EP2047117B1 - Method for fault localization and diagnosis in a fluidic installation - Google Patents

Abstract

In a method for error containment and diagnosis in a fluid power system the fluid volumetric flow in the overall system or at least a part thereof and the fluid pressure (P) is detected as a measurement quantity in each case during a duty cycle and is compared with stored references. In each case at the point in time of a deviation or a change in the deviation from the reference it is determined at which component or at which components (10 through 14) of the system an event has occurred influencing fluid consumption in order to recognize same as subject to error. Guide value quantities (Q/P) are derived from the respective volumetric flow values (Q) and the measured pressure (P) and are integrated or summated over the duty cycle to form guide values (KD), a corresponding guide value reference curve (KDref) as a reference being chosen from a stored selection matrix, which has the guide value reference curves (KDref) or time dependent guide values for different operating conditions.

Description

The invention relates to a method for fault isolation and diagnosis at a fluidic system, wherein the fluidic volume flow of the entire system or at least a portion thereof and the fluid pressure during each operating cycle is detected and compared with stored references, and wherein at the time of a deviation or a change the deviation from the reference is determined in which component or components of the system, the fluid consumption influencing process has taken place to then recognize them as faulty.

In such, from the WO 2005/111433 A1 known methods, the air consumption curve is evaluated for error localization. In case of deviations from a reference, it is concluded from the time of the deviation on the faulty subsystem (for example, valve actuator unit). Such errors, which can occur in fluidic systems, have their causes, for example, in the wear of the components, improper mounting, loose fittings, porous hoses, process disturbances and the like., Which manifest themselves in the movements of the fluidic drives, and other leaks of various kinds Diagnostic errors due to changes in certain boundary conditions, such as pressure and temperature, to avoid, this document mentions the possible correction of air consumption with pressure and temperature. However, the method for this is not described, and temporal or batch-dependent fluctuations can not be considered.

An object of the present invention is to improve the method of the aforementioned type so that changes in the boundary conditions and in particular different operating conditions are taken into account so that they do not lead to misdiagnosis.

This object is achieved by a method having the features of claim 1.

The advantage of the method according to the invention is, in particular, that the diagnosis by means of the conductivity value easily compensates for natural fluctuations in a fluidic system, caused by unavoidable pressure and / or temperature fluctuations. In addition, different operating states can also be taken into account by selecting corresponding stored reference value reference curves. The comparison of the conductance with a reference and possible deviations in terms of time as well as amount allow very exact statements on the nature of the fault and the location of the fault. Thus, it is advantageously also possible to make statements as to whether leaks are the cause of the fault (changed air consumption) or whether the cause of the fault is due to a changed actuator movement, for example slower cycle times due to friction, wear, slower switching control valves and the like.

The measures listed in the dependent claims advantageous refinements and improvements of claim 1 method are possible.

The different operating states for which master value reference curves are stored for selection preferably relate to the warm-up, the operation after a longer standstill, the restart during retrofitting and the operation after predefinable time intervals.

wobei T die Betriebstemperatur ist. Um auch eine Anpassung an unterschiedliche verwendete Fluide zu erreichen, können die Leitwertgrößen auch fluidabhängig adaptiert werden, insbesondere durch den Faktor $\sqrt{K_F},$

wobei K_F ein fluidabhängiger Kennwert ist. Noch exaktere Diagnosedaten und Diagnoseaussagen erhält man durch Adaption der Leitwertgrößen durch den Feuchtegehalt und/oder den Partikelgehalt des jeweiligen Fluids, insbesondere durch den Faktor $1/\sqrt{K_{\mathrm{H}}},$

wobei K_H ein vom Feuchte- und/oder Partikelgehalt abhängiger Kennwert ist.The Leitwertgrößen be compensated for even better adaptation to the behavior of the overall system temperature dependent, in particular by the factor $1/\sqrt{T}.$

where T is the operating temperature. In order to achieve an adaptation to different fluids used, the Leitwertgrößen can also be adapted fluid dependent, in particular by the factor $\sqrt{K_F}.$

where K _{F is} a fluid-dependent characteristic value. Even more accurate diagnostic data and diagnostic statements are obtained by adapting the Leitwertgrößen by the moisture content and / or the particle content of the respective fluid, in particular by the factor $1/\sqrt{K_{\mathrm{H}}}.$

where K _{H is} a dependent moisture and / or particle content characteristic value.

In order to be able to take account of different operating states, that is to say to ensure that the comparison between the reference value and the current master value yields a correct statement, the selected reference must correspond to the corresponding operating state. This means that from the stored selection matrix the reference value curve corresponding to the respective operating state has to be selected. Advantageously, this is before the diagnosis of leakage, the duration of an operating cycle by comparing the current Leitwertmesskurve with this operating cycle assigned Leitwertreferenzkurve checked, with only a predetermined deviation, the switchover to at least one more Leitwertreferenzkurve. If a runtime deviation is detected, the presence of a proportional time shift between the actual master value curve and the master value reference curve is additionally checked, and only in the case of a determined proportional time shift does the switch to at least one further reference value reference curve take place. If, after checking all master value reference curves, it is determined that all of them exceed the specified deviation, the entire system is far outside the operating point and a corresponding message is generated. The diagnosis of leakage is then not carried out because it makes no sense.

Figur 1

eine pneumatische Anlage, in deren Zuführung ein Durchflussmesser geschaltet ist, und

Figuren 2 bis 4

Leitwertdiagramme zur Erläuterung verschiedener Diagnoseergebnisse.

An embodiment of the invention is illustrated in the drawing and explained in more detail in the following description. Show it:

FIG. 1

a pneumatic system, in whose supply a flow meter is connected, and

FIGS. 2 to 4

Conductance diagrams for explaining various diagnostic results.

In FIG. 1 a pneumatic system is shown schematically, which could in principle also be another fluidic system, such as a hydraulic system, act.

The pneumatic system consists of five subsystems 10 to 14, which may each be actuators, such as valves, cylinders, linear drives and the like, act, as well as Combinations thereof. These subsystems 10 to 14 are fed by a pressure source 15, wherein in a common supply line 16, a flow meter 17 for measuring the flow or the volume flow is arranged. The subsystems 11, 12, on the one hand, and the subsystems 13, 14, on the other hand, in turn each form a system with a common supply line.

An electronic control device 18 is used to specify the process flow of the system and is electrically connected to the subsystems 10 to 14 via corresponding control lines. The subsystems 10 to 14 receive control signals from the electronic control device 18 and send sensor signals back to them. Such sensor signals are, for example, position signals, limit switch signals, pressure signals, temperature signals and the like.

The flow meter 17 is connected to an electronic diagnostic device 19, which in addition to the signals of a temperature sensor 20 and a pressure sensor 21 for measuring the temperature (T) and the pressure (P) in the supply line 16, ie the temperature and the pressure of the fluid supplied are. Furthermore, a fluid sensor 23 for detecting the type of fluid used and a moisture and / or particle sensor 24 for detecting the moisture content and the particle content of the fluid are connected to the diagnostic device 19. This has additional access to the sequence program of the electronic control device 18. The diagnostic results are supplied to a display 22, these diagnostic results of course also stored, printed, visually and / or acoustically displayed or a central office via lines or wirelessly can be transmitted.

Of course, the diagnostic device 19 can also be integrated in the electronic control device 18, which may contain, for example, a microcontroller for carrying out the sequence program and optionally for diagnosis.

In a very large number of subsystems, these can be divided into several groups, each group has its own flow meter 17 to independently diagnose the subregions of the system associated with the groups, as described in the above-mentioned prior art. The procedure for fault isolation and diagnosis will now be described below with reference to the described pneumatic system and in the FIGS. 2 to 4 illustrated Leitwertdiagramme explained.

First, the conductance and the determination of the conductance will be explained. The volume flow into the fluidic system is measured by means of the flow meter 17 and divided by the measured form P, measured with the pressure sensor 21. This quotient forms the conductance value, which in each case summed over an operating cycle or, when integrated, gives the conductance K _D : $$K_D=\underset{t_0}{\overset{t_e}{\int }}\frac{Q}{P}\cdot \mathrm{dt}$$

This conductance can still be compensated by the measured operating temperature T, measured with the temperature sensor 20. Furthermore, this conductance value can also be determined as a function of the particular fluid used, measured with the fluid sensor 23, with the characteristic value K _F and optionally also with the characteristic value K _H as a function of the moisture content and / or the particle content of the air, measured with the moisture content. and / or particle sensor 24, are adapted. This then gives the following conductivity: $$K_D=\underset{t_0}{\overset{t_e}{\int }}\frac{Q}{P}\cdot \frac{1}{\sqrt{T}}\cdot \sqrt{\frac{K_F}{K_H}}\cdot \mathrm{dt}$$

Depending on the complexity and desired accuracy, the influences of the temperature T and / or the characteristic values K _F or K _{H can} also not be taken into account, so that in the simplest case the conductance depends only on the volume flow and the admission pressure.

The conductivity is additionally dependent on time and / or batch, that is, depending on the operating condition, other conductance curves arise. Such operating states are, for example, the warm-up, the operation after a long standstill, the reclosure when retrofitting or the operation after predetermined time intervals, so for example after a one-hour or ten-hour or several hours of operation.

For these different operating states and different parameters, conductance reference curves are now detected, for example in a learning process, and stored in the diagnosis device 19 in a selection matrix. The diagnostic control value or the diagnostic control values are characteristic variables of a fluidic system or a fluidic system that consists of a variety of subsystems. The conductance characterizes the behavior of the entire system or a subsystem over a defined repeating cycle. It compensates for normal fluctuations and fluctuations in the operating variables pressure, temperature, humidity, particle content, depending on how complex it is formed. The evaluation of this conductance by reference comparison, ie comparison with stored master value reference curves, thus showing the errors and the causes of errors in fluidic systems.

First, a parameter-dependent master value reference curve adapted to the respective operating state must be selected. This takes place initially as a function of the applied sensor signals. Then, the runtime of the system is first checked as a function of the respective operating state and checked for correlation with the initially selected master reference curve. If the selected master value reference curve correlates with the current measured curve, the diagnosis is released. Deviations then actually indicate a leak in the detected period and can be assigned to these error-causing actuators in accordance with the sequence program.

First, however, a further check is made in the event of a determined runtime deviation of the conductance curve as to whether there are constant time cuts between characteristic curve points. Thus, for example, divide the entire curve in a characteristic number of curve points, with a time deviation will change the time difference between the curve points. For the entire curve, there must be a linear relationship of the individual time differences between the curve points within defined limits, so that it can be assumed that there is no error, e.g. by the faster moving axles after the start phase. This means that all time differences of the curve must change proportionally.

If the selected reference does not satisfy the required agreement, then the diagnosis is released, that is, the Deviation does not stem from a time shift, but from a malfunction of the plant ago, in particular from a leak.

If, on the other hand, a linear relationship of the gradients within defined limits is determined when the runtime deviation is first determined, a changeover to another master value reference curve takes place. This is repeated until a suitable master value reference curve is found. If no such can be found, the entire system is outside the operating point, and it is generated a corresponding message, that is displayed, reported, stored and the like.

If a suitable conductance _{reference curve} K _{Dref is} found, then this is compared with the currently measured conductance _curve K _Da . In the FIGS. 2 to 4 Three possible cases are shown.

According to FIG. 2 the measured conductance _curve K _Da deviates continuously more and more from the conductance _{reference curve} K _Dref . This is clearly a cause of the fault leakage, namely a system leak, that is, a leak in the supply line 16 or in associated lines. The difference ΔK _D increases more and more with time t and is a function of time.

According to FIG. 3 At time t1, a deviation ΔK _D occurs, which remains constant from this point in time until the end t _{e of} the cycle. This means that a subsystem, for example a valve actuator unit that was active at time t1, has a leak. The timing of the deviation may be compared with the process image or control program in the controller 18 to locate the error-causing subsystem. If several subsystems were active at time t1, which could be the case for larger systems, the error must be limited during the following activities of these subsystems in which they are no longer active together.

According to FIG. 4 the cycle duration has changed by the value .DELTA.t, the change having occurred at the time t2. The value of the conductance remains constant from this time t2, there is only a time shift. This allows the conclusion that the travel time of the active at this time t2 actuator has changed, for example, by clamping, increased wear, switching errors on the valve or the like. It is thus also possible to detect time errors in the pneumatic system based on the conductance.

It can of course also in the FIGS. 2 to 4 reported occurrences during a cycle cumulative and / or occur multiple times. By corresponding curve, several different errors occurring during a cycle can then be detected. For safety, of course, the diagnostic cycles will be repeated upon the occurrence of a fault to determine if it is a one-time fault or a faulty measurement or fault.

Claims (9)

1. Method for fault isolation and diagnosis for a fluidic system, wherein the fluidic volumetric flow rate of the overall system or at least a part thereof, together with the fluidic pressure, are each determined during an operating cycle and compared with stored reference values, and wherein in each case at the time of a deviation or a change in the deviation from the reference it is established for which component or components of the system an event affecting fluid consumption has taken place, so that this or these may be identified as defective, characterised in that from the respective volumetric flow values (Q) and the recorded pressure (P), master value figures (Q/P) are formed and over the operating cycle are integrated or totalled to give master values (K_D), wherein as reference a suitable master value reference curve (K_Dref) is selected from a selection matrix which contains the master value reference curves (K_Dref) or time-dependent master values for different operating states.
2. Method according to claim 1, characterised in that the different operating states are at least two of the following different operating states: warm-up, operation after lengthy shutdown, restart after modification, operation after presettable time intervals.
3. Method according to claim 1 or 2, characterised in that the master value figures are subject to temperature-dependent compensation, in particular through the factor $1/\sqrt{T},$

   

   wherein T is the operating temperature.
4. Method according to any of the preceding claims, characterised in that the master value figures are adapted depending on fluid, in particular by the factor $\sqrt{K_F},$

   

   wherein K_F is a fluid-dependent parameter.
5. Method according to any of the preceding claims, characterised in that the master value figures are adapted for the moisture content and/or the particle content of the fluid, in particular by the factor $1/\sqrt{K_H},$

   

   wherein K_H is a parameter dependent on the moisture and/or particle content.
6. Method according to any of the preceding claims, characterised in that before diagnosis for leakage, the duration of an operating cycle is checked by comparing the latest master value measured curve (K_Da) with a master value reference curve (K_Dref) assigned to this operating cycle, wherein only after a presettable deviation is the switch made to at least one further master value reference curve (K_Dref).
7. Method according to claim 6, characterised in that in the event of a determined operating time deviation, the existence of a proportional time shift between current master value measured curves (K_Da) and master value reference curves (K_Dref) is checked, and the switch to at least one further master value reference curve (K_Dref) is made only in the case of an established proportional time shift.
8. Method according to claim 6 or 7 characterised in that, if the presettable deviation is exceeded in all master value reference curves (K_Dref) checked, a suitable message is generated and no diagnosis for leakage is made.
9. Method according to any of the preceding claims, characterised in that, if there is a large number of components (10-14), a split is made into several groups, which are diagnosed independently of one another.

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