• 专利附录
  • 专利说明
  • 权利要求
  • 类似技术
  • 同族专利
  • 引用文献
  • 法律状态
  • 优先权
    • 专利摘要:
    A monitoring system (110) for use in an industrial plant (100) is provided. The monitoring system comprises at least one sensor (200) configured to detect at least one operating parameter in the industrial plant. A calculation device. (201) connected to said at least one sensor, and comprising a communication interface. (230) which is configured to receive a plurality of signals each of which is representative of the operating parameter. A processor (214) connected to the communication interface and programmed to calculate a moving average, such as an adaptive moving average, for each signal to enable identification of at least one fault in the industrial plant. The calculation of the moving average of each signal consists of an iterative calculation based at least in part on the calculation of a present value of the average estimate of a first signal.
    公开号:SE1251347A1
    申请号:SE1251347
    申请日:2012-11-28
    公开日:2013-06-08
    发明作者:Steven Hadley
    申请人:Gen Electric；
    IPC主号:
    专利说明:

    [22] In more detail, Equation 1 is a linear adaptive version of an exponential moving average. Using Equation 1, in the output example, the processor 214 is programmed to calculate the present value of the mean value estimate of the signal, Yi, at least in part by calculating a product of the temporal weight factor, ai, and the current signal value, Si, indicated by the current signal as analyzed. In Equation 1, the temporal weight factor, ai, is a function of a data window characteristic, a sample property of the data window, where the window indicates two or fl consecutive data values in a time series which is used to obtain the temporal time factor, ai, which such is the temporal weighting factor, ai, a signal average weighting over a period of time, i, which varies as a function of a window characteristic. In the exemplary embodiment, the temporal weighting factor, ai, is a varying numerical value between about 0 and about 1. In more detail, the window characteristic used to calculate the temporal weighting factor, ai, may be any result where an increase of ai coincides with an increase. in the signal trend. An example of a useful window characteristic is the percentage of window points that is greater than a moving average plus two standard deviations for a normally varying data reference. The processor is programmed to calculate the value of the temporal weight factor a in a data window characteristic via a transform function which converts the data window characteristic to a numerical value from 0 to 1 over a period of time. The temporal weighting factor ai can, for example, be derived from the data window characteristic (data window samples) by using a monotonically increasing function transform, such as a sigrnoid function or power function, which converts the data window characteristic to a numerical value of between about 0 and about 1. Alternatively, the temporal weight function, ai, may be a constant numerical value between approximately o and l.
    Further, in calculating the present value of the signal average estimate, Yi, for the current signal, the processor 214 is programmed to calculate at least one product of a complement (or complement amount) to the temporal weight factor, 1- ai, and the previous signal mean estimate, Yi_i, which was calculated for the previous signal received from the sensor 200 immediately before the reception of the current signal. The processor 214 is also programmed to calculate the sum of the product of the temporal weight factor, ai, and the current signal value, Si, indicated by the current signal with the product of the temporal weight factor complement, 1- ai, and the previous signal mean value estimate, Yi_i .
    Furthermore, the processor 214, in the execution example, is programmed with limit values for a present value of a signal average estimate, Yi, for a number of signals representative of normal drive parameters. For example, processor 214 may also be programmed to generate an output, such as a graphical representation, of the data of normal operating parameters of a component, such as a drive shaft, and processor 214 calculates an average and / or a standard deviation of the data information. The limit values can then be calculated taking into account the mean value and / or the standard deviation of a moving average value output, Y, calculated from a set of normal price data. Furthermore, the processor 214 may be programmed to compare the current signal average estimate, Yi, obtained for each of the signals received from the sensor 200 with the limit values.
    The term “processor” generally refers to any programmable system including systems and micro-controllers, RISCs (Reduced Instruction Set Circuits), and ASIC (Application Speci Integrc Integrated Circuits) circuits. ”), PLC (“ Programmable Logic Circuits ”) and any other circuit or process unit capable of executing the functions described herein. The examples mentioned above are only examples, and are thus not intended to limit in any way the definition and / or meaning of the term 'process- 79 S01'.
    In the exemplary embodiment, the memory device 218 includes one or more devices which enable information such as executable instructions and / or data to be stored and retrieved. Furthermore, in the exemplary embodiment, the memory device 218 includes one or more computer-readable media, such as, without limitation, DRAM (Dynamic Random Access Memory), SRAM (Static Random Access Memory), a solid state disc and / or hard disk. In the exemplary embodiment, the memory device 21 8 stores, without limitation, application source code, application object code, configuration data, additional input events, application states, assumption statements, validation results, and / or other types of data. In more detail, the memory device 218 stores, in the exemplary embodiment, inputs (input data) received by the user via the user interface 205 and / or information received from other components of the monitoring system 110, such as the sensor 200 and / or the power generation system 100.
    Furthermore, in the exemplary embodiment, the computing device 201 includes a communication interface 230 which is connected to the processor 214 via the system bus 220. Furthermore, according to the exemplary embodiment, the communication interface 230 is connected to the sensor 200 via a channel 202.
    The communication interface 230 receives a number of signals representative of at least one operating parameter of at least one component, such as the drive shaft 104, in the power generation system 100 from the sensor 200.
    During drive fi, due to wear, damage, or vibration, for example, one or more of your components may have at least one fault (not shown in fi gur), such as a crack inside the drive shaft 104. Before monitoring and / or or the testing of the drive shaft 104, then a normal drive shaft without defects can be monitored and / or tested to determine a standard set of data or a set of reference data. For example, a set of data taken during normal operation can be used to calculate reference characteristics, averages and standard deviations, for a moving average Y. This statistic, or characteristic, can then be used to calculate alarm thresholds and to calculate the temporal weighting factor, ai.
    Once the default value characteristic or the reference value characteristic has been determined, the monitoring system 110 can measure at least one drive parameter for the drive shaft 104 to obtain data for the drive shaft 104 for presentation to a user, such as an operator of the power generation system 100. In more detail, in the exemplary embodiment, sensor 200 at least one operating parameter of the drive shaft 104, such as measuring and / or monitoring the distance between the shaft 104 and sensor 200 to detect at least one fault, such as a crack inside the drive shaft 104 and / or a misalignment of the drive shaft 104. More detail In the exemplary embodiment, the sensor 200 uses one or fl your microwave signals to measure a presence or proximity, such as a frequency, static and / or vibration presence of the drive shaft 104 relative to the sensor 200.
    In the exemplary embodiment, sensor 200 transmits a number of signals to the computing device 201, such as a first signal and a second signal, each representing at least one drive parameter for the drive shaft 104. In the exemplary embodiment, the signals, such as the first and second signals, are received incrementally of the communication interface 230. For example, the second signal is received by the communication interface 230 before receiving the first signal.
    The signals are then transmitted to the processor 214.
    Using Equation 1, processor 214 then calculates a moving average value for each signal received from sensor 200. For example, using Equation 1, the processor calculates the signal current mean estimate, Yi, for the first signal at least in part by calculating a product of the temporal weight factor, ai, and the current signal value, Si, indicated by the first signal. In calculating the signal current average estimate, Yi, for the first signal, the processor 214 calculates a product of the temporal complementary weight factor 1- ai, and the previous signal average estimate, Yi-i, which was calculated for the second signal received from the sensor 200. immediately before receiving the first signal. Further, the processor 214 calculates the sum of the product of the temporal weight factor, ai, and the current signal value, Si, indicated by the first signal and the product of the temporal complementary weight factor 1- ai, and the previous signal mean estimate Yi_i, for the second signal. The results of the calculations are then transmitted to the presentation interface 207 so that the user can see the data information. According to the exemplary embodiment, an output such as a Greek and / or text representation is provided to the user via display device 210. By calculating a moving average for each signal, the resulting output, such as a Greek representation of data, will be correct even if one of the signals is incorrect.
    According to the exemplary embodiment, during the handling of signals which are representative of the operating parameters of the drive shaft 104 and which are within normal limits, the temporal weight factor, ai, remains approximately at its minimum value since the corresponding driver characteristics remain within its expected drive range. Accordingly, the present value of the signal average estimate, Yi, obtained for each of the received signals is substantially similar and a substantially even output is presented to the user. However, when the sensor 200 begins to detect the fault within the drive shaft 104, the temporal weighting factor, ai, begins to rise. The increase in the temporal weight factor, ai, results in a substantially rapid change in the present value of the signal mean estimate, Yi, obtained for each of the signals. The resulting output presented to the user is a substantially incorrect amount of output so that the user can reliably identify that the drive shaft 104 has an error. 10 15 20 25 30 ll Further according to the exemplary embodiment, the processor 214 is programmed with limit values for the present value of the signal average estimate, Yi, for signals representative of normal dri fi parameters. When the sensor 200 begins to detect the error inside the drive shaft 104, the values of the present value of the signal mean estimate, Yi, obtained for each of the signals are compared with the limit values. If the present value of the signal mean estimate, Yi, obtained for each of the signals exceeds the limit values, then the processor 214 generates a visual output, such as a textual representation of an alarm and / or a warning. Alternatively, processor 214 may generate an audible alarm and / or audible warning. The output is presented to the user via the presentation interface 207. Consequently, the users of the monitoring system 110 may be able to correctly identify the error inside the drive shaft 104. By comparing values of the current signal average estimate, Yi, obtained for each of the signals with the present value limit of signal means, Yi, for signals that are representative of normal operating parameters, false lands can be counteracted.
    In comparison with known systems and methods used to monitor the operation of an industrial plant, the examples of systems and methods described herein provide a monitoring system for use with industrial plants which is capable of providing a substantially accurate output of data representative of any fault within the plant. . The monitoring system described herein includes at least one sensor configured to detect at least one operating parameter in the industrial plant. A calculation device is connected to the sensor and includes a communication interface which is configured to receive a number of signals, each of which is representative of the operating parameter. A processor is connected to the communication interface and programmed to calculate a moving average value for each signal to enable the identification of at least one fault in the industrial plant.
    Calculating the moving average of each signal is an iterative calculation based at least in part on the calculation of a present value of the signal average estimate, Yi, for a first signal. By calculating a moving average value for each signal, the resulting output data, such as a Greek representation of the data, will probably be correct even if one of the signals is incorrect. Accordingly, false indications and / or false alarms regarding faults inside the industrial plant can be prevented.
    A technical effect of the systems and methods described herein includes at least one of: (a) detecting at least one operating parameter of an industrial plant; (b) transmitting a number of signals representative of at least one three parameter to a computing device; (c) receiving, via a communication interface, a number of signals; and (d) calculating, via a processor, a moving average of each signal, the calculation of the moving average of each signal being an iterative calculation that includes calculating a present value of a signal average estimate for a first signal.
    Exemplary embodiments of systems and methods are described in detail above. The systems and methods are not limited to the specific embodiments described herein, but rather the components of the devices, systems and / or steps of the methods may be used independently and separately from other components and / or steps described herein. For example, the system may also be used in combination with other devices, systems and methods and is not limited to use with only the system described herein. Rather, the embodiments can be implemented and utilized in connection with many other applications.
    Although specific features of different embodiments of the invention may be shown in some drawings and not in others, this is for practical convenience only. In accordance with the principles of the invention, a feature of a drawing may be specified and / or included in claims in combination with any other feature of any other drawing.
    This written description uses examples to illustrate the invention, including the best practice, and also to present with a view to enabling one skilled in the art to practice the invention, including the manufacture and use of any device or system and performing any of the present procedures. The patentable scope of the invention is defined by the claims, and may include other examples which will become apparent to those skilled in the art. Such other examples are intended to be within the scope of the claims if they have structural elements which do not differ from the wording of the claims, or if they include equivalent elements with non-substantial difference from the wording of the claims. 13 SYSTEMS AND PROCEDURES FOR USE IN SUPERVISION OF AN INDUSTRIAL PLANT List of parts 1 00 Kra fi generation system 101 Machine 1 02 Rotor 1 04 Drive shaft 1 06 Generator 1 07 Distribution system 1 10 Monitoring system 200 Sensor table 20 Calculation device 206 Canal interface 202 Can interface 210 Display device 214 Processor 21 8 Memory device 220 Sister bus 230 Communication interface
    权利要求:
    Claims (10)
    [1]
    A monitoring system (110) for use in an industrial plant (100), said monitoring system comprising: at least one sensor (200) configured to detect at least one operating parameter in the industrial plant; and a computing device (201) connected to said at least one sensor, said computing device comprising: a communication interface (230) configured to receive a plurality of signals each representative of the at least one operating parameter, and a processor (214) connected to the communication interface and programmed to calculate a moving average of each signal to enable the identification of at least one fault in the industrial plant, the calculation of the moving average of each signal being an iterative calculation based at least in part on calculation of a present value of an average value estimate for a first signal.
    [2]
    A monitoring system (110) according to claim 1, wherein said processor (214) is programmed to calculate the present value of the mean value estimate based at least in part on a temporal weight factor, a current signal value indicated by the first signal, and a previous mean value estimate of a second signal received by the communication interface (230) before receiving the first signal.
    [3]
    The monitoring system (110) according to claim 2, wherein said processor (214) is programmed to calculate the present value of the average estimate of the first signal at least in part by calculating a product of the temporal weight factor and the current signal value indicated by the first signal.
    [4]
    The monitoring system (110) according to claim 2, wherein said processor (214) is programmed to calculate the present value of the mean value estimate of the first signal at least in part by calculating a product of a complement value for a temporal weight factor and the previous signal mean value estimate of the second signal. the signal received by said communication interface (230).
    [5]
    The monitoring system (110) according to claim 2, wherein said processor (214) is programmed to calculate the present value of the average estimate of the first signal by calculating a sum of a product of the temporal weight factor and the current signal value indicated by the first signal with a product of a complementary value for the temporal weight factor and previous signal average estimate of the second signal.
    [6]
    The monitoring system (110) of claim 2, wherein said processor (214) is programmed to calculate the temporal weighting factor from a data window statistic via a transform function that converts the data window statistic to a numeric value from about 0 to about 1 over a period of time such that the temporal weight factor comprises a varying numerical value between about 0 and about 1.
    [7]
    The monitoring system (110) according to claim 1, wherein said processor (214) is programmed to calculate at least one limit value of the mean value estimate of the signal, said processor is further programmed to compare the at least one limit value of the present value of the mean value estimate with the present value of the average estimate of the first signal.
    [8]
    An industrial plant (100) comprising: at least one machine (101) comprising at least one component (10 2); and a monitoring system (110) connected to said at least one component, said monitoring system comprising: at least one sensor (200) configured to detect at least one operating parameter of said at least one component; and a computing device (201) connected to said at least one sensor, said computing device comprising: a communication interface (230) which is configured to receive a number of signals each of which is representative of the at least one three parameter, and a processor (214) connected to the communication interface and programmed to calculate a moving average of each signal to enable identification of at least one error in the at least one component, calculating the moving average of each signal being an iterative calculation based at least in part on calculating a present value of an average estimate for a first signal.
    [9]
    An industrial plant (100) according to claim 8, wherein said processor (214) is programmed to calculate the present value of the mean value estimate based at least in part on a temporal weight factor, a current signal value indicated by the first signal, and a previous signal mean value estimate of a second signal received through the communication interface (230) before receiving the first signal.
    [10]
    An industrial plant according to claim 9, wherein said processor (214) is programmed to calculate the present value of the average estimate of the first signal at least in part by calculating a product of the temporal weight factor and the current signal value indicated by the first signal.
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    法律状态:
    2015-03-31| NAV| Patent application has lapsed|
    优先权:
    申请号 | 申请日 | 专利标题
    US13/313,568|US20130151199A1|2011-12-07|2011-12-07|Systems and methods for use in monitoring an industrial facility|
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