Heat adjustment monitoring device, heat adjustment monitoring program, and heat adjustment monitoring method

Abstract

To suitably compare time series data.SOLUTION: A heat regulation monitoring device comprises a first acquisition unit of acquiring a plurality time series data in the whole period, each showing the temporal change of flame activity in the whole period of a combustion sequence, and a second acquisition unit of acquiring a plurality of partial time series data by extracting partial time series data showing the temporal change of flame activity in a partial period of the combustion sequence, from each of the plurality of time series data in the whole period. A heat regulation monitoring device 20 comprises a comparison unit that compares the plurality of partial time series data to output the result of the comparison. The partial period is constituted by a period of 30 seconds subsequent to the timing of finishing pre-purging, a period of 10 seconds prior to the timing of finishing steady combustion and a period of 5 seconds subsequent to the timing of finishing the steady combustion.SELECTED DRAWING: Figure 8

Description

Technical Field

[0001] The present invention relates to a heat conditioning monitoring device, a heat conditioning monitoring program, and a heat conditioning monitoring method for monitoring a state quantity of heat conditioning such as heating or cooling.

Background Art

[0002] Patent Document 1 discloses a technique for monitoring the activity (ultraviolet intensity in Patent Document 1) of a burner flame for each of a plurality of sub-sequences (in Patent Document 1, "pilot ignition (trial)", "pilot only", "main ignition", and "main stable") that constitute a combustion sequence. In this technique, when the activity of the burner flame to be monitored deviates from the normal state determined for each sub-sequence, it is determined that there is a malfunction in the combustion device.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the technology described in the above Patent Document 1, the presence or absence of a malfunction is determined based on the activity of the flame at a certain timing. For this reason, in the above technology, it is difficult for the user to grasp this malfunction when a malfunction appears at a timing other than the above certain timing. Therefore, the inventor of the present application has found that a plurality of time-series data indicating the temporal change in the activity of the flame in a series of combustion sequences are compared. As a result, the user can grasp how the current time-series data has changed with respect to the past time-series data, and can grasp the signs of a malfunction and the occurrence of a malfunction from this manner of change. However, when comparing the time-series data obtained in a series of combustion sequences, that is, the time-series data for the entire period of the entire combustion sequence, there may be inconveniences such as the time-series data to be compared becoming large, or comparing even parts that do not need to be compared originally (for example, a period when the burner flame does not occur at all like pre-purge). Furthermore, for example, the length of the main stable period of the combustion sequence may change for each combustion sequence. In this case, since the time axis of the time-series data to be compared is shifted, there may also be an inconvenience that the time-series data cannot be simply compared.

[0005] The present invention has been made in view of the above points, and an object thereof is to appropriately compare time-series data.

Means for Solving the Problems

[0006] In order to solve the above problems, a heat regulation monitoring device according to a first aspect of the present invention is a heat regulation monitoring device that monitors a state quantity of heat regulation performed by a predetermined heat regulation process, and includes a first acquisition unit configured to acquire a plurality of full-period time-series data each indicating a temporal change in the state quantity of the heat regulation during at least a part of the entire period of the heat regulation process, a second acquisition unit configured to acquire a plurality of partial time-series data by extracting, from each of the plurality of full-period time-series data, partial time-series data indicating a temporal change in the state quantity of the heat regulation during a partial period of the entire period, and a comparison unit configured to compare the plurality of partial time-series data and output a comparison result.

[0007] The plurality of all-period time series data are stored in the storage unit, and the partial period may be settable by the user after the plurality of all-period time series data are stored in the storage unit.

[0008] The first acquisition unit is configured to acquire each of the plurality of all-period time series data by sequentially acquiring the state quantity of the heat adjustment in real time over the entire period, and the second acquisition unit is configured to extract the partial time series data by sequentially acquiring in real time the state quantity of the heat adjustment that the first acquisition unit sequentially acquires in real time during the partial period of the entire period.

[0009] The partial period may be discrete in time series and may be composed of a plurality of periods of the same length among the plurality of partial time series data.

[0010] The comparison unit compares a plurality of reference partial time series data serving as a reference among the plurality of partial time series data with a plurality of partial time series data that are newer than the plurality of reference partial time series data among the plurality of partial time series data, and generates deviation time series data indicating the degree of deviation of the state quantity of the new partial time series data with respect to the distribution of the state quantities of the plurality of reference partial time series data at each time point corresponding to each other in time series.

[0011] The first acquisition unit is configured to acquire each of the plurality of full-period time series data by sequentially acquiring the state quantity of the heat adjustment in real time over the entire period, and the second acquisition unit is configured to extract the partial time series data by sequentially acquiring in real time the state quantity of the heat adjustment that the first acquisition unit sequentially acquires in a partial period of the entire period. Each time the second acquisition unit sequentially acquires each state quantity of the new partial time series data, the comparison unit derives the degree of deviation, and each time the degree of deviation is derived, the derived degree of deviation is sequentially additionally displayed on the display unit, thereby drawing a graph of the time change of the degree of deviation in real time. It may be configured as such.

[0012] The comparison unit may be configured to display, on the display unit, the graph of the new partial time series data and the graph of the deviation time series data in association with each other.

[0013] The comparison unit may be configured to estimate the presence or absence of a malfunction of the heat adjustment device and the type thereof when there is a malfunction based on the deviation time series data, and output an estimation result.

[0014] The comparison unit may be configured to output, as the comparison result, an image in which a graph based on reference partial time series data serving as a reference among the plurality of partial time series data and a graph of partial time series data that is newer than the reference partial time series data among the plurality of partial time series data are associated with each other.

[0015] The heat adjustment process may be composed of a plurality of sub-processes, and the partial period may include one or more periods based on the start or end timing of one of the plurality of sub-processes.

[0016] The heat treatment monitoring program according to the second aspect of the present invention causes a heat treatment monitoring computer that monitors the state quantity of heat treatment performed by a predetermined heat treatment process to function as a first acquisition unit that acquires a plurality of full-period time series data each indicating the time change of the state quantity of the heat treatment during at least a part of the entire period of the heat treatment process, a second acquisition unit that acquires a plurality of partial time series data by extracting, from each of the plurality of full-period time series data, partial time series data indicating the time change of the state quantity of the heat treatment during a partial period of the entire period, and a comparison unit that compares the plurality of partial time series data and outputs a comparison result.

[0017] The heat treatment monitoring method according to the third aspect of the present invention is a heat treatment monitoring method for monitoring the state quantity of heat treatment performed by a predetermined heat treatment process, and includes a first acquisition step of acquiring a plurality of full-period time series data each indicating the time change of the state quantity of the heat treatment during at least a part of the entire period of the heat treatment process, a second acquisition step of acquiring a plurality of partial time series data by extracting, from each of the plurality of full-period time series data, partial time series data indicating the time change of the state quantity of the heat treatment during a partial period of the entire period, and a comparison step configured to compare the plurality of partial time series data and output a comparison result.

Effect of the Invention

[0018] According to the present invention, time series data can be appropriately compared.

Brief Description of the Drawings

[0019]

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BEST MODE FOR CARRYING OUT THE INVENTION

[0020] Hereinafter, embodiments of the present invention and modifications thereof will be described with reference to the drawings.

[0021] (Embodiment) As shown in FIG. 1, a heat adjustment monitoring device 20 according to an embodiment of the present invention is used in a heating system 10. The heating system 10 is configured to heat the inside of a combustion chamber R by burning fuel gas and heat an object to be heated inside the combustion chamber R. The heat adjustment monitoring device 20 is configured to monitor the intensity of the burner flame as a state quantity of the heating inside the combustion chamber R. The user grasps the presence or absence of a malfunction in the heating (heat adjustment) in the combustion device 30, in other words, inside the combustion chamber R, by checking the monitoring result (the comparison result between the latest partial time-series data and the reference partial time-series data described later). "Malfunction" refers to an abnormality at an operable level of the combustion device 30 before the combustion device 30 becomes inoperable, that is, a mild abnormality.

[0022] In addition to the heat adjustment monitoring device 20, the heating system 10 includes a combustion device 30 that burns combustion gas and a combustion control device 70 that controls the combustion by the combustion device 30. Hereinafter, the combustion device 30 and the combustion control device 70 will be described first, and then the heat adjustment monitoring device 20 will be described.

[0023] The combustion device 30 includes a combustion appliance 40, an air supply system 50, and a fuel supply system 60.

[0024] The combustion appliance 40 burns fuel gas inside the combustion chamber R. The combustion appliance 40 includes a combustion furnace 41 that forms the combustion chamber R and a main burner 42 that burns fuel gas to heat the inside of the combustion chamber R. The combustion appliance 40 further includes a pilot burner 43 that burns fuel gas to ignite the main burner 42 and an ignition device (igniter) 44 that generates an ignition spark for igniting the pilot burner 43. The combustion appliance 40 further includes a flame detector 45 that detects the activity of the flame of each burner 42 and 43 by converting the activity into an electrical signal and a temperature sensor 46 that detects the temperature inside the combustion chamber R by converting the temperature into an electrical signal. The activity of the flame is the degree indicating how actively the flame is generated, and here, it is the intensity of the flame.

[0025] The flame detector 45 includes a discharge tube 45A including two electrodes and a package containing the two electrodes together with a predetermined gas. The flame detector 45 further includes a window 45B that transmits electromagnetic waves (here, ultraviolet rays) radiated from the flame of the main burner 42 or the pilot burner 43 and guides them to the discharge tube 45A. In the discharge tube 45A, when electromagnetic waves radiated from the flame of each burner 42 or 43 are incident into the package with a voltage applied between the two electrodes, a discharge occurs between the two electrodes. An electrical signal is output from the flame detector 45 due to this discharge. In this way, the flame detector 45 converts the intensity of the electromagnetic waves radiated from the flame of each burner 42 or 43, that is, the activity of the flame, into an electrical signal and outputs it. The output electrical signal is here a voltage signal whose voltage value changes according to the activity of the flame, but the electrical signal may be a current signal whose current value changes according to the activity of the flame. The above voltage signal is also referred to as the frame voltage VF, and the above current signal is also referred to as the frame current IF. The voltage value of the frame voltage VF and the current value of the frame current IF indicate the activity of the flame. The frame voltage VF and its voltage value in the following description can be changed to the frame current IF and its current value.

[0026] The air supply system 50 supplies air to each of the burners 42 and 43 of the combustion device 40. The fuel supply system 60 supplies external fuel gas to the main burner 42 and the pilot burner 43 of the combustion device 40. The configurations of each of the systems 50 and 60 are arbitrary. Each of the systems 50 and 60 is configured to supply air and fuel gas such that the air-fuel ratio, which is the ratio of air to fuel gas, is within a predetermined range favorable for combustion.

[0027] The combustion control device 70 is configured to include various computers such as a PLC (Programmable Logic Controller) and a personal computer. The combustion control device 70 is also called a burner controller. The combustion control device 70 may be configured to include a burner controller and a thermostat that activates the burner controller so that the temperature detected by the temperature sensor becomes a desired temperature.

[0028] The combustion control device 70 controls the operation of the combustion device 30 by executing a predetermined combustion sequence. At the start of the combustion sequence, it is assumed that the air supply system 50 and the fuel supply system 60 are controlled to a closed state where they do not supply air and fuel to the main burner 42 and the pilot burner 43. As shown in FIG. 2, the combustion sequence includes sub-sequences such as "pre-purge" (step S1), "pilot ignition" (step S2), "pilot only" (step S3), "main ignition" (step S4), "main stabilization" (step S5), and "steady combustion" (step S6).

[0029] In the pre-purge, the combustion control device 70 controls the air supply system 50 to an open state and sends fresh air into the combustion chamber R through the main burner 42 and the pilot burner 43. Thereby, the fuel gas remaining in the combustion chamber R is discharged to the outside. The pre-purge is performed for a certain period of time.

[0030] After the pre-purge, the combustion control device 70 controls the fuel supply system 60 to start fuel supply to the pilot burner 43 and executes pilot ignition that operates the ignition device 44 to generate an ignition spark. Thereby, the pilot burner 43 is ignited. The combustion control device 70 detects the ignition of the pilot burner 43 when the activity of the flame detected by the flame detector 45 exceeds a first predetermined value. After this detection, the combustion control device 70 executes pilot only to stabilize the flame of the pilot burner 43.

[0031] After only the pilot, the combustion control device 70 controls the fuel supply system 60 to execute main ignition to start fuel supply to the main burner 42. As a result, the main burner 42 is ignited using the flame of the pilot burner 43 as the kindling. The combustion control device 70 detects the ignition of the main burner 42 when the activity of the flame detected by the flame detector 45 exceeds a second predetermined value or increases by a predetermined amount from the detection of ignition of the pilot burner 43. After detecting the ignition, the combustion control device 70 executes main stabilization to stabilize the flame of the main burner 42. In this embodiment, it is assumed that the flame of the pilot burner 43 is not extinguished after the main burner 42 is ignited, but the flame of the pilot burner 43 may be extinguished after the main burner 42 is ignited.

[0032] After only the main, the combustion control device 70 shifts to steady combustion. The steady combustion uses the temperature in the combustion chamber R supplied from the temperature sensor 46 as a feedback value, and ends when the temperature reaches a target value and that state continues for a predetermined period. The combustion control device 70 controls the air supply system 50 and the fuel supply system 60 to a closed state at the timing of the end of the steady combustion, and stops the supply of air and fuel to the main burner 42 and the pilot burner 43. As a result, the flames of the burners 42 and 43 are extinguished. The above target value and predetermined period are supplied from a host device of the combustion control device 70 or the like and set in the combustion control device 70. The length of the steady combustion may vary for each combustion sequence depending on the temperature in the combustion chamber R before the steady combustion and the length of the above predetermined period. In the steady combustion, the supply amounts of fuel and air may be feedback-controlled using the temperature in the combustion chamber R as a feedback value.

[0033] During the combustion sequence, the combustion control device 70 performs analog-to-digital conversion on the frame voltage VF output from the flame detector 45 at a predetermined sampling rate, and generates time-series data indicating the temporal change in the flame activity indicated by the voltage value of the frame voltage VF. The combustion control device 70 outputs this time-series data to the heat adjustment monitoring device 20 as overall period time-series data indicating the temporal change in the flame activity (frame voltage VF) during the entire period of the combustion sequence. The frame voltage VF indicates the flame activity of the pilot burner 43 when only the pilot burner 43 is emitting a flame, and indicates the sum of the flame activities of both burners 42 and 43 when both burners 42 and 43 are emitting flames. Note that the overall period time-series data may be time-series data indicating the temporal change in the flame activity (frame voltage VF) during a partial overall period of the combustion sequence.

[0034] Next, the heat adjustment monitoring device 20 will be described. The heat adjustment monitoring device 20 monitors the flame activities of both burners 42 and 43 based on the overall period time-series data output from the combustion control device 71. The heat adjustment monitoring device 20 is configured to include various computers such as a personal computer. As shown in FIG. 3, the heat adjustment monitoring device 20 includes a processor 21 such as a CPU (Central Processing Unit), a RAM (Random Access Memory) 22 that functions as the main memory of the processor 21, and a non-volatile storage device 23 that stores a heat adjustment monitoring program executed by the processor 21. The storage device 23 also stores the overall period time-series data group, partial time-series data group, and reference time-series data, which will be described later. The heat adjustment monitoring device 20 further includes a display 24 that displays various screens described later, an operating device 25 operated by the user, and a communication module 26 for the processor 21 to communicate with the combustion control device 71.

[0035] In this embodiment, the processor 21 operates as the first acquisition unit 21A, the second acquisition unit 21B, and the comparison unit 21C shown in FIG. 4 by executing the heat adjustment monitoring program stored in the storage device 23.

[0036] The first acquisition unit 21A communicates with the combustion control device 71 via the communication module 26, acquires the entire-period time-series data output from the combustion control device 71 every time a combustion sequence is executed, and stores it in the storage device 23. For example, every time the first acquisition unit 21A acquires the entire-period time-series data, it executes the entire-period time-series data storage process shown in FIG. 5.

[0037] In the entire-period time-series data storage process of FIG. 5, the first acquisition unit 21A stores the entire-period time-series data in the Nth (initial value is 0) storage area among the storage areas of the entire-period time-series data provided in the storage device 23 (step S11). After that, the first acquisition unit 21A determines whether N is 9 (step S12). If N is not 9 (No), 1 is added to N (step S13). When N is 9 (step S12; Yes), the first acquisition unit 21A initializes N to 0 (step S14). Through such a series of processes, when 10 pieces of entire-period time-series data with N = 0 to 9 are stored in the storage device 23, the subsequent entire-period time-series data will be overwritten starting from N = 0. As a result, the latest 10 pieces of entire-period time-series data are always stored in the storage device 23. This data group of these 10 time-series data is stored in the storage device 23 as the entire-period time-series data group.

[0038] The first acquisition unit 21A further acquires reference time-series data serving as a reference for later comparison and stores it in the storage device 23 by starting the reference time-series data processing shown in FIG. 6 from the first operation start after the manufacture of the combustion device 30. In the reference statistical data generation process shown in FIG. 6, the first acquisition unit 21A monitors each storage area of N = 0 to 9 in the storage device 23 and waits until the entire period time-series data is stored in all of them (step S21). When the entire period time-series data is stored in each storage area of N = 0 to 9 (step S21; Yes), the first acquisition unit 21A stores these 10 pieces of entire period time-series data as 10 pieces of reference time-series data in another storage area of the storage device 23 (step S22). The set of 10 pieces of reference time-series data stored in the other storage area is also referred to as a reference time-series data group hereinafter. Note that the number of reference time-series data constituting the reference time-series data group is not limited to 10 and may be any number of 1 or more.

[0039] The reference time-series data processing shown in FIG. 6 may be started before the operation test after the manufacture of the combustion device 30, or may be started after the start of the actual operation of the combustion device 30 after the end of the operation test. The manufacture includes the case where the combustion device 30 is renewed by repairing, fixing, modifying, or replacing the flame detector 45. Further, the reference time-series data processing may be started at any timing when the user wants to register the reference time-series data group. In this case, the user instructs to that effect via the operation device 25. The reference time-series data processing may be executed when no trouble has occurred in the combustion device 30. That is, the reference time-series data group is generated by a combustion sequence executed after the manufacture of the combustion device 30 and before any trouble occurs in the combustion device 30.

[0040] Returning to FIG. 4, the second acquisition unit 21B extracts some time-series data from the latest entire period time-series data among the entire period time-series data group stored in the storage device 23 at that time at any timing after the reference time-series data group is registered in the storage device 23. Further, the second acquisition unit 21B also extracts some time-series data from each reference time-series data constituting the reference time-series data group.

[0041] The extraction of the time-series data by the second acquisition unit 21B is performed for the comparison described later by the comparison unit 21C. To explain this point in detail, as described above, the length of the steady combustion period in the combustion sequence may vary for each combustion sequence. For this reason, as shown in each graph of the entire period time-series data A and B in FIG. 7, the timing at the end of steady combustion may shift for each combustion sequence. Also, during the pre-purge period, since ignition of the pilot burner 43 is not performed, the flame activity (flame voltage VF) does not change. Therefore, there is no need to compare the flame activity for the pre-purge. Thus, in this embodiment, the above extraction is performed for the purpose of absorbing the difference in the length of the steady combustion period between the time-series data to align the timing at the end of steady combustion, and omitting the pre-purge period to reduce the data processing load during comparison. The second acquisition unit 21B extracts, for example, as shown in FIG. 8, time-series data for each of a plurality of periods discretely arranged in time series, such as 30 seconds from the end timing of the pre-purge, and 10 seconds before and 5 seconds after the end timing of the steady combustion, from the entire period time-series data. The set of the extracted plurality of time-series data is hereinafter also referred to as partial time-series data. In this embodiment, the partial time-series data is arranged in time series as shown in the graph of FIG. 8 and is treated as one time-series data.

[0042] The second acquisition unit 21B acquires the partial time-series data by extracting the partial time-series data from the entire period time-series data. The second acquisition unit 21B stores the acquired partial time-series data in the storage device 23. The acquisition of the partial time-series data is performed for each of the entire period time-series data constituting the latest entire period time-series data and the reference time-series data. The plurality of partial time-series data acquired for these are stored in the storage device 23 as a partial time-series data group. Note that, among the partial time-series data group, the partial time-series data extracted from the latest entire period time-series data is also referred to as the latest partial time-series data. On the other hand, each partial time-series data extracted from each of the reference time-series data constituting the reference time-series data is also referred to as the reference partial time-series data.

[0043] When a partial time-series data group is stored in the storage device 23, the comparison unit 21C reads out this partial time-series data group from the storage device 23 and compares each partial time-series data. In this embodiment, the malfunction score time-series data described later is generated by this comparison. The above-mentioned arbitrary timing that triggers the operation of the second acquisition unit 21B may be, for example, the timing when the user operates the operation device 25 because the user wants to check the malfunction score time-series data.

[0044] The comparison unit 21C sequentially compares the flame activity (frame voltage VF) of the latest partial time-series data acquired by the second acquisition unit 21B with the flame activity (frame voltage VF) of each reference partial time-series data in time series order. The comparison unit 21C generates malfunction score time-series data, which is time-series data indicating the continuous time change of the malfunction score described later, by this comparison.

[0045] The comparison unit 21C performs the above comparison and the like, for example, by executing the comparison process shown in FIG. 9. In the comparison process shown in FIG. 9, the comparison unit 21C first compares the latest partial time-series data with each reference partial time-series data using kernel density estimation (step S31).

[0046] The reference partial time-series data X for n = 10 times compared in step S31 i (i = 1, 2, 3 ··· n) are respectively set as "X 1 = X 1,1 , X 1,2 , X 1,3 , ··· X 1,M ", "X 2 = X 2,1 , X 2,2 , X 2,3 , ··· X 2,M ", ··· "X n = X n,1 , X n,2 , X n,3 , ··· X n,M ". Further, one reference partial time-series data is also referred to as reference partial time-series data X. Here, X i,1 ~X i,Mis the flame activity at each time point that constitutes the reference partial time series data, and is arranged in time series order. M is the number of data points of the flame activity, that is, the number of the time points. In addition, when there is a deviation in the sampling timing for obtaining the entire period time series data that is the basis of the reference partial time series data, or when the number of data points of the flame activity is different, the comparison unit 21C may perform time stretching using a known technique such as DTW (Dynamic Time Warping) to align the sampling timing and the number of data between the reference partial time series data.

[0047] Here, if the latest partial time series data is "Y = Y 1 ,Y 2 ,Y 3 ,···Y M ", then the comparison unit 21C obtains the kernel density estimator fm for the flame activity Y m at a certain time point m from the following formula (1).

Equation

[0048] K in formula (1) is a kernel function, and the comparison unit 21C calculates it by, for example, the Gaussian formula of the following formula (2).

Equation

[0049] h in the above formula (1) is an adjustment parameter called the bandwidth. The comparison unit 21C may obtain h from the flame activity X i,m in the reference partial time series data X by a method such as cross-validation, or may obtain it heuristically using Scott's method or Silverman's method. Here, Scott's method using the following formula (3) is adopted. s below is the sample standard deviation of X i,m , q(0.75) and q(0.25) are the 0.75 quantile and 0.25 quantile of the sample respectively, and min(a, b) is a function that takes the minimum value of a and b.

number

[0050] Then, for each calculated fm, a malfunction score Em is defined by the following formula (4). The malfunction score Em is a value that increases as the latest partial time series data Y to be processed at each point in time m deviates more from the distribution of the reference partial time series data X (the possible range of activity of each flame of the multiple reference partial time series data X constituting the reference partial time series data group). In other words, the malfunction score Em indicates the degree of deviation, and if the malfunction score Em is large, there is a high possibility that a malfunction is occurring at that point in time.

number

[0051] In this manner, in step S31, the comparison unit 21C compares the latest partial time series data Y with a plurality of reference temporary time series data X 1 ~X n (n=10) and the flame activity (Y m ,X 1,m ,X 2,m ,X 3,m ,···X n,m ) and obtains a malfunction score Em indicating the degree of deviation of the flame activity at each time point. The set of the degrees of deviation at each time point, that is, the deviation time series data indicating the change over time in the degree of deviation, is hereinafter also referred to as malfunction score time series data E. Through the above comparison and acquisition, the comparison unit 21C generates the malfunction score time series data E as a comparison result.

[0052] The comparison unit 21C then correlates the malfunction score time series data E and the latest partial time series data Y, graphs them, outputs them to the display 24, and displays the graphs of each data on the display 24 (step S32). The user can check the graphs displayed on the display 24 to understand whether or not the combustion device 30 is malfunctioning.

[0053] Here, graphs of a plurality of reference partial time-series data X are shown in FIG. 10, and examples of graphs of the latest partial time-series data Y and the malfunction score time-series data E displayed on the display 24 are shown in FIGS. 11 to 15. In FIGS. 11 to 15, the graph of the latest momentary time-series data Y is generated by connecting the graphs of the time-series data of a plurality of periods constituting a partial period, but the graphs of the time-series data of the plurality of periods may be handled separately.

[0054] In FIG. 10, three of the ten reference partial time-series data X are depicted representatively. The graph in FIG. 10 is a graph of partial time-series data during normal times (non-abnormal times) when there is no malfunction in the combustion device 30 or the heating by the combustion device 30, that is, before a malfunction occurs. As shown representatively in FIG. 10, the graphs of the ten partial time-series data have similar shapes.

[0055] FIG. 11 shows graphs of the latest partial time-series data Y and the malfunction score time-series data E obtained from the combustion sequence of the combustion device 30 before a malfunction occurs. As shown in FIG. 11, when there is no malfunction, the malfunction score Em fluctuates near 0. In particular, even when the flame activity changes greatly from near 0 (ignition timing) to near 3.4 (steady combustion), there is no significant change in the malfunction score Em.

[0056] FIG. 12 shows a graph when a malfunction occurs in the combustion device 30 where the frequency of false discharges (discharges other than electromagnetic wave discharges) occurring in the flame detector 45 is high. If a threshold for determining the presence or absence of a malfunction is set near the value of the malfunction score Em = 10, it can be seen that the malfunction occurs periodically. A user who sees such a graph can grasp that there is a malfunction and that the type of the malfunction may be false discharges (discharges other than electromagnetic wave discharges) in the flame detector 45.

[0057] FIG. 13 shows a graph when a problem occurs in the combustion device 30 because the window 45B of the flame detector 45 is soiled with soot or the like. For example, similar to FIG. 12, if a threshold for determining the presence or absence of a problem is set near the value of the problem score Em = 10, it can be seen that the problem has continued for a long time. Note that a limiter is provided for the problem score Em when graphing, and when the upper limit value is exceeded, the value is converted to the upper limit value. A user who views the graph of FIG. 13 can grasp that there is a problem and that the type of the problem may be the soiling of the window 45B.

[0058] FIG. 14 shows a graph when the air-fuel ratio, which is the ratio of air and fuel gas supplied to the main burner 42 and the pilot burner 43, is disturbed. Similar to the above, if a threshold for determining the presence or absence of a problem is set near the value of the problem score Em = 10, a user who views such a graph can grasp that a problem has occurred in each period near the start and end of combustion, and can grasp that the type of the problem may be the disturbance of the air-fuel ratio.

[0059] As described above, the heat adjustment monitoring device 20 of this embodiment extracts partial time-series data indicating the time change of the flame activity in a partial period of the combustion sequence from each of a plurality of full-period time-series data. Then, the heat adjustment monitoring device 20 compares the plurality of partial time-series data obtained by this extraction and outputs the comparison result. Here, the partial period is composed of a period of 30 seconds from the end timing of pre-purge, and periods of 10 seconds before and 5 seconds after the end timing of steady combustion. Thereby, in the comparison of the partial time-series data, it is possible to suppress the inconvenience of comparing even a period in which no burner flame occurs, such as pre-purge. Further, even if the main stable periods are different between the partial time-series data to be compared, the time axis can be aligned by the above extraction. And by the above extraction, the data amount at the time of comparing the partial time-series data is reduced. Thus, in this embodiment, the partial time-series data can be appropriately compared with each other, and thereby the user can appropriately grasp the malfunction or combustion malfunction of the combustion device 30.

[0060] When extracting partial time series data from the full-period time series data, the partial period may be settable by an operation input via the operation device 25 by the user. In particular, it may be settable even after the full-period time series data is stored in the storage device 23. In this embodiment, after the full-period time series data is once stored in the storage device 23, partial time series data is extracted. Therefore, the user can change the partial period a plurality of times, and can check a graph of the malfunction score time series data E or the like each time the change is made. Thereby, the user can search for a partial period that is optimal for grasping the malfunction. The partial period may be composed of a period of 30 seconds from the end timing of pre-purge and a period of 5 seconds before and after the end timing of steady combustion. The partial period may be composed of a period from the end of pre-purge to the end of main ignition, an arbitrary 10-second period in steady combustion, and a period of 5 seconds before and after the end timing of steady combustion.

[0061] When extracting each of the plurality of partial time series data acquired by the second acquisition unit 21B, the partial period may be composed of a plurality of periods that are discretely separated in time series as described above, and the plurality of periods may have the same length among the plurality of partial time series data. Thereby, the time axes of each of the plurality of partial time series data can be aligned, and the comparison becomes appropriate.

[0062] The partial period may include one or more periods based on the start or end timing of one sub-sequence among a plurality of sub-sequences of the combustion sequence. Since such a period is easily affected by a malfunction, the comparison of the partial time series data is appropriately performed. Note that the period includes a certain period before or after the start or end timing of the sub-sequence, and a certain period before and after the start or end timing of the sub-sequence. The certain periods before and after may be the same or different.

[0063] By checking the malfunction score time-series data E, if there is a period with a high malfunction score Em, the user can recognize that there is a malfunction in the combustion device 30. In particular, since the malfunction score time-series data E shows the continuous change over time of the malfunction score Em (the degree of deviation of the flame activity of the latest partial time-series data Y with respect to the distribution of the flame activity of each of the reference partial time-series data X), the occurrence of malfunctions is confirmed not at a specific timing but over a certain period as a whole. Thus, according to this embodiment, the user can appropriately recognize the presence or absence of a malfunction in the combustion device 30. If the user can appropriately recognize the malfunction of the combustion device 30, the user can detect a sign of failure.

[0064] In this embodiment, the malfunction score Em is obtained by comparing the flame activities of the reference partial time-series data X and the latest partial time-series data Y in time series for corresponding ones. Therefore, even if a certain threshold value is set for the malfunction score Em, the threshold value will change according to the passage of time. For this reason, an optimal threshold value for malfunction determination will be set.

[0065] Furthermore, in the above embodiment, a graph associating the graph of the latest partial time-series data Y and the graph of the malfunction score time-series data E is output and displayed on the display 24, so that the user can compare and check the time changes of the former and the latter. Thereby, the user can appropriately recognize in which sub-sequence a malfunction is occurring. As shown in FIGS. 11 to 14, when the period of each sub-sequence is also displayed in the graph, it facilitates the user's understanding of the sub-sequence of the malfunction. Furthermore, as shown in FIGS. 11 to 14, as the above association, by overlapping and displaying the graph of the latest partial time-series data Y and the graph of the malfunction score time-series data E on the same plane, the two graphs can be more easily compared. Note that the two graphs may be associated as two graphs with the horizontal axes corresponding to each other. The above association only needs to make the two graphs comparable. Note that the above comparison may be performed for each sub-sequence, and the above graphs may be separately displayed for each sub-sequence.

[0066] The reference partial time series data X is prepared based on the frame voltage VF measured in the combustion sequence actually executed by the combustion device 30. As a result, reference partial time series data X reflecting the individual idiosyncrasies of the plurality of produced combustion devices 30 can be obtained, so that the user can more appropriately grasp the malfunction of the combustion device 30.

[0067] As described above, since the comparison between the latest partial time series data Y and the plurality of reference partial time series data X is performed by kernel density estimation, a malfunction score Em with high accuracy can be obtained. Furthermore, by graphing the malfunction score Em, which is a numerical value representing the kernel density estimation amount fm, the user can intuitively grasp that the higher the malfunction score Em, the higher the possibility of malfunction. Note that the numerical values to be time-series data and graphed may be any numerical values representing the kernel density estimation amount fm, and are not limited to the malfunction score Em. The numerical value representing the kernel density estimation amount fm may be the kernel density estimation amount fm itself. That is, the kernel density estimation amount fm may be made into time-series data and graphed. The kernel density estimation amount fm can also be said to be the value of the degree of deviation described above.

[0068] (Modification example) The configuration of the above embodiment can be arbitrarily changed. Modification examples are illustrated below. Each modification example can also be combined with at least some of the others.

[0069] (Modification example 1) The configuration of the combustion device 30 is arbitrary. For example, the combustion device 30 may be of a type having only the main burner 42 without the pilot burner 43.

[0070] (Modification example 2) The comparison unit 21C may perform a process of estimating the presence or absence of a malfunction of the combustion device 30 and the type thereof when there is a malfunction based on the malfunction score time series data E. In this case, every time new full-period time series data is stored in the storage device 23, the second acquisition unit 21B operates to perform the above-described extraction, and upon completion of the extraction, the comparison unit 21C may perform the estimation result output process shown in FIG. 15.

[0071] As shown in FIG. 15, the comparison unit 21C estimates the presence or absence of a malfunction in the combustion device 30 and the type thereof if there is a malfunction based on the malfunction score time-series data E (step S41). When the comparison unit 21C determines that there is a malfunction as a result of the estimation (step S42; Yes), it outputs the result of the estimation (step S43).

[0072] Regarding the malfunction score Em, as shown in FIG. 12, if a period exceeding a predetermined threshold value occurs periodically and each of the periods is less than a predetermined length, the comparison unit 21C estimates that a malfunction such as false discharge has occurred in the flame detector 45 of the combustion device 30. Regarding the malfunction score Em, as shown in FIG. 13, if a period exceeding the predetermined threshold value occurs periodically and each of the periods is equal to or longer than the predetermined period, the comparison unit 21C estimates that a malfunction such as fouling of the window 45B of the flame detector 45 of the combustion device 30 has occurred. When the malfunction score Em exceeds the predetermined threshold value in each of the periods near the start of combustion and near the end of steady combustion as shown in FIG. 11, the comparison unit 21C estimates that a malfunction of air-fuel ratio disturbance has occurred.

[0073] The comparison unit 21C displays the result of the above estimation on the display 24. Examples of the display content include messages such as "There may be a high frequency of false discharge in the flame detector", "The window of the flame detector may be fouled", and "The air-fuel ratio is disturbed".

[0074] According to this modification example, since the user is notified of the presence or absence of a malfunction in the combustion device 30 and the type of the malfunction if there is a malfunction, the user can more appropriately grasp the malfunction of the combustion device 30. Note that the malfunction score time-series data E may be appropriately changed to time-series data indicating the continuous time change of the kernel density estimator fm.

[0075] (Modification Example 3) The comparison unit 21C may compare the two time series data by associating a first graph based on one or more reference partial time series data with a second graph of the latest partial time series data, and output each associated graph as the comparison result. For example, as shown in FIG. 16, the comparison unit 21C arranges the first graph (upper graph) and the second graph (lower graph) with the time axis corresponding to the vertical direction one above the other and displays them on the display 24. Thereby, the user can grasp the presence or absence of malfunction by comparing the two graphs. As another example of the above association, the first graph and the second graph may be superimposed and displayed within the same coordinate plane. The first graph may be a graph of any one of the plurality of reference partial time series data, or may be a graph showing the average value of the flame activity at each time point of the plurality of reference partial time series data.

[0076] (Modification Example 4) Based on all the full-period time series data groups other than the latest one among the full-period time series data groups, extraction of partial time series data and comparison between the extracted partial time series data and the reference partial time series data group may be performed. The extracted partial time series data only needs to be newer than each reference partial time series data. The time series data constituting each of the full-period time series data group, the reference time series data group, and the partial time series data group may be divided according to each condition such as time (such as morning, noon, or night) or the temperature in the combustion chamber R before the temperature rise, and stored and used individually.

[0077] (Modification Example 5) The combustion control device 70 outputs in real time the activity levels of each flame that constitutes the time series data for the entire period. The first acquisition unit 21A may acquire the time series data for the entire period by sequentially acquiring in real time the activity levels of each flame over the entire period of the time series data for the entire period. The first acquisition unit 21A repeats such acquisition to acquire a plurality of time series data for the entire period. The second acquisition unit 21B may be configured to extract partial time series data by sequentially acquiring in real time, for example from the first acquisition unit 21A, the activity levels of each flame that the first acquisition unit 21A sequentially acquires in real time during a partial period of the entire period. That is, the partial time series data may be acquired by the second acquisition unit 21B during the acquisition of the time series data for the entire period. For example, the extraction of the partial time series data may be performed by selecting, for each of the activity levels, the activity levels that constitute the time series data for the entire period, which are supplied in real time from the combustion control device 70 to the reheating monitoring device 20 and acquired by the first acquisition unit 21A. For example, the second acquisition unit 21B acquires the activity level for 30 seconds from the end timing of the pre-burn, and does not acquire the activity level otherwise, for the values of the activity levels sequentially acquired by the first acquisition unit 21A. With these configurations, it may not be necessary to store the time series data for the entire period in the storage device 13, and in that case, the load on the storage capacity of the storage device 13 is reduced.

[0078] Further, each time the second acquisition unit 11B sequentially acquires the activity levels of the second graph of the latest partial time series data, the comparison unit 11C derives the degree of deviation (malfunction score Em), and each time the degree of deviation is derived, the derived degree of deviation is sequentially additionally displayed on the display 24, so that a graph of the time change of the degree of deviation (that is, a graph of the malfunction score time series data E) may be drawn in real time. Thereby, as the combustion sequence progresses, the malfunction score time series data E is sequentially drawn. Further, the comparison unit 11C may sequentially draw the latest partial time series data Y and the malfunction score time series data E in real time as the combustion sequence progresses. By doing so, the user can follow the malfunction score Em etc. in real time.

[0079] (Modification Example 6) The first acquisition unit 21A may acquire time-series data indicating temporal changes such as air flow rate, fuel gas flow rate, furnace temperature, and pressure, which are appropriately measured by various sensors provided in the combustion control device 71 for the combustion device 30. In this case, for example, when the user designates a concerning part on the graph of the malfunction score time-series data using the operation device 25, the comparison unit 21C may display the temporal changes in air flow rate, fuel gas flow rate, furnace temperature, pressure, etc. for a certain period before and after that part. Thereby, the user can accurately detect signs of abnormality in the combustion device 30 and perform appropriate maintenance on the combustion device 30, enabling efficient operation of the combustion device 30.

[0080] (Modification Example 7) The comparison unit 21C may store a plurality of malfunction score time-series data in the storage device 23 and output a graph obtained by associating and graphing them (for example, a graph in which graphs of each malfunction score time-series data are superimposed and displayed on the same plane). Thereby, the user can grasp whether the malfunction score is transient or gradually increasing due to clock degradation or the like. Thereby, the user can grasp places where the malfunction score is likely to increase.

[0081] (Modification Example 8) The activity of the flame may be indicated by the number of discharges per unit time of the discharge occurring between the electrodes of the discharge tube 45A of the flame detector 45. When the activity of the flame is high, for example, when the ultraviolet intensity is high, the number of discharges per unit time increases. That is, the increase in the number of discharges corresponds to the increase in the voltage value of the frame voltage described above. Note that the number of discharges also increases in the case of false discharges. In such a case, it is advisable to provide the combustion device 30 with a counting unit that counts the number of discharges and a measuring unit that measures the counting period.

[0082] (Modification Example 9) The hardware configuration of the heating malfunction monitoring device 20 is arbitrary. The heating malfunction monitoring device 20 may be configured as a gateway to which the combustion control device 70 and other devices are connected. At least a part of the first acquisition unit 21A, the second acquisition unit 21B, and the comparison unit 21C may be constituted by various logic circuits such as an ASIC (Application Specific Integrated Circuit) and an FPGA (Field-Programmable Gate Array). At least a part of the units 21A to 21C may be provided in the combustion control device 71. The heating malfunction monitoring device 20 may be a server computer, a cloud computer, or the like. The output destination of the comparison result such as the malfunction score time series data and the estimation result may be a display such as a user terminal. The output destination of the comparison result may be a printer, a storage medium, a network, another computer, or the like. Each device such as the heating malfunction monitoring device 20 includes a system in which the components of the device are grouped in one housing and a system in which the components of the device are separately housed in a plurality of housings. The combustion monitoring program may be stored in a computer-readable non-transitory storage medium such as the storage device 23.

[0083] (Modification Example 10) The flame detector 45 may take in electromagnetic waves from the flame through a window provided in the combustion furnace 41. In this case, the window provided in the combustion furnace 41 is soiled by soot or the like, causing the combustion device 30 to malfunction. That is, the soiling of the window 45B of the flame detector 45 replaces the soiling of the window of the combustion furnace 41. The flame detector 45 may be fitted into the through-hole of the combustion furnace 41 from the outside. In this case, the window of the combustion furnace 41 may be constituted by the window 45B of the flame detector 45.

[0084] (Modification Example 11) The present invention is generally applicable to the technology of heat control monitoring for monitoring state quantities of heat control such as heating or cooling executed according to a heat control process such as the above combustion sequence. The heat control process may be composed of a plurality of sub-processes such as the above sub-sequences. The heat control monitoring device 20 may monitor, for example, the state quantity of heating by an electric heater or the like. The heat control monitoring device 20 may monitor, for example, the state quantity of cooling by a refrigerator or the like. As the state quantity, any type of quantity for detecting a malfunction of heat control is adopted. The state quantity may be, in addition to the activity of the above flame, other physical quantities (air flow rate, fuel gas flow rate, furnace body temperature, pressure, etc.) detected by various sensors, an operation quantity input to a heat control device controlled by feedback, and the like. The entire period time series data may be, for example, time series data indicating the time change of the state quantity of the heat control in at least a part of the entire period of the heat control process. The partial time series data may be, for example, a part of the entire period time series data, that is, time series data indicating the time change of the state quantity of the heat control in a partial period of the entire period.

[0085] (Heat control monitoring method) By the processing executed by the heat control monitoring device 20, acquisition of entire period time series data, extraction of partial time series data, comparison of partial time series data, for example, comparison of reference partial time series data X and the latest partial time series data Y, generation and output of malfunction score time series data E, etc. are performed. However, at least a part of the method may be performed by something or someone other than the heat control monitoring device 20.

[0086] (Scope of the present invention) The present invention has been described above with reference to the embodiments and modification examples, but the present invention is not limited to the above embodiments and modification examples. For example, the present invention includes various changes to the above embodiments and modification examples that can be understood by those skilled in the art within the scope of the technical idea of the present invention. Each configuration described in the above embodiments and modification examples can be appropriately combined within a non-contradictory range.

Explanation of reference numerals

[0087] 10… Heating system, 20… Heat adjustment monitoring device, 21… Processor, 21A… First acquisition unit, 21B… Second acquisition unit, 21C…… Comparison unit, 23… Storage device, 24… Display, 25… Operating device, 30… Combustion device, 40… Combustion equipment, 42… Main burner, 43… Pilot burner, 44… Ignition device, 45… Flame detector, window… 45B, 50… Air supply system, 60… Fuel supply system, 70… Combustion control device.

Claims

1. A heat conditioning monitoring device that monitors the state quantity of heat conditioning performed by a predetermined heat conditioning process, a first acquisition unit configured to acquire a plurality of full-period time series data each indicating a temporal change in the state quantity of the heat conditioning during at least a part of the entire period of the heat conditioning process, a second acquisition unit configured to acquire a plurality of partial time series data by extracting, from each of the plurality of full-period time series data, partial time series data indicating a temporal change in the state quantity of the heat conditioning during a partial period of the entire period, a comparison unit configured to compare the plurality of partial time series data and output a comparison result, and the comparison unit is configured to compare a plurality of reference partial time series data serving as a reference among the plurality of partial time series data with partial time series data that are newer than the plurality of reference partial time series data among the plurality of partial time series data, and generate deviation time series data indicating the degree of deviation of the state quantity of the new partial time series data with respect to the distribution of the state quantities of the plurality of reference partial time series data at each time point corresponding to each other in time series. Heat conditioning monitoring device.

2. The plurality of full-period time series data are stored in a storage unit, and the partial period can be set by a user after the plurality of full-period time series data are stored in the storage unit. The heat conditioning monitoring device according to claim 1.

3. The first acquisition unit is configured to acquire each of the plurality of full-period time series data by sequentially acquiring the state quantity of the heat conditioning in real time over the entire period, and the second acquisition unit is configured to extract the partial time series data by sequentially acquiring in real time the state quantity of the heat conditioning that the first acquisition unit sequentially acquires in real time during the partial period of the entire period. The heat conditioning monitoring device according to claim 1.

4. A heat conditioning monitoring device that monitors the state quantity of heat conditioning performed by a predetermined heat conditioning process, a first acquisition unit configured to acquire a plurality of full-period time series data each indicating a temporal change in the state quantity of the heat conditioning during at least a part of the entire period of the heat conditioning process, a second acquisition unit configured to acquire a plurality of partial time series data by extracting, from each of the plurality of full-period time series data, partial time series data indicating a temporal change in the state quantity of the heat conditioning during a partial period of the entire period, A comparison unit configured to compare a plurality of partial time series data and output a comparison result; The partial period is discrete in time series and is composed of a plurality of periods of the same length among the plurality of partial time series data. A heat regulation monitoring device.

5. The first acquisition unit is configured to acquire each of the plurality of full-period time series data by sequentially acquiring the state quantity of the heat regulation in real time over the entire period. The second acquisition unit is configured to extract the partial time series data by sequentially acquiring in real time the state quantity of the heat regulation that the first acquisition unit sequentially acquires in real time during the partial period of the entire period. The comparison unit Derives the degree of deviation each time the second acquisition unit sequentially acquires each state quantity of the new partial time series data. By sequentially adding and displaying the derived degree of deviation on the display unit each time the degree of deviation is derived, a graph of the time change of the degree of deviation is drawn in real time. The heat regulation monitoring device according to claim 1.

6. The comparison unit is configured to display on the display unit by associating the graph of the new partial time series data with the graph of the deviation time series data. The heat regulation monitoring device according to claim 1 or 5.

7. The comparison unit is configured to estimate the presence or absence of a malfunction of the heat regulation device and the type thereof when there is a malfunction based on the deviation time series data, and output an estimation result. The heat regulation monitoring device according to any one of claims 1, 5, or 6.

8. The comparison unit is configured to output, as the comparison result, an image in which a graph based on reference partial time series data serving as a reference among the plurality of partial time series data and a graph of partial time series data that is newer than the reference partial time series data among the plurality of partial time series data are associated with each other. The heat regulation monitoring device according to any one of claims 1 to 7.

9. The heat regulation process is composed of a plurality of sub-processes. The partial period includes one or more periods based on the start or end timing of one of the plurality of sub-processes. The heat regulation monitoring device according to any one of claims 1 to 8.

10. A heating monitoring program that causes a computer that monitors the state quantity of heating performed by a predetermined heating process to function as the heating monitoring device according to claim 1 or 4 when executed on the computer.

11. A heating monitoring method for monitoring the state quantity of heating performed by a predetermined heating process, comprising: a first acquisition step of acquiring a plurality of full-period time series data each showing the time change of the state quantity of the heating in at least a part of the entire period of the heating process; a second acquisition step of acquiring a plurality of partial time series data by extracting partial time series data showing the time change of the state quantity of the heating in a partial period of the entire period from each of the plurality of full-period time series data; a comparison step of comparing the plurality of partial time series data and outputting a comparison result, wherein in the comparison step, a plurality of reference partial time series data serving as a reference among the plurality of partial time series data are compared with partial time series data that are newer than the plurality of reference partial time series data among the plurality of partial time series data, and deviation time series data showing the degree of deviation of the state quantity of the new partial time series data with respect to the distribution of each state quantity of the plurality of reference partial time series data at each time point corresponding to each other in time series is generated; Heating monitoring method.

12. A heating monitoring method for monitoring the state quantity of heating performed by a predetermined heating process, comprising: a first acquisition step of acquiring a plurality of full-period time series data each showing the time change of the state quantity of the heating in at least a part of the entire period of the heating process; a second acquisition step of acquiring a plurality of partial time series data by extracting partial time series data showing the time change of the state quantity of the heating in a partial period of the entire period from each of the plurality of full-period time series data; a comparison step of comparing the plurality of partial time series data and outputting a comparison result, wherein the partial periods are discrete in time series and are composed of a plurality of periods of the same length among the plurality of partial time series data; Heating monitoring method.

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