阅读说明：本技术 用于工艺阀的诊断方法，诊断模块和工艺阀 (Diagnostic method for a process valve, diagnostic module and process valve ) 是由 克劳斯·贝克 安德烈亚斯·昂格雷尔 于 2021-05-28 设计创作，主要内容包括：本发明涉及一种用于在正常运行中对工艺阀进行连续的功能监控的诊断方法。所述诊断方法包括以下步骤：a)从输送给工艺阀的输入信号中确定具有时间离散的工艺目标值的工艺目标数据(S)；b)借助于与工艺阀相关联的路程测量系统来确定具有时间离散的工艺实际值的工艺实际数据(s)；c)通过将工艺目标数据(S)和工艺实际数据(s)相互比较,分析与工艺目标数据(S)相关的工艺实际数据(s),以便识别限定的故障状态。(The invention relates to a diagnostic method for continuous function monitoring of a process valve during normal operation. The diagnostic method comprises the following steps: a) determining process target data (S) having time-discrete process target values from the input signal supplied to the process valve; b) determining process actual data(s) having time-discrete process actual values by means of a path measuring system associated with the process valve; c) the process actual data (S) related to the process target data (S) are analyzed by comparing the process target data (S) and the process actual data (S) with each other in order to identify a defined fault state.)

1. A diagnostic method for continuous functional monitoring of a process valve (10) in normal operation, the method comprising the steps of:

a) determining process target data (S) having time-discrete process target values from the input signal supplied to the process valve (10);

b) determining process actual data(s) having time-discrete process actual values by means of a path measuring system (50) associated with the process valve (10);

c) analyzing the process actual data (S) in relation to the process target data (S) by comparing the process target data (S) and the process actual data (S) with each other in order to identify a defined fault state.

2. The diagnostic method according to claim 1, wherein said diagnostic reagent is a reagent,

wherein the process target value and the process actual value are normalized values.

3. The diagnostic method according to any one of the preceding claims,

wherein the defined fault condition comprises: excessive network pressure, plugging of the process valves, leakage, pressure fluctuations, and/or run time variations.

4. The diagnostic method according to any one of the preceding claims,

wherein if the process actual value (303) approaches the process target value (203) with a rate of change which is smaller in absolute value than a predefined rate of change (503), an excessively low network pressure is identified, in particular in the above case the process actual value does not approach the process target value (203) to the extent that: is below a predetermined minimum spacing (403) between the process actual value (303) and the process target value (203).

5. The diagnostic method according to any one of the preceding claims,

wherein a blockage of the process valve (10) is detected if the rate of change of the process actual value (304) decreases to a predefined maximum rate of change within a predefined maximum time interval (504) during the process actual value approaching the process target value (204) with a predefined minimum value, in particular if the process actual value (304) does not approach the process target value (204) within the defined time interval to such an extent that it falls below a predefined minimum value spacing (404) between the process actual value and the process target value.

6. The diagnostic method according to any one of the preceding claims,

wherein a leak is identified if the process actual value (305) is further away from the process target value (205) over time, in particular although the process target value (205) is fixed, preferably wherein a predetermined minimum spacing (405) between the process actual value (305) and the process target value (205) is exceeded.

7. The diagnostic method according to any one of the preceding claims,

wherein a pressure fluctuation is detected if the process actual value (306) is not only increased but also decreased within a time interval (Δ t) of a defined length without changing the process target value (206), in particular wherein the rate of change of the process actual value (306) has more than one sign change within the time interval, preferably wherein the process actual value (306) and/or the rate of change differ by no more than a predefined value before the start of the time interval and after the end of the time interval, respectively.

8. The diagnostic method of any one of the preceding claims, further comprising the steps of:

a) generating process actual reference data (507) by storing the process actual data (507) in relation to the process target data (207) before and/or at the start of normal operation; and

b) comparing the process actual data (307) with corresponding process actual reference data (507), wherein a run-time change is detected if the rate of change of the process actual data (307) differs from the rate of change of the process reference data (507) by a predetermined minimum distance (407) if the process target data (207) are identical.

9. A computer-implemented diagnostic module (110) for a process valve (10), wherein the diagnostic module comprises code to run a diagnostic method according to any of the preceding claims on a processor.

10. A diagnostic unit (100) for a process valve (10), the diagnostic unit comprising: a first interface for an input signal of the process valve; a second interface for a position signal of the range measurement system; a memory having code of the diagnostic module of claim 9 stored thereon; and a processor for executing the code in order to execute the diagnostic method according to any one of claims 1 to 8.

11. A process valve (10) comprising a valve control mechanism with a diagnostic module (110) according to claim 9 and/or a diagnostic unit (100) according to claim 10.

Technical Field

The present invention relates to a diagnostic method for continuous function monitoring of a process valve during normal operation, a diagnostic module for a process valve and a process valve.

Background

Process valves can be used in a wide variety of applications. An illustrative example is the food industry. There, for example, filling facilities are used in order to fill the containers with the liquid. The filling plant has process valves, which are in turn usually controlled by solenoid valves. The process valves are pneumatically actuated and the pneumatic pressure required for this purpose is controlled again by means of solenoid valves.

Different ways of ensuring as correct a function of the process valve as possible are known from the prior art.

EP 1555472 a shows a method for function monitoring in a valve for fluid control, which has at least one electrical operating element for valve operation, which is coupled to an operating state display for displaying the current operating state of the operating element. The method comprises the following steps: the change in the displayed operating state is detected optically by means of an optical sensor and is defined as a starting time t₀. Furthermore, the starting point in time t is detected by means of a detection device as a result of a change in the operating state₀The pressure change at the valve output is measured and a pressure related signal associated with the pressure change is generated. The switching state of the valve is now verified by checking: from a starting point in time t₀Whether a particular pressure-related signal is present after a particular time.

Disclosure of Invention

One object is to identify a malfunction of a process valve early, without interrupting the normal operation of the process installation, so that a deactivation of the process valve can be avoided as far as possible while the operation is in progress.

In this context, a diagnostic method for continuous function monitoring of a process valve during normal operation is proposed.

The diagnostic method comprises the following steps: process target data having time-discrete process target values are determined from the input signals supplied to the process valves.

The diagnostic method further comprises: the process actual data with time-discrete process actual values are determined by means of a path measurement system associated with the process valve.

According to one aspect, a diagnostic method comprises: the process actual data related to the process target data are analyzed by comparing the process target data and the process actual data with each other in order to identify a fault state defined in the manner described.

In this way, only the total existing path measurement system of the process valve is used for the diagnosis in order to determine the corresponding process actual data and the process actual data is evaluated in combination with the process target data determined from the input signals of the process valve. Advantageously, no additional sensing means are required. The diagnosis can be carried out permanently or continuously in normal operation.

According to an advantageous aspect, the process target value and the process actual value may be normalized (dimensionless) values. This simplifies direct comparison of the process target values with the process actual values. The normalized (dimensionless) value may be derived from the corresponding position or attitude of the process valve, which has been detected by means of the course measurement system.

According to another advantageous aspect, the defined fault conditions include an excessively low network pressure, clogging of process valves, leakage, pressure fluctuations and/or operating time variations. Preferably, all mentioned fault states are identified.

Once the process actual value approaches the process target value at a rate of change that is less in absolute terms than the predefined rate of change, an excessively low network pressure may be identified. The predefined rate of change is furthermore dependent on the configuration of the process valve, its dimensions and possibly also other process parameters. The predefined rate of change (as a limit value) is therefore preferably determined experimentally. It is particularly clear if in this case the process actual value only approaches the process target value to the extent that: not below a predetermined minimum spacing between the actual process value and the target process value, an excessively low network pressure can be identified. The minimum spacing value can also be selected as desired or determined experimentally.

Once the rate of change of the process actual value decreases to a predetermined maximum rate of change within a predetermined maximum time interval at a predefined minimum value during the process actual value approaches the process target value, a blockage of the process valve may be identified. In many cases, the rate of change decreases almost directly to zero upon occlusion. The identification is particularly unambiguous in the following cases: when the actual value of the process no longer reaches the target value of the process after the change rate is changed, namely: the process actual value does not approach the process target value within a time interval to less than a predetermined minimum spacing between the process actual value and the process target value.

As the process actual value becomes farther and farther from the process target value over time, a leak (e.g., in a pipe) may be identified, particularly when the process target value is fixed. In this case, it is particularly clearly recognized that a minimum distance between the process actual value and the process target value, which is selected as required, is exceeded.

As soon as the actual process value increases and decreases within a short defined time interval without a change in the target process value, a pressure fluctuation (also referred to as a pressure surge) can be detected. In particular, the rate of change of the process real-world value within the time interval may have more than one symbol transition. In particular, it is identified with certainty that the process actual value and/or the rate of change differ by no more than a predefined value before the start and after the end of the defined time interval, respectively. The predefined values can also be selected as required.

To be able to identify run-time variations, the diagnostic method may comprise: generating process actual reference data by storing the process actual data in relation to the process target data before and/or at the start of normal operation; and comparing the process actual data with corresponding process actual reference data. If the rate of change of the process actual data differs from the rate of change of the process reference data by a predetermined minimum distance (selected as required) with the same process target data, a run-time variation is identified.

Further, a computer-implemented diagnostic module for a process valve is provided. The diagnostic module comprises code by means of which the described diagnostic method can be executed on a (micro) processor.

Furthermore, a diagnostic unit for a process valve is provided. The diagnosis unit includes: a first interface for an input signal of a process valve; a second interface for a position signal of a path measurement system associated with the process valve; a memory having stored thereon code for a diagnostic module; and a processor for executing the code to execute the diagnostic method.

Additionally provided is a process valve including a valve control mechanism having a diagnostic module or unit.

In principle, the process actual data is compared with the process target data when analyzing the process actual data related to the process target data.

Thus, a fault condition of the process valve is identified, which is not a control fault.

In particular, for this purpose, a profile of the actual process data, for example a profile of the valve position over time, is compared with a profile that is to be expected from the process target data, i.e. a profile based on the process target data.

The data used for the comparison and based on the process target data can also be referred to as expected process actual data, wherein a corresponding expected curve profile is generated from the process target data and compared with the curve profile of the process actual data in order to identify a characteristic deviation.

In this respect, it can additionally be provided that, based on the determined process target data, process actual data to be expected, i.e. a curve profile to be expected, are first determined. In the analysis, the expected process actual data are then compared with the process actual data, i.e. the curve profile which is expected on the basis of the process target data is compared with the curve profile of the process actual data.

As mentioned at the outset, the corresponding data are data which have been determined by means of a path measurement system, i.e. for example the valve position of a process valve. In other words, the process actual data are data determined on the basis of the valve position or the valve attitude, i.e. data determined by means of a path measuring system.

Thus, the actual valve position (process actual data) can be compared with the predefined valve position (process target data), wherein the corresponding deviations are recognized and characterized. Accordingly, from the characterization of the determined deviation, a relevant defined fault state of the process valve is deduced.

In comparison, therefore, in principle, a characteristic deviation can be detected, via which a defined fault state can be detected.

This means that deviations of the actually existing curve profile based on the process actual data from the expected curve profile based on the process target data are determined, wherein the deviations are unambiguous for a defined fault state according to their characteristics, so that a defined fault state is identified on the basis of the identified deviations.

The fault diagnosis is carried out during normal operation, in particular, no comparison is carried out during a target value change or only during a defined time period, for example 1 or 2 seconds, during which a target value change has not previously occurred. In other words, if the process target data was previously fixed, the comparison is performed. It can thus be ensured that the process valve approaches the target process data overall with its actual process data in order to be able to detect a corresponding defined fault state.

Preferably, the comparison is only performed if no target value mutation or target value change has occurred before.

This is because, according to the invention, it is not intended to detect control faults, such as adjustment times, actuation times or control deviations. Rather, a continuous fault state, in particular a fault state which is independent of the control, is to be detected, so that a comparison of the process actual data and the process target data, in particular of their profile, is only carried out if no target value change has taken place before.

Although the analysis may be performed permanently in normal operation, if a change in the target value has previously occurred, the comparison and hence the analysis is at least (temporarily) aborted, or the analysis results are discarded.

In other words, the diagnostic method according to the invention is based on a long-term deviation of the actual process data from the target process data, i.e. a deviation which occurs over time given the target values.

In particular, the comparison can be carried out shortly before the target value changes.

During the evaluation, in particular when comparing the process target data with the process actual data, it can also be determined how fast the process target data are, i.e. at what rate of change, approaching the process actual data in order to thus determine whether one of the defined fault states, in particular an excessively low network pressure, is present. For this purpose, the determined rate of change is compared, for example, with a reference rate of change at which the process actual data approach the corresponding process target data, wherein the reference rate of change is determined, in particular, from empirical data and/or historical data.

The process target data may be manipulation data, i.e. data for manipulating a process valve.

A comparison of the curve shapes can thus be carried out such that a corresponding characteristic deviation of the curve shape of the curve profile of the process actual data from the curve shape of the curve profile of the process target data is detected, which in turn is associated with an associated defined fault state of the process valve.

Drawings

Features and aspects of the invention are explained in detail below with reference to embodiments and with reference to the drawings. Shown here are:

figure 1 shows a simplified schematic block diagram of a process control loop with a process valve;

figure 2 shows a simplified schematic block diagram of a process valve with a diagnostic unit;

fig. 3 shows a diagram with schematic diagrams of process actual data and process target data to visualize characteristic features in network pressure monitoring;

fig. 4 shows a diagram with schematic diagrams of process actual data and process target data to visualize the characteristic features at the time of plug identification;

FIG. 5 shows a diagram with schematic diagrams of process actual data and process target data to visualize the characteristic features in leak monitoring;

fig. 6 shows a diagram with schematic diagrams of process actual data and process target data to visualize the characteristic features at the time of pressure fluctuation identification; and

fig. 7 shows a diagram with schematic diagrams of process actual data and process target data to visualize the characteristic features when detecting runtime changes.

Detailed Description

The process valve 10 in the process control loop 60 is shown in a simplified block diagram in fig. 1. The process valve 10 includes an implement valve 20, a control module 30, an implement system 40, and a path measurement system 50. The process valve 10 is combined with a process controller 70, a process 80 and a process sensor 90 into a process control loop 60. The process sensor 90 may be any sensor and may measure a physical variable such as, for example, temperature, flow, or pressure.

Fig. 2 shows the process valve 10 with the diagnostic unit 100 as a simplified block diagram. The diagnostic unit 100 including the diagnostic module 110 is connected to the process valve 10 such that the diagnostic module 110 can process a process target value S (hereinafter also referred to simply as "target value" or "target data") and a process actual value S (hereinafter also referred to as "actual value" or "actual data").

The diagnostic unit 100 comprises a first interface for an input signal of the process valve; a second interface for a position signal of the range measurement system; a memory storing code for the diagnostic module 100; and a processor for executing the code. The computer-implemented diagnostic module 110 includes code to run the described diagnostic method on a processor. Alternatively, the diagnostic module 110 may be implemented directly in the valve control mechanism of the process valve 10 as a software function.

The actual data s are detected while the process control loop 60 is running (control operation) by means of the path measuring system 50 of the process valve 10. The detected actual data S is compared with the known target data S. Typical faults are identified from the characteristic deviations, such as, for example, problems with network pressure, blockages in the fitting or drive, leaks in the drive or the actuating system, pressure fluctuations or operating time variations.

The diagnostic method for continuous function monitoring of the process valve 10 during normal operation comprises the following steps:

determining process target data S having time-discrete process target values from the input signal fed to the process valve 10;

determining process actual data s with time-discrete process actual values by means of a path measuring system 50 associated with the process valve 10;

-analyzing the process actual data (S) related to the process target data (S) by comparing the process target data (S) and the process actual data (S) with each other in order to identify a defined fault condition.

The process target value and the process actual value are normalized values. Preferably, the normalized values are dimensionless.

Defined fault conditions include excessive network pressure, plugging of process valves, leakage, pressure fluctuations, and/or run time variations.

In other words, a typical fault state in a process valve can be identified by simply analyzing and comparing the actual curve with the target curve, i.e. the curve course of the actual value and the target value. For this purpose, the shape of the curve in normal operation is used.

The comparison of the actual curve with the target curve is explained below on the basis of five characteristic deviations, which are shown in fig. 3 to 7 and described in detail below.

The corresponding target data and actual data are shown in fig. 3 to 7 as normalized values in percentage (on the y-axis) with respect to time in seconds (on the x-axis). The input signal is plotted as a solid line as the target curve 203-207. The respectively assigned actual curves 303-.

Fig. 3 shows a characteristic deviation of the target curve 203 from a typical actual curve 303, as occurs in the case of problems with network pressure. During the undisturbed switching process starting at time t0, the actual curve 303 moves smoothly towards the end value E of the target value. During the disturbed switching process starting at time t1, the actual curve 303 moves significantly slower than normal toward the end value E', which does not correspond to the target value E. However, it is also possible that the target value E has not yet been reached. Thus, not only the target value E but also the time profile to reach the target value E are characteristic. The fault is not only for example not reaching the target value E at all, but also although it does, however, not occur within a defined time.

Thus, if the process actual value 303 approaches the process target value 203 at a rate of change that is, in absolute terms, less than the predefined rate of change 503, then an excessively low network pressure is identified. In the above case, the process actual value does not approach the process target value 203 to the extent that: below a predetermined minimum spacing 403 between the process actual value 303 and the process target value 203.

Fig. 4 shows a characteristic deviation from the target curve 204 as occurs in the case of a driver jam. During the switching process starting at time t0, the actual curve 304 reaches the target value end E. During the disturbed switching process starting at time t1, the actual curve 304 shows a sharp interruption at time t2 at a final value E ", which does not correspond to the target value E. Until time t3 the target value E is not reached.

Thus, if the rate of change of the process actual value 304 decreases to a predetermined maximum rate of change (abruptly) within a predetermined maximum time interval 504 with a predefined minimum value during which the process actual value 304 approaches the process target value 204, a blockage of the process valve 10 is identified. In the above case, the process actual value 304 does not approach the process target value 204 within the time interval to the extent that: below a predetermined minimum spacing 404 between the actual process value 304 and the target process value 204.

Fig. 5 shows a characteristic deviation from the target curve 205 as occurs in the case of a leak. After the switching process at time t0, at time t4 the actual curve 305 reaches the end value E of the target curve 205. Although no target value change occurs and thus the control variable should not change, the actual value 305 leaves either up 305a or down 305b in the event of a fault. Where the actual value exits from the tolerance band 405.

Thus, if the process actual value 305 becomes farther and farther from the process target value 205 over time, despite the process target value 205 being fixed, a leak is identified. The criterion may be whether a predetermined minimum spacing 405 (the aforementioned tolerance band) between the process actual value 305 and the process target value 205 is exceeded.

Fig. 6 shows the characteristic deviations from the target curve 206 as occur in the case of pressure fluctuations. After the switching process at time t0, at time t5 the actual curve 306 reaches the end value E of the target curve 206. The actual curve 306 shows a characteristic representation of the pressure fluctuations between the time points t3 and t4 (Δ t).

If the actual process value 306 increases and decreases within a time interval of defined length without changing the process target value 206, a pressure fluctuation is identified. Here, the rate of change of the process actual value 306 has more than one sign change within the time interval. The process actual value 306 or the rate of change thereof differs by no more than a predefined value before and after the beginning and the end of the time interval of the pressure fluctuation.

Fig. 7 shows two actual curves 507, 307 and a target curve 207. In the new state of the plant, the position/time profile of the process valve 10 is recorded as an x/t diagram and stored in the diagnostic unit 100 as a reference profile 507. By comparing the reference with the x/t profile (e.g. the actual profile 307) in normal operation, for example, a varying friction and the resulting risk of jamming can be detected.

The diagnosis method comprises the following steps: generating process actual reference data by storing 507 the process actual data in relation to the process target data 207 before and/or at the start of normal operation; and comparing the process actual data 307 with corresponding process actual reference data 507 while the operation is in progress. If the rate of change of the process actual data 307 differs from the rate of change of the process reference data 507 by a predetermined minimum distance 407 if the process target data 507 are identical, a run time change is identified.

List of reference numerals

10 craft valve

20 actuator valve

30 control module

40 execution system

50 distance measuring system

60 Process control Loop

70 process controller

80 process to be controlled

90 process sensor

100 diagnostic unit

110 diagnostic module

203 … … 207 target curve

303 … … 307, 507 actual curve

403 … … 407 predetermined minimum spacing

503 predefined rate of change

504 predetermined maximum time interval

S Process target value

s actual value of process

t0 … … t7 time point

End value of E Process target value

end value of actual value of e '… … e' process