Source: http://www.google.com.hk/patents/US6907383
Timestamp: 2013-05-24 05:21:49
Document Index: 89183804

Matched Legal Cases: ['art 2', 'art 3', 'art 3', 'art 2', 'art 2', 'art 4', 'art 4']

�M�Q US6907383 - Flow diagnostic system - Google �M�Q�j�M �Ϥ� �a�� Play YouTube �s�D Gmail ���ݵw�� ��h »�i���M�Q�j�M | �������� | �n�J�i���M�Q�j�M�M�QA flow diagnostic system for a flow sensing element and impulse lines. A pressure transmitter coupled to the impulse lines provides digital pressure data to a control system. The control system provides the pressure data and real time clock readings to a diagnostic application. The diagnostic application...http://www.google.com.hk/patents/US6907383?utm_source=gb-gplus-share�M�Q US6907383 - Flow diagnostic system���}��US6907383 B2�X���������v�ӽЮѽs��09/852,102�o�G���2005�~6��14���ӽФ��2001�~5��9�� �u���v���1996�~3��28����L���}�M�Q��CN1514928ACN100507465CEP1407233A1EP1407233B1US20020029130WO2002090894A1�o��HEvren EryurekKadir Kavaklioglu��M�Q�v�HRosemount Inc. ���M�Q������702/183702/4773/1.5773/1.71702/100��ڱM�Q������G05B23/02G01F25/00G01F1/00G01F1/34G01L19/00G05B21/02G01F1/50G05B13/02G01F1/36G05D7/06 �X�@����G05B13/0275G01F25/0007G05D7/0617G01F1/50G01F1/363G05B21/02 �ڬw������G01F25/00AG01F1/36AG05B21/02G01F1/50G05D7/06FG05B13/02C2�ѦҤ��m�M�Q�ޥ� (125)�D�M�Q�ޥ� (104)�Q�H�U�M�Q�ޥ� (24)�~���s�����M�Q�ӼЧ� ���M�Q�ӼЧ��M�Q����T�� �ڬw�M�Q��Flow diagnostic systemUS 6907383 B2�K�n A flow diagnostic system for a flow sensing element and impulse lines. A pressure transmitter coupled to the impulse lines provides digital pressure data to a control system. The control system provides the pressure data and real time clock readings to a diagnostic application. The diagnostic application calculates a difference between current pressure data and its moving average. A condition of the primary element or impulse lines is diagnosed from a current pressure data set relative to an historical data set. The diagnostic application is downloadable from an application service provider (ASP). The application can run on the control system, a remote computer or the ASP. A diagnostic report is preferably provided.
Disassembly and inspection of the impulse lines is one method used to detect and correct plugging of lines. Another known method for detecting plugging is to periodically add a ��check pulse�� to the measurement signal from a pressure transmitter. This check pulse causes a control system connected to the transmitter to disturb the flow. If the pressure transmitter fails to accurately sense the flow disturbance, an alarm signal is generated indicating line plugging. Another known method for detecting plugging is sensing of both static and differential pressures. If there is inadequate correlation between oscillations in the static and differential pressures, then an alarm signal is generated indicating line plugging. Still another known method for detecting line plugging is to sense static pressures and pass them through high pass and low pass filters. Noise signals obtained from the filters are compared to a threshold, and if variance in the noise is less than the threshold, then an alarm signal indicates that the line is blocked.
FIG. 1 is a schematic illustration of a generalized example of a flow diagnostic system 100 that diagnoses the condition of impulse lines 104 and/or a primary flow element 106 placed in a fluid piping system 108. The impulse lines 104 and the primary element 106 are referred to collectively as a ��pressure generator.��
The term ��pressure generator�� as used in this application means a primary element (e.g., an orifice plate, a pitot tube, a nozzle, a venturi, a shedding bar, a bend in a pipe or other flow discontinuity adapted to cause a pressure drop in flow) together with impulse pipes or impulse passageways that couple the pressure drop from locations near the primary element to a location outside the flow pipe. The spectral and statistical characteristics of this pressure presented by this defined ��pressure generator�� at a location outside the flow pipe to a connected pressure transmitter 102 can be affected by the condition of the primary element as well as on the condition of the impulse pipes. The connected pressure transmitter can be a self-contained unit, or it can be fitted with remote seals as needed to fit the application. A flange on the pressure transmitter 102 (or its remote seals) couples to a flange adapter on the impulse lines 104 to complete the pressure connections in a conventional manner. The pressure transmitter 102 couples to a primary flow element 106 via impulse lines 104 to sense flow. Primary element 106, as illustrated, is an orifice plate clamped between pipe flanges 105.
In difference algorithm 540, the moving average is calculated according to the series in Eq. 1: A j = ∑ k = 0 m ⁢ ( P j + k ) ⁢ ( W k ) Eq. 1 where A is the moving average, P is a series of sequentially sensed pressure values, and W is a numerical weight for a sensed pressure value, m is a number of previous sensed pressure values in the series. Provision can also be made in difference circuit 540 to filter out spikes and other anomalies present in the sensed pressure. In FIG. 5, the historical data comprises statistical data, for example, the mean (�g) and standard deviation (�m) of the difference output or other statistical measurements, and the diagnostic output 558 indicates impulse line plugging. The diagnostic application switches between a training mode when it is installed and a monitoring mode when it is in use measuring flow as illustrated by switch 550. The calculate algorithm 554 stores historical data in the training mode. The diagnostic data output 558 indicates a real time condition of the pressure generator. In FIG. 5, statistical data, such as the mean �g and standard deviation �m, are calculated based on a relatively large number of data points or flow measurements. The corresponding sample statistical data, such as sample mean X and sample standard deviation s, are calculated from a relatively smaller number of data points. Typically, hundreds of data points are used to calculate statistical data such as �g and �m, while only about 10 data points are used to calculate sample statistical data such as X and s. The number of data points during monitoring is kept smaller in order to provide diagnostics that is real time, or completed in about 1 second. Diagnostic algorithm 556 indicates line plugging if the sample standard deviation s deviates from the standard deviation �m by a preset amount, for example 10%.
Power spectral density, Fi, can also be calculated using Welch's method of averaged periodograms for a given data set. The method uses a measurement sequence x(n) sampled at fs samples per second, where n=1, 2, . . . N. A front end filter with a filter frequency less than fs/2 is used to reduce aliasing in the spectral calculations. The data set is divided into Fk,i as shown in Eq. 2: F k , i = ( 1 / M ) ⁢ �� ∑ n = 1 M ⁢ X k ⁡ ( n ) ⁢ ⅇ - j2 ⁢ ⁢ �k ⁢ ⁢ ⅈ ⁢ ⁢ �G ⁢ ⁢ f ⁢ ⁢ n �� 2 Eq. 2 There are Fk,i overlapping data segments and for each segment, a periodogram is calculated where M is the number of points in the current segment. After all periodograms for all segments are evaluated, all of them are averaged to calculate the power spectrum: F ⁢ ⁢ i = ( 1 / L ) ⁢ ∑ k = 1 L ⁢ F k , i Eq. 3 Once a power spectrum is obtained for a training mode, this sequence is stored in memory, preferably EEPROM, as the baseline power spectrum for comparison to real time power spectrums. Fi is thus the power spectrum sequence and i goes from 1 to N which is the total number of points in the original data sequence. N, usually a power of 2, also sets the frequency resolution of the spectrum estimation. Therefore, Fi is also known as the signal strength at the ith frequency. The power spectrum typically includes a large number points at predefined frequency intervals, defining a shape of the spectral power distribution as a function of frequency.
The algorithm starts at 702. A moving average is subtracted from differential pressure data as shown at 704 to calculate a difference. During a train mode, historical data on the calculated difference is acquired and stored at 706 as statistical data �g and �m, for example. During an operational MONITOR mode, current data on the difference is acquired and stored at 708 as statistical data X and s. The smaller sample of current data is compared to the larger sample of the historical data to diagnose the condition of the impulse lines. Comparisons 710 of historical and current statistical data are made at 714, 716, 718 and a selected diagnostic output is generated at 730, 732, 734 as a function of the comparisons made at 712, 714, 716, 718 respectively.
After completion of any diagnostic output, the process loops back at 720, 722, 724, 726 or 728 to repeat the monitor mode diagnostics, or the transmitter can be shut down until maintenance is performed. If the diagnostic process itself fails, an error indication is provided on the diagnostic output at 736. In the method of diagnosis illustrated in FIG. 7, the historical data set comprises statistical data such as data on the mean (�g) and standard deviation (�m) of the calculated difference; the current data set comprises current sample statistical data, such as the sample average (X) and sample deviation (s) of the calculated difference. The sample deviation (�m) is compared to the standard deviation (�m) to diagnose impulse line plugging, for example. Other known statistical measures of uncertainty, or statistical measures developed experimentally to fit this application can also be used besides mean and standard deviation. When there is an unusual flow condition where X is much different than �g, the diagnostics can be temporarily suspended as shown at 712 until usual flow conditions are reestablished. This helps to prevent false alarm indications.
The flow diagnostics system can also be used with a transmitter (not illustrated) which connects to taps near the bottom and top of a tank. The transmitter provides an output that represents a time integral of flow in and out of the tank. The transmitter includes circuitry, or alternatively software, that measures the differential pressure between the taps and computes the integrated flow as a function of the sensed differential pressure and a formula stored in the transmitter relating the sensed pressure to the quantity of fluid in the tank. This formula is typically called a strapping function and the quantity of fluid which has flowed into or out of the tank can be integrated as either volumetric or mass flow, depending on the strapping function stored in transmitter. The transmitter can be located either near the bottom or the top of tank, with a tube going to the other end of the tank, often called a ��leg.�� This leg can be either a wet leg filled with the fluid in the tank, or a dry leg filled with gas. Remote seals can also be used with such a transmitter.
FIG. 11 is a block diagram of a discrete wavelet transformation. FIG. 11 illustrates an example in which an original set of digital pressure data or signal S is decomposed using a sub-band coder of a Mallet algorithm. The signal S has a frequency range from 0 to a maximum of fMAX. The signal is passed simultaneously through a first high pass filter 250 having a frequency range from ½ fMAX to fMAX, and a low pass filter 252 having a frequency range from 0 to ½ fMAX. This process is called decomposition. The output from the high pass filter provides ��level 1�� discrete wavelet transform coefficients 254. The ��level 1�� coefficients 254 represent the amplitude as a function of time of that portion of the input signal which is between ½ fMAX and fMAX. The output from the 0-1/2 fMAX low pass filter 252 is passed through subsequent high pass (¼ fMAX-½ fMAX) filter 256 and low pass (0-¼ fMAX) filter 258, as desired, to provide additional levels (beyond ��level 1��) of discrete wavelet transform coefficients. The outputs from each low pass filter can be subjected to further decompositions offering additional levels of discrete wavelet transformation coefficients as desired. This process continues until the desired resolution is achieved or the number of remaining data samples after a decomposition yields no additional information. The resolution of the wavelet transform is chosen to be approximately the same as the sensor or the same as the minimum signal resolution required to monitor the signal. Each level of DWT coefficients is representative of signal amplitude as a function of time for a given frequency range. Coefficients for each frequency range are concatenated to form a graph such as that shown in FIG. 10.
FIG. 17 illustrates a computer platform 1 that connects via an interface 2 to one of several Hart interchange Devices 4. Interface 2 can be an RS232-RS485 converter, an ethernet connection, an intranet or internet connection, or other suitable interface that communicates information to the computer platform 1. The computer platform 1 is typically a personal computer located in a maintenance shop area that includes application software such as an Asset Management Solutions (AMS) software application from Rosemount Inc. Each Hart interchange devices 4 couples to one or more pressure transmitters 6 via a termination panel 8. The Hart interchange devices 4 are coupled via a DIN rail or bus 10 to a control system 12. A diagnostic application 14 as described above in connection with FIGS. 1-16 also resides on computer platform 1. Computer platform 1 provides a diagnostic report as explained above. The arrangement illustrated in FIG. 17 allows substantially all of the diagnostic software to run on computer platform 1 (which is a small control system) rather than place additional overhead on control system 12. The term ��control system�� as used in this application includes control systems such as control system 112 in FIG. 1 which provide electrical feedback to a fluid processing plant as well as computers that perform a monitoring function such as computer platform 1, where the feedback to the fluid processing plant comprises human intervention based on a diagnostic report generated by the computer platform 1.
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