Flow rate monitoring method, flow rate monitoring device, and flow rate monitoring system

Abstract

To provide a flow rate monitoring method and the like that improves a detection accuracy of changes in a flow rate of powder or a granular material in a pipe.SOLUTION: A flow rate monitoring method includes: acquiring first data, which is data of vibrations occurring in a first period in a pipe through which powder or a granular material flows; dividing the first period of the first data into a plurality of frames, which are a plurality of time intervals; detecting a frequency characteristic of a corresponding portion of the first data corresponding to each of the plurality of frames; detecting a first feature amount of the first data based on a frequency characteristic of the plurality of frames; and monitoring a flow rate of the powder or the granular material by comparing the first feature amount with a first threshold value.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to a method, an apparatus, and a system for monitoring a flow rate of powder or granular material. [Background technology]

[0002] For example, Patent Document 1 discloses a method for detecting blockages in a transport pipe that transports granulated waste plastic. An acoustic sensor is attached to the transport pipe. The impact sound of powder or granular material detected by the acoustic sensor is frequency analyzed, and if the frequency spectrum falls below a specified value, it is determined that a blockage has occurred in the pipe. In the above determination, the sum of the spectrum values ​​of multiple peaks contained in the characteristic frequency band of 3kHz (kilohertz)-6kHz of the impact sound of waste plastic in the pipe is compared with the specified value. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2001-206546 A Summary of the Invention [Problem to be solved by the invention]

[0004] The detection method of Patent Document 1 detects large changes in the flow rate of waste plastics, such as the occurrence of pipe clogging, but may not be able to detect small changes in flow rate. The present disclosure provides a flow rate monitoring method, a flow rate monitoring device, and a flow rate monitoring system that improve the detection accuracy of changes in the flow rate of powder and granular material in a pipe. [Means for solving the problem]

[0005] A flow rate monitoring method according to one embodiment of the present disclosure includes acquiring first data, which is data on vibrations occurring during a first period in a pipe through which powder or granular material flows, dividing the first period of the first data into a plurality of frames which are a plurality of time intervals, detecting frequency characteristics in corresponding portions of the first data corresponding to each of the plurality of frames, detecting a first feature of the first data based on the frequency characteristics in the plurality of frames, and monitoring the flow rate of the powder or granular material by comparing the first feature with a first threshold value. [Brief description of the drawings]

[0006] [Figure 1] FIG. 1 is a diagram showing an example of a configuration of a flow rate monitoring system according to an exemplary embodiment. [Diagram 2] FIG. 2 is a cross-sectional side view showing an example of the configuration of a sensor according to an embodiment. [Diagram 3] FIG. 3 is a flowchart showing an example of the operation of the flow rate monitoring device according to the embodiment in the stand-alone mode. [Figure 4] FIG. 4 is a flowchart showing an example of the operation of the flow rate monitoring device according to the embodiment in the stand-alone mode. [Diagram 5] FIG. 5 is a diagram showing an example in which N frames F are set for a detection signal in a processing target period. [Figure 6] FIG. 6 is a diagram showing an example of a frequency analysis processing result of one frame. [Figure 7] FIG. 7 is an image diagram of a method for calculating the amount of variation in the power spectrum between two frames. [Figure 8] FIG. 8 is a flowchart showing an example of the operation of the flow rate monitoring device according to the embodiment in the mixed mode. [Figure 9] FIG. 9 is a flowchart showing an example of the operation of the flow rate monitoring device according to the embodiment in the mixed mode. [Figure 10] FIG. 10 is a diagram showing an example of a frequency analysis processing result of one frame in the mixed mode. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0007] In the following, exemplary embodiments of the present disclosure will be described with reference to the drawings. The embodiments described below are all comprehensive or specific examples. Among the components in the following embodiments, components that are not described in an independent claim showing a top concept will be described as optional components. Each figure in the attached drawings is a schematic diagram and is not necessarily illustrated precisely. In each figure, substantially the same components are given the same reference numerals, and duplicated descriptions may be omitted or simplified. In this specification and claims, "apparatus" may mean not only one apparatus but also a system including multiple apparatuses. "Apparatus" may also include "facility".

[0008] The configuration of a flow rate monitoring system 100 according to an exemplary embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram showing an example of the configuration of the flow rate monitoring system 100 according to an exemplary embodiment. The flow rate monitoring system 100 monitors changes in the flow rate of powder or granular material flowing through a pipe. Although not limited thereto, in this embodiment, the flow rate monitoring system 100 monitors the flow rate of powder or granular material flowing through a pipe 20 included in a plant 1.

[0009] A powder or granular material is an aggregate of solid particles, and although it is solid, it has the property of a fluid that it flows in response to an external force. In this specification and claims, "powder or granular material" includes "powder", "granules", and "mixture of powder and granules". A powder may be an aggregate of particles having a particle diameter of less than 1 mm. A powder may include any of powder, fine powder, and ultrafine powder, which are classified as powder, fine powder, and ultrafine powder. For example, a powder classified as above may be an aggregate of particles having a particle diameter of 3 μm (micrometer) or more and less than 1 mm (millimeter), a fine powder may be an aggregate of particles having a particle diameter of 0.01 μm or more and 10 μm or less, and an ultrafine powder may be an aggregate of particles having a particle diameter of 0.0001 μm or more and 0.3 μm or less. A granular material may be an aggregate of particles having a particle diameter of 1 mm or more. A granular material may include particles having a particle diameter of several mm or more, or particles having a particle diameter of several tens of mm or more.

[0010] The flow rate monitoring system 100 includes, as components, a sensor 110, a flow rate monitoring device 120, an input device 130, and an output device 140. The flow rate monitoring system 100 does not need to include all of the components described above. The flow rate monitoring system 100 may include, as a component, a plant 1. The plant 1 is a target to be monitored by the flow rate monitoring system 100.

[0011] The plant 1 may be any plant that includes piping through which powder or granular material flows. Examples of the plant 1 may include industrial plants, chemical plants, and environmental plants. Examples of industrial plants may include food factories, pharmaceutical factories, steel plants, cement factories, power plants, etc. Examples of chemical plants may include chemical plants, petrochemical plants, oil refineries, gas refineries, etc. Examples of environmental plants may include waste treatment plants, sewage treatment plants, etc.

[0012] The present embodiment will be described by taking the plant 1 as a waste treatment plant as an example. The plant 1 includes an incinerator 11, a boiler 12, a dust collector 13, a nitrogen oxide removal device 14, a chimney 15, a power generation device 16, and a chemical tank 17. The boiler 12 is connected to the incinerator 11, and is, for example, integrated with the incinerator 11. The dust collector 13 is connected to the boiler 12 via a pipe 20a, which is a part of the pipe 20. The dust collector 13 is connected to the nitrogen oxide removal device 14 via a pipe 20b, which is a part of the pipe 20. The nitrogen oxide removal device 14 is connected to the chimney 15 via a pipe 20c, which is a part of the pipe 20. The power generation device 16 is connected to the boiler 12 via a pipe 20d, which is a part of the pipe 20. The chemical tank 17 is connected to the pipe 20a via a pipe 20e, which is a part of the pipe 20.

[0013] The plant 1 may not include one or more of the above components, and may further include, in addition to the above components, an exhaust gas scrubbing device that removes acid gases and heavy metals, etc. from the exhaust gas, a storage tank that stores fuel or waste, and a transfer device such as a crane that transfers the fuel or waste in the storage tank to the incinerator 11.

[0014] The incinerator 11 receives and burns fuel or waste, including biomass. Exhaust gas, which is a combustion gas generated in the incinerator 11, is sent to the boiler 12. In the boiler 12, water flowing in the boiler 12 is evaporated by the heat of the exhaust gas. The steam is sent to the power generation device 16, which rotates the turbine 16a in the power generation device 16. This causes the power generation device 16 to generate electricity. The exhaust gas from the boiler 12 is sent to the dust collector 13. The dust collector 13 removes soot and dust contained in the exhaust gas from the exhaust gas. A filter-type dust collector may be used as the dust collector 13. The exhaust gas after dust collection is sent to the nitrogen oxide removal device 14, which removes nitrogen oxides (NOx) from the exhaust gas by adding ammonia gas or ammonia water to the exhaust gas. The exhaust gas after the treatment in the nitrogen oxide removal device 14 is sent to the chimney 15, and is discharged from the chimney 15 into the atmosphere.

[0015] The chemical tank 17 includes a slaked lime storage tank 17a, an activated carbon storage tank 17b, and supply devices 17c and 17d. The slaked lime storage tank 17a stores slaked lime powder. The activated carbon storage tank 17b stores activated carbon powder. The first supply device 17c supplies the slaked lime powder from the slaked lime storage tank 17a to the pipe 20e. The slaked lime powder is supplied into the pipe 20a through the pipe 20e by the action of the first supply device 17c. The second supply device 17d supplies the activated carbon powder from the activated carbon storage tank 17b to the pipe 20e. The activated carbon powder is supplied into the pipe 20a through the pipe 20e by the action of the second supply device 17d. The chemical tank 17 may include only one of the slaked lime storage tank 17a and the activated carbon storage tank 17b, or may include both.

[0016] The structure of the supply devices 17c and 17d is not particularly limited as long as it is a structure that can supply powder or granular material into the pipe 20a through the pipe 20e. For example, the supply devices 17c and 17d may include a structure for injecting a gas such as air, such as a blower or an ejector, and may have a function of injecting powder or granular material together with the gas. The supply devices 17c and 17d may include a pressure-feeding structure such as a pump or a piston, and may have a function of pressure-feeding the powder or granular material.

[0017] Slaked lime (Ca(OH)2) reacts with hydrogen chloride (HCl) contained in the exhaust gas to produce calcium chloride (CaCl2) and water. Slaked lime (Ca(OH)2) also reduces the amount of sulfur oxides (SO x ) to produce calcium sulfite (CaSO3) and water. The hydrogen chloride and sulfur oxides are removed from the exhaust gas as calcium chloride and calcium sulfite, respectively, and the calcium chloride and calcium sulfite are collected by the dust collector 13 as soot and dust.

[0018] The activated carbon removes dioxins from the exhaust gas by adsorbing the dioxins contained in the exhaust gas. The activated carbon after adsorption is collected as soot and dust by the dust collector 13.

[0019] The sensor 110 is attached to the pipe 20e. The sensor 110 is connected to the flow rate monitoring device 120 via wired communication, wireless communication, or a combination of wireless communication and wired communication. Any wired communication and wireless communication may be used. The sensor 110 detects waves occurring in the pipe 20e and its surroundings. Examples of waves may include vibrations and sounds. Although not limited thereto, in this embodiment, the sensor 110 detects vibrations occurring in the pipe 20e. Examples of vibrations detected by the sensor 110 may include vibrations occurring in the pipe 20e due to powder and granular material flowing through the pipe 20e, vibrations due to sounds occurring in the pipe 20e due to powder and granular material, vibrations occurring in the pipe 20e due to disturbances acting on the pipe 20e, vibrations due to sounds outside the pipe 20e, and the like. The vibrations may include sounds. In this embodiment, the sensor 110 is a vibration sensor, but may also be a sensor such as a microphone that detects sounds occurring in the pipe 20e and its surroundings.

[0020] Fig. 2 is a cross-sectional side view showing an example of the configuration of sensor 110 according to the embodiment. As shown in Fig. 2, sensor 110 has a structure for detecting vibrations in one axis direction D1 and D2 intersecting with outer wall surface 20ea, which is the outer surface of wall 20eb of pipe 20e. Sensor 110 may have a structure for detecting vibrations in two intersecting axial directions, or may have a structure for detecting vibrations in three intersecting axial directions. In this embodiment, by using sensor 110 that detects vibrations in one axial direction, the amount of processing of the detection result of sensor 110 can be reduced.

[0021] The sensor 110 includes a support 111, a vibrator 112, a guide 113, a biasing member 114, a detection coil 115, and a detection circuit 116. The support 111 supports other components of the sensor 110 and is attached to the pipe 20e. The guide 113 has a cylindrical shape and is supported by the support 111. The vibrator 112 has a cylindrical shape and is disposed inside the cylinder of the guide 113. The vibrator 112 is supported by the guide 113 so as to be slidable in a direction D1 approaching an outer wall surface 20ea of ​​the pipe 20e and a direction D2 away from the outer wall surface 20ea. Although not limited thereto, in this embodiment, the directions D1 and D2 are perpendicular to the outer wall surface 20ea. The material forming the vibrator 112 is a magnetic material.

[0022] The biasing member 114 biases the vibrator 112 in the direction D1. The biasing member 114 biases the vibrator 112 by elastic force. For example, the biasing member 114 may include a spring or bellows structure. While being elastically biased in the direction D1 by the biasing member 114, the vibrator 112 brings the tip of the vibrator 112 into contact with the outer wall surface 20ea.

[0023] The detection coil 115 is disposed so as to surround the cylindrical outer peripheral surface of the vibrator 112. The detection coil 115 is connected to the detection circuit 116. When the vibrator 112 slides in the directions D1 and D2, the detection coil 115 generates an induced electromotive force, and the detection circuit 116 detects the induced electromotive force. The detection circuit 116 detects the position, i.e., the phase, of the vibrator 112 relative to the detection coil 115 based on the induced electromotive force. The detection circuit 116 outputs a signal indicating the detection result to the flow monitoring device 120. For example, the detection circuit 116 may detect the phase of the vibrator 112 at every predetermined sampling period, and output a detection signal indicating the phase at every predetermined sampling period as a signal strength to the flow monitoring device 120. The sensor 110 as described above has a structure of a pickup sensor, which is one of acceleration sensors.

[0024] When the powder flowing through the pipe 20e vibrates the pipe 20e, the vibrator 112 vibrates so as to move back and forth in directions D1 and D2. The changing phase of the vibrator 112 is detected by the detection circuit 116. The detection circuit 116 outputs a detection signal indicating the phase and detection timing to the flow rate monitoring device 120. Such a detection signal can represent the vibration of the vibrator 112, that is, the vibration generated in the pipe 20e.

[0025] In this embodiment, in order to suppress the propagation of vibration through the wall 20eb of the pipe 20e, a flexible member is used for the wall 20eb. This suppresses the vibration generated at a position away from the point where the vibrator 112 contacts the outer wall surface 20ea from propagating through the wall 20eb and vibrating the vibrator 112. The vibration of the vibrator 112 can indicate the flow state of the powder and granular material in the pipe 20e with higher accuracy. A resin pipe is used as such a pipe 20e. Furthermore, in order to suppress the attenuation of vibration at the wall 20eb, a hard resin pipe 20e is used. A non-flexible metal pipe or a soft resin pipe may be used as the pipe 20e.

[0026] Returning to FIG. 1, the input device 130 may be located anywhere. The input device 130 is connected to the flow monitoring device 120 via wired communication, wireless communication, or a combination of wireless communication and wired communication. Any wired communication and wireless communication may be used. The input device 130 can transmit and receive commands, information, data, etc. to the flow monitoring device 120. For example, the input device 130 accepts an input by a user and transmits commands, information, data, etc. corresponding to the input content to the flow monitoring device 120. The input device 130 may include one or more of a button, a lever, a dial, a joystick, a mouse, a key, a touch panel, a microphone, and a motion capture device as a device to which an input is given through a user's operation. The input device 130 may be a terminal device. Examples of the terminal device may be smart devices such as smartphones and tablets, personal information terminals, other terminal devices, devices using these, and improved devices of these.

[0027] The output device 140 may be located anywhere. The output device 140 is connected to the flow monitoring device 120 via wired communication, wireless communication, or a combination of wireless communication and wired communication. Any wired communication and wireless communication may be used. The output device 140 may transmit and receive commands, information, data, etc. to the flow monitoring device 120. For example, the output device 140 may output information, data, etc. received from the flow monitoring device 120 visually, audibly, or both. The output device 140 may include one or more of a display, a projector, a light-emitting lamp, an indicator, a speaker, etc. The output device 140 may output an image via one or more of a display and a projector, and output sound via a speaker. Examples of a display may include a liquid crystal display, an organic EL (Electro Luminescence), and an inorganic EL.

[0028] The flow rate monitoring device 120 receives a signal or data indicating the detection result of the sensor 110 from the sensor 110, and uses the result of processing the signal or data to determine the state of the powder or granular material flow rate that may be indicated by the detection result. The flow rate monitoring device 120 may output information and data including the determination result to one or more of the output device 140 and an external device. The external device may be a device external to the flow rate monitoring system 100.

[0029] In this embodiment, examples of the flow monitoring device 120 may include electronic circuit boards, electronic control units, microcomputers, personal computers, workstations, smart devices such as smartphones and tablets, and other electronic devices.

[0030] The flow rate monitoring device 120 may include a circuit or a processing circuit. The circuit may include a processing circuit. The processing circuit or circuit includes a processor P and a memory device M, etc. In this embodiment, the flow rate monitoring device 120 includes a processing circuit, and includes a processor P and a memory device M. The processing circuit or circuit transmits and receives commands, information, data, etc. to and from other devices. The processing circuit or circuit inputs signals from various devices and outputs control signals to controlled objects.

[0031] The memory device M may include a memory, a storage, or both a memory and a storage. Examples of the memory may include a volatile semiconductor memory such as a random access memory (RAM) and a non-volatile semiconductor memory such as a read-only memory (ROM). Examples of the storage may include a semiconductor memory such as a flash memory, a hard disk, and a solid state drive (SSD). For example, the memory device M stores a processing circuit or a program executed by the circuit, various data, and the like.

[0032] At least some of the functions of the flow monitoring device 120 may be realized by cooperation between the processor P and the storage device M. The processor P and memories including RAM and ROM may function as components of a computer system. For example, the computer system may realize the above functions by the processor P using the RAM as a work area to execute a program recorded in the ROM.

[0033] Some or all of the functions of the flow monitoring device 120 may be realized by a computer system, by a dedicated hardware circuit such as an electronic circuit or an integrated circuit, or by a combination of a computer system and a hardware circuit. The flow monitoring device 120 may execute processing by centralized control using a single processing circuit or circuits, or may execute processing by distributed control using the cooperation of multiple processing circuits or circuits.

[0034] For example, the processor P may include, but is not limited to, one or more of a CPU (Central Processing Unit), an MPU (Micro Processing Unit), a GPU (Graphics Processing Unit), a microprocessor, a processor core, a multiprocessor, an ASIC (Application-Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), and a reconfigurable processor. The processor P may realize processing by a logic circuit or a dedicated circuit, which is a hardware circuit formed in an integrated circuit such as an IC (Integrated Circuit) chip and an LSI (Large Scale Integration). The multiple functions of the flow monitoring device 120 may be realized by an integrated circuit individually integrated into one chip. The multiple functions of the flow monitoring device 120 may be realized by an integrated circuit integrated into one chip so as to include some or all of the functions.

[0035] The flow rate monitoring device 120 can operate in a single mode and a mixed mode. The flow rate monitoring device 120 operates in the single mode or the mixed mode according to a command received from the input device 130. The single mode is a mode in which powdered material of slaked lime or activated carbon is supplied to the pipe 20e from one of the slaked lime storage tank 17a and the activated carbon storage tank 17b. In the single mode, the flow rate monitoring device 120 monitors the flow rate of one type of powdered material flowing through the pipe 20e. The mixed mode is a mode in which powdered material of slaked lime and activated carbon is supplied to the pipe 20e from both the slaked lime storage tank 17a and the activated carbon storage tank 17b. In the mixed mode, the flow rate monitoring device 120 monitors the flow rates of two types of powdered material flowing through the pipe 20e. The flow rate monitoring device 120 outputs the monitoring result to the output device 140 and causes the output device 140 to present the monitoring result to a user.

[0036] The flow rate monitoring device 120 receives information on threshold values ​​used in processing via an input to the input device 130 or from an external device connected to the flow rate monitoring device 120, and stores the information in the memory device M. The threshold values ​​can be set according to one or more of the type, particle size, particle size distribution, flow rate, etc. of the powder or granular material flowing through the pipe 20e.

[0037] The operation of the flow rate monitoring device 120 in the stand-alone mode will be described with reference to Fig. 3 and Fig. 4. Fig. 3 and Fig. 4 are flowcharts showing an example of the operation of the flow rate monitoring device 120 in the stand-alone mode according to the embodiment. In the following, the flow rate monitoring device 120 will be described as monitoring a state in which slaked lime powder is supplied from the slaked lime storage tank 17a to the pipe 20e at a supply amount within a predetermined range. The supply amount of powder is the supply amount per unit time, and corresponds to the flow rate of powder in the pipe 20e.

[0038] In step S101, the flow rate monitoring device 120 continuously receives a detection signal from the sensor 110. The detection signal indicates the phase of the oscillator 112 for each predetermined sampling period as a signal intensity. The phase of the oscillator 112 corresponds to the amplitude of vibration of the oscillator 112. The flow rate monitoring device 120 stores information on the detection signal, including the phase of the oscillator 112 and the detection time or detection order of the detection signal in association with each other, in the memory device M.

[0039] Next, in step S102, the flow monitoring device 120 determines whether it is time to process the detection signal. If it is time to process the detection signal (Yes in step S102), the flow monitoring device 120 proceeds to step S103. If it is not time to process the detection signal (No in step S102), the flow monitoring device 120 returns to step S101.

[0040] The processing timing may be any timing. For example, the processing timing may be a timing according to a command input to the input device 130. The processing timing may be a preset timing. For example, the processing timing may be a timing for each predetermined period. Although not limited thereto, in the present embodiment, the processing timing is a timing for each predetermined period, and the predetermined period is one second.

[0041] Next, in step S103, the flow rate monitoring device 120 reads and acquires information on the detection signal included in a processing period Tc (Tc=Ta-Tb) between a timing Tb that is a predetermined time before the processing timing Ta and the processing timing Ta from the storage device M. The processing period Tc is a period including N frames F arranged along a time axis. The frames F are frames that divide a preset time period. Although not limited to this, in this embodiment, the processing period Tc is 1 second, and the time period of the frames F is 100 ms (milliseconds). The processing period Tc may be a period including N frames F arranged such that adjacent frames F partially overlap each other along the time axis by an overlap period Td. Although not limited to this, in this embodiment, the overlap period Td is a period that is 10% of the time period of the frames F, for example, a period of 10 ms.

[0042] Next, in step S104, the flow monitoring device 120 sequentially sets N frames F for the processing period Tc. The N frames F are set so that adjacent frames F partially overlap each other by an overlap period Td. For example, the N frames F may be set in order going back from the processing timing Ta. In this embodiment, N=11, and eleven 100 ms frames F are set. For example, FIG. 5 shows an example of setting N frames F for the detection signal for the processing period Tc. The horizontal axis indicates the elapsed time T, and the vertical axis indicates the phase of the transducer 112, which is the intensity P of the detection signal.

[0043] Next, in step S105, the flow monitoring device 120 performs processing using a window function on the information of the detection signal contained in each of the N frames F. The processing using the window function is processing that makes the waveforms of the detection signals of adjacent frames F have continuity at the start and end points of both ends of the frame F. This improves the accuracy of the analysis results by the frequency analysis performed later. Although not limited to this, in this embodiment, a Hanning window that sets the amplitude of the detection signal at the start and end points of the frame F to zero is used as the window function. A Hamming window that does not set the amplitude of the detection signal at the start and end points of the frame F to zero may also be used as the window function.

[0044] The information of each detection signal after the window function processing includes the signal strength at the detection timing of the detection signal. The signal strength corresponds to the phase of the transducer 112. The flow monitoring device 120 may convert the phase to another parameter before the window function processing. For example, the flow monitoring device 120 may convert the phase of the transducer 112 to the amplitude of the transducer 112.

[0045] Next, in step S106, the flow monitoring device 120 performs frequency analysis processing on the information of the detection signals after the window function processing included in each of the N frames F. The frequency analysis processing of the frame F can show the distribution of frequency components for all the detection signals included in the frame F. Although not limited thereto, in this embodiment, a spectrum analysis based on Fourier transform is used as the frequency analysis method. Examples of the Fourier transform may include the discrete Fourier transform (DFT) and the fast Fourier transform (FFT). In this embodiment, the flow monitoring device 120 uses the fast Fourier transform, which is an algorithm for quickly calculating the discrete Fourier transform on a computer.

[0046] In the frequency analysis process, a frequency band including the entire detection signal is divided into M samples at a constant sampling frequency fs. In each frame F after the frequency analysis process, the amount of signal included in each frequency band for each sampling frequency fs is included as power. For example, FIG. 6 is a diagram showing an example of the frequency analysis process result of one frame F. The horizontal axis indicates frequency F, and the vertical axis indicates power P. FIG. 6 shows the power spectrum of frame F.

[0047] Next, in step S107, the flow rate monitoring device 120 calculates the amount of variation in the power spectrum between adjacent frames F. The flow rate monitoring device 120 calculates the amount of variation in the power spectrum for all combinations of two adjacent frames F.

[0048] The flow rate monitoring device 120 calculates the power difference in the same frequency bin between two adjacent frames F. The flow rate monitoring device 120 calculates the power difference for all frequency bins and calculates the sum of the differences for all frequency bins as the amount of fluctuation in the power spectrum. The frequency bins correspond to the frequency bands for each sampling frequency fs. The total number of frequency bins is the same as the number of samples M.

[0049] For example, the flow rate monitoring device 120 calculates the flow rate of the h-th frame F by using the relational expression shown in the following Equation 1. h and the (h-1)th frame F h-1 The amount of fluctuation in the power spectrum Flux(h) between the hth frame F h is the h-th frame in the processing period Tc from the start point to the end point. h [k] is the hth frame F h is the power in the kth frequency bin in , where the kth frequency bin is the kth frequency bin in order starting from frequency zero. M is the total number of frequency bins.

[0050]

number

[0051] FIG. 7 is an image diagram of a method for calculating the amount of variation in the power spectrum between two frames, as shown in the relational expression of Expression 1. As shown in FIG. 7, the total sum of the power differences between adjacent frames F is calculated for all frequency bands included in frame F as the amount of variation in the power spectrum. In Expression 1, (P h [k]-P h-1 [k]) is calculated, but is not limited to this. For example, (P h [k]-P h-1 The sum of the absolute values ​​of (P h [k]-P h-1 For h=1, (P h [k]-P h-1 Alternatively, P0[k] may not be calculated or may be set to zero. Alternatively, the power spectrum of the 11th frame F in the processing period Tcp1 that is processed immediately before the processing period Tc may be used as the subject of P0[k].

[0052] Next, in step S108, the flow monitoring device 120 calculates a feature of the power spectrum fluctuation. The flow monitoring device 120 calculates statistics for the power spectrum fluctuation of all combinations of two adjacent frames F. Examples of the statistics may include the average value of the power spectrum fluctuation, the standard deviation of the power spectrum fluctuation, the median value of the power spectrum fluctuation, the mode of the power spectrum fluctuation, and a variation width that is the difference between the maximum and minimum values ​​of the power spectrum fluctuation. Although not limited thereto, in this embodiment, the statistics is the average value of the power spectrum fluctuation. Examples of the average value may include the arithmetic mean value, the power mean value, the geometric mean value, the harmonic mean value, and the weighted mean value. In this embodiment, the arithmetic mean value is used as the average value. The flow monitoring device 120 determines the calculated statistics as the feature value of the processing period Tc.

[0053] Next, in step S109, the flow monitoring device 120 compares the feature amount of the processing period Tc with a first threshold. If the feature amount is greater than the first threshold amount (Yes in step S109), the flow monitoring device 120 proceeds to step S110. If the feature amount is equal to or less than the first threshold amount (No in step S109), the flow monitoring device 120 proceeds to step S112.

[0054] In step S110, the flow monitoring device 120 reads out from the memory device M the feature amounts determined for the past processing periods Tcp that were processed before the processing period Tc. The flow monitoring device 120 reads out the feature amounts of Pa processing periods Tcp. Pa is 1 or more, and in this embodiment, Pa is 4. Therefore, the feature amounts of four processing periods Tcp1, Tcp2, Tcp3, and Tcp4 are read out. The processing periods Tcp4, Tcp3, Tcp2, Tcp1, and Tc have been processed in this order.

[0055] Next, in step S111, the flow monitoring device 120 calculates the average value of the feature quantities for the current and past processing periods Tcp4, Tcp3, Tcp2, Tcp1, and Tc, and determines the average value as the feature quantity for the processing period Tc. In this embodiment, an arithmetic mean value is used as the average value. This reduces periodic peaks in the feature quantities. The periodic peaks may be caused by disturbances other than vibrations generated by the flowing powder or granular material. For example, vibrations caused by external sound may also be a cause of the periodic peaks.

[0056] In step S112, the flow monitoring device 120 reads out the feature amounts determined for past processing periods Tcp from the memory device M. The flow monitoring device 120 reads out feature amounts of Pb processing periods Tcp. Pb is greater than Pa. Although not limited thereto, in this embodiment, Pb is at least twice as large as Pa, and is 14. The flow monitoring device 120 reads out feature amounts of processing periods Tcp1 to Tcp14. Processing periods Tcp14 to Tcp1 and Tc have been processed in this order.

[0057] Next, in step S113, the flow monitoring device 120 calculates one or more moving average values ​​MA of order A for the feature quantities of the current and past processing periods Tcp14 to Tcp1 and Tc. Although not limited thereto, in this embodiment, the order A is 5. The flow monitoring device 120 calculates ten moving average values ​​MA1 to MA10 in order from the processing period Tc to Tcp14. The moving average value MA1 is the average value of the feature quantities of the processing periods Tc and Tcp1 to Tcp4, and the moving average value MA10 is the average value of the feature quantities of the processing periods Tcp10 to Tcp14. In this embodiment, an arithmetic mean value is used as the average value.

[0058] Next, in step S114, the flow monitoring device 120 compares the moving average value MA with the second threshold value. Specifically, the flow monitoring device 120 determines whether all of the moving average values ​​MA of a predetermined number Lc calculated sequentially from the processing target period Tc to Tcp14 are greater than the second threshold value. One of the moving average values ​​MA of the predetermined number Lc includes the feature amount of the processing target period Tc. In this embodiment, Lc is 10. If all of the moving average values ​​MA1 to MA10 are greater than the second threshold value (Yes in step S114), the flow monitoring device 120 proceeds to step S115. In this case, the moving average value over the past 10 seconds from the processing timing Ta is greater than the second threshold value. If any of the moving average values ​​MA1 to MA10 is equal to or less than the second threshold value (No in step S114), the flow monitoring device 120 proceeds to step S116.

[0059] In step S115, the flow rate monitoring device 120 determines that the supply amount of the powder or granular material is within a predetermined range, that is, the supply amount of the powder or granular material is normal. The flow rate monitoring device 120 returns to step S101, and repeats the processes of steps S101 to S114 at each processing timing.

[0060] In step S116, the flow rate monitor 120 determines that the supply rate of the powder or granular material is not within a predetermined range, that is, the supply rate of the powder or granular material is not normal.

[0061] Next, in step S117, the flow rate monitoring device 120 causes the output device 140 to output an alarm indicating that the supply rate of the powder or granular material is not normal.

[0062] Through steps S101 to S117 as described above, the flow rate monitoring device 120 performs a process of determining whether or not the supply amount of powder or granular material is normal at a processing timing, for example, at the timing of each processing period Tc. The flow rate monitoring device 120 uses the frequency characteristics of the detection signal in all frequency bands for the above determination. This improves the detection accuracy of fluctuations in the supply amount of powder or granular material. Furthermore, the flow rate monitoring device 120 uses a feature amount of the fluctuation amount of the frequency characteristics in the processing period Tc for the above determination. This improves the detection accuracy of whether or not the supply amount of powder or granular material is normal. Furthermore, the flow rate monitoring device 120 uses a moving average of the feature amount for the above determination. This smooths out fluctuations in the feature amount due to disturbances, and improves the detection accuracy of whether or not the supply amount of powder or granular material is normal.

[0063] The first threshold value and the second threshold value are preset and stored in the storage device M according to one or more of the type, particle size, particle size distribution, and supply flow rate of the powder or granular material. For example, the first threshold value and the second threshold value may be set using data of the detection signal of the sensor 110 during a test run of the plant 1, may be set using accumulated data of the detection signal of the sensor 110 during operation of the plant 1, or may be set using both of these data. During the test run, the environment of the plant 1 can be changed to various environments, which allows various first and second threshold values ​​to be set.

[0064] The operation of the flow rate monitoring device 120 in the mixed mode will be described with reference to Fig. 8 and Fig. 9. Fig. 8 and Fig. 9 are flowcharts showing an example of the operation of the flow rate monitoring device 120 in the mixed mode according to the embodiment. In the following, the flow rate monitoring device 120 will be described as monitoring a state in which the slaked lime powder is supplied from the slaked lime storage tank 17a to the pipe 20e at a first supply amount within a predetermined range, and the activated carbon powder is supplied from the activated carbon storage tank 17b to the pipe 20e at a second supply amount within a predetermined range.

[0065] Steps S201 to S206 are the same as steps S101 to S106 in the stand-alone mode, respectively.

[0066] In step S207, the flow rate monitoring device 120 detects two peaks in the power spectrum of each of the N frames F. The slaked lime powder and the activated carbon powder have different characteristics in terms of one or more of particle shape, particle size, particle size distribution, supply amount, density, and flow characteristics. Therefore, the slaked lime powder and the activated carbon powder have different frequency characteristics, and therefore, in the power spectrum, two peaks are formed, for example, as shown in FIG. 10. FIG. 10 is a diagram showing an example of the frequency analysis processing result of one frame in the mixed mode. As shown in FIG. 10, the mixture of the slaked lime powder and the activated carbon powder forms peaks P1 and P2 in two frequency bands.

[0067] The characteristics of the peak portion formed by the power spectrum of the slaked lime powder and the characteristics of the peak portion formed by the power spectrum of the activated carbon powder are preset and stored in the memory device M. The characteristics of the peak portion may include the frequency band of the peak portion, the power of the peak portion, etc. The characteristics of the peak portion may be set according to the type, particle size, particle size distribution, and supply flow rate of the powder or granular material. For example, the characteristics of the peak portion may be set using the detection data of the sensor 110 during a test run of the plant 1, or may be set using accumulated data of the detection data of the sensor 110 during the operation of the plant 1, or may be set using both of these data. The flow rate monitoring device 120 detects the two peak portions using the characteristics of the peak portions stored in the memory device M.

[0068] Next, in step S208, the flow rate monitoring device 120 divides the power spectrum of each frame F into two based on the two peak parts. This forms a first power spectrum related to the slaked lime powder and a second power spectrum related to the activated carbon powder. The first power spectrum includes a peak part corresponding to one of the two peak parts, and the second power spectrum includes a peak part corresponding to the other of the two peak parts. Examples of methods for dividing the power spectrum may include Independent Component Analysis (ICA) and Nonnegative Matrix Factorization (NMF). Both Independent Component Analysis and Nonnegative Matrix Factorization are methods for separating data related to sound corresponding to a sound source.

[0069] In steps S209 to S215 following step S208, the flow monitoring device 120 performs the same process as steps S107 to S113 on the first power spectra of the N frames F, and performs the same process as steps S107 to S113 on the second power spectra of the N frames F. In step S211, a first threshold value set for slaked lime and a first threshold value set for activated carbon are used.

[0070] In step S216, the flow rate monitoring device 120 compares the moving average value of the predetermined number Lc related to slaked lime with the second threshold value of slaked lime, and compares the moving average value of the predetermined number Lc related to activated carbon with the second threshold value of activated carbon. If all of the moving average values ​​of the predetermined number Lc related to slaked lime are greater than the second threshold value set for slaked lime and all of the moving average values ​​of the predetermined number Lc related to activated carbon are greater than the second threshold value set for activated carbon (Yes in step S216), the flow rate monitoring device 120 proceeds to step S217. Otherwise (No in step S216), the flow rate monitoring device 120 proceeds to step S218.

[0071] In step S217, the flow rate monitoring device 120 determines that the supply rates of both the slaked lime powder and the activated carbon powder are normal. The flow rate monitoring device 120 returns to step S201, and repeats the processes from step S201 to S216 at each processing timing.

[0072] In step S218, the flow rate monitoring device 120 determines that the supply rate of at least one of the slaked lime powder and the activated carbon powder is abnormal. Furthermore, for example, the flow rate monitoring device 120 may determine that the supply rate of slaked lime is abnormal when any of the moving average values ​​of the predetermined number Lc related to slaked lime is equal to or less than the second threshold value of slaked lime. The flow rate monitoring device 120 may determine that the supply rate of activated carbon is abnormal when any of the moving average values ​​of the predetermined number Lc related to activated carbon is equal to or less than the second threshold value of activated carbon.

[0073] Next, in step S219, the flow monitoring device 120 causes the output device 140 to output an alarm indicating the result of the determination.

[0074] Through steps S201 to S219 as described above, the flow rate monitoring device 120 determines whether the supply amount of slaked lime powder and the supply amount of activated carbon powder are normal or not for each processing timing. In the above determination, the flow rate monitoring device 120 determines and uses the frequency characteristics of the slaked lime powder and the frequency characteristics of the activated carbon powder separately. This improves the detection accuracy of the supply amount of each of the slaked lime powder and the activated carbon powder.

[0075] [Other embodiments] Although exemplary embodiments of the present disclosure have been described above, the present disclosure is not limited to the above-described embodiments. In other words, various modifications and improvements are possible within the scope of the present disclosure. For example, the scope of the present disclosure also includes embodiments in which various modifications have been made and embodiments constructed by combining components in different embodiments.

[0076] For example, in the embodiment, the flow rate monitoring device 120 monitors the flow rate of one powder or granular material in the single mode and monitors the flow rates of two powder or granular materials in the mixed mode, but is not limited to this. For example, the flow rate monitoring device 120 may monitor the flow rates of three or more powder or granular materials in the mixed mode. In this case, the flow rate monitoring device 120 may detect three or more peak portions in the power spectrum of each of the N frames F, and divide the power spectrum of each frame F into three or more based on the detected peak portions. Furthermore, the flow rate monitoring device 120 may perform the same process as in the mixed mode of the two powder or granular materials for each divided power spectrum.

[0077] Examples of each aspect of the technology of the present disclosure are given as follows: A flow rate monitoring method according to a first aspect of the present disclosure includes acquiring first data, which is data of vibrations occurring during a first period in a pipe through which powder or granular material flows, dividing the first period of the first data into a plurality of frames which are a plurality of time intervals, detecting frequency characteristics in corresponding portions of the first data corresponding to each of the plurality of frames, detecting a first feature amount of the first data based on the frequency characteristics in the plurality of frames, and monitoring the flow rate of the powder or granular material by comparing the first feature amount with a first threshold value.

[0078] According to the above aspect, a first feature of the first data is detected using frequency characteristics in a plurality of frames forming a first period. The first feature can indicate a feature over the entire first period as a feature related to frequency characteristics. In other words, the first feature is a feature in which frequency characteristics over the entire first period are taken into consideration. The flow rate of the powder or granular material is monitored using a comparison result between such a first feature and a first threshold, thereby improving monitoring accuracy.

[0079] In the above first aspect, a flow rate monitoring method according to a second aspect of the present disclosure may include detecting frequency components of the corresponding parts as the frequency characteristics by performing frequency analysis on the corresponding parts, detecting an amount of fluctuation in the frequency components between adjacent frames, and detecting the first feature based on the amount of fluctuation in the frequency components between adjacent frames.

[0080] According to the above aspect, the first feature is detected using the amount of variation in frequency components between adjacent frames. The first feature can indicate the variation in frequency characteristics over the entire first period. By using the result of comparing the first feature with the first threshold, the accuracy of monitoring the flow rate of the powder or granular material is improved.

[0081] In the above second aspect, in a flow rate monitoring method according to a third aspect of the present disclosure, the detection of the fluctuation amount of the frequency component may involve detecting a difference in frequency components of the same frequency band between adjacent frames for all of a plurality of frequency bands corresponding to each of the frequency components, and detecting the sum of the differences in the plurality of frequency bands as the fluctuation amount of the frequency component.

[0082] According to the above aspect, the variation of the frequency components between adjacent frames includes the variation between frames for all of the multiple frequency bands corresponding to the frequency components. The variation of the frequency components between adjacent frames indicates the variation across the multiple frequency bands. The first feature based on such variation can indicate the frequency components across the multiple frequency bands.

[0083] In any of the first to third aspects above, a flow rate monitoring method according to a fourth aspect of the present disclosure may include acquiring a second feature value previously detected for second data, the second data being vibration data generated in the piping in a second time period prior to the first time period, and monitoring the flow rate of the powder or granular material by comparing an average value of the first feature value and the second feature value with the first threshold value.

[0084] According to the above aspect, the flow rate of the powder or granular material is monitored by using an average value of the first characteristic amount and the second characteristic amount detected in the past. This smoothes the first characteristic amount. Even if the first characteristic amount is affected by a temporary or instantaneous disturbance to the piping, the influence of the disturbance on the monitoring result is reduced. This improves the monitoring accuracy.

[0085] In any of the first to fourth aspects above, a flow rate monitoring method according to a fifth aspect of the present disclosure may include acquiring N (i+1)th feature values ​​for N (i+1)th data items in N (i+1)th periods (i=1, 2,...,N) prior to the first period (N is a natural number equal to or greater than 2), calculating a moving average value using the first feature values ​​and the N (i+1)th feature values, and monitoring the flow rate of the powder or granular material by comparing the moving average value with the first threshold value.

[0086] According to the above aspect, a moving average of the first feature amount and N previously detected feature amounts is used to monitor the flow rate of the powder or granular material. This further smoothes the first feature amount. This further reduces the influence of disturbances on the first feature amount on the monitoring result.

[0087] In the above fifth aspect, a flow rate monitoring method according to a sixth aspect of the present disclosure may include calculating a plurality of moving average values ​​using the first feature and the (i+1)th feature values, the N feature values ​​being equal to or less than the first threshold value, and determining that the flow rate of the powder or granular material is not normal.

[0088] According to the above aspect, when all of the moving average values ​​exceed the first threshold value over the N (i+1)th period and the first period, the flow rate of the powder or granular material is determined to be normal. In other words, when the flow rate of the powder or granular material continues to be normal, the flow rate of the powder or granular material is determined to be normal. Therefore, the accuracy of monitoring the flow rate of the powder or granular material is improved.

[0089] In any of the above first to sixth aspects, a flow rate monitoring method according to a seventh aspect of the present disclosure may include, when the first feature exceeds a second threshold, acquiring a second feature previously detected for second data, the second data being vibration data generated in the piping in a second period prior to the first period, and determining the first feature to be an average value of the first feature and the second feature.

[0090] According to the above aspect, the average value of the first feature amount and the second feature amount is determined as the first feature amount. As a result, the first feature amount is smoothed to match the feature amount detected before the first feature amount. In other words, periodic peaks of the feature amount that exceed the second threshold value are reduced. The periodic peaks may be caused by disturbances other than vibrations generated by the flowing powder. The effect of such disturbances on the feature amount is reduced.

[0091] In any of the above first to sixth aspects, a flow rate monitoring method according to an eighth aspect of the present disclosure may include, when the first feature exceeds a second threshold, acquiring M (j+1)th feature values ​​for M (j+1)th data items in M ​​(j+1)th periods (i=1, 2,...,N) (M is a natural number equal to or greater than 2) prior to the first period, and determining the first feature value to be an average value of the first feature value and the M (j+1)th feature values.

[0092] According to the above aspect, the average value of the first feature amount and the M (j+1)th feature amounts is determined as the first feature amount. This allows the first feature amount to be smoothed so as to match the multiple feature amounts detected before the first feature amount. This makes it possible to effectively reduce periodic peaks in the feature amount.

[0093] In any one of the first to eighth aspects described above, a flow rate monitoring method according to a ninth aspect of the present disclosure includes acquiring, as the first data, vibration data generated in a pipe through which a mixture of a first powder or granular material and a second powder or granular material flows, detecting a frequency component of the corresponding part as the frequency characteristic by frequency analyzing the corresponding part of the first data, detecting a first peak part and a second peak part formed by the frequency components in the corresponding part, dividing the frequency components of the corresponding part into a first frequency component of the first powder or granular material including a part corresponding to the first peak part and a second frequency component of the second powder or granular material including a part corresponding to the second peak part, detecting an amount of fluctuation of the first frequency component between the frames, detecting the first characteristic amount of the first powder material based on the amount of fluctuation of the first frequency component between adjacent frames, detecting an amount of fluctuation of the second frequency component between adjacent frames, detecting the first characteristic amount of the second powder material based on the amount of fluctuation of the second frequency component between adjacent frames, and monitoring the flow rates of the first powder material and the second powder material by comparing the first characteristic amount of the first powder material with the first characteristic amount of the first powder material and comparing the first characteristic amount of the second powder material with the first threshold value of the second powder material.

[0094] According to the above aspect, the frequency components of the corresponding portion of the first data are divided into a first frequency component of the first powder or granule and a second frequency component of the second powder or granule. Further, a first characteristic amount is detected for each of the first frequency component and the second frequency component, and the first characteristic amount of the first powder or granule and the first characteristic amount of the second powder or granule are compared with respective first thresholds. It is possible to monitor the flow rate of the first powder or granule and the flow rate of the second powder or granule.

[0095] In any of the above first to ninth aspects, a flow rate monitoring method according to a tenth aspect of the present disclosure may include receiving a detection signal from a sensor attached to the piping and detecting vibrations in the piping, extracting a detection signal for each of the first time periods from the detection signal as the first data, and repeatedly performing a process of monitoring the flow rate of the powder or granular material for each of the first time periods.

[0096] According to the above aspect, it is possible to periodically monitor the flow rate of the powder or granular material while receiving a detection signal from the sensor. As a result, for example, if an abnormality occurs in the flow rate of the powder or granular material during a process in which the powder or granular material is sent through a pipe, the abnormality can be immediately detected by periodic monitoring using the detection signal from the sensor.

[0097] A flow rate monitoring device according to an eleventh aspect of the present disclosure includes a processing circuit that monitors the flow rate of the powder or granular material by executing the flow rate monitoring method according to any one of the first to tenth aspects. According to the above aspect, the same effects as those of the flow rate monitoring method according to each aspect of the present disclosure can be obtained.

[0098] In the eleventh aspect, the processing circuit of the flow rate monitoring device according to the twelfth aspect of the present disclosure may output a command to issue an alarm when a result of comparing the first characteristic amount with the first threshold indicates that the flow rate of the powder or granular material in the pipe is abnormal. According to the above aspect, the flow rate monitoring device can notify that the flow rate of the powder or granular material is abnormal.

[0099] In the above-mentioned eleventh or twelfth aspect, the flow rate monitoring device according to a thirteenth aspect of the present disclosure may further include a sensor attached to the piping and detecting vibrations in the piping, and the processing circuit may extract a detection signal for the first period from a detection signal of the sensor as the first data. According to the above-mentioned aspect, the flow rate monitoring device can measure vibrations of the piping and monitor the flow rate based on the measurement result.

[0100] A flow rate monitoring system according to a fourteenth aspect of the present disclosure includes the flow rate monitoring device according to the eleventh or twelfth aspect, a plant, and a sensor attached to a pipe of the plant and detecting vibrations in the pipe, and the processing circuit extracts a detection signal for the first period from the detection signal of the sensor as the first data. According to the above aspect, the same effect as that of the flow rate monitoring device according to each aspect of the present disclosure can be obtained. The flow rate monitoring system can measure the vibrations of the pipe and monitor the flow rate based on the measurement results.

[0101] The present disclosure may be a computer program that causes a computer to execute the flow rate monitoring method according to each aspect of the present disclosure. Such a computer program can achieve the same effects as the flow rate monitoring method according to each aspect of the present disclosure. The computer program may be, for example, a program recorded on a non-transitory computer-readable recording medium, and may be configured to be read from the recording medium using a drive device for the recording medium and installed on a computer. The computer program may be, for example, a program that can be distributed via a transmission medium such as the Internet, and may be configured to be downloaded and installed on a computer.

[0102] The functions of the elements disclosed herein can be performed using circuits or processing circuits, including general purpose processors, special purpose processors, integrated circuits, ASICs, conventional circuits, and / or combinations thereof, configured or programmed to perform the disclosed functions. A processor is considered a processing circuit or circuit because it includes transistors and other circuits. In this disclosure, a circuit, unit, or means is hardware that performs the recited functions or hardware that is programmed to perform the recited functions. The hardware may be hardware disclosed herein or other known hardware that is programmed or configured to perform the recited functions. Where the hardware is a processor, which is considered a type of circuit, the circuit, means, or unit is a combination of hardware and software, and the software is used to configure the hardware and / or the processor.

[0103] All numbers such as ordinal numbers and quantities used in this specification are exemplified to specifically explain the technology of the present disclosure, and the present disclosure is not limited to the exemplified numbers. The connection relationships between components are exemplified to specifically explain the technology of the present disclosure, and the connection relationships that realize the functions of the present disclosure are not limited to these.

[0104] Since the present disclosure may be implemented in various forms without departing from the scope of its essential characteristics, the scope of the present disclosure is defined by the appended claims rather than the description in the specification, and therefore the exemplary embodiments and modifications are illustrative and not limiting. All modifications within the scope of the claims and their equivalents are intended to be embraced by the claims. [Explanation of symbols]

[0105] 1. Plant 100 Flow Monitoring System 110 Sensors 120 Flow monitoring device 20e Piping

Claims

1. Acquiring first data, which is data on vibrations occurring in a first period in a pipe through which powder or granular material flows; Dividing the first period of the first data into a plurality of frames, which are a plurality of time intervals; detecting a frequency characteristic of a corresponding portion of the first data corresponding to each of the plurality of frames; Detecting a first feature amount of the first data based on frequency characteristics in the plurality of frames; and monitoring the flow rate of the powder or granular material by comparing the first characteristic amount with a first threshold value. Flow rate monitoring method.

2. detecting a frequency component of the corresponding portion as the frequency characteristic by performing a frequency analysis on the corresponding portion; Detecting a variation in frequency components between adjacent frames; and detecting the first feature amount based on a variation amount of a frequency component between the adjacent frames.

2. The method of claim 1.

3. In the detection of the amount of fluctuation of the frequency component, Detecting a difference in frequency components in the same frequency band between adjacent frames for each of a plurality of frequency bands corresponding to the frequency components; A sum of the differences in the plurality of frequency bands is detected as a fluctuation amount of the frequency component.

3. The method of claim 2.

4. acquiring a second feature amount previously detected for second data, the second data being vibration data generated in the piping during a second time period prior to the first time period; and monitoring the flow rate of the powder or granular material by comparing an average value of the first characteristic amount and the second characteristic amount with the first threshold value.

2. The method of claim 1.

5. acquiring N (i+1)th feature amounts for N (i+1)th data items in N (i+1)th periods (i=1, 2, ..., N) (N is a natural number equal to or greater than 2) prior to the first period; calculating a moving average value using the first feature amount and the N (i+1)-th feature amounts; and monitoring the flow rate of the powder or granular material by comparing the moving average value with the first threshold value.

2. The method of claim 1.

6. calculating a plurality of moving average values ​​using the first feature amount and the N (i+1)-th feature amounts; determining that the flow rate of the powder or granular material is abnormal if any of the plurality of moving average values ​​is equal to or less than the first threshold value.

6. The method of claim 5.

7. When the first characteristic amount exceeds a second threshold value, acquiring a second characteristic amount previously detected for second data, which is vibration data generated in the piping during a second period prior to the first period; determining an average value of the first feature amount and the second feature amount as the first feature amount. A method for monitoring flow rate according to any one of claims 1 to 6.

8. When the first feature amount exceeds a second threshold, acquiring M (j+1)th feature amounts for M (j+1)th data items in M ​​(j+1)th periods (i=1, 2, ..., N) (M is a natural number equal to or greater than 2) prior to the first period; determining an average value of the first feature amount and the M number of the (j+1)th feature amounts as the first feature amount. A method for monitoring flow rate according to any one of claims 1 to 6.

9. acquiring, as the first data, vibration data generated in a pipe through which a mixture of the first powder / granular material and the second powder / granular material flows; performing a frequency analysis on the corresponding portion of the first data to detect a frequency component of the corresponding portion as the frequency characteristic; detecting a first peak portion and a second peak portion formed by the frequency component in the corresponding portion; Dividing the frequency components of the corresponding portions into a first frequency component of the first powder or granule material including a portion corresponding to the first peak portion and a second frequency component of the second powder or granule material including a portion corresponding to the second peak portion; Detecting an amount of variation in the first frequency component between adjacent frames; Detecting the first characteristic amount of the first powder or granular material based on a fluctuation amount of the first frequency component between adjacent frames; Detecting an amount of variation in the second frequency component between adjacent frames; Detecting the first feature amount of the second powder or granular material based on a fluctuation amount of the second frequency component between adjacent frames; and monitoring the flow rates of the first powder and the second powder by comparing the first characteristic amount of the first powder with the first characteristic amount of the second powder and comparing the first characteristic amount of the second powder with the first threshold value of the second powder.

2. The method of claim 1.

10. receiving a detection signal from a sensor attached to the piping and detecting vibrations in the piping; extracting the detection signal for each of the first periods from the detection signal as the first data; and repeating the process of monitoring the flow rate of the powder or granular material for each of the first periods.

2. The method of claim 1.

11. A processing circuit for monitoring the flow rate of the powder or granular material by executing the flow rate monitoring method according to claim 1. Flow monitoring device.

12. The processing circuit outputs a command to issue an alarm when a result of comparing the first characteristic amount with the first threshold indicates that a flow rate of the powder or granular material in the pipe is not normal.

12. The flow monitor of claim 11.

13. a sensor attached to the piping and detecting vibrations in the piping; The processing circuit extracts the detection signal of the first period from the detection signal of the sensor as the first data.

12. The flow monitor of claim 11.

14. A flow monitoring device according to claim 11; The plant, a sensor attached to a piping of the plant and detecting vibrations in the piping; The processing circuit extracts the detection signal of the first period from the detection signal of the sensor as the first data. Flow monitoring system.

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