Reassessment of valve suitability and functionality on process lines

Abstract

Control systems are configured to monitor the operation of flow control devices, such as control valves. These configurations can use continuous or real-time data to evaluate the suitability or function of devices under operating conditions. This feature can alert operators to problems or issues with one or more devices or the entire process line. These problems may indicate, for example, that a valve is incorrectly sized for the actual operating conditions. As a result, because the design process for process line layout relies on design loads that reflect future maximum values ​​(plus some safety factor) and not on the actual operating conditions that may prevail after the device is used in the field, engineers may realize that a valve is too large (or oversized) or too small (or undersized).

Description

[Technical Field]

[0001] Flow control devices play a critical role in many industrial facilities. For example, power plants and industrial processing facilities use different types of flow control devices to manage the flow of materials, typically fluids, throughout vast networks of pipes, tanks, generators, and other equipment. During the design phase, engineers develop and layout the structures for process lines or other distribution networks in these facilities. The design process often utilizes software to select flow control devices, such as control valves. Engineers provide or input data into the software, including flow rates, pressures, and material properties, among other system-related parameters. The software then identifies appropriately sized (or configured) valves that theoretically achieve specific parameters on the process line. However, the "design" data may not reflect actual operating parameters because these parameters are only known after the process line is constructed and the valves have been in use for some time.

[0002] Control software in industrial plants often provides "real-time" diagnostics to address this lack of data during the design phase. These systems can collect information describing the performance of a control valve, such as data defining travel or position, air usage, packing friction, etc. From this data, the system can generate values ​​to map or trend performance. By comparing the values ​​to expected thresholds, such as predicted positions, the system can identify abnormal operation that could potentially be a precursor to more disruptive or problematic operation. Summary of the Invention

[0003] The subject matter of this disclosure relates to improved device and process diagnostics. Of particular interest herein are embodiments capable of evaluating flow control devices, such as control valves, in use as part of a process line. These embodiments can include systems that provide real-time analysis of control valves using not only data collected by a control system from the device, but also data describing actual operating conditions on the process line. The use of this "operating data" can compensate for inconsistencies or incorrect assumptions made during the design phase, since it takes into account the suitability and function of the control valve under the actual conditions it will encounter in use. As a result, the systems proposed herein can identify problems, such as undersized or oversized valves, valve cavitation, or similar performance anomalies or issues, that may go unnoticed by operators and maintenance personnel when using only data describing the specific performance of each device. [Brief explanation of the drawings]

[0004] This specification makes reference to the following drawings: [Figure 1] FIG. 1 is a schematic diagram of an embodiment of a valve control system. [Figure 2] 1 is a flow diagram of an embodiment of a method for operating a valve control system. [Figure 3] 1 is a flow diagram of an embodiment of a method for operating a valve control system.

[0005] These drawings and any descriptions herein represent examples that may disclose or describe the invention. These examples, including the best mode, enable one skilled in the art to practice the invention, including making and using any device or system and performing any incorporated methods. The drawings are not to scale unless otherwise noted in the description. Elements in each example may appear in one or more of the figures or in combinations of multiple figures. The figures may use like reference numerals to indicate identical or corresponding elements. Each method is merely exemplary and may be modified, for example, by reordering, adding, removing, and / or changing individual steps or steps. In this specification, such steps, as well as any parts, components, elements, or functions, may be identified in the singular using the word "a" or "an." However, this should not exclude the plural of such designation unless the specification expressly states or describes such exclusion. Similarly, reference to "one embodiment" or "one implementation" should not be interpreted as excluding the existence of additional embodiments or implementations that also incorporate the recited features. DETAILED DESCRIPTION OF THE INVENTION

[0006] The following describes features of the embodiments shown in the above figures. These embodiments use device-level diagnostics as part of a process line management system. These systems provide operators or facility personnel, such as technicians or engineers, with tools to understand or evaluate assets in service on a process line. These tools are useful for resolving problems, predicting potential failures, and proactively scheduling maintenance. As a result, operators are in a much better position to avoid lengthy and costly outages that can impact production. Other embodiments are contemplated within the scope and spirit of this disclosure.

[0007] 1 shows a schematic diagram of one embodiment of a control system 100. This embodiment is typically part of a distribution network 102 designed to transport material 104 throughout a network of conduits 106. A flow controller 108 can be connected in series with the conduits 106. The flow controller 108 can include a valve body 110 that houses a seat 112 and a closure member 114 that can move to various positions relative to the seat 112 to regulate the flow of the material 104. A valve stem 116 can connect the closure member 114 to an actuator 118. The flow controller 108 can also include a valve positioner 120 with operating hardware 122. In one implementation, the control system 100 can include a feedback loop 124 that provides data to a system controller 126, which generates a control signal C.

[0008] Generally, the control system 100 can be configured to evaluate device performance. These configurations can process data that defines the actual operating conditions of the device. This data can occur in real time, or a process can periodically collect data and store it in a repository for later processing. These characteristics update the analysis of the device performed during the layout or design of the facility. The results are new values ​​that can better describe the device suitability or functionality when the device operates under different conditions, which may differ from the conditions available during the layout or design phase.

[0009] The distribution network 102 may be configured to deliver or move resources. These configurations may embody vast infrastructures. The materials 104 may include gases, liquids, or mixtures of liquids or gases. The conduits 106 may include pipes or pipelines that often connect to pumps, boilers, etc. The pipes may also connect to tanks or reservoirs. In many facilities, this equipment forms a complex network.

[0010] Flow control devices 108 can be configured to regulate the flow of material 104 through conduits 106 in this complex network. These configurations can include control valves and similar devices. The valve body 110 in such devices is often made of cast metal or forged. This structure can form flanges at openings I, O. Adjacent pipes 106 can connect to these flanges to allow material 104 to flow through the device, for example, through openings in seats 112. The closure member 114 can embody a metal disk or plug. The valve stem 116 can embody an elongated cylinder or rod that connects to the plug at one end. The other end of the rod can be coupled to a pneumatic or electric manipulator that embodies an actuator 118.

[0011] The valve positioner 120 can be configured to process and generate signals. These configurations can control the position or "set point" of the flow controller 108. For example, the operating hardware 122 can use electrical and computing components (e.g., a processor, memory, executable instructions, etc.). These components may also include electro-pneumatic devices. Together, these devices can process the input control signal C to generate an output actuator control signal S2 to the actuator 118 and the appropriate pressure (or other parameter) for the control valve 108 to deliver the material 104 downstream in accordance with process parameters.

[0012] The feedback loop 124 can be configured to provide data indicative of operating parameters on the process line. These configurations can measure various operating parameters or conditions prevailing on, at, or near the flow control device 108. Sensors or similar data collection mechanisms can be present on the valve(s) as well as throughout the pipe or conduit. These sensors can provide device-specific information. In one example, the sensor can embody a mechanical linkage coupling the valve stem 116 to a rotatable disk on the valve positioner 120. The disk may rotate in response to the mechanical linkage. This feature changes the position of a magnet relative to a magnetic flux sensor, which indicates the position of the closure member 114. Other sensors can include pressure sensors, temperature sensors, humidity sensors, flow sensors, etc.

[0013] The system controller 126 can be configured to control devices on the process line. These configurations may be part of a larger control network (or "distributed control system" or "DCS"). The DCS maintains the operation of all devices on the process line to ensure that material, for example, flows according to a predetermined process. In use, the system controller 124 can generate a control signal C to each of these devices. This electronic signal can define operating parameters, for example, valve setpoints. As described above, the valve positioner 120 can convert this signal into a suitable actuator control signal S2 that is effective against the actuator 118.

[0014] FIG. 2 shows a flow diagram of example steps of a method 200 for operating the system controller 126 or valve positioner. These steps may correspond to executable instructions, such as a computer or software program, that configure the system controller 100 for specific operations. The instructions may, for example, process data to arrive at values ​​that define the operation of the flow control 108. These operations may configure the flow control 108 to provide material to a process at required parameters. In one implementation, the method 200 may include receiving input or feedback in step 202 and calculating a performance parameter of the target valve(s) based on the input in step 204. The method 200 may also include identifying a relationship between the performance parameter and a value of the target valve(s) in step 206. The method 200 may further include generating an output based on the relationship in step 208.

[0015] In stage 202, the system controller 126 may receive several inputs. These inputs may include the valve position or pressure of the control signal S2. This information may also reflect data about the process line itself. This data may include parameters of the material 104, including the pressure or temperature upstream and downstream of the valve. In one implementation, the data may also represent ambient conditions, such as the temperature, relative humidity, and pressure at or around the device. As mentioned above, the data can identify the operating conditions of devices on the process line. However, the present disclosure contemplates that some data may reflect "proxy" data, or data that may be selected or provided by an operator, especially when real-time data is not available or feasible.

[0016] In step 204, the system controller 126 may calculate a performance parameter. The result may represent one of a variety of values ​​that characterize the target device when it operates under current or “actual” operating conditions. In one implementation, the value may describe the valve size, for example, its flow coefficient (Cv) or an equivalent metric. The value may also describe other “key performance indicators” or “KPIs,” as desired. KPIs may define noise, cavitation, valve travel or position, or fluid characteristics (such as velocity, flow rate, or Mach number), among others. The algorithms and mathematical models for arriving at the KPIs may conform to industry standards. However, using data that reflects actual operating conditions on the process line is beneficial because this “actual” KPI may represent a better and more accurate analysis of the target valve’s performance.

[0017] In step 206, the system controller 126 may compare the “actual” KPI to several thresholds. The relationship between these two values ​​may indicate problems or potential issues with the device, process line, or process. The target device may be too large (oversized) or too small (undersized) for the process. Either of these deficiencies can lead to noise that exceeds system specifications or industry standards. Undersized valves can “starve” the process of process fluid due to their limited flow capacity. These valves also have higher pressure drops and, in some cases, can cause upstream pressure buildup. This buildup generates backpressure that can damage pumps or other upstream equipment. Oversized valves can be more costly and larger in size (and weight). Because the DCS must “chase” the device's appropriate setpoint to meet process parameters, devices that are larger than necessary are usually more difficult to control, leading to process instability. It is not uncommon for the plug (or disc) of an oversized valve to operate in a position close to the seat. This location can result in higher fluid velocities that can cause cavitation, noise, erosion, or other operational defects that can damage components and potentially result in device failure.

[0018] In step 208, the system controller 126 may generate an indicator. This relationship may indicate that the target valve (or valves) are not "compatible" with the actual operating conditions on the process line. The indicator can alert the operator to this problem. In one implementation, this alert can provide the operator with information regarding changes to the valve configuration, such as changing valve trim, that can remedy any of the sizing issues described above. This information may also identify an appropriate valve size or model that the operator can use to replace the target valve. The indicator can also alert the operator to potential cavitation, noise, backpressure, etc. These alerts can be resolved on the user interface or as a message (e.g., email or text message) on a connected device.

[0019] FIG. 3 shows a flow diagram of another embodiment of method 200. This embodiment may include, in step 210, identifying a flow regime for the current operating conditions. The flow regime may include a “subcritical” flow regime, which may occur, for example, when the downstream pressure (P2) is less than or equal to half the upstream pressure (P1) of the device. This subcritical regime allows method 200 to continue applying subcritical theory to calculate the performance parameter(s) in step 212. Alternatively, the flow regime may correspond to a “critical” or “choked” flow regime, where the downstream pressure (P2) is greater than half the upstream pressure (P1) on the device. In this regime, any increase in pressure drop at a constant inlet pressure does not result in any increase in flow through the device, so the flow rate may be limited or capped. In the case of choked flow, method 200 may continue applying choked flow theory to calculate the performance parameter in step 214.

[0020] Liquid flow coefficient (C v ) may correspond to each flow regime. For subcritical flows, for example, the value may be determined according to equation (1) below:

[0021]

number

[0022]

number

[0023] Operators can use these values ​​to differentiate between valves on a process line. For example, indicators can be used to detect "actual" flow coefficients (C) that deviate from the initial calculated values ​​during the design phase. v ) can alert the operator to be careful of flow control devices having a pressure or flow rate. The method 200 can also maintain a record of these values ​​to present to the operator as a reference for possible changes on the process line, such as changes in pressure or flow rate, that might not otherwise be apparent from conventional data analysis.

[0024] Both the "subcritical" and "choked" flow regimes can result in cavitation. This phenomenon can increase noise and cause damage to the flow control device 108, as well as any adjacent or associated pipes 106 or equipment connected thereto. In one implementation, the method 200 can include quantifying a cavitation value or "sigma index" for both regimes. The indicator can correspond to a warning to notify an operator that the sigma index exceeds the service sigma, which can help the operator avoid problems caused by cavitation on the device.

[0025] The method 200 may also include steps for quantifying other parameters. These parameters may include a % open value for the valve in both modes, which defines the position of the closure member 114 relative to the seat 112, preferably relative to a closed position (or 0% open), which represents the closure member 114 in contact with the seat 112. The parameters may further include steps for calculating the velocity or flow rate of the material 104 as it passes through the valve body 110.

[0026] In view of the above, improvements herein can help facilities maintain efficient production processes. The proposed design evaluates valves online using data reflecting operating conditions accompanied by analysis. This feature can identify adverse effects that may occur to a line valve in response to, for example, operator changes to process parameters necessary to accommodate different feedstocks or other production anomalies. In one implementation, the design can uncover fit and function issues with a particular valve as new parameters may deviate from the valve's original "design" criteria. These issues may gradually spread undetected for some time until the valve itself fails or begins to fail before its known end-of-life design.

[0027] To illustrate embodiments contemplated within the scope and spirit of the present disclosure, the following examples include particular elements or items, one or more of which may be combined with other elements and items. The scope includes and is contemplated by those skilled in the art. Such other examples are intended to be within the scope of the claims if they have structural elements that do not differ from the literal language of the claims, or if they have equivalent structural elements that differ insignificantly from the literal language of the claims.

Claims

1. 1. A method comprising: receiving data about a valve on a process line reflecting an operating condition of the valve; calculating valve parameters for the valve based on the data; comparing said valve parameter to a known threshold level; generating an output based on a relationship between the valve parameter and the known threshold level.

2. The method of claim 1 , wherein the valve parameter is a flow coefficient.

3. The method of claim 1 , wherein the output identifies the suitability of the valve on the process line as related to the operating conditions.

4. The method of claim 1 , wherein the output correlates the size of the valve on the process line as related to the operating conditions.

5. The method of claim 1 , wherein the output correlates a percentage opening value of the valve on the process line as related to operating conditions.

6. The method of claim 1 further comprising quantifying a cavitation index of the valve.

7. identifying a flow regime for the valve based on the data; and The method of claim 1 , further comprising: applying a specific computational theory corresponding to the flow regime.

8. The method of claim 1 , wherein the valve parameters are based on a computational theory of choked flow.

9. The method of claim 1 , wherein the valve parameters are based on computational theory of subcritical flow.

10. The method of claim 1 , wherein the valve parameters describe a flow rate through the valve.

11. 1. A control system comprising: A controller; a feedback loop that provides data to the controller describing operating conditions of valves on the process line; The controller stores the data as calculating valve parameters for the valve based on the data; comparing said valve parameter to a known threshold level; generating an output based on a relationship between the valve parameter and the known threshold level; and a control system configured to process according to the relationship between the valve parameter and the known threshold level.

12. The control system of claim 11 , wherein the valve parameter is a flow coefficient.

13. The method of claim 11 , wherein the output identifies the suitability of the valve on the process line as related to the operating conditions.

14. The method of claim 11 , wherein the output correlates the size of the valve on the process line as related to the operating conditions.

15. 12. The method of claim 11, wherein the output correlates a percentage opening value of the valve on the process line as related to operating conditions.

16. The method of claim 11 , further comprising quantifying a cavitation index of the valve.

17. identifying a flow regime for the valve based on the data; and The method of claim 11 , further comprising: applying a specific computational theory corresponding to the flow regime.

18. The method of claim 11 , wherein the valve parameters are based on a computational theory of choked flow.

19. 12. The method of claim 11, wherein the valve parameters are based on computational theory of subcritical flow.

20. The method of claim 11 , wherein the valve parameters describe a flow rate through the valve.

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