously recorded, including a time series of measured values ​​of variables measured by the measuring device and the time of measurement.

[0018] Based on training data included in the data, a dynamic reference state of the variable is determined, which corresponds to the time-related distribution of the expected variable values ​​when the measuring device is undamaged;

[0019] Repeatedly determine the deviation between the monitored behavior and the reference behavior, corresponding to the time-related distribution of the measured values ​​of the variables determined based on data recorded during the monitoring period; and

[0020] Based on the deviation, the monitoring results are determined and provided at least once or repeatedly by performing at least one of the following:

[0021] a) When the deviation exceeds a first deviation range, detect the damage and provide an output notifying the damage.

[0022] b) By performing time series forecasting to predict the remaining time until the deviation exceeds a second deviation range corresponding to a predetermined limit and providing an output indicating the remaining time given by or corresponding to the time predicted by the time series forecast, the remaining time until the degree of damage to the dominant condition within the pipeline system exceeds the predetermined limit is determined.

[0023] Monitoring conditions based on variables measured by different types of measuring devices offers the following advantages: each device is affected by corrosion, wear, or buildup in different ways. Variables exhibiting varying dependencies on damage offer the advantage of covering a correspondingly wide range of damage effects, which in turn makes it possible to detect damage based on each of these different effects.

[0024] Dynamic reference states offer the following advantages: they constitute an application-specific characteristic of the undamaged state. Reference states not only reflect the values ​​of variables but also take into account all application-specific influencing factors affecting those variables, particularly those associated with the dynamic processes performed on or using the piping system. This reflects the time dependencies and interdependencies among the variables expected during the undamaged operation of the piping system. This highly accurate, application-specific representation of the undamaged state allows for the detection of damaged conditions developing during monitoring at very early stages. Furthermore, by considering all application-specific influencing factors, the time dependencies and interdependencies of the variables offer the advantages of significantly reducing or even eliminating the number of false detections and achieving a high level of reliability in monitoring results.

[0025] The first improvement to this method involves a method in which:

[0026] a) The variable is stationary, and the reference behavior includes the stationary behavior of variables describing the linear or nonlinear time dependence of the variable, as well as the fixed correlation between the interdependent variables; or

[0027] b) The variable is stationary during a specific identifiable phase, which is particularly identifiable and / or identifiable based on the properties of the measured values ​​of the specific phase and / or particularly given by a time interval during which the piping system operates in a specific operating mode or specific process steps of a process performed on or using the piping system are executed during the time interval, and the reference behavior includes the stationary behavior of variables describing the time dependence of the variable and the correlation between the interdependent variables during these phases; and the monitored behavior is determined based on the dataset included in the data recorded during the specific phase that occurs during the monitoring period; or

[0028] c) The variable is a non-stationary variable that describes a reproducible pattern during a specific identifiable phase, particularly a phase identifiable and / or identifiable based on the properties of the measured values ​​of the specific phase, and / or particularly a phase given by a time interval during which the piping system operates in a specific operating mode or performs specific process steps on or using the piping system during the time interval, and the reference behavior includes the characteristics of the pattern described by the non-stationary variable during these phases and the correlation between the interdependent variables; and the monitored behavior is determined based on the dataset included in the data recorded during the specific phase that occurs during the monitoring period.

[0029] A second improvement to the method further includes the following steps: for each variable, determining a time scale for the change of the corresponding variable based on the training data; filtering the data based on the time scale such that the filtered data includes only data recorded during a time interval, during which the measurement of each of the variables changes over time according to the time scale determined for the corresponding variable; and performing determination of the reference behavior and each monitored behavior based on the filtered data.

[0030] A third improvement to the method includes performing the following steps at least once or repeatedly:

[0031] For at least two or each of the variables, time series forecasting is performed based on the measured values ​​of the corresponding variables included in the data recorded during the monitoring period or filtered data obtained by filtering the data recorded during the monitoring period, the time series forecasting predicting the remaining variable-specific time until the measured value of the corresponding variable will exceed a predetermined variable-specific range;

[0032] The shortest of the specified remaining times is determined as the minimum remaining time until the damage caused by the dominant condition within the pipeline exceeds the predetermined limit; and at least one of the following is performed:

[0033] Provides the output of a measuring device that provides notification of the minimum time, determines the shortest one of the variable's specific remaining time, and / or measures the variable that determines the shortest one of the variable's specific remaining time;

[0034] Based on the minimum time, perform a likelihood check on the remaining time determined based on the deviation; and

[0035] A warning is issued when the difference between the remaining time and the minimum time exceeds a predetermined threshold.

[0036] The fourth improvement to this method further includes the following steps:

[0037] Determine training data for the markers, the training data comprising or consisting of a dataset of recorded data already recorded during damage time intervals, wherein during each of the damage time intervals, the measuring device suffers damage corresponding to a known or subsequently determined damage type corresponding to the dominant condition within the piping system; wherein the training data for the markers comprises training data for markers for at least two different types of damage; and perform at least one of the following:

[0038] a) Based on training data labeled for each of the different types of damage, determine criteria for determining the existence of the corresponding damage type based on the recorded data; when the data recorded during monitoring meets the criteria determined for the corresponding damage type, determine the existence of one of the at least two different types of damage at least once or repeatedly based on the criteria, and provide an output notifying the determined damage type; and

[0039] (b) For each of the different types of damage, based on labeled training data, a type-specific direction in which the monitored behavior will deviate from a reference behavior when the corresponding damage type is present is determined, wherein each type-specific direction is determined in the form of a vector defined in a multidimensional coordinate system including coordinate axes for each variable. For at least one of the monitored behaviors determined based on the recorded data or filtered data obtained by filtering the recorded data, the monitoring direction in which the corresponding monitored behavior deviates from the reference behavior in the multidimensional coordinate system is determined. Based on the monitoring direction and the type-specific direction, the damage type of the condition in which the damage is dominant within the pipeline system is determined, and the damage type determined therefrom is provided.

[0040] The fifth improvement to this method further includes the following steps:

[0041] Perform at least one of the following:

[0042] a) Define at least one damage category, wherein each damage category includes at least one damage type and is specified by a category variable, said category variable being given by one of the measured variables that is capable of detecting damage of the damage type included in the corresponding damage category earliest; and

[0043] b) Determine at least one subcategory, wherein each subcategory includes at least one damage type and is specified by a category variable and a reference mode for each of a set of at least one subcategory variable, the category variable being given by one of the variables capable of detecting damage of the damage type included in the respective subcategory earliest, wherein each subcategory variable is given by one of the measured variables and is different from the category variable, and wherein each reference mode represents the manner in which the respective subcategory variable is affected by damage of the damage type included in the respective subcategory, particularly the manner given by the damage causing the respective subcategory variable to increase, decrease, be above or below a reference value or be above or below a given threshold;

[0044] The method further includes the following steps:

[0045] Based on data recorded during monitoring, it is determined which of the measured variables enables the earliest detection of damage developing within the pipeline system. The variable enabling the earliest detection may be determined as one of the measured variables that first exceeds or falls below a variable-specific threshold defined for that variable, and / or is given by one of the measured variables that first exceeds or falls below a variable-specific threshold defined for that variable, or may be determined as one of the variables and / or is given by one of the variables for which a time series prediction of the remaining variable-specific time until the measured value of the corresponding variable exceeds a predetermined variable-specific range reveals the shortest variable-specific remaining time; and

[0046] Perform at least one of the following:

[0047] a) Identify the damage as included in the damage category specified by the category variable, and provide an output that informs the damage category, wherein the category variable is equal to the variable that enables the earliest detection; and

[0048] b) For each sub-category variable of at least one sub-category specified by a category variable equal to the variable that can be detected earliest, determine how the measurement of the sub-category variable is affected by the damage; if the measurement of the sub-category variable of that particular sub-category conforms to the corresponding reference mode, determine the damage as damage belonging to the particular sub-category of the sub-category, and provide an output that informs the particular sub-category of the sub-category.

[0049] The fifth improvement includes the following steps:

[0050] Perform at least one of the following:

[0051] a) Predefine at least one category of damage based on the measured variables; and

[0052] b) Determine at least one of the subcategories by: b1) based on data recorded during monitoring, for at least some or each of the damages that occurred during monitoring, determining which of the variables measured by the measuring device could detect the corresponding damage earliest, and determining how the measured values ​​of other variables have been affected by the damage; and b2) determining at least one subcategory based on the variables that could be detected earliest and the corresponding ways in which other variables have been affected;

[0053] Then perform at least one of the following: a) apply the damage category and / or the subcategory to classify the detected damage; and b) after determining at least once or repeatedly that the detected damage belongs to a damage type included in one of the damage categories and / or one of the subcategories, perform the following steps: determine the damage type that dominates the damage within the piping system; store the determined damage type as a damage type included in the corresponding damage category and / or the corresponding subcategory; and whenever the detected damage is determined to be a damage type included in the corresponding damage category and / or the corresponding subcategory, subsequently indicate the damage type included in the corresponding damage category and / or the corresponding subcategory.

[0054] According to the improvements based on the fourth and / or fifth improvements, the different types of damage include at least one of the following:

[0055] Types of damage caused by accumulation;

[0056] At least two different types of damage caused by the stacking, each type of damage being specified by a specific type of stacking and / or by a predefined range of at least one property of the stacked layer formed by the stacking, the property including at least one of the following: the thickness of the stacked layer, the stiffness of the stacked layer, and the density of the stacked layer;

[0057] Types of damage caused by corrosion or wear; and

[0058] At least two different types of damage, said at least two different types of damage caused by corrosion or wear and specified by a predefined range of material removal caused by corrosion or wear.

[0059] According to the fourth and / or fifth improved method, wherein the damage to the condition is caused by accumulation, and the different types of damage include at least two different types of damage caused by accumulation; the method includes the following steps: repeatedly determining the damage type based on data recorded during monitoring; and scheduling and performing cleaning of the piping system based on the cleanability of the accumulation layer associated with the determined damage type.

[0060] According to the sixth improvement, the variables measured by the measuring device include at least two of the following: a) at least one electrical variable, each electrical variable being given by, related to, or determined based on at least one electrical property affected by corrosion, wear, and / or buildup; b) at least one vibration variable, each vibration variable being given by, related to, or determined based on at least one vibration property of the vibration of a vibrating component of a pipe in the pipeline or a measuring device exposed to the fluid; and c) at least one signal propagation variable, each signal propagation variable being given by, related to, or determined based on at least one signal property of a signal received by the measuring device, the measuring device measuring a corresponding signal propagation variable along a signal propagation path that extends along and / or through at least one surface area exposed to fluid affected by corrosion, wear, or buildup occurring on at least one surface area.

[0061] According to the seventh improvement, the measuring device includes at least one or at least two of the following:

[0062] At least one vibration device, the at least one vibration device comprising a vibrating component exposed to the fluid, a driver configured to cause the vibrating component to vibrate in at least one predetermined vibration mode, at least one sensor for sensing the generated vibration, and electronic devices configured to determine and provide measurements of at least one variable, each variable being given by a vibration variable, the vibration variable being given by, related to, or determined based on at least one vibration property of the vibration of the vibrating component; the vibration variable including: frequency, resonant frequency, amplitude, and / or damping of the vibration of the vibrating component for at least one of the vibration modes, and / or stiffness of the vibrating component relative to at least one of the vibration modes;

[0063] At least one measuring device or accelerometer is installed on one of the pipes in the pipeline and measures at least one variable given by a vibration variable, which is given by, related to or determined based on at least one vibration property of the vibration of the pipeline;

[0064] At least one measuring device configured to measure at least one variable given by an electrical variable, said electrical variable being given by, related to, or determined based on at least one of the following: the impedance, resistance, conductivity, and at least one other electrical property of electrical connections and / or electrical components affected by corrosion, wear, and / or buildup caused by said fluid; and

[0065] At least one measuring device is configured to measure at least one variable given by a signal propagation variable, the signal propagation variable being given by, related to, or determined based on at least one signal property of a signal received by the corresponding measuring device along a signal propagation path extending along and / or through at least one surface region exposed to the fluid, wherein the at least one signal property includes at least one of the following: signal attenuation, signal amplitude, signal reflection properties, properties related to or determined based on the amplitude spectrum and / or phase spectrum, signal propagation time, and at least one other signal property affected by corrosion, wear, or buildup occurring on the at least one surface region.

[0066] Based on the improvements of the seventh improvement,

[0067] a) The at least one vibration measuring device includes at least one of the following:

[0068] A first measuring device, a level switch, or a density measuring device, wherein the vibrating component is provided by or includes an oscillating element in a pipe extending into the pipe; and

[0069] A second measuring device, a Coriolis measuring device, or a Coriolis measuring device measures at least one of the flow rate, density, and viscosity of the fluid; wherein the vibrating component is provided by or includes a pipe connected to or inserted into one of the pipes in the pipeline, such that at least a portion of the fluid flowing through the pipeline system flows through the pipe;

[0070] b) At least one measuring device configured to measure at least one variable given by an electrical variable includes at least one of the following:

[0071] A measuring device or conductivity sensor, the measuring device or conductivity sensor comprising two electrodes extending into the pipe and electronic components connected to the electrodes, the electronic components being configured to determine and provide a measured value of at least one electrical variable measured by the measuring device; and

[0072] A measuring device provided by a magnetic induction flowmeter, the magnetic induction flowmeter comprising a tube, a set of two or more electrodes, and electronic components, the tube being connected to or inserted into a pipe within a conduit system such that at least a portion of the fluid flowing through the conduit system flows through the tube, the set of two or more electrodes being electrically coupled to or directly exposed to the fluid flowing through the tube, and the electronic components being connected to the electrodes and configured to determine and provide at least one electrical variable measured by the magnetic induction flowmeter; and / or

[0073] c) At least one measuring device configured to measure at least one variable given by a signal propagation variable includes at least one of the following:

[0074] Measuring devices provided by ultrasonic equipment, ultrasonic flow meters, clamp-on ultrasonic flow meters, or ultrasonic concentration meters;

[0075] A measuring device comprising an acoustic waveguide exposed to fluid flowing through the piping system, a transmitting interdigitated transducer and a receiving interdigitated transducer spaced apart from each other on the acoustic waveguide, and electronic devices connected to the interdigitated transducers and configured to determine and provide the at least one signal propagation variable; and

[0076] Measuring equipment provided by microwave devices, microwave flow meters, or microwave concentration meters.

[0077] An eighth improvement to the method, wherein the damage to the condition is caused by buildup, the method includes the steps of: performing cleaning of the piping system at least once, repeatedly, and / or based on the monitoring results; for at least one cleaning, determining the effectiveness of the cleaning as the difference between or based on the difference between at least one deviation determined based on data recorded prior to the corresponding cleaning and at least one deviation determined based on data recorded after the corresponding cleaning; and performing at least one of the following: providing an output informing of the effectiveness of the cleaning, issuing a warning if the cleaning is ineffective, and performing additional cleaning or another remedy if the cleaning is ineffective.

[0078] A ninth improvement to the method, wherein the damage to the condition is caused by buildup, the method includes the steps of: performing a cleaning of the piping system at least once; and determining each remaining time to be determined after the cleaning, based solely on deviations already determined based on data recorded after the last cleaning.

[0079] According to at least one of the eighth and / or ninth improvements, each cleaning time interval for cleaning the pipeline system is: provided by the user of the method, by a superior unit, or by a control system that initiates and / or controls the performance of the cleaning; or determined by a computing unit that has been trained or learned to perform the determination of the cleaning time interval, and performs each determination of the effectiveness and / or the remaining time based on the cleaning time interval determined by the computing unit based on the data.

[0080] The tenth improvement includes at least one of the following steps:

[0081] a) Determine the magnitude of the deviation, and determine and provide the extent of damage to the dominant condition within the piping system given by or corresponding to the magnitude of the deviation;

[0082] b) An alarm is issued when the deviation exceeds the third deviation range;

[0083] c) When the deviation occurs within the first deviation range, provide an output informing the piping system of its undamaged condition; and

[0084] d) The remaining time before the end of the remaining time is used to schedule and perform maintenance actions, wherein the maintenance actions include cleaning the piping system and / or at least one component in or installed on the piping system that is exposed to the fluid, or repairing or replacing at least one pipe and / or at least one component in or installed on the piping system that is exposed to the fluid.

[0085] The present invention further includes a monitoring system for performing the method according to the present invention, the monitoring system comprising: measuring devices; and a computing unit directly or indirectly connected to or communicating with each of the measuring devices; wherein the computing unit is configured to receive the data and record the data by storing the data at least temporarily in a memory associated with the computing unit; and wherein the computing unit is configured to determine the reference behavior to determine the deviation and to determine and provide the monitoring results. Attached Figure Description

[0086] The invention and other advantages will be explained in more detail with the aid of the accompanying drawings.

[0087] Figure 1 A monitoring system including measuring equipment installed on a piping system is shown;

[0088] Figure 2 The time series of measurements of an exemplary variable is shown;

[0089] Figure 3 The continuously determined deviation is shown;

[0090] Figures 4 to 9 Examples of measuring devices are shown respectively;

[0091] Figure 10 The type-specific direction of the deviation of the monitored behavior is shown; and

[0092] Figure 11 The measurements are shown by two different measuring devices installed adjacent to each other. Detailed Implementation

[0093] The present invention relates to a method, particularly a computer-implemented method, for monitoring the predominant condition within a piping system regarding damage that may develop over time due to accumulation, wear, or corrosion caused by one or more fluids flowing through the piping system, and a monitoring system for performing the monitoring method.

[0094] The piping system can be any piping system comprising at least one pipe 1 for conveying one or more fluids. Examples include piping systems used in the oil and gas industry for transporting oil, naphtha, or other liquids or gases; piping systems used in the chemical industry for transporting chemicals (e.g., acids); piping systems used for transporting other fluids (e.g., fluids including lime, paint, or varnish); and piping systems used in the food and beverage industry (e.g., food production or bottling plants). One or more pipes 1 of the piping system may include, for example, at least one metal pipe, at least one plastic pipe, and / or at least one pipe 1 comprising an outer pipe (e.g., a metal outer pipe) and an inner liner.

[0095] The method includes installing at least two measuring devices Mi (i:=1,…,n; n≥2) on a piping system. Each measuring device Mi is susceptible to damage corresponding to damage associated with the dominant condition within the piping system and is configured to measure one or more variables Vi indicating the damage. The measuring devices Mi are selected such that each of the measuring devices Mi is of a different type, and at least two, preferably at least three, of the variables Vi measured by the different measuring devices Mi each exhibit different dependencies on the damage. Figure 1 The illustration shows an example of a monitoring system comprising two exemplary measuring devices M1, M2 installed on or connected to one of the pipes 1 in a piping system. The measuring device M1 preferably comprises or consists of equipment required on the piping system, such as measuring at least one quantified variable mi (e.g., physical, electrical, and / or chemical properties of one or more fluids) and / or measuring devices for monitoring, regulating, and / or controlling process parameters performed at a site including the piping system. Additionally or alternatively, the measuring device M1 may, for example, include at least one device installed solely for the purpose of monitoring the dominant conditions within the piping system.

[0096] During the operation of the pipeline system, the measuring device Mi measures variable Vi and the time series data D of the measured value vi of variable Vi measured by the measuring device Mi, and continuously records their measurement time t. Figure 2 The figure shows an exemplary time series of measurements v1, v2, and v3 for three different variables V1, V2, and V3.

[0097] Based on training data included in data D recorded during the training phase, a dynamic reference state BR for the variable Vi is determined. This dynamic reference state BR corresponds to the time-dependent distribution of the value of the variable Vi, which is expected to be the measured value vi when the measuring device Mi is undamaged. The training phase is, for example, the time interval following the installation of the measuring device Mi, during which the dominant conditions within the piping system are undamaged, and the newly installed measuring device Mi is undamaged. The reference state BR is determined, for example, such that it reflects the expected value and time dependence of the variable Vi during the operation of the piping system, as well as their interdependencies. The reference state BR depends on the specific application of the method, particularly on the measured variable Vi and the type of process performed on or using the piping system.

[0098] As a first example, in a particular application where the variable Vi is stationary, the reference behavior BR may, for example, include the stationary behavior of the variable Vi describing the linear or nonlinear time dependence of the variable Vi, as well as the fixed correlation between the interdependent variables Vi. As a second example, in applications where the variable Vi is found to be stationary only during specific identifiable phases (e.g., during which the piping system operates in a specific mode of operation or during which specific process steps of a process performed on or using the piping system are timed), the reference behavior BR may, for example, include the stationary behavior of the variable VI, which describes the time dependence of the variable Vi during these phases and the correlation between the interdependent variables Vi. As a third example, in some applications, the variable Vi may be found to be a non-stationary variable describing a reproducible pattern during a specific identifiable phase, for example, during which the piping system operates in a specific mode of operation or during which specific process steps of a process performed on or using the piping system are timed. In this case, the reference behavior BR may, for example, include the characteristics of the pattern described by the non-stationary variable Vi during these phases and the correlation between the interdependent variables Vi. As an example, the characteristics may be described, for example, in the form of a probability density function of the distribution of the time-dependent values ​​of the variable Vi. In the second and third examples, the occurrence of the corresponding specific stage is preferably determined based on the training data, for example, by identifying the properties of the measurement values ​​vi based on the specific stage, and then, as described above, the reference behavior BR is determined based on the dataset of the training data, each dataset being recorded during one of the specific stages.

[0099] After determining the reference behavior BR, the dominant condition within the pipeline system is monitored based on the data D recorded during the monitoring period. To this end, the method includes the following steps: repeatedly determining the deviation ΔB between the monitored behavior BM and the reference behavior BR, corresponding to the time-dependent distribution of the measured value vi of the variable Vi determined based on the data D recorded during the monitoring period. Each monitored behavior BM is determined, for example, in the same form as the reference behavior BR, and accordingly reflects the magnitude of the measured value vi, the time dependence of the measured value vi, and their interdependencies. In the case where the reference behavior BR is determined based on a dataset of training data recorded during a specific phase, the monitored behavior BM is determined based on the dataset included in the data D recorded during the specific phase occurring during the monitoring period. Similar to the specific phase occurring during the training phase, the specific phase occurring during the monitoring period is preferably identified based on the properties of the measured value vi during that specific phase.

[0100] The method further includes the step of determining and providing a monitoring result MR at least once or repeatedly based on a previously determined deviation ΔB. For this purpose, the method includes, for example, detecting a dominant damage condition within the piping system when the deviation ΔB exceeds a first deviation range R1, and providing an output notifying of the damage condition. The first deviation range R1 is, for example, a deviation range determined based on statistical fluctuations and / or variations in a measurement VI applied to determine a reference behavior state BR. Additionally or alternatively, the method includes determining the remaining time RT until the extent of damage from the dominant condition within the piping system exceeds a predetermined limit, and providing an output notifying of the remaining time RT. The remaining time RT is determined by performing a time series forecast and by defining the remaining time RT as the time given by or corresponding to the time predicted by the time series forecast, which predicts the remaining time until the deviation ΔB exceeds a second deviation range R2 corresponding to a predetermined limit. This is in Figure 3 As shown in the figure, Figure 3 An example of a continuously determined deviation ΔB is shown, wherein the deviation ΔB exceeds a first deviation range R1 at a first time t1, and wherein the remaining time RT, determined based on the deviation ΔB determined at or before the first time t1, ends at the second time t2, according to the time series prediction indicated by the dashed arrow.

[0101] like Figure 1 As shown, the monitoring system performing the above monitoring method includes a measuring device Mi installed on the pipeline system and a computing unit 3. The computing unit 3 is implemented, for example, as a hardware unit, such as a computer or computing system located near or remotely to the measuring device Mi. Alternatively, cloud computing can be applied. Cloud computing is a method in which IT infrastructure (e.g., hardware, computing power, memory, network capacity, and / or software) is provided via a network (e.g., via the Internet). In this case, the computing unit 3 is implemented in the cloud.

[0102] The computing unit 3 is configured to receive data D, including the measurement variable vi and its measurement time t provided by the measuring device Mi, and to record the data D by storing the data D at least temporarily in the memory 5 associated with the computing unit 3. For this purpose, each measuring device Mi is directly connected to and / or communicates with the computing unit 3, as shown by arrow a, via a higher-level unit 7, such as shown by arrows b1 and b2, and / or via an edge device 9 located near the measuring device Mi, such as shown by arrows c1 and c2. For this purpose, hardwired or wireless connections and / or communication protocols known in the art, such as LAN, W-LAN, Fieldbus, Profibus, HART, Bluetooth, NFC, etc., can be applied. As an example, the measuring device Mi, the edge device 9, and / or the higher-level unit 7 can be connected directly or indirectly to the computing unit 3 via the Internet (e.g., via a communication network, such as TCP / IP).

[0103] The computing unit 3 is implemented (e.g., programmed) to determine the reference behavior BR based on the data D recorded during the training phase, subsequently monitor the dominant condition within the pipeline system as described above, determine the deviation ΔB, and determine and provide the monitoring result MR. As an example, the monitoring result MR may be provided, for instance, in the form of an email or a message automatically generated by the computing unit 3 and sent to a predetermined recipient or device (e.g., the parent unit 7, a computer, or a mobile device, such as a cellular phone, tablet, or service tool).

[0104] The present invention provides the advantages described above. Alternatively, the various steps of the method and / or components of the system can be implemented in different ways without departing from the scope of the invention. Several alternative embodiments are described in more detail below.

[0105] As an example, determining and providing monitoring results MR may include, for instance, determining the magnitude of the deviation ΔB, and determining and providing the degree of damage to the dominant condition within the piping system given by or corresponding to the magnitude of the deviation ΔB. Alternatively, providing monitoring results MR may include providing an output informing the piping system of an undamaged condition when the deviation ΔB falls within a first deviation range R1. As an additional or alternative option, an alarm may be issued when the deviation ΔB exceeds a third deviation range R3. Figure 3 As shown, the third deviation range R3 is, for example, an intermediate range that is greater than the first deviation range R1 and less than the second deviation range R2.

[0106] Alternatively, the reference behavior BR is determined, for example, in the form of a probability density function of the time-related value of the variable Vi expected without impairment. In this case, the monitored behavior BM is determined, for example, in the form of the measured value Vi and its measurement time t, and the magnitude of the deviation ΔB is determined, for example, as the Mahalanobis distance between the measured value Vi and the distribution described by the probability density function. In this case, the first, second, and / or third deviation ranges R1, R2, R3 are each defined, for example, in the form of the corresponding confidence level that the monitored behavior BM conforms to the reference distribution described by the probability density function.

[0107] Additionally or as an alternative, the method may further include scheduling maintenance actions based on the remaining time RT and performing the maintenance actions before the remaining time RT expires. Depending on the type of damage, the maintenance actions may include cleaning the piping system and / or at least one component C included in or installed on the piping system that is exposed to one or more fluids, or may include repairing or replacing at least one pipe 1 included in or installed on the piping system that is exposed to one or more fluids. Figure 1 An exemplary component C is shown, given here as a valve mounted on pipe 1. Other examples of component C include, for example, thermocouple sheaths, compensators, sensors, pumps, assemblies, and / or at least one other device.

[0108] Cleaning of the piping system is preferably performed while the measuring device Mi is in its proper position on the piping system. For this purpose, a cleaning method called Cleaning-in-Place (CIP) can be applied. This has the advantage that the measuring device Mi is cleaned in the same manner as the piping system during each cleaning. This is equally applicable to any component C that can be anticipated on the piping system and kept in place during cleaning.

[0109] Figure 1 The exemplary measuring devices M1 and M2 shown are provided by two different types of vibration devices. Each of them includes a vibrating component 11, 13 exposed to one or more fluids, a driver 15 configured to cause the vibrating component 11, 13 to vibrate in at least one predetermined vibration mode, at least one sensor 17 sensing the generated vibrations, and an electronic device 19 configured to determine and provide a measured value vi of one or more variables Vi measured by the respective measuring devices M1, M2.

[0110] The vibrating component 11 of the first measuring device M1 includes an oscillating element, such as a rod or tuning fork, extending into one of the pipes 1. When a tuning fork with two spaced-apart rods attached to a diaphragm is applied, the vibration modes include, for example, a mode in which the rods perform antiphase vibrations in a direction perpendicular to their longitudinal axis. Alternatively, the first measuring device M1 may be, for example, a level switch or a density measuring device.

[0111] The vibrating component 13 of the second measuring device M2 is or includes a pipe connected to or inserted into one of the pipes 1, such that, as indicated by arrow F, at least a portion of the fluid(s) flowing through the piping system flows through the pipe. Alternatively, the second measuring device M2 is, for example, a Coriolis measuring device, comprising one, two, or even more pipes, such as at least one straight pipe and / or at least one bend. The Coriolis measuring device is implemented, for example, to measure at least one quantified variable mi, such as the flow rate, density, and / or viscosity of the fluid(s) flowing through its (one or more) pipes. Figure 1 In the tube, the tube is straight, and the vibration modes excited by the actuator 15 interacting with the tube include, for example, a transverse mode L and / or a torsional mode T. In the transverse mode L, the tube performs transverse vibration perpendicular to its longitudinal axis, and in the torsional mode T, the tube performs torsional vibration about its longitudinal axis.

[0112] Because their vibrating components 11, 13 are exposed to one or more fluids, each of the measuring devices M1, M2 is susceptible to damage corresponding to the dominant conditions within the piping system caused by buildup, corrosion, or wear of its vibrating components 11, 13. Regardless of whether the damage is caused by buildup, corrosion, or wear, it alters the vibrational quality and characteristics of the vibration of the respective vibrating component 11, 13. Accordingly, the variable Vi measured by each of the two measuring devices M1, M2 includes at least one vibration variable associated with the vibration of its vibrating component 11, 13, indicating damage to the respective measuring device M1, M2. Vibration variables include, for example, the frequency, resonant frequency, vibration amplitude, and / or damping of the vibration of the respective vibrating component 11, 13 relative to at least one of the vibration modes, and / or the stiffness of the respective vibrating component 11, 13 relative to at least one of the vibration modes. Examples of vibration variables and their measurements are described, for instance, in US 7,665,357 B2, DE 102017102550 A1, German patent application DE 102020111127.4 filed April 23, 2020, WO 2012 / 062551 A1, DE 102019124709 A1 and WO2007 / 045539 A.

[0113] The resonant frequencies measured by the first and second measuring devices M1 and M2 are inversely proportional to the vibrating mass, which increases in the case of accumulation and decreases in the case of corrosion or wear. Furthermore, damping and resonant frequencies are affected by the viscosity and density of one or more fluids, as well as the deposits formed on the respective vibrating components 11 and 13. The stiffness of the respective vibrating components 11 and 13 relative to at least one of the vibration modes decreases due to corrosion or wear and increases due to the deposits formed on the respective vibrating components 11 and 13, particularly when the deposits harden or solidify on the vibrating components 11 and 13. Therefore, each vibration variable listed above exhibits a different dependence on damage caused by accumulation, corrosion, or wear. Additionally, for each of the different vibration variables, the dependence of the corresponding vibration variable measured by the first measuring device M1 on damage differs from the dependence of the same vibration variable measured by the second measuring device M2 due to the different masses, shapes, and vibration modes of the two different vibrating components 11 and 13. Therefore, even when the variable Vi measured by different types of measuring devices Mi only includes vibration variables, when the different vibration variables provided by different types of vibration devices are combined and their interrelationships and time dependencies that occur during the operation of the piping system are taken into account, they provide a powerful means for detecting damage at an early stage with a high level of reliability.

[0114] By applying different types of measuring devices Mi, ensuring that the variable Vi measured by Mi includes at least two different types of variables, the capabilities of the monitoring system and methods can be further improved. Examples of different types of variables include vibration variables, electrical variables, and signal propagation variables.

[0115] Vibration variables are related to the vibration of objects exposed to one or more fluids flowing through a piping system. Examples include those generated by... Figure 1 The vibration device shown measures different types of vibration variables, where the objects are given by the corresponding vibrating components 11, 13. As another example, the object could be given by one of the pipes 1. This is based on... Figure 4 The measuring device M3 shown is configured to measure and provide at least one vibration variable, which is given by, related to, or determined based on at least one vibration property of the vibration of the pipe 1 on which the measuring device M3 is mounted. Figure 4 In this context, the measuring device M3 is, for example, an accelerometer. In this case, the variable Vi includes, for example, the frequency and / or amplitude of the vibration of pipe 1.

[0116] Electrical variables are given by, related to, or determined based on at least one electrical property affected by damage. These variables include, for example, electrical variables given by or related to the impedance, resistance, conductivity, and / or other electrical properties of electrical connections and / or electrical components affected by corrosion, wear, and / or buildup from one or more fluids. Optionally, electrical variables may include at least one auxiliary electrical variable determined based on two or more measured electrical variables. Figure 5 and Figure 6 An example of a measuring device Mi for measuring at least one electrical variable is shown.

[0117] Figure 5 The illustrated measuring device M4 includes two electrodes 21 extending into the pipe 1 and electronic components 23 connected to the electrodes 21. In this example, electrical variables include, for example, impedance, resistance, and / or conductivity, measured by the electronic components 23, for example, by measuring the current flowing through the electrodes 21 when an AC voltage is applied to them. As an example, the measuring device M4 is, for example, a conductivity sensor that measures the measured variable mi given by the conductivity of one or more fluids. Alternatively, a conductivity sensor comprising more than two electrodes (e.g., three or four electrodes as known in the art) can be used.

[0118] Figure 6 The measuring device M5 shown is a magnetic induction flowmeter for measuring the measured variable mi given by the flow of one or more slightly conductive fluids. The flowmeter is mounted on a piping system such that at least a portion of the fluid(s) flowing through the piping system passes through the pipe 25 of the measuring device M5, which is connected to or inserted into a pipe 1 of the piping system. The flowmeter includes a generator that generates a constant magnetic field B extending through the pipe 25 in a direction perpendicular to the longitudinal axis of the pipe 25. The generator includes, for example, a pair of coils 27 mounted radially opposite each other on opposite sides of the pipe 25 and a current generator 29 that provides alternating polarity switching direct current to the coils 27. The flowmeter further includes a set of electrodes electrically coupled to or directly exposed to the fluid(s) flowing through the pipe 25 and electronics 31 connected to the electrodes. The electrodes include two measuring electrodes 33 positioned radially opposite each other on opposite sides of the pipe 25 in a direction perpendicular to the magnetic field B. In some embodiments, the electrodes may additionally include at least one reference electrode 35. The electronic device 31 is configured to measure flow rate based on the voltage induced between the measuring electrodes 33 in a direction perpendicular to the magnetic field B and perpendicular to the longitudinal axis of the tube 25.

[0119] Electronic device 31 is further configured to measure and provide at least one variable Vi, which is given by, related to, or determined based on at least one electrical property affected by damage. The electrical variable includes, for example, a variable Vi given by or determined based on at least one of the following: conductivity, impedance, resistance, or another type of electrical property measured between two electrodes (e.g., between two measuring electrodes 33 or between one of the measuring electrodes 33 and a reference electrode 35). Examples of electrical variables are described, for example, in DE10356007 B3, US 8,046,194 B1, and DE 102009002539 A1.

[0120] The signal propagation variable is given by, related to, or determined based on at least one signal property of the signal (e.g., microwave, ultrasonic, or acoustic signal), which is received by a measuring device Mi that measures a corresponding variable Vi along the signal propagation path, which extends along and / or through at least one surface area exposed to fluid(one or more) flowing through a piping system. The received signal is, for example, a signal component sent to a receiver at the measuring device Mi and / or a signal component reflected to the receiver. Signal properties include, for example, signal attenuation, signal amplitude, signal reflection characteristics, amplitude and / or phase spectra of the signal affected by corrosion, wear, or buildup occurring on the surface area(s), or characteristics determined based on them. Figure 7 , 8 Examples of measuring devices M6, M7, and M8 configured to measure at least one variable Vi given by signal propagation are shown in Figures 9 and 1.

[0121] Figure 7 The measuring device M6 shown is an ultrasonic device comprising a tube 37 connected to or inserted into one of the pipes 1, such that at least a portion of the fluid(s) flowing through the pipe system passes through the tube 37. Alternatively, it may be designed as a clamping device held on the circumference of one of the pipes 1 used as a tube. The ultrasonic device includes two transducers 39 and electronics 41 connected to the transducers 39. The electronics 41 is configured to measure and provide signal propagation variables affected by corrosion, wear, or buildup on the tube 37, for example, signal propagation variables given by or determined based on at least one of the following: the signal amplitude, signal attenuation, and signal propagation time of the ultrasonic signal received by one of the transducers 39 along a signal propagation path extending along and / or through at least one surface area exposed to the fluid(s) flowing through the pipe system. Alternatively, Figure 7The measuring device M6 shown is, for example, an ultrasonic flow meter, which measures the measured variable mi given by the flow rate of one or more fluids flowing through pipe 1. In this case, transducers 39 are mounted outside pipes 37, one upstream of the other, and tilted at an angle relative to pipes 37 towards each other. Each transducer 39 alternately acts as a transmitter emitting ultrasonic signals and a receiver receiving ultrasonic signals emitted towards it by the other transducer 39. Figure 7 In the tube 37, transducers 39 are positioned spaced apart from each other on the same side, such that an ultrasonic signal emitted by one of the transducers 39 travels along the path of the tube 37. Figure 7 The signal propagation path, indicated by the dashed line, propagates to another transducer 39. This path extends through the pipe wall portion on which the transmitting transducer 39 is mounted to the opposite pipe wall, which reflects the incident ultrasonic signal to the receiving transducer 39 through the interior of the pipe 37 and the pipe wall portion on which the receiving transducer 39 is mounted. Alternatively, the transducer 39 may be mounted on the opposite side of the measuring pipe 37. Because the ultrasonic signal propagates along the same propagation path with and against the flow rate of one or more fluids flowing through the pipe 37, the difference between the upstream and downstream propagation times of the ultrasonic signal is directly proportional to the flow velocity of one or more fluids. Therefore, the volumetric flow rate is determined by the electronics 41 based on the product of the cross-sectional area of ​​the measuring pipe 37 and the flow velocity determined based on the difference in propagation times. Alternatively, other types of ultrasonic devices known in the art, such as ultrasonic concentration measuring devices, may be modified to additionally measure and provide at least one of the signal propagation variables listed above in the context of an ultrasonic flow meter. For example, DE102006030964 A1 describes an example of an ultrasonic concentration measuring device that measures the concentration of components included in a gas flowing through its tube based on the measurement of the velocity of sound in the gas and the temperature measurement.

[0122] Figure 8The measuring device M7 shown includes an acoustic waveguide 43 exposed to one or more fluids flowing through a piping system. For this purpose, the acoustic waveguide 43 is, for example, mounted to one of the pipes 1 such that it is immersed in one or more fluids flowing through the pipe 1, or connected to one of the pipes 1 such that at least a portion of the fluids flowing through the piping system passes through the acoustic waveguide 43. Two interdigital transducers 45 are mounted spaced apart from each other on the outside of the acoustic waveguide 43. One of the interdigital transducers 45 is operated as a transmitter to generate sound waves, while the other is operated as a receiver to receive incident sound waves. The transmitted sound waves propagate along the acoustic waveguide 43 based on one or more wave modes, as indicated by arrow A. When the sound waves come into contact with the fluid located inside the acoustic waveguide 43, the waves disperse into the fluid. As indicated by arrow B, this involves mode conversion at the Rayleigh angle θ. The Rayleigh angle θ depends on the speed of sound of the sound wave traveling along the waveguide wall and the speed of sound in the fluid. Therefore, the propagation of the sound wave signal is affected by corrosion or wear of the acoustic waveguide 43, as well as by the deposits formed inside the acoustic waveguide 43. Accordingly, the measuring device M7 includes electronics 47 connected to the interdigital transducer 45 and configured to measure and provide at least one signal propagation variable indicating damage. These signal propagation variables include, for example, signal propagation time and / or amplitude attenuation for at least one of the wave modes. Alternatively, Figure 8 The measuring device M7 shown is configured, for example, to measure at least one quantified variable mi, such as acoustic impedance, acoustic density, and / or sound velocity in one or more fluids. Based on the temperature of one or more fluids, the acoustic impedance, acoustic density, and sound velocity in one or more fluids, as measured by the temperature sensor 48 mounted on the acoustic waveguide 43, and reference data, the concentration of substances included in the fluid can be determined. The measuring device providing these quantified variables is sold by the Endress+Hauser Group under the product name "Teqwave". In the context of this invention, these devices can be modified to additionally measure and provide the signal propagation variables listed above.

[0123] Other examples of measuring devices Mi configured to measure the signal propagation variable indicating damage include microwave devices, such as microwave flow meters and microwave concentration meters. As an example, Figure 9The measuring device M8 shown is a microwave device comprising a tube 49 connected to or inserted into one of the pipes 1, such that at least a portion of one or more fluids flowing through the pipe system passes through the tube 49. The microwave device includes two antennas 51 located on opposite sides of the measuring tube 49 and electronics 53 connected to the two antennas 51. This microwave device is implemented, for example, as a concentration measuring device that measures the concentration of dry matter included in one or more fluids flowing through the tube 49 based on the signal propagation time and / or signal attenuation of a microwave signal propagating from the transmitting antenna 51 through the tube 49 to the receiving antenna 51. In some embodiments, the measuring device M8 may include a dielectric liner 52 lining the inner surface of the tube 49. As in the previous examples, the signal propagation of the microwave signal is affected not only by the fluid properties but also by build-up, corrosion, or wear of the tube 49 or the liner 52. Accordingly, the electronics 53 of the measuring device M8 are configured to measure and provide at least one signal propagation variable indicating damage. In this regard, one of the antennas 51 is operated, for example, as a transmitting antenna, and the signal propagation variable is determined, for example, based on signals received by the other antennas 51. Additionally or alternatively, one of the antennas 51 may be operated, for example, as a transmitting antenna and a receiving antenna for receiving reflections of the transmitted signal. Signal propagation variables include, for example, the signal propagation time when attenuation reaches its extreme, amplitude attenuation, frequency, the nature of the amplitude spectrum, and / or the phase difference between the transmitted and received signals. Examples of signal propagation variables indicating damage caused by accumulation are disclosed, for example, in German patent applications DE102020133855.4 and DE 102020133858.9, filed December 16, 2020.

[0124] As described above, some or all variables Vi measured by the measuring device Mi may be affected not only by the damage to be detected but also by other influencing factors, such as the properties of (one or more) fluids and / or factors associated with processes performed on or using the piping system. In this regard, as an option, the monitoring method can be further improved by filtering the recorded data D and subsequently determining the reference behavior BR and the monitored behavior BM based on the filtered data FD. Various different filtering methods can be applied for this purpose. For example, filtering can be performed based on the time scale of change of the variable Vi measured by the measuring device Mi. In this case, the method includes: for each variable Vi, determining the time scale of change of the corresponding variable Vi based on training data recorded during the training phase. These time scales are then applied to determine time intervals during which the measured value vi of each variable Vi measured during the monitoring period changes over time according to the time scale determined for the corresponding variable Vi. When this filtering method is applied, the filtered data FD includes only the data D recorded during the time interval during which the measured value vi of each variable Vi changes over time according to the time scale determined for the corresponding variable Vi. In this case, the computing unit 3 is implemented, for example, to determine the time scale based on the data D recorded during the training phase, then to determine the time interval based on the data D recorded during the monitoring phase, and to filter the data D based on the previously determined time interval.

[0125] As an additional or alternative option, the monitoring method may include the following steps: for at least two or each variable Vi, determining the variable-specific remaining time RTvi at least once or repeatedly, and determining the shortest of the variable-specific remaining time RTvi as the minimum time RTmin remaining until the degree of damage caused by the dominant condition in the pipeline exceeds a predetermined limit. Here, by performing time series forecasting, predicting the variable-specific remaining time RTvi remaining until the measured value vi of the corresponding variable Vi exceeds a predetermined variable-specific range, each variable-specific remaining time RTvi is determined based on the measured value vi of the corresponding variable Vi included in the data D recorded during monitoring or in the corresponding filtered data FD. In this case, the monitoring result MR includes, for example, an output notifying the minimum time RTmin, the variable Vi (for which the shortest of the variable-specific remaining time RTvi has been determined), and / or the measuring device Mi measuring (for which the shortest of the variable-specific remaining time RTvi has been determined) the variable Vi. Alternatively, the minimum time RTmin may be determined and provided, for example, as an additional safety measure and / or applied to perform a likelihood check. In the latter case, the calculation unit 3 is configured, for example, to determine the remaining time RT and the minimum time RTmin, and to issue a warning when the difference between the two exceeds a predetermined threshold.

[0126] Depending on the application, different types of damage may occur, such as damage caused by deposition or damage caused by corrosion or abrasion. Damage caused by corrosion or abrasion can be further subdivided into different types of damage caused by corrosion or abrasion, wherein a predefined range of material removal caused by each of these different types of corrosion or abrasion is specified. Damage caused by deposition can be subdivided into different types of damage, each of which is given by a specific type of deposition. As an example, different types of deposition can be specified, for example, by a predefined range of at least one property of the deposition layer formed by the deposition. Examples of properties of the deposition layer include the thickness of the deposition layer, the stiffness of the deposition layer, and the density of the deposition layer.

[0127] Alternatively, the disclosed method may be further modified to include method steps for determining, at least once or repeatedly, the type of damage that predominates within the pipeline system and providing an output that notifies the determined type of damage.

[0128] The determination of the damage type is achieved, for example, by a method including the step of identifying labeled training data for at least two different types of damage. The labeled training data is preferably determined based on recorded data D and includes a dataset of or composed of recorded data D, which has been recorded during damage time intervals, during which the measuring device Mi suffers damage corresponding to a known or subsequently determined damage type corresponding to the dominant condition within the piping system. The damage time interval is determined, for example, by determining the dominant damage type within the piping system at consecutive inspection times and subsequently identifying a given length of time interval preceding the corresponding inspection time as one of the damage time intervals during which the damage type determined at the inspection time exists. In this case, the length of the time interval preceding the inspection time is preferably significantly shorter than the time scale of the increase in damage severity. At the inspection time, the damage type is determined, for example, by inspecting the condition of one of the measuring devices Mi or the condition of an inspection probe 55 extending into the piping system, which can be more easily removed from the piping system to be inspected. Figure 4 An example of an inspection probe 55 is shown, which is releasably mounted on one of the pipes 1 such that the stern surface 57 of the inspection probe 55 is exposed to one or more fluids flowing through the pipe system.

[0129] Then, for example, training data with labels defined for each different type of damage is applied to determine criteria for determining the presence of a corresponding damage type within the pipeline system based on the recorded data D. The criteria are determined, for example, by analysis of the labeled training data (e.g., analysis including correlation analysis, pattern recognition methods, autocorrelation analysis, and / or another data analysis method capable of identifying features of the measurement value vi indicating the corresponding damage type). After this, the criteria are applied at least once to determine the dominant damage type within the pipeline system. In this case, when the data D recorded during monitoring meets the criteria for determining the corresponding damage type, it is determined that one of the different types of damage exists.

[0130] As an alternative, the method may include: for each type of damage, determining a type-specific orientation dj based on labeled training data, wherein the monitored behavior BM will deviate from a reference behavior BR when the damage condition is due to the corresponding damage type. Each type-specific orientation dj is determined as a vector pointing to the corresponding direction in a multidimensional coordinate system, which includes coordinate axes for each variable Vi. This is in Figure 10 As shown in the figure, Figure 10 An example of two type-specific directions d1 and d2 in a coordinate system spanned by three variables V1, V2, and V3 is shown. In this embodiment, the method includes the following steps: for at least one of the monitored characteristics BM determined based on recorded data D or filtered data FD, a monitored direction dm is determined as the deviation of the corresponding monitored characteristic BM from a reference characteristic BR in a multidimensional coordinate system. Thereafter, the damage type causing this deviation ΔB is determined based on the monitored direction dm and the type-specific direction di. As an example, the damage type determination is performed, for instance, based on the degree of conformity between the monitored direction dm and the type-specific direction di, for example, by determining the projection of the monitored direction dm onto each type-specific direction di, and determining the damage type to be given by the damage type corresponding to the type-specific direction di that presents the longest projection.

[0131] For example, the damage type determination is performed by computing unit 3, which is configured to execute at least one of the two determination methods described above. In this case, providing the monitoring result MR includes providing an output that notifies the damage type that has been determined.

[0132] Regarding the determination of damage type, the application of a measuring device Mi that measures at least two different types of variables (e.g., vibration variables, electrical variables, and / or signal propagation variables) offers the following advantages: it enables more accurate differentiation between different types of damage. Figure 11 It shows the result of Figure 6The measured values ​​vi of the electrical variable Va, measured by the magnetic induction measuring device M5, and the measured values ​​vi of the signal propagation variable Vb, measured by the microwave measuring device M8 near the magnetic induction measuring device M8 installed on the piping system, have been recorded over a period of several weeks. This period includes a first time period T1 where the dominant condition within the piping system is relatively stable, a second time period T2 where the deposit within the piping system increases, and a third time period T3 during which the properties of the deposit change. The measured values ​​vi are normalized such that a value of 1 corresponds to an undamaged condition. In the second time period T2, the electrical variable Va, which is related to the conductivity of the deposit, decreases faster than the signal propagation variable Vb, which is related to the dielectric properties of the deposit. Therefore, when the signal propagation variable Vb has not yet indicated damage, the electrical variable Va allows for the determination of damage at an early stage (e.g., in the early stages of the pipe system). Figure 11 Accumulation was detected at time t1 (as shown). In the third time period T3, the signal propagation variable Vb increased back to the value measured during the first time period T1, while the electrical variable Va only increased to an intermediate value that still indicated accumulation. The different ways in which the two variables were affected in the third time period T3 indicate that the nature of the accumulation layer and therefore the type of damage had changed.

[0133] Even though distinguishing between different types of damage is most effective, it can also be performed when variable Vi includes different types of variables Vi, or when variable Vi only includes variables Vi of the same type, thus exhibiting different dependencies on damage. In either case, the method may, for example, include defining at least one damage category. Each damage category includes at least one damage type and is specified by a category variable Vk given by one of the measured variables Vi, which enables the earliest detection of damage (one or more) of the damage types included in the corresponding damage category. This definition provides the advantage that damage categories can be defined even when no information about the types (one or more) of damage included in the corresponding damage category is available. The variable Vi that enables the earliest detection of damage may, for example, be determined by one of the measured variables Vi and / or by a variable that first exceeds or falls below a variable specific threshold defined for the corresponding variable Vi due to damage occurring within the piping system. Figure 11 In this context, the electrical variable Va is the first electrical variable to fall below the normalization threshold of 0.6. Alternatively, the variable Vi that enables the earliest detection of damage may be identified, for example, as one of the variables Vi that exhibits the shortest variable-specific remaining time RTvi and / or given by one of the variables Vi that exhibits the shortest variable-specific remaining time RTvi.

[0134] Additionally or alternatively, the method may include determining at least one subcategory comprising at least one type of damage. Each subcategory is specified by a category variable Vk given by one of the variables Vi, which enables the earliest detection of damage of one or more damage types included in the corresponding subcategory, and a reference mode for each of the set of at least one subcategory variable Vn. Each subcategory variable Vn is given by one of the measured variables Vi and is different from the category variable Vk. Furthermore, a reference mode determined for each subcategory variable Vn is determined such that it represents the manner in which the corresponding subcategory variable Vn is affected by damage of one or more damage types included in the corresponding subcategory. As an example, each reference mode is given, for example, by damage of one or more damage types included in the corresponding subcategory, such that the corresponding subcategory variable Vn increases, decreases, is higher or lower than a reference value and / or is higher or lower than a given threshold.

[0135] Next, for example, classification is performed based on data D recorded during monitoring to determine which of the measured variables Vi is the earliest detectable damage occurring within the pipeline system. Subsequently, the damage is identified, for example, as belonging to a damage category specified by a categorical variable Vk, which is equal to a previously determined specific variable Vi that enables the earliest detection. Furthermore, it is preferable to provide an output notifying the damage category thus determined. Additionally or alternatively, the classification may, for example, include determining, for each subcategory variable Vn of at least one or each subcategory specified by the categorical variable Vk, which is equal to the variable Vi enabling the earliest detection, how the measured value vn of the corresponding subcategory variable Vn has been affected by damage. Similarly, each manner is determined, for example, by determining whether the measured value vn has increased, decreased, is above or below a reference value and / or is above or below a given threshold. If such determined manner conforms to the corresponding reference manner of a particular subcategory, the damage is identified as damage of the type included in that particular subcategory. Furthermore, it is preferable to provide an output notifying the particular subcategory thus determined within the subcategory.

[0136] Optionally, damage categories, the types of damage included in each damage category, subcategories, and / or the types of damage included in each subcategory are determined, for example, based on labeled training data identified for at least two different types of damage. Alternatively, the definition of damage categories and the determination of subcategories can be performed without labeled training data and without prior knowledge of the types of damage that may occur in a particular application of the method. In this case, damage categories are predefined, for example, based on the measured variable Vi, and subcategories are determined, for example, based on data D recorded during monitoring. The latter is obtained, for example, by determining, for at least some or each of the damages occurring during monitoring, which of the variables Vi measured by the measuring device Mi can detect the corresponding damage earliest, and determining how the measured values ​​Vi of the other variables Vi are affected by the damage. Next, at least one subcategory is determined based on the corresponding ways in which the previously determined variable Vi, which can be detected earliest, and the other variables Vi are affected. This determination of subcategories offers the advantage that new subcategories can be added when a new type of damage occurs during the execution of the method that is not included in one of the previously determined subcategories.

[0137] One or more damage categories and / or one or more subcategories are applied, for example, to classify the detected damage accordingly. This is possible even when no information about the types of damage included in the corresponding damage category or subcategory is available. This information is preferably added when it becomes available. To this end, the method may include determining, at least once or repeatedly, the dominant damage type within the pipeline system after determining that the detected damage belongs to one of the damage categories and / or one of the subcategories, for example by examining the dominant condition within the pipeline system, as described above in the context of determining the training data. The damage type thus determined is then stored as a damage type included in the corresponding damage category and / or the corresponding subcategory. Subsequently, whenever a detected damage is determined to have a type included in the corresponding damage category and / or the corresponding subcategory, the type of damage included in the corresponding damage category and / or the corresponding subcategory is indicated.

[0138] Determining the type of damage is particularly useful for different types of deposits. One reason is that it allows for the modification of the nature of the deposit layer formed within the piping system to be inspected. While soft deposit layers, even when they have become quite thick, can be removed fairly easily by cleaning the piping system, hardened deposit layers within the piping system can be much more difficult to remove. Here, repeatedly determining the type of damage caused by the deposit, particularly regarding the type of damage specified by the density and / or stiffness of the deposit layer, provides valuable information that is preferably applied to scheduling the cleaning of the piping system accordingly. In this case, the cleaning of the piping system is scheduled and performed, for example, based on the cleanability of the deposit layer associated with the type of damage already determined by the monitoring method.

[0139] In applications involving repetitive cleaning of piping systems, such as periodic cleaning or cleaning based on monitoring results MR provided by a monitoring method, the method may additionally include a method step of determining the effectiveness of a cleaning for at least one or each cleaning performed. In this case, providing the monitoring results MR may include, for example, providing an output notifying the effectiveness of the cleaning. As an additional or alternative option, a warning may be issued when cleaning is determined to be ineffective, and / or additional cleaning or another remedy may be performed in the event of ineffective cleaning. The effectiveness of cleaning is determined, for example, by or based on the difference between at least one of the deviations ΔB determined by data D recorded before the corresponding cleaning and at least one of the deviations ΔB determined by data D recorded after the corresponding cleaning. The cleaning time during cleaning may be defined, for example, in the form of a cleaning time interval ΔTc, which begins at the start of the corresponding cleaning and ends at the end of the corresponding cleaning. Furthermore, the calculation unit 3 is configured to perform the determination of effectiveness based on the corresponding cleaning time interval ΔTc and the deviations ΔB determined by the calculation unit 3 based on data D recorded before and after the corresponding cleaning time interval ΔTc.

[0140] One or more cleaning time intervals ΔTc are provided to the computing unit 3, for example, by the user of the method via an interface 59 connected to or communicating with the computing unit 3, or by a higher-level unit 7 or another control system that initiates and / or controls the cleaning performance connected to or communicating with the computing unit 3. Alternatively, the computing unit 3 may be trained or designed to learn the determination of the cleaning time interval ΔTc and subsequently determine the cleaning time interval ΔTc itself based on the recorded data D. The training or learning for determining the cleaning time interval ΔTc is performed, for example, based on labeled training data recorded during the cleaning time interval ΔTc. As an example, the computing unit 3 determines the cleaning time interval ΔTc, for example, based on data D recorded during monitoring by identifying time intervals during which the measured values ​​Vi of all variables Vi exhibit a time-related distribution that conforms to the expected time-related distribution during the cleaning time interval ΔTc, which is determined based on labeled training data. Alternatively, an unsupervised learning method may be performed to learn the determination of the cleaning time interval ΔTc. This is possible because cleaning is always associated with significant sudden changes in the measured value vi, which can be easily detected by unsupervised learning methods. In this scenario, the learning method thus determined is then applied to determine the cleaning interval ΔTc based on the recorded data D. Unsupervised learning offers the advantage of being able to be performed without labeled training data. This is particularly useful when the pipeline system is rarely cleaned.

[0141] In embodiments including a monitoring method for determining the remaining time RT, each remaining time RT determined after at least one cleaning is preferably determined solely based on a deviation ΔB, which is based on data D recorded after the last cleaning. In this respect, the determination of the cleaning time interval ΔTc performed by the calculation unit 3 offers the advantage that this "reset" of the determination of the remaining time RT can be performed automatically by the calculation unit 3 without requiring any external input regarding the (one or more) cleanings performed.

[0142] List of reference numbers

[0143] 1. Pipeline 33 Measuring Electrode

[0144] 3. Calculation Unit 35. Reference Electrode

[0145] 5. Memory 37. Measuring tube

[0146] 7. Upper-level unit 39 Transducer

[0147] 9. Edge devices 41. Electronic components

[0148] 11 Vibrating components 43 Acoustic waveguide

[0149] 13 Vibrating components 45 Interdigitated transducers

[0150] 15 Drivers 47 Electronic Components

[0151] 17 Sensors 48 Temperature Sensors

[0152] 19 Electronic Components 49 Measuring Tubes

[0153] 21-electrode 51-antenna

[0154] 23 Electronic components 52 Lining

[0155] 25 Measuring tubes 53 Electronic components

[0156] 27 Coil 55 Inspection Probe

[0157] 29 Current generator 57 Stern surface

[0158] 31 Electronic Components 59 Interfaces

Claims

1. A method for monitoring a dominant condition within a piping system, the piping system comprising at least one pipe (1), the damage being attributed to buildup, abrasion, or corrosion caused by one or more fluids flowing through the piping system; the method comprising the steps of: At least two measuring devices (Mi) are installed on the piping system; wherein each measuring device (Mi) is configured to measure one or more variables (Vi) indicating the damage, for different types of damage corresponding to the predominant condition within the piping system; and wherein the variables (Vi) measured by the different measuring devices (Mi) include at least two or at least three variables (Vi), each variable (Vi) exhibiting a different dependence on the damage; During the operation of the pipeline system, data (D) is continuously recorded, including a time series of measured values ​​(vi) of a variable (Vi) measured by the measuring device (Mi) and its measurement time (t); Based on the training data included in the data (D), a dynamic reference state (BR) of the variable (Vi) is determined, the dynamic reference state (BR) corresponding to the time-related distribution of the expected value of the variable (Vi) when the measuring device (Mi) is undamaged, wherein the dynamic reference state (BR) is determined such that it reflects the value of the variable (Vi) and its time correlation and interdependence; Repeatedly determine the deviation (ΔB) between the monitored behavior (BM) and the reference behavior (BR) corresponding to the time-related distribution of the measured values ​​(vi) of the variable (Vi) determined based on data (D) recorded during monitoring, wherein the monitored behavior (BM) is determined such that it reflects the value and time correlation and interdependence of the variable (Vi); and Based on the deviation (ΔB), the monitoring result (MR) is determined and provided at least once or repeatedly by performing at least one of the following: a) When the deviation (ΔB) exceeds the first deviation range (R1), detect the damage and provide an output notifying the damage. b) By performing a time series forecast that predicts the remaining time until the deviation (ΔB) exceeds a second deviation range (R2) corresponding to a predetermined limit, and providing an output that provides a notification of the remaining time (RT) given by or corresponding to the time predicted by the time series forecast, the remaining time (RT) until the degree of damage to the dominant condition in the pipeline system exceeds the predetermined limit is determined.

2. The method according to claim 1, wherein, The method described is a computer-implemented method.

3. The method according to claim 1, wherein: a) The variable (Vi) is stationary, and the reference behavior (BR) includes the stationary behavior of the variable (Vi) describing the linear or nonlinear time dependence of the variable (Vi) and the fixed correlation between the interdependent variables (Vi). or b) The variable (Vi) is stationary during a specific identifiable phase, which is a phase identifiable and / or identifiable based on the properties of the measured value (vi) of the specific phase and / or a phase given by the following time intervals: during which the piping system operates in a specific operating mode or during which a specific process step of a process performed on or using the piping system is carried out, and the reference state (BR) includes the stationary state of the variable (Vi) describing the time dependence of the variable (Vi) and the correlation between the interdependent variables (Vi) during these phases; And the monitored behavior (BM) is determined based on the dataset included in the data (D) recorded during a specific phase of the monitoring period; or c) The variable (Vi) is a non-stationary variable that describes a reproducible pattern during a specific identifiable phase, which is a phase identifiable and / or identifiable based on the properties of the measured values ​​(vi) of the specific phase, and / or a phase given by the time interval during which the piping system operates in a specific operating mode or a specific process step of a process performed on or using the piping system is carried out during the time interval, and the reference behavior (BR) includes the characteristics of the pattern described by the non-stationary variable (Vi) during these phases and the correlation between the interdependent variables (Vi); And the monitored behavior (BM) is determined based on the dataset included in the data (D) recorded during a specific phase that occurs during the monitoring period.

4. The method according to any one of claims 1 to 3, comprising the following steps: For each variable (Vi), based on the training data, determine the time scale of change for the corresponding variable (Vi); Based on the time scale, the data (D) is filtered such that the filtered data (FD) includes only the data (D) recorded during the time interval during which the measurement (vi) of each of the variables (Vi) changes over time according to the time scale determined for the corresponding variable (Vi); as well as The determination of the reference behavior (BR) and each monitored behavior (BM) is performed based on the filtered data (FD).

5. The method according to any one of claims 1 to 3, comprising performing the following steps at least once or repeatedly: For at least two or each of the variables (Vi), a time series prediction is performed based on the measured value (vi) of the corresponding variable (Vi) included in the data (D) recorded during the monitoring period or the filtered data (FB) obtained by filtering the data (D) recorded during the monitoring period, predicting the remaining variable-specific time (RTvi) until the measured value (vi) of the corresponding variable (Vi) exceeds a predetermined variable-specific range. The shortest of the variable-specific remaining time (RTvi) is determined as the minimum remaining time (RTmin) until the damage caused by the dominant condition within the pipeline exceeds the predetermined limit; and at least one of the following is performed: Provides the output of a measuring device (Mi) that provides notification of the minimum time (RTmin), determines the shortest one of the variable-specific remaining times (RTvi), and / or measures the variable (Vi) that determines the shortest one of the variable-specific remaining times (RTvi); Based on the minimum time (RTmin), perform a likelihood check on the remaining time (RT) determined based on the deviation (ΔB); as well as A warning is issued when the difference between the remaining time (RT) and the minimum time (RTmin) exceeds a predetermined threshold.

6. The method according to any one of claims 1 to 3, comprising the following steps: Determine training data for the markers, the training data comprising or consisting of a dataset of recorded data (D) already recorded during damage time intervals, wherein during each of the damage time intervals, the measuring device (Mi) suffers damage corresponding to a known or subsequently determined damage type corresponding to the dominant condition within the piping system; wherein the training data for the markers comprises training data for markers for at least two different types of damage; and perform at least one of the following: a) Based on training data labeled for each of the different types of damage, determine criteria for determining the existence of a corresponding damage type based on the recorded data (D); when the data (D) recorded during monitoring meets the criteria determined for the corresponding damage type, determine the existence of one of the at least two different types of damage at least once or repeatedly based on the criteria, and provide an output notifying the determined damage type; and b) For each of the different types of damage, based on labeled training data, determine the type-specific direction (dj) by which the monitored behavior (BM) will deviate from the reference behavior (BR) when the corresponding damage type is present, wherein each type-specific direction (dj) is determined in the form of a vector defined in a multidimensional coordinate system including coordinate axes for each variable (Vi), for at least one of the monitored behaviors (BM) determined based on the recorded data (D) or filtered data (FD) obtained by filtering the recorded data (D), determine the monitoring direction (dm) by which the corresponding monitored behavior (BM) deviates from the reference behavior (BR) in the multidimensional coordinate system, and based on the monitoring direction (dm) and the type-specific direction (di), determine the damage type of the condition in which the damage is dominant in the pipeline system, and provide the damage type thus determined.

7. The method according to any one of claims 1 to 3, further comprising the step of: Perform at least one of the following: a) Define at least one damage category, wherein each damage category includes at least one damage type and is specified by a category variable (Vk), said category variable (Vk) being given by one of the measured variables (Vi) capable of earliest detecting damages including one or more damage types in the corresponding damage category; and b) Determine at least one subcategory, wherein each subcategory includes at least one type of damage and is specified by a category variable (Vk) and a reference mode for each of a set of at least one subcategory variable (Vn), the category variable (Vk) being given by one of the variables (Vi) capable of detecting damage of one or more types of damage included in the corresponding subcategory earliest, wherein each subcategory variable (Vn) is given by one of the measured variables (Vi) and is different from the category variable (Vk), and wherein each reference mode represents the manner in which the corresponding subcategory variable (Vn) is affected by damage of one or more types of damage included in the corresponding subcategory; The method further includes the following steps: Based on the data (D) recorded during monitoring, determine which of the measured variables (Vi) enables the earliest detection of damage developing within the pipeline system. The variable (Vi) enabling the earliest detection may be determined as one of the measured variables (Vi) that first exceeds or falls below a variable-specific threshold defined for that variable (Vi) and / or given by one of the measured variables (Vi) that first exceeds or falls below a variable-specific threshold defined for that variable (Vi), or may be determined as one of the following variables (Vi) and / or given by one of the following: for said variable (Vi), a time series prediction of the shortest variable-specific remaining time (RTvi) before the measured value (vi) of the corresponding variable (Vi) exceeds a predetermined variable-specific range; and Perform at least one of the following: a) Identify the damage as included in the damage category specified by the category variable (Vk), and provide an output that informs the damage category, wherein the category variable (Vk) is equal to the variable (Vi) that enables the earliest detection; and b) For each subcategory variable (Vn) of at least one or each subcategory specified by a category variable (Vk) equal to the earliest detectable variable (Vi), determine how the measured value (vn) of the subcategory variable (Vn) is affected by the damage; if the measured value (vn) of the subcategory variable (Vn) of a particular subcategory conforms to the corresponding reference mode, determine the damage as damage belonging to the particular subcategory of the subcategory, and provide an output notifying the particular subcategory of the subcategory.

8. The method according to claim 7, wherein, Each reference mode represents the way, given by the damage, that causes the corresponding subclass variable (Vn) to increase, decrease, be above or below a reference value, or be above or below a given threshold.

9. The method according to claim 7, comprising the following steps: Perform at least one of the following: a) Predefine at least one damage category based on the measured variable (Vi); as well as b) Determine at least one of the subcategories by: b1) Based on data (D) recorded during monitoring, for at least some or each of the damages that occurred during monitoring, determine which of the variables (Vi) measured by the measuring device (Mi) was able to detect the corresponding damage earliest, and determine the manner in which the measured values ​​(vi) of the other variables (Vi) have been affected by the damage; And b2) Based on the earliest continuously determined variable (Vi) that can be detected and the correspondence that has affected other variables (Vi), determine at least one subclass; as well as Then perform at least one of the following: a) apply one or more of the damage categories and / or one or more of the subcategories to classify the detected damage; and b) after determining at least once or repeatedly that the detected damage belongs to a damage type included in one of the damage categories and / or one of the subcategories, perform the following steps: determine the damage type that predominates within the piping system; store the determined damage type as a damage type included in the corresponding damage category and / or the corresponding subcategory; and whenever the detected damage is determined to be a damage type included in the corresponding damage category and / or the corresponding subcategory, subsequently indicate one or more types of damage included in the corresponding damage category and / or the corresponding subcategory.

10. The method according to claim 6, wherein, The different types of damage include at least one of the following: Types of damage caused by accumulation; At least two different types of damage caused by the stacking, each type of damage being specified by a specific type of stacking and / or by a predefined range of at least one property of the stacked layer formed by the stacking, the property including at least one of the following: the thickness of the stacked layer, the stiffness of the stacked layer, and the density of the stacked layer; Types of damage caused by corrosion or wear; as well as At least two different types of damage, said at least two different types of damage caused by corrosion or wear and specified by a predefined range of material removal caused by corrosion or wear.

11. The method according to claim 6, wherein, The damage in the condition is caused by accumulation, and the different types of damage include at least two different types of damage caused by accumulation; the method includes the following steps: Based on the data (D) recorded during monitoring, the type of damage is repeatedly determined; and The cleaning of the piping system is scheduled and performed based on the cleanability of the deposit layer associated with the identified damage type.

12. The method according to any one of claims 1 to 3, wherein, The variables (Vi) measured by the measuring device (Mi) include at least two of the following: a) At least one electrical variable, each electrical variable being given by, related to, or determined based on at least one electrical property affected by corrosion, wear, and / or buildup; b) at least one vibration variable, each vibration variable being given by, related to, or determined based on at least one vibration property of the vibration of a vibrating component (11, 13) of one of the pipes (1) or one of the measuring devices (M1, M2) exposed to the one or more fluids; and c) At least one signal propagation variable, each signal propagation variable being given by, related to, or determined based on at least one signal property of the signal received by the measuring devices (M6, M7, M8), the measuring devices (M6, M7, M8) measuring the corresponding signal propagation variable along a signal propagation path that extends along and / or through at least one surface area exposed to one or more fluids affected by corrosion, wear, or buildup occurring on at least one surface area.

13. The method according to any one of claims 1 to 3, wherein, The measuring device (Mi) includes at least one or at least two of the following: At least one vibration device, the at least one vibration device comprising a vibrating component (11, 13) exposed to the one or more fluids, a driver (15) configured to cause the vibrating component (11, 13) to vibrate in at least one predetermined vibration mode, at least one sensor (17) for sensing the generated vibrations, and electronics (19) configured to determine and provide a measurement (vi) of at least one variable (Vi), each variable being given by a vibration variable, the vibration variable being given by, related to, or determined based on at least one vibration property of the vibration of the vibrating component (11, 13); the one or more vibration variables including: frequency, resonant frequency, amplitude, and / or damping of the vibration of the vibrating component (11, 13) for at least one of the vibration modes, and / or stiffness of the vibrating component (11, 13) relative to at least one of the vibration modes; At least one measuring device (M3) or accelerometer is installed on one of the pipes in the pipe (1) and measures at least one variable (Vi) given by a vibration variable, which is given by, related to or determined based on at least one vibration property of the vibration of the pipe (1); At least one measuring device (M4, M5) is configured to measure at least one variable (Vi) given by an electrical variable, said electrical variable being given by, related to, or determined based on at least one of the following: the impedance, resistance, conductivity, and at least one other electrical property of electrical connections and / or electrical components affected by corrosion, wear, and / or buildup caused by said one or more fluids; and At least one measuring device (M6, M7, M8) is configured to measure at least one variable (Vi) given by a signal propagation variable, the signal propagation variable being given by, related to, or determined based on at least one signal property of a signal received by the respective measuring device (M6, M7, M8) along a signal propagation path, the signal propagation path extending along and / or through at least one surface region exposed to the one or more fluids, wherein the at least one signal property includes at least one of the following: signal attenuation, signal amplitude, signal reflection properties, properties related to or determined based on the amplitude spectrum and / or phase spectrum, signal propagation time, and at least one other signal property affected by corrosion, wear, or buildup occurring on the at least one surface region.

14. The method of claim 13, wherein: a) The at least one measuring device (M1, M2) includes at least one of the following: A first measuring device (M1), a level switch, or a density measuring device, wherein the vibrating component (11) is provided by or includes an oscillating element extending into one of the pipes (1); and A second measuring device (M2), a Coriolis measuring device, or a Coriolis measuring device measures at least one of the flow rate, density, and viscosity of the one or more fluids; wherein the vibrating component (13) is provided by or includes a pipe connected to or inserted into one of the pipes in the pipe system, such that at least a portion of the one or more fluids flowing through the pipe system flows through the pipe. b) At least one measuring device (M4, M5) configured to measure at least one variable (Vi) given by an electrical variable includes at least one of the following: A measuring device (M4) or conductivity sensor, the measuring device (M4) or conductivity sensor comprising two electrodes (21) extending into the pipe (1) and an electronic device (23) connected to the electrodes (21), and the electronic device (23) being configured to determine and provide a measured value (vi) of at least one electrical variable measured by the measuring device (M4); and A measuring device (M5) provided by a magnetic induction flowmeter, the magnetic induction flowmeter comprising a tube (25), a set of two or more electrodes, and an electronic device (31), the tube (25) being connected to or inserted into one of the pipes (1) of the pipeline (1) such that at least a portion of one or more fluids flowing through the pipeline system flows through the tube (25), the set of two or more electrodes being electrically coupled to or directly exposed to the one or more fluids flowing through the tube (25), and the electronic device (31) being connected to the electrodes and configured to determine and provide at least one electrical variable measured by the magnetic induction flowmeter; and / or c) At least one measuring device (M6, M7, M8) configured to measure at least one variable (Vi) given by the signal propagation variable includes at least one of the following: Measuring devices (M6) provided by ultrasonic equipment, ultrasonic flow meters, clamp-on ultrasonic flow meters or ultrasonic concentration meters; A measuring device (M7) comprising an acoustic waveguide (43) exposed to one or more fluids flowing through the piping system, transmitting interdigitated transducers (45) and receiving interdigitated transducers (45) spaced apart from each other on the acoustic waveguide (43), and electronic devices (47) connected to the interdigitated transducers (45) and configured to determine and provide the at least one signal propagation variable; and Measuring equipment (M7) provided by microwave equipment, microwave flow meter or microwave concentration meter.

15. The method according to any one of claims 1 to 3, wherein, The damage in the condition is caused by accumulation, and the method includes the following steps: Cleaning of the piping system shall be performed at least once, repeatedly, and / or based on the monitoring results (MR). For at least one cleaning, the effectiveness of the cleaning is determined as the difference between at least one deviation (ΔB) determined based on data (D) recorded before the corresponding cleaning and at least one deviation (ΔB) determined based on data (D) recorded after the corresponding cleaning, or the effectiveness of the cleaning is determined based on that difference; and Perform at least one of the following: provide output informing of the effectiveness of the cleaning, issue a warning if the cleaning is ineffective, and perform additional cleaning or another remedy if the cleaning is ineffective.

16. The method according to any one of claims 1 to 3, wherein, The damage in the condition is caused by buildup, and the method includes the following steps: performing a cleaning of the piping system at least once; and determining each remaining time (RT) to be determined after a cleaning based solely on a deviation (ΔB), which has been determined based on data (D) recorded after the last cleaning.

17. The method according to claim 15, wherein, Each cleaning time interval (ΔTc) for cleaning the piping system is: Provided by the user of the method, by the superior unit (7), or by the control system that initiates and / or controls the performance of the cleaning; or The calculation unit (3) is determined to perform the determination of the cleaning time interval (ΔTc) and performs each determination of the validity and / or the remaining time (RT) based on the cleaning time interval (ΔTc) determined by the calculation unit (3) based on the data (D).

18. The method according to claim 16, wherein, Each cleaning time interval (ΔTc) for cleaning the piping system is: Provided by the user of the method, by the superior unit (7), or by the control system that initiates and / or controls the performance of the cleaning; or The calculation unit (3) is determined to perform the determination of the cleaning time interval (ΔTc) and performs each determination of the cleaning effectiveness and / or the remaining time (RT) based on the cleaning time interval (ΔTc) determined by the calculation unit (3) based on the data (D).

19. The method according to any one of claims 1 to 3, comprising at least one of the following steps: a) Determine the magnitude of the deviation (ΔB), and determine and provide the extent of damage to the dominant condition within the piping system given by or corresponding to the magnitude of the deviation (ΔB); b) An alarm is issued when the deviation (ΔB) exceeds the third deviation range (R3); c) When the deviation (ΔB) occurs within the first deviation range (R1), provide an output informing the piping system of its undamaged condition; and d) The remaining time (RT) before the maintenance action is scheduled and executed, where, The maintenance action includes cleaning the piping system and / or at least one component (C) in or installed on the piping system that is exposed to the one or more fluids, or includes repairing or replacing at least one pipe (1) and / or at least one component (C) in or installed on the piping system that is exposed to the one or more fluids.

20. A monitoring system for performing the method according to any one of claims 1 to 19, comprising: Measuring device (Mi); as well as A computing unit (3) is directly or indirectly connected to or communicates with each of the measuring devices (Mi); The computing unit (3) is configured to receive the data (D) and record the data (D) by storing the data (D) at least temporarily in a memory (5) associated with the computing unit (3); and The computing unit (3) is implemented to determine the reference behavior (BR). To determine the deviation (ΔB) and to determine and provide the monitoring results (MR).

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