Method for monitoring operation of compressor and its support device

Abstract

The invention relates to a method for monitoring the operation of a compressor and its support equipment. According to one embodiment, there is disclosed a method for monitoring the operation of a compressor, the method comprising iteratively performing the following steps: measuring (107) a process amount indicative of an instantaneous operation of the compressor; and estimating (102) a process amount of the compressor based on one or more setting parameters (101) of the compressor using a model; comparing (103) the estimated process quantity with the measured process quantity, thereby obtaining an instantaneous performance indicator (201); characterized in that the method further comprises the steps of: determining a degradation parameter (108) based on a series of consecutive instantaneous performance metrics; and wherein the estimation (102) is further made on the basis of a performance indicator (108); the operation is reported based on the degradation parameter (108).

Description

Technical Field

[0001] The present invention relates to a method for monitoring a compressor and support equipment for such a compressor. Background Art

[0002] A compressor is a mechanical machine designed to provide gas (such as ambient air) at a relatively high pressure for applications in industrial processes and / or the medical sector. Depending on the required pressure, the desired application, the desired result and other boundary conditions, there are various compressor technologies to choose from, such as axial compressors vs. centrifugal compressors, and oil-free compressors vs. oil-lubricated compressors.

[0003] Furthermore, the compressor may be equipped with peripheral equipment, also referred to as support equipment, such as coolers, oil separators, filters or air filters, dryers, drive motors and the like.

[0004] In addition, there may also be a cooling and / or lubrication circuit with a coolant and / or lubricant other than oil, such as water. When oil is mentioned as a coolant and / or lubricant, it should be understood that this may also include the use of another type of coolant and / or lubricant, such as water.

[0005] Furthermore, it is obvious that in most industrial environments and / or the medical sector, high availability of the compressor is desired without necessarily compromising performance. However, like most mechanical machines, some form of degradation will inevitably occur over time due to the presence of rotating parts, contamination in the ambient air surrounding the machine, exposure to large temperature differences, loss of oil, and other internal or external influences that may hinder and / or degrade the normal operation of the compressor.

[0006] Therefore, there is a need for a method of monitoring the operation of the compressor and, if necessary, the peripherals supporting the compressor (if any), so as to be able to warn or at least inform the operator, fleet manager, etc. that normal operation is compromised or that a more relaxed approach is no longer optimal.

[0007] It is therefore an object of the present invention to provide a method for monitoring a compressor and support equipment of such a compressor. Summary of the invention

[0008] According to the present invention, the purpose of the above confirmation is achieved by providing a computer-implemented method for monitoring the operation of a compressor and / or its supporting equipment according to the first claim according to the first aspect of the present invention, the method comprising iteratively performing the following steps: measuring one or more process quantities indicating the instantaneous operation of the device and / or the compressor; estimating one or more process quantities of the device and / or the compressor based on one or more setting parameters of the compressor using a model; comparing the estimated process quantity with the measured process quantity, thereby obtaining an instantaneous performance indicator, characterized in that the method also includes the following steps: determining a degradation parameter based on a series of continuous instantaneous performance indicators, and wherein the estimation is further performed based on the degradation parameter; followed by a step of reporting the operation based on the degradation parameter.

[0009] The measuring step is defined as the quantitative determination of a quantity obtained from one or more observations, recordings or samplings at a specific measurement location with the aid of a measuring instrument suitable for making measurements, such as a sensor for expressing the observed quantity as a number with associated units that can be compared with other values ​​of the same quantity.

[0010] The estimation step is defined as the determination of the value of a quantity based on measured process quantities and / or setting parameters using a scientific model representing the technical process and / or the equipment, with measured process quantities and / or setting parameters as input and a value that needs to be determined based on one or more calculations and is therefore estimated as output.

[0011] In a first step, process quantities indicative of the instantaneous operation of the compressor and / or the equipment are measured. These process quantities are the temperature of the gas, the current of the compressor drive motor, the rotational speed of the rotating parts of the compressor, the inlet pressure of the compressor, the outlet pressure of the compressor, the ambient pressure around the compressor, the humidity level of the gas, the flow rate of the gas and / or the valve position. It should also be noted that this list is not exhaustive and is therefore not limited to the quantities mentioned. On the other hand, it should also be noted that not all process quantities are measured, but some of them.

[0012] In a second step, one or more process quantities of the device and / or the compressor are estimated. The estimation is based on one or more setting parameters of the compressor (used as input to a scientific model of the compressor), optionally in combination with the device, wherein the output of the model is the estimated process quantity. According to one embodiment, the estimation can also be based on measured process quantities, in other words, other process quantities can be derived based on the measured process quantities. Note that, therefore, estimating the process quantity is a calculation as already mentioned.

[0013] The model used is initially a model of the compressor and / or supporting equipment without defects, in other words a model of an ideal machine as compressor and / or supporting equipment.

[0014] In this text, later on, reference will be made to machines, compressors and / or equipment, but further note that for the purpose of discussing the present invention, these terms are interchangeable. When the term machine is referred to, it may refer to the compressor, the support equipment, or a combination of both.

[0015] The model representing the machine is a scientific model, such as a physical model or a multi-physics model, comprising a system of differential equations and / or empirical relations describing different physical parts of the machine and related to each other by one or more common variables.

[0016] It should also be noted that the first step and the second step can be performed in parallel at the same time. Therefore, the terms "first" and "second" used are used to distinguish different steps without indicating a specific time sequence and / or hierarchy between the two steps.

[0017] Subsequently, the measured process quantity is compared with the estimated process quantity. Since the process quantity is initially estimated using a model of an ideal machine (i.e. a machine without any defects), the difference (also called delta) between the measured process quantity and the estimated process quantity will in principle indicate a deviation behavior between the ideal or healthy machine and the actual machine. The larger this difference is, the greater the deviation behavior of the machine is compared to a healthy machine.

[0018] The difference between the measured process quantity and the estimated process quantity is further referred to as a performance indicator, since it is in principle an indication of the performance of the machine compared to an ideal machine.The performance indicator calculated for a specific point in time is then an instantaneous performance indicator at that specific point in time.

[0019] The step of estimating the process quantity and the step of measuring the process quantity are performed iteratively, in other words, these steps are repeatedly performed, thereby obtaining a series of continuous instantaneous performance indicators.

[0020] According to the novel innovative concept of the present invention, the computer-implemented method further comprises the following steps: determining a degradation parameter based on a series of continuous instantaneous performance indicators, and further performing an estimation based on the degradation parameter.

[0021] In principle, likewise, a series of consecutive instantaneous performance indicators calculated at a series of consecutive time points is an indication of the deviation behavior of the machine compared to a healthy machine in principle, but in this case not instantaneously but over a certain period of time. The period of time then contains consecutive time points. For example, if the series of instantaneous performance indicators shows a linear downward trend, according to its definition, this indicates that the deviation behavior is gradually decreasing. The instantaneous performance indicator is then defined as the difference between the estimated value on the one hand and the measured value on the other hand. As a result, the performance indicator will decrease with increasing degradation. This gradually decreasing deviation behavior further indicates decay, aging or degradation of the machine. Based on the series of consecutive instantaneous performance indicators, the degradation parameters defined above are determined or derived.

[0022] In other words, to determine the degradation parameter, a certain amount of data over a predefined limited period of time is analyzed, during which the degradation parameter is assumed to be constant. This batch of data consists of a series of continuous instantaneous performance indicators, which further reduces the impact of potential noise on the data. Over a longer period of time, both the performance indicator and the degradation parameter will show a decreasing or increasing trend according to their definition.

[0023] It is noted that aging, decay or degradation of mechanical machines, although undesirable, is inevitable even under ideal conditions and will occur from the moment it is put into service and will continue to occur during operation. This degradation is caused by friction of moving parts, corrosion of materials, deformation such as fatigue or creep of materials, metal fatigue or permanent deformation, external factors such as contamination and the presence of dust particles, seasonal temperature differences, oil loss and / or other factors known to the skilled person.

[0024] In such a case, a series of instantaneous performance indicators will gradually decrease according to their definition. On the other hand, the series may also have abrupt or abrupt changes, so that large differences can be noticed throughout the series. This can indicate the presence of a defect or malfunction that deviates from the normal degradation of the machine.

[0025] Subsequently, an estimation of the process quantity will also be performed based on the determined degradation parameter.Finally, the operation of the compressor and / or the supporting equipment can then be reported based on the degradation parameter.

[0026] An advantage of this method for monitoring the operation of a compressor and / or supporting machine is that in this way, undesirable but natural or expected degradation of the machine in normal operation is taken into account. This provides a more correct and accurate picture of the actual operation of the machine.

[0027] On the other hand, as already mentioned, a sudden change will then indicate an acute defect or failure of the machine. In addition, in this case, the machine operator will get a better picture of the operation of the compressor and / or the supporting equipment.

[0028] According to one embodiment, the method further comprises the step of updating the model based on the degradation parameter.

[0029] The model that initially represents an ideal machine will also include parameters that make the model become representative of a machine that is already in operation. This results in a model that is more representative of the actual machine. As a result, the estimated value of the process quantity is closer to the actual value.

[0030] According to one embodiment, the model may also include a parametric model including one or more model parameters such as heat transfer coefficients, efficiency parameters, temperature correction parameters, cooling parameters, speed correction parameters, friction parameters, or any other parameters suitable for modeling the machine.

[0031] The parametric model comprises a set of model parameters linked to each other directly or indirectly via a set of variables. The inputs of the parametric model are then the setting parameters of the machine corresponding to the variables of the model and a selection of measured process quantities, after which the process quantities can be estimated based on the model parameters. Furthermore, some of the measured process quantities can be used to verify the outputs of the model. Then, a step of updating the model is performed by updating the model parameters.

[0032] According to one embodiment, the computer-implemented method for monitoring the operation of a compressor and / or support equipment further comprises the step of deriving a health indicator based on the model parameters.

[0033] A parametric model including model parameters describes the operation of the machine. Because the model parameters are iteratively updated to make the estimated values ​​consistent with the observed values ​​based on the measurements while the operation of the machine is monitored according to the described method, these model parameters also represent its operation. The health indicator then represents the set of model parameters with at least a single value, whereby the health indicator represents the operation of the compressor and / or the support equipment. In other words, at least one value (the health indicator) represents the condition or operation of the compressor and / or the support equipment. Alternatively, multiple health indicators can be derived based on multiple partial selections of the model parameters. In addition, it is noted that the health indicator already takes into account possible degradation of the machine. Therefore, the health indicator is a correct representation of the actual machine condition and therefore not a correct representation of an ideal machine. In addition, as mentioned above, these steps will further limit the possible impact of noise on the measured values.

[0034] In an optional step, health indicators can also be reported.

[0035] According to an embodiment of the invention, the method further comprises the step of limiting the range of the setting parameter of the compressor based on the degradation parameter.

[0036] If it can be inferred from the deterioration parameters that the machine is working suboptimally or there is a risk that the machine will work suboptimally, this can already be anticipated by limiting the range of setting parameters. This prevents the risk of sudden failures based on setting parameters that may have a negative impact on the further operation of the machine and also prevents any further damage to the machine in case the machine continues to operate. These setting parameters include pressure, flow rate, optionally humidity level and / or power of the compressor or other possible setting parameters.

[0037] Another advantage is that the availability of the machine can be optimized. Although the machine will then operate suboptimally, it will be possible to ensure that it does remain operational. This can then be further anticipated by scheduling maintenance in a timely manner. In addition, the operation of the compressor room controller used to control the compressor unit can also be optimized.

[0038] Furthermore, the method may also comprise a step of shutting down the compressor when the degradation parameter exceeds a predefined value. Note that this is a limiting case of limiting the range of the setting parameter, which in turn limits the range to a limit value, i.e. a value that completely prevents operation. This step will be performed, for example, if the value of the degradation parameter indicates an acute danger, or when urgent maintenance needs to be carried out.

[0039] According to a second aspect of the present invention, a data processing system is disclosed, the data processing system comprising a processing unit configured to perform the method according to the first aspect of the present invention.

[0040] According to a third aspect of the present invention, a computer program product is disclosed, the computer program product comprising computer executable instructions for performing the method of the first aspect when the program is executed on a computer.

[0041] According to a fourth aspect of the present invention, a computer readable storage device comprising the computer program product of the third aspect is disclosed.

[0042] According to a fifth aspect of the present invention, a compressor comprising a data processing system according to the second aspect of the present invention is disclosed.

[0043] According to a sixth aspect of the present invention, a method for monitoring the operation of a compressor and / or its supporting equipment is disclosed, the method comprising iteratively performing the following steps: measuring one or more process quantities indicating the instantaneous operation of the device and / or the compressor; and estimating one or more process quantities of the device and / or the compressor based on one or more setting parameters of the compressor using a model; comparing the estimated process quantities with the measured process quantities, thereby obtaining an instantaneous performance indicator, characterized in that the method further comprises the following steps: determining a degradation parameter based on a series of continuous instantaneous performance indicators; and wherein the estimation is further performed based on the degradation parameter; and reporting the operation based on the degradation parameter.

[0044] Additionally, one or more process quantities may be estimated based on the measured process quantities.

[0045] Furthermore, the method comprises the step of updating the model based on the degradation parameter.

[0046] The process quantity includes one or more of the group of temperature, flow, velocity, inlet pressure, outlet pressure, ambient pressure, humidity, flow rate, and / or valve position.

[0047] The model may include a parameter model including one or more model parameters. Thus, the updating may be performed by updating the model parameters. Furthermore, the method may include the step of deriving a health indicator based on the model parameters. Thus, the model parameters may include one or more of the group consisting of a heat transfer coefficient, an efficiency parameter, a temperature correction parameter, a cooling parameter, a speed correction parameter, and a friction parameter.

[0048] Furthermore, the method may comprise the step of limiting the range of setting parameters of the compressor based on the degradation parameter.The setting parameters may then comprise one or more of the group of pressure, flow rate, humidity level, power.

[0049] Furthermore, the method may comprise the step of shutting down the compressor when the degradation parameter exceeds a predefined value. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The present invention will be further illustrated with reference to the accompanying drawings, in which:

[0051] Figure 1 A method for calculating instantaneous performance indicators of a compressor and / or supporting equipment is schematically illustrated;

[0052] Figure 2 schematically illustrates a method for monitoring the operation of a compressor and / or supporting equipment according to one embodiment of the present invention;

[0053] Figure 3 A physical model representing the operation of the compressor and supporting equipment is illustrated;

[0054] Figure 4 Another model representing the operation of the compressor and supporting equipment is illustrated;

[0055] Figure 5 A schematic diagram of a closed cooling circuit including oil and the temperature increase of the oil is illustrated;

[0056] FIG. 6A to FIG. 6C The diagram shows the Figure 3 The results of regression training of the parameters and / or coefficients in the model illustrated in FIG.

[0057] FIG. 7A to FIG. 7B The diagram shows how to adjust Figure 3 The results of adjusting the pollution parameters in the model to match their estimated values ​​with the measured values, where the cooling circuit has a pollution degree of 75%;

[0058] FIG. 8A to FIG. 8B The diagram shows how to adjust Figure 3 The results of adjusting the pollution parameters in the model to match their estimated values ​​with the measured values, where the cooling circuit has a pollution degree of 92%;

[0059] FIG. 9A to FIG. 9B The diagram shows how to adjust Figure 3 The results of adjusting the pollution parameters in the model to match their estimated values ​​with the measured values, where the cooling circuit has a pollution degree of 94.8%;

[0060] Fig.10 illustrates the pollution parameter adjusted as a function of the pollution level in the diagrams of Figures 7 to 9; and

[0061] Fig.11 Determination of healthy areas based on pollution parameters as a function of pollution levels is illustrated. DETAILED DESCRIPTION

[0062] The present invention will be described with respect to certain embodiments and with reference to certain drawings, but the invention is not limited thereto and is determined solely by the claims. The drawings described are schematic and non-restrictive. In the drawings, the dimensions of certain elements may be exaggerated and are not drawn to scale for purposes of illustration. Dimensions and relative dimensions do not necessarily correspond to actual practical embodiments of the invention.

[0063] Furthermore, the terms "first," "second," "third," etc., are used in the specification and claims to distinguish between similar elements and are not necessarily used to describe a sequential or chronological order. These terms are interchangeable where appropriate, and embodiments of the invention may be practiced in sequences other than those described or illustrated herein.

[0064] In addition, the terms "top", "bottom", "upper", "lower", etc. are used in the specification and claims for illustrative purposes, and these terms are not necessarily used to describe relative positions. The terms so used are interchangeable under appropriate circumstances, and the embodiments of the invention described herein can be implemented in orientations other than those described or illustrated herein.

[0065] Furthermore, although the various embodiments are referred to as "preferred embodiments," these are to be interpreted as exemplary ways to practice the invention, rather than limiting the scope of the invention.

[0066] The term "comprising" used in the claims should not be interpreted as being limited to the devices or steps set forth below; the term does not exclude other elements or steps. The term should be interpreted as specifying the presence of the referred features, elements, steps or components, but does not exclude the presence or addition of one or more other features, elements, steps or components or groups thereof. Therefore, the scope of the expression "a device comprising parts A and B" should not be limited to a device consisting of only components A and B. Meaning, for the present invention, only components A and B of the device are listed, and the claims will be further interpreted to also include equivalents of these components.

[0067] Figure 1 The method for calculating the instantaneous performance index of the compressor and / or supporting equipment is schematically illustrated. The first step includes the measurement data 101 as input to the model 102 representing the compressor and / or supporting equipment. For example, the model 102 is as follows Figure 3 The physical model is further illustrated in . The input includes the velocity and pressure 300, inlet temperature 302 and the heat transfer coefficient UA108. Then, in 303, the power P can be calculated based on the velocity and pressure 300 compr Then, on this basis, for example by taking into account the efficiency coefficient, such as Figure 3 As shown in the figure, the heat generated by the compressor when it is running can be calculated as Q heat generated 305. The air outlet temperature T can be used out 309. Air inlet temperature T in , air outlet pressure p out and air inlet pressure p in , the required compressor power is determined based on the compression model 308 .

[0068] It is also understood that the above illustrated example of the physical model 102 may be replaced by other models representing the compressor and / or supporting equipment. Figure 4, a set of inputs 401 to 405 are provided, for example, velocity 401, pressure 402, inlet temperature 403, ventilation conditions 404 and oil temperature 405 at a certain point in time, so that the oil temperature 407 at a subsequent point in time can be calculated using a set of equations 406.

[0069] Reference again Figure 3 And thus referring to the physical model 102, reference numeral 304 includes a method for determining the cooling capacity P of the cooling circuit of the cooler. cooler Model, the cooler exists in an arrangement including a compressor. Figure 5 , the cooling circuit 500 is, for example, a closed oil circuit. The oil circulates to one or more machine components 502 by means of a pump 501, where heat is removed to the oil. The oil is then cooled again in an oil cooler 504, for example by means of a ventilator 505. The oil can then be further used as a lubricant 506 for machine components, such as a gearbox, and is recirculated in the cooling circuit 500 by means of the pump 501.

[0070] The correct operation of the oil circuit 500 may be negatively affected in various ways. For example, the oil may become contaminated due to wear of the moving parts in the oil circuit 500, which may clog the ducts and hinder the lubrication and cooling of the bearings and gears. At the beginning, the oil will be very pure, but when very fine particles in the cooling air sucked from the environment are no longer retained by the filter, the oil may become contaminated. This phenomenon may occur in oil-injected compressors. Non-injected compressors have a closed oil circuit, which means that the oil does not flow along the compressor elements, so this phenomenon is less likely to occur. However, just like oil-injected compressors, the air side of the oil cooler 504 can also become clogged with dirt particles in the air. This phenomenon is also called clogging 503, and the oil cooler 504 will operate suboptimally over time. This is because heat transfer becomes more difficult, causing the overall temperature of the oil to increase. This in turn leads to an increase in the temperature of the compressed air because, for example, the housing also reaches a higher temperature. In addition, the lubrication conditions of the bearings and gears will be suboptimal, causing these components to heat up further, age in an accelerated manner, and endanger the availability of the compressor.

[0071] The closed loop can be modeled as a system in which the parameters are only time-dependent, also called a lumped system, in which the temperature rise 509 of the oil depends on the heat absorbed as a result of losses 507 and on the heat released by the cooler 508 and therefore on the cooling capacity.

[0072] The cooling capacity is then the amount of heat Q removed during operation heat removed , and with the oil temperature T oil and cooling air temperature T air inletThe difference between the two is proportional to the heat transfer coefficient UA108 of the cooler. In addition, an additional fan state factor is added, which takes into account whether forced ventilation is effective. The cooling air temperature itself can be modeled as a correction on the temperature of the compressor housing. The cooling capacity P corresponding to the heat removed is then cooler Change to P cooler (fanstate,UA,T oil , T air inlet , ...) = Q heat removed 307.

[0073] The temperature rise of the oil in the oil circuit can be described as Q heat generated -Q heat removed , denoted by reference numeral 306. Based on the above, using an operator 308 optionally supplemented by a gain coefficient, the oil temperature at a certain point in time can be calculated as an output 309 of the model.

[0074] Reference again Figure 1 , then the difference between the estimated value 309 and the measured value 107 can be calculated in 103. Reference numeral 104 then comprises a series of residuals.

[0075] In principle, the above mentioned gain coefficients, which represent the respective parameters and / or coefficients describing the operation of the compressor and the cooling circuit, can be determined based on a sufficient number of measurements of new and / or healthy machines. These can then be determined, for example, via least squares regression. FIG. 6A to FIG. 6C The result of such a regression training is illustrated. The y-axis of the illustrated graph shows the oil temperature in degrees Celsius, the compressor speed in rpm and the inlet temperature in degrees Celsius, respectively, as a function of time. It should be further noted that Figure 6B , Figure 7B , Figure 8B and Fig. 9B There are two y-axes, where the right y-axis represents the outlet pressure in bar.

[0076] The above model can be used to determine the efficiency of the cooling system and / or compressor as long as it can be assumed that the oil circuit is healthy. In this way, the measured values ​​and the estimated values ​​via calculation will agree with each other. However, when the cooler starts to clog, the heat transfer coefficient UA of the cooler will decrease. By introducing an additional coefficient β further referred to as the contamination parameter U , this degradation can be included in the model, β U is an example of a degradation parameter defined above, where the value ranges between 1 corresponding to a healthy machine and 0 where there is no heat transfer at all. Thus, the capacity of the cooler is P cooler =Q heat removed=[fanstate.β U .β fanon +(1-fanstate)·β fanoff ]UA(T oil -T air inlet ).

[0077] Therefore, the model 102 used includes the contamination parameter β U , which represents the health state of the machine or its parts (such as the cooling circuit), or in other words the degradation state. In addition, in the example of model 102, a gain factor representing the friction coefficient of the compressor and / or peripheral equipment may be used. n As an indication of the state of health. When the compressor and / or peripheral equipment is put into service, it will be equal to the expected friction coefficient of a new machine, but over time, significant differences will appear between the measured and estimated values, as the friction coefficient no longer corresponds to that of a new machine.

[0078] refer to Figure 2 , the degradation of the compressor and / or peripherals and the associated cooling circuits will be taken into account according to the new innovative method 200. Figure 1 As shown in Figure 2 1 shows measured data 101 as input, a model 102 representing the compressor and / or supporting equipment, the calculation of the difference 103 between the measured value 107 and the estimated value 309, and a series of residuals 104. However, as with Figure 1 Unlike the method illustrated in FIG. 2 , in step 201, one or more parameters of the model 102 (such as the contamination parameter β) are updated by using feedback 202. U and gain factor α n ), so that the residual 104 is minimized.

[0079] Other parameters may also be optionally adjusted, such as those used in other aspects of the model, such as compressor efficiency, oil velocity, friction coefficient, etc. In other words, by adjusting the parameters and / or variables in the model 102, the estimated values ​​will be brought into agreement with the measured values, and thus the residual 104 will be reduced to a minimum, i.e., to the noise level.

[0080] For example, if in a simple case only the friction coefficient is changed via feedback 202, the friction coefficient may show a monotonically increasing trend in case of natural or expected degradation of the cooling circuit 500. On the other hand, depending on the reference and definition of this coefficient in the model, a monotonically decreasing trend may also be noted. Therefore, it should be understood that due to feedback 202, one or more parameters change over time.

[0081] refer to Fig. 7A, a graphical representation of the oil temperature on the y-axis versus the time on the x-axis is given, wherein the solid line represents the measured value 107 and the dashed line represents the estimated value based on the model 102. Thus, the difference between them is calculated as the error [%], which corresponds to the residual 104. By means of feedback 202, the above-mentioned parameters are adjusted so that the estimated value is consistent with the measured value. In addition, Figure 7B , the velocity on the left y-axis and the exhaust pressure on the right y-axis measured at the same time point as the oil temperature measurement are shown over time on the x-axis.

[0082] In order to bring the estimated values ​​into agreement with the measured values, the parameters are adjusted so that a higher degree of fouling or clogging is imposed on the chillers in the model. This provides insight into the degree of fouling of the chillers. Figure 2 , then, the degree of contamination 205 of the cooler can be derived based on the feedback 202 via an additional model 204 (e.g., a regression model). Here, block 201 is a minimizer that proposes a new value for parameter 108 leading to the next iteration via feedback 202. After convergence is achieved, the result is an updated version of the converged value of the degradation parameter 203, so 108 is the proposed value of the degradation parameter.

[0083] In Figure 7, this contamination level corresponds to 75%. FIG. 8A to FIG. 8B and FIG. 9A to FIG. 9B In FIG. 7A to FIG. 7B Further illustrations are given in FIG. 8 , where in FIG. 8 the cooler has a contamination level of 92% and in FIG. 9 the cooler has a contamination level of 94.8%.

[0084] In addition, Fig.10 Here, it is expressed as the normalized value β clog The pollution parameter β " Depending on the degree of cooler contamination, there is a tendency to decrease. On this basis, a healthy range can be determined as to how much this parameter represents the health of the cooling circuit and therefore the health of the compressor. Fig.11 , for example, shows three regions: a completely blocked cooler, “Completely Blocked”; a partially blocked cooler, “Partially Blocked”; and a healthy cooler, “Healthy”.

[0085] By determining the degree of contamination, maintenance can be planned more effectively. As soon as the degree of contamination exceeds a limit value, e.g. Fig.10As shown in the diagram, this maintenance can be scheduled to ensure machine availability and efficiency. Maintenance can thus be planned when necessary, rather than purely periodic, and therefore as a preventive measure. Finally, the risk of failure of the oil cooler (and thereby of the compressor) can also be better estimated and, if necessary, the operator can be informed in time so that no unexpected failure is encountered.

Claims

1. A computer-implemented method for monitoring the operation of a compressor and / or its supporting equipment, the method comprising iteratively performing the following steps: - measuring (107) one or more process quantities (101) indicative of the instantaneous operation of the device and / or the compressor; and - using a model (102, 400) to estimate (102) one or more process quantities of the device and / or the compressor based on one or more setting parameters of the compressor; - comparing the estimated process quantity with the measured process quantity (103), thereby obtaining an instantaneous performance indicator (104); It is characterized in that The method further comprises the following steps: - determining (202) a degradation parameter (203) based on a series of consecutive instantaneous performance indicators (104); and wherein said estimating (102) is further performed based on said degradation parameter (108); - reporting said operation based on said degradation parameter (108).

2. The computer-implemented method of claim 1 , wherein: The estimation of the one or more process quantities is further performed based on the measured process quantity (107).

3. The computer-implemented method according to any one of the preceding claims, further comprising the step of updating (202) the model based on the degradation parameter (108).

4. A computer-implemented method according to any one of the preceding claims, wherein: The process quantity (101) includes one or more of the group consisting of temperature, flow, velocity, inlet pressure, outlet pressure, ambient pressure, humidity, flow rate and / or valve position.

5. A computer-implemented method according to any one of the preceding claims, wherein: The model (102, 400) comprises a parametric model including one or more model parameters.

6. A computer-implemented method according to claim 5 as appended to claim 3 or 4, wherein: The updating (202) is performed by updating the model parameters (305, 306, 307).

7. The computer-implemented method according to any one of claims 5 to 6, further comprising the steps of: - deriving a health indicator (205) based on the model parameters (305, 306, 307).

8. The computer-implemented method of any one of claims 5 to 7, the model parameters comprising one or more of the group consisting of heat transfer coefficient, efficiency parameter, temperature correction parameter, cooling parameter, speed correction parameter, friction parameter.

9. The computer-implemented method according to any one of the preceding claims, further comprising the steps of: - limiting the range of compressor setting parameters based on said degradation parameter (108).

10. The computer-implemented method of claim 9, the setting parameters comprising one or more of the group consisting of pressure, flow rate, humidity level, power.

11. The computer-implemented method according to any one of the preceding claims, further comprising the steps of: - When the degradation parameter (108) exceeds a predefined value, shutting down the compressor.

12. A data processing system comprising a processing unit configured to perform the method according to any one of the preceding claims.

13. A computer program product comprising computer executable instructions for performing the method according to any one of claims 1 to 11 when said program is executed on a computer.

14. A computer storage medium comprising a computer program product according to claim 13.

15. A compressor comprising the data processing system according to claim 12.

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