The present invention relates to a piping network leak detection system detecting and outputting a position where a compressed gas or liquid leaks and the amount of the leakage in a piping network including a device supplying the compressed gas or liquid, piping, and equipment consuming the compressed gas or liquid.
A pneumatic system as a piping facility that supplies compressed air to each department in a factory temporarily accumulates the compressed air compressed by an air compressor in an air tank. Subsequently, the system supplies the compressed air from the air tank via a piping path and pneumatic equipment (such as a filter, a dryer, and a control valve) to equipment (terminal facility) consuming the compressed air in a production process in the factory such as an air cylinder and an air blow in the factory. In many cases, compressed air leakage occurs in the piping network during the compressed air supply from the air compressor to the terminal facility through the piping network due to, for example, air piping deterioration attributable to the passage of time and clearances at piping joints and curved parts. It can be said in general statistics that the compressed air leakage is equivalent to approximately 20% to 30% of an air compressor discharge flow rate in a factory without measures against compressed air leakage. Further, similar liquid leakage may occur in a liquid-supplying piping network as well.
Further, in recent years, electric power consumption reduction is required in factories and the like regarding the trend of electric power consumption reduction related to global warming prevention and energy conservation laws. To that end, it is important to grasp a compressed air leak amount and a compressed air leak position and take leakage prevention measures in order to reduce the electric power consumption of an air compressor. In some cases, however, concrete leakage countermeasure implementation is not easy because compressed air leakage is invisible, without smell, or harmless to the human body and the environment.
According to conventional compressed air leakage countermeasures, an air compressor needs to be operated on a day when no factory production is conducted such as a non-work day and a leak amount needs to be calculated on the basis of a value measured by a flow meter or an electric power meter attached to a terminal facility so that the occurrence or nonoccurrence of compressed air leakage can be confirmed. Actual leak position grasping is quite burdensome on a worker's part as the air compressor should be operated on a non-production day as described above, he or she should look around the factory, and ultrasonic waves with a frequency of around 40 KHz should be detected with an ultrasonic leak detector or the like. In addition, periodic confirmation and repair are necessary as compressed air leaks from air piping joints and so on in many cases and leakage may be repeated over time after fixing due to deterioration, looseness, or the like.
The background art pertaining to this technical field includes JP 2011-54209 A (Patent Document 1). A compressed air leakage diagnosis technique is disclosed in Patent Document 1. According to Patent Document 1, a user inputs a compressed air leak position candidate in a network and solves an optimization problem to minimize an objective function to be defined by using network values calculated and measured by a piping network simulation device. In this manner, the user performs compressed air leak location candidate and leak amount calculations.
Patent Document 1: JP 2011-54209 A
As described above, in Patent Document 1, a compressed air leak position candidate is input beforehand in a piping network defined as virtual compressed air consumption equipment configured from pneumatic equipment and compressed air leakage. In addition, the steady state of the entire piping network at a certain time is calculated with respect to every combination of designated compressed air leakage locations and the optimization problem described above is solved for the purpose of compressed air leak position determination.
Indispensable for the technique described in Patent Document 1 is for the user to pre-input compressed air leak location candidates, and a highly likely candidate is output from the input compressed air leak location candidates. In other words, whether leakage actually occurs is diagnosed with respect to the compressed air leak location candidates, and thus a location not designated as a leak location candidate is not included in the leak locations and omission may occur during the leak location detection. Besides, optimization calculation needs to be conducted with respect to every compressed air leak location combination and a problem arises from an enormous amount of calculation processing as for a large-scale piping network.
The technique described in Patent Document 1 provides no specific description at all with regard to measured values pertaining to a piping network. In other words, nothing is described in Patent Document 1 regarding, for example, locations and numbers required for measurement. Optimization calculation results are highly dependent on selection of the measured values, and thus a problem arises as no precision of detection is guaranteed concerning compressed air leak locations and amounts.
The present invention has been made in view of the above circumstances, and the purpose of the present invention is to provide a piping network leak detection system and a leak detection device and a leak detection method used in the system capable of detecting and outputting the position and amount of leaks of a compressed gas or liquid on the basis of desired time duration measurement values acquired during operation of a compressor and eliminating the need for leak location candidates to be designated in a piping network.
In order to achieve the above purpose, the present invention has the following configuration as an example. A device for detecting leaks of a gas or liquid in a piping network temporarily accumulates a compressed gas or liquid compressed by a compressor in a supply tank and then supplies the compressed gas or liquid from the supply tank via piping to a terminal facility consuming the compressed gas or liquid. The leak detection device includes a time series measurement value acquisition unit acquiring a time series measurement value for each of a supply tank pressure and supply tank flow rate supplied from the gas or liquid supply tank and a terminal facility pressure at an entrance of the terminal facility, a time series measurement data extraction unit extracting time series measurement data exhibiting a high change in pressure for a certain time duration from the time series measurement value, a piping network model construction unit creating a piping network model including the compressor, the supply tank, the terminal facility, and the piping, a time series response calculation unit calculating a time series response of a flow rate and pressure within the piping network on the basis of the piping network model, the extracted time series measurement data being used as a boundary condition in the calculation, a leak position/amount determination unit determining the position and amount of a leak of the gas or liquid within the piping network on the basis of the calculated time series response of the flow rate and pressure, and an output display unit displaying the leak position and leak amount.
According to the present invention, it is possible to provide a piping network leak detection system and a leak detection device and a leak detection method used in the system with which conventionally required periodic inspections are unnecessary. The system uses time series measurement values acquired during compressor operation, and thus high-precision leak detection can be performed.
Hereinafter, examples of the present invention will be described with reference to accompanying drawings.
The piping network leak detection system illustrated in
In
The piping network leak detection device X2 calculates the internal pressure and flow rate of a piping network by using the detection values of the pressure sensors X11 and X13 and the flow rate sensor X12 as inputs, detects a leak position and the leak amount at the leak position, and displays the result of the detection on a display device. It should be noted that these processes are executed by software processing.
The piping network leak detection device X2 includes a time series measurement value acquisition unit X21, a time series measurement data extraction unit X22, a piping network model construction unit X23, a time series response calculation unit X24, a leak position/amount determination unit X25, and an output display unit X26. A schematic configuration of the piping network leak detection device X2 will be described below.
The time series measurement value acquisition unit X21 acquires and stores air tank pressure measurement data P0 detected from the pressure sensor X11, air tank exit flow rate measurement data G0 detected from the flow rate sensor X12, and terminal facility entrance pressure measurement data P1 detected from the pressure sensor X13.
The time series measurement data extraction unit X22 extracts measurement data of a certain time duration from the time series measurement value acquired by the time series measurement value acquisition unit X21. The extracted measurement data is a boundary condition of the time series response calculation of the intra-piping network pressure and flow rate in the time series response calculation unit X24. Here, in the present example, repeated calculation is required for the leak position and leak amount determination. Accordingly, the measurement data of a time duration that exhibits a high change is preferentially extracted so that the leak position and the leak amount are detected with high precision and in a short calculation time. Specific examples of the time series measurement data extraction unit according to the present example will be described below with reference to
ΣNi=1|Xi−Xi+1| (1)
In Equation (1), Xi is a measurement value with respect to time ti, Xi+1 is a measurement value with respect to time ti+1, and N is the number of sampling points with respect to an evaluation time duration. In the examples illustrated in
Next, the air tank exit pressure time series measurement data with respect to the extraction time duration of 14:30 to 15:00 is extracted and stored as an air tank exit pressure boundary condition P01. Likewise, the air tank flow rate time series measurement data with respect to 14:30 to 15:00 is extracted and stored as G01. In the present example, the amount of change with respect to each time duration is calculated on the basis of Equation (1) from the time series measurement data and the measurement data of the time duration exhibiting a high change is automatically extracted and stored as the boundary condition, and thus no human work is required.
The piping network model construction unit X23 constructs a network simulation model expressing the joint and a pneumatic device such as the compressor, the terminal facility, and the air tank as nodes and expressing the air piping as a line via the input device X3. The input screen of the piping network leak detection system will be described below with reference to
As illustrated in
On the basis of the piping network model, the time series response calculation unit X24 calculates a time series response of the intra-piping network pressure and flow rate with respect to the air tank exit pressure boundary condition P01 and the terminal facility entrance pressure boundary condition P11 extracted by the time series measurement data extraction unit X22 in view of the friction and heat losses of the pneumatic device and the piping.
The leak position/amount determination unit X25 determines the compressed air leak position/amount on the basis of the time series response of the intra-piping network pressure and flow rate calculated by the time series measurement data extraction unit X22. Specifically, the leak position/amount determination unit X25 solves the problem of minimizing the difference between the air tank exit flow rate time series measurement data G01 and air tank exit flow rate time series calculation data G01 by the intra-piping network time series response calculation by using the leak amount as an unknown parameter. Here, it is assumed that the compressed air leaks at the terminal facility, a valve, the joint for piping connection, and the like and the leak position is limited to the nodes on the piping network model.
The output display unit X26 displays the leak position on the piping network model. Also, a loss cost is calculated from the leak amount at the leak position. It should be noted that the output unit of the output display unit X26 may be provided in the piping network leak detection device with the display unit provided with an output screen separate from the device for display on the output screen.
In the example that is illustrated in
The schematic configuration of the piping network leak detection device X2 has been described above.
The input device X3 is provided with a keyboard, a mouse, and the like and constructs the network simulation model.
A schematic configuration of the piping network leak detection system has been described above.
Next, the flow of calculation processing for the leak position/amount determination according to the present example will be described with reference to
As Step S2 (air tank flow rate calculation step), the air tank exit flow rate time series calculation data G0′ is calculated by the time series response of the intra-piping network pressure and flow rate being calculated by piping network model information, the air tank exit pressure time series measurement data P01, and the terminal facility entrance pressure time series measurement data P11 being used as boundary conditions.
As Step S3 (air tank flow rate calculation data and flow rate measurement data confirmation step), a difference ΔG between the air tank exit flow rate time series measurement data G01 and the air tank exit flow rate time series calculation data G0′ calculated in Step S2 is calculated and it is determined whether or not the difference value falls within a certain threshold value. The processing is terminated when the determination result is Yes. The processing proceeds to Step S4 (node-specific leak amount correction step) when the determination result is No. Here, ΔG is calculated from the following Equation (2).
ΔG=∫|G0′−G01|dt (2)
As Step S4 (node-specific leak amount correction step), the node-specific leak amount predicted in Step S1 is corrected by a known optimization calculation method such that the objective function calculated from Equation (2) is minimized. Then, the processing returns to Step S2.
The flow of the calculation processing for the intra-piping network leak position/amount determination has been described above.
In the present example, X21 (time series measurement value acquisition unit) is capable of performing calculations for leak position/amount determination both at night and on work days without requiring periodic inspections of an entire factory conventionally required for leakage position grasping. Accordingly, leak position/amount determination can be performed without manual work.
In X22 (time series measurement data extraction unit), X24 (time series response calculation unit), and X25 (leak position/amount determination unit), the time series response of the flow rate and pressure within the piping network is calculated on the basis of the measurement data of a time duration exhibiting a high change during operation of the air compressor and the compressed air leak position/amount are determined by the leak amount being corrected such that the time series measurement value and the time series response calculation value coincide with each other. Accordingly, it is possible to obtain a highly accurate leak information-related detection result and prompt measures can be taken against compressed air leakage.
In addition, no leak location candidate designation is necessary in the piping network, a detected leak position is displayed with respect to the piping network model on the output screen in X23 (piping network model construction unit) and X26 (output display unit), and a leak point can be quickly identified. Further, it is possible to output an annual loss result based on the leak amount and confirm an economic effect.
As described above, in the present example, conventionally required periodic inspections are unnecessary and the time series measurement value acquired during compressor operation is used. Accordingly, it is possible to provide a piping network leak detection system along with a leak detection device and a leak detection method used in the high-accuracy leak detection system.
Described below is an example of the piping network leak detection system that is capable of extracting the time series measurement data more than once, performing leak detection, and confirming the history and the result of the detection.
Omitted is a block diagram illustrating the configuration of the piping network leak detection system according to the present example, which is almost identical to
A specific example of the output screen according to the present example is illustrated in
Illustrated in
In the present example, leak position/amount detection is performed more than once with respect to different time durations, and leak rates are calculated with respect to leak positions as a result. Accordingly, high-precision leak position/amount detection can be achieved along with each effect of the first example. In addition, leak points can be sequentially improved in accordance with the leak rates. Further, new measurement data-based periodic and automatic detection is possible for points where leakage may be repeated over time after fixing due to deterioration, looseness, or the like.
Although examples have been described above, the present invention is not limited to the examples described above. The present invention includes various modification examples. For instance, the air compressor in the description of the examples can be replaced with compressors for general gases and liquids. Conceivable as the compressors in that case are a gas-sending air compressor or blower, a liquid-sending pump, and the like. In other words, the air in the examples described above may be replaced with a gas or a liquid. In addition, the air tank in the examples described above may be a gas tank or a liquid tank and the tanks may be collectively referred to as supply tanks.
Number | Date | Country | Kind |
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2016-160680 | Aug 2016 | JP | national |
Filing Document | Filing Date | Country | Kind |
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PCT/JP2017/028605 | 8/7/2017 | WO | 00 |