Deterioration diagnostic device, deterioration diagnostic system, and deterioration diagnostic method

Abstract

To provide a deterioration diagnostic device, a deterioration diagnostic system, and a deterioration diagnostic method, capable of performing deterioration diagnosis in accordance with constant indices from the past to the present, while considering the effects of changes in an operating status of an ozone generator.SOLUTION: A deterioration diagnostic device according to the present disclosure includes: a case-related information acquisition unit that acquires case-related information, including information on constant operating conditions of an ozone generator; a measurement unit that acquires measurement data indicating an operating status of the ozone generator; and a diagnostic unit that calculates a performance evaluation index indicating the performance of the ozone generator under the operating status, in accordance with the constant operating conditions, based on the case-related information and the measurement data, and diagnoses a deterioration status of the ozone generator.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to a deterioration diagnostic device, a deterioration diagnostic system, and a deterioration diagnostic method for diagnosing deterioration of a silent discharge ozone generator. [Background technology]

[0002] In silent discharge ozone generators, the efficiency of ozone generation often gradually decreases over time. For this reason, it is common to perform maintenance such as open inspection, open cleaning, part replacement, and repair at regular intervals. However, performing maintenance at regular intervals can lead to problems such as unnecessary maintenance being performed more frequently than necessary, or failures that occur due to maintenance not being completed in time. Therefore, a method has been proposed that monitors the performance of the ozone generator and issues an alarm when performance deteriorates, to notify the user of the need for maintenance.

[0003] The ozone generation efficiency used in the deterioration diagnosis of an ozone generator mainly depends on three parameters: the temperature of the cold water used to cool the ozone generator, the ozone concentration, and the power density (discharge power divided by the discharge area in the ozone generator). In order to accurately evaluate the performance of an ozone generator, it is necessary to take into consideration that these parameters change depending on the operating conditions of the ozone generator. In Patent Document 1, the power consumption rate is used as a performance evaluation index of the ozone generator, an initial value of the power consumption rate is calculated corresponding to the current water temperature, and the initial value of the power consumption rate is compared with the current value, thereby making it possible to detect a deterioration in the performance of the ozone generator even if the water temperature is different between the initial operation and the current operation. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Publication No. 8-217415 Summary of the Invention [Problem to be solved by the invention]

[0005] However, in the conventional technology, since the initial value of the performance evaluation index is calculated in correspondence with the parameter value in the current operating condition, it is only possible to compare the current state with the initial state, and there is a problem that it is difficult to diagnose deterioration according to a constant index from the past to the present.

[0006] The present disclosure has been made to solve the problems described above, and aims to provide a deterioration diagnosis device, a deterioration diagnosis system, and a deterioration diagnosis method that are capable of diagnosing deterioration according to certain indicators from the past to the present, while taking into account the effects of changes in the operating conditions of an ozone generator. [Means for solving the problem]

[0007] The deterioration diagnosis device according to the present disclosure includes a case-related information acquisition unit that acquires case-related information including information on certain operating conditions of an ozone generator, a measurement unit that acquires measurement data indicating the operating status of the ozone generator, and a diagnosis unit that calculates a performance evaluation index that indicates the performance of the ozone generator in an operating status according to the certain operating conditions based on the case-related information and the measurement data, and diagnoses the deterioration status of the ozone generator.

[0008] The deterioration diagnosis system according to the present disclosure includes an ozone generator, a case-related information acquisition unit that acquires case-related information including information on certain operating conditions of the ozone generator, a measurement unit that acquires measurement data indicating the operating status of the ozone generator, and a diagnosis unit that calculates a performance evaluation index that indicates the performance of the ozone generator in an operating status corresponding to the certain operating conditions based on the case-related information and the measurement data, and diagnoses the deterioration status of the ozone generator.

[0009] The degradation diagnosis method according to the present disclosure includes the steps of acquiring case-related information including information on certain operating conditions of an ozone generator, acquiring measurement data indicating the operating status of the ozone generator, and calculating a performance evaluation index indicating the performance of the ozone generator in the operating status according to the certain operating conditions based on the case-related information and the measurement data, and diagnosing the degradation status of the ozone generator. Effect of the Invention

[0010] According to the deterioration diagnosis device, deterioration diagnosis system, and deterioration diagnosis method disclosed herein, the performance of an ozone generator is evaluated using case-related information including certain operating conditions of the ozone generator and measurement data indicating the operating status of the ozone generator, thereby enabling deterioration diagnosis according to certain indicators from the past to the present while taking into account the effects of changes in the operating status of the ozone generator. [Brief description of the drawings]

[0011] [Figure 1] 1 is a schematic configuration diagram showing a degradation diagnosis system according to a first embodiment of the present disclosure. [Diagram 2] 1 is a schematic configuration diagram showing a hardware configuration of a degradation diagnosis device according to a first embodiment of the present disclosure. [Diagram 3] 4 is a flowchart showing a degradation diagnostic method of the degradation diagnostic device according to the first embodiment of the present disclosure. [Figure 4] 4 is a table showing the correspondence relationship between the design generation efficiency, power density, ozone concentration, and water temperature of the degradation diagnosis device according to the first embodiment of the present disclosure. [Diagram 5] 4 is a graph showing an example of a generation amount index and discharge power of the degradation diagnostic device according to the first embodiment of the present disclosure. [Figure 6] FIG. 11 is a schematic configuration diagram showing a degradation diagnosis device according to a second embodiment of the present disclosure. [Figure 7] 13 is a graph showing an example of a generation amount index and discharge power of a degradation diagnostic device according to a second embodiment of the present disclosure. [Figure 8] 13 is a flowchart showing a degradation diagnostic method of a degradation diagnostic device according to a third embodiment of the present disclosure. [Figure 9] 13 is a flowchart showing a degradation diagnostic method of a degradation diagnostic device according to embodiment 4 of the present disclosure. [Figure 10] 10 is a flowchart showing a subroutine in a degradation diagnostic method for a degradation diagnostic device according to embodiment 4 of the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] Embodiment 1 Fig. 1 is a schematic configuration diagram showing a degradation diagnosis system according to a first embodiment of the present disclosure. As shown in Fig. 1, a degradation diagnosis system 100 includes an ozone generator 10 and a degradation diagnosis device 1. The degradation diagnosis device 1 of the present disclosure includes a case-related information acquisition unit 2, a measurement unit 4, and a diagnosis unit 5. Here, Fig. 1 shows an example in which the degradation diagnosis device 1 includes a case-specific information calculation unit 3, but the case-specific information calculation unit 3 may be included as a function in the case-related information acquisition unit 2, or may be included as a function in the diagnosis unit 5.

[0013] The case-related information acquisition unit 2 acquires case-related information 12, which is determined by a case in which the ozone generator 10 is used and includes certain operating conditions of the ozone generator 10. The certain operating conditions of the ozone generator 10 are predetermined conditions that are uniquely determined when the ozone generator 10 is introduced, and are, for example, predetermined values ​​such as the rated conditions of the ozone generator 10. The case-specific information calculation unit 3 calculates case-specific information 13 based on the case-related information. The measurement unit 4 acquires measurement data 14 indicating the operating status of the ozone generator 10. At this time, the operating status of the ozone generator 10 indicates the transition of each piece of data during operation of the ozone generator 10 from the past to the present, for example, from the initial value to the current value of data that can be acquired during operation of the ozone generator 10. The diagnosis unit 5 uses the case-related information 12 and the measurement data 14 to calculate a performance evaluation index that indicates the performance of the ozone generator in the current operating state or the operating state at the time of the deterioration diagnosis according to certain operating conditions of the ozone generator 10, and diagnoses the deterioration state of the ozone generator based on the value of the performance evaluation index according to the operating state. This deterioration state indicates the aging change of the performance deterioration of the ozone generator 10 and the degree of the performance deterioration.

[0014] The ozone generator 10 is, for example, a general silent discharge type ozone generator. When a raw material gas containing oxygen is input into the ozone generator 10, power is supplied to the ozone generator 10 from a power supply device (not shown). This causes silent discharge inside the ozone generator 10, and ozone is generated from the oxygen in the raw material gas, which is then discharged as an ozone-containing gas. Since heat is generated by the discharge at this time, cold water for cooling the ozone generator 10 passes through the ozone generator 10. In general, the cold water flow rate is set for the ozone generator 10 so that the cold water outlet temperature is about 3 to 5° C. higher than the cold water inlet temperature.

[0015] The amount of ozone generated is expressed as the product of the ozone concentration and the raw material gas flow rate. The rated ozone generation amount is the highest amount of ozone generated that is expected in the operation of the ozone generator 10. Hereinafter, the ozone concentration and raw material gas flow rate required to obtain the rated ozone generation amount are referred to as the rated ozone concentration and the rated raw material gas flow rate.

[0016] In normal operation, the ozone generator 10 is often operated with the ozone generation rate lower than the rated ozone generation rate. Hereinafter, such operation is called partial load operation. There are two types of control methods for partial load operation: a constant concentration / varying raw gas flow rate method, and a constant raw gas flow rate / varying concentration method.

[0017] The constant concentration / varying feed gas flow rate method is a method of lowering the feed gas flow rate while keeping the ozone concentration at the rated ozone concentration. This method is often adopted when liquid oxygen is used as the feedstock, because it can save on the feed gas flow rate.

[0018] The constant raw gas flow rate / varying concentration method is a method for lowering the ozone concentration while keeping the raw gas flow rate at the rated raw gas flow rate. This method is often adopted when the raw gas cost (including the electricity cost for production) is relatively cheap and reducing the raw gas flow rate does not contribute much to reducing the raw gas cost, or when the raw material supply device is structurally difficult to follow arbitrary changes in the raw material gas flow rate. Specifically, this applies when the raw material gas for the ozone generator 10 is air raw material or a PSA raw material. When the raw material gas is a VPSA raw material, both constant concentration / varying raw material gas flow rate and constant raw material gas flow rate / varying concentration are adopted.

[0019] In the first embodiment, a case will be described in which partial load operation is performed with a control method of constant concentration and varying raw gas flow rate.

[0020] FIG. 2 is a schematic diagram showing a hardware configuration of the degradation diagnosis device according to the first embodiment of the present disclosure. The computer 22 includes, for example, a CPU (Central Processing Unit) 23, a main storage device 24, and an auxiliary storage device 25. For example, the main storage device 24 may be a RAM, and the auxiliary storage device 25 may be a storage medium such as a hard disk. An input device 21 and an output device 28 are provided outside the computer 22. The input device 21 may be, for example, a mouse or a keyboard. The output device 28 may be, for example, a display monitor that displays an output result from the computer 22. As shown in FIG. 2, the computer 22 is connected to an external storage device 27 via a network 26, and obtains information required for calculation from an external recording medium. The computer 22 may be configured to store the calculation result in an external storage medium.

[0021] The case-related information acquisition unit 2, the case-specific information calculation unit 3, the measurement unit 4 and the diagnosis unit 5 are realized by the CPU 23 and the main storage device 24 as internal calculation processes of the computer 22. That is, each process in the diagnosis unit 5 etc. is realized by the CPU 23, which is a processor, executing a program deployed on the main storage device 24, which is a memory. The CPU 23 reads data on the main storage device 24, performs each process, and stores the results in the main storage device 24.

[0022] 3 is a flowchart showing a degradation diagnosis method of the degradation diagnosis device according to embodiment 1 of the present disclosure. A method for diagnosing degradation of ozone generator 10 by degradation diagnosis device 1 will be described below with reference to FIG.

[0023] First, in step S101, the project-related information acquisition unit 2 executes a process of acquiring project-related information 12. The project-related information 12 is, for example, the structural specifications and certain operating conditions of the ozone generator 10 used in the target project to which the degradation diagnosis system is applied. The project-related information is uniquely determined once the target project is determined. Projects do not need to be limited to those determined for each plant or each construction project. For example, if two types of ozone generators A and B exist in a project called A Water Purification Plant B Phase Construction, there may be two projects called A Water Purification Plant B Phase Construction A and A Water Purification Plant B Phase Construction B.

[0024] The case-related information 12 includes, for example, the raw material type, the rated ozone generation rate Gr [kg / h], the rated ozone concentration Cr and its unit (the unit is [g / m 3 These include the rated cold water temperature tr [℃], the rated cold water flow rate fw [L / min], the number of electrodes p in the ozone generator, and the maximum discharge power Emax [kW]. The raw material type includes, for example, air raw material, liquid oxygen raw material, (V)PSA raw material, etc. The rated cold water temperature is the rated value of the temperature at the raw material inlet of the ozone generator.

[0025] In this embodiment, it is assumed that the ozone generator 10 is operated at a partial load with a control method of constant concentration and varying raw material gas flow rate. Therefore, the project-related information 12 includes the rated ozone concentration Cr but does not include the rated raw material gas flow rate. On the other hand, for example, when the ozone generator 10 is operated at a partial load with a control method of constant raw material gas flow rate and varying concentration, the project-related information 12 may include the rated raw material gas flow rate but not the rated ozone concentration Cr. Furthermore, the project-related information 12 may include information on the control method for partial load operation.

[0026] In the description of this embodiment, the units of the rated ozone concentration are described in principle in a manner that corresponds to both, but when narrowing down to one example, an example in which [wt%] is selected will be shown.

[0027] Next, in step S102, the case-specific information calculation unit 3 executes a process of calculating case-specific information 13 based on the case-related information 12. The case-specific information 13 may be, for example, a discharge area S [cm 2 ], rated feed gas flow rate fr [m 3 / h(N)], maximum power density D[W / cm 2 ], maximum condition design generation efficiency emax [kWh / kg], etc. In this example, the project-specific information 13 is calculated from the project-related information 12, but the project-specific information 13 may be input in advance as the project-related information 12.

[0028] Discharge area S[cm 2 ] is calculated from the number of electrodes p of the ozone generator included in the case-related information 12, and the electrode diameter r [cm] and electrode discharge length L [cm], which are constants specific to the ozone generator, using equation (1).

[0029]

number

[0030] When there are a plurality of electrode discharge lengths L [cm], the information on these lengths may also be used as the case-related information 12.

[0031] In addition, the rated feed gas flow rate fr (unit: [m 3 / h (N)] or [kg / h]) is calculated by dividing the rated ozone generation rate Gr [kg / h] and the rated ozone concentration Cr (unit: [g / m 3 (N)] or [wt%]) as shown in formula (2) or formula (3).

[0032]

number

[0033] As shown in equation (3), if the unit of the rated ozone concentration is selected as [wt%], the rated feed gas flow rate is considered to be in [kg / h]. In that case, the feed gas flow meter at the site is in [kg / h], and the measurement data is also in [kg / h].

[0034] In addition, the maximum power density Dmax [W / cm 2 ] is the maximum discharge power Emax [kW] included in the project-related information 12 and the discharge area S [cm 2 ] can be used to obtain the formula (4).

[0035]

number

[0036] The maximum power density Dmax may be included in the case-related information 12.

[0037] FIG. 4 is a table showing the correspondence relationship between the design generation efficiency, power density, ozone concentration, and water temperature of the degradation diagnosis device according to the first embodiment of the present disclosure. The design generation efficiency is the ozone generation efficiency of the ozone generator 10, and generally varies depending on three parameters, ozone concentration, cold water inlet temperature, and power density. In the degradation diagnosis device 1 of the present disclosure, these characteristics are acquired in advance by a type test or the like of the ozone generator 10, and the design generation efficiency for the three parameters, ozone concentration, cold water inlet temperature, and power density, is stored in advance as a database. In the upper table of FIG. 4, as an example, the power density is 0.01 [W / cm 2 The table shows the design generation efficiency of the ozone generator 10 with respect to the ozone concentration and the cold water inlet temperature when the power density is 0.02 [W / cm]. The horizontal direction (column direction) represents the cold water inlet temperature, and the vertical direction (row direction) represents the difference in ozone concentration, and the generation efficiency (***) under that condition is recorded at each intersection. Although not shown in FIG. 4, if a similar table were created with a power density of 0.02 [W / cm], 2 ], 0.03 [W / cm 2 ]... etc., up to the maximum possible power density of 0.01 [W / cm 2By using a database like that shown in Figure 4, the design generation efficiency can be obtained for any ozone concentration, chilled water inlet temperature, and power density.

[0038] The divisions of the database table do not have to be as shown in FIG. 4. The rated ozone concentration and rated chilled water temperature rarely have fractions, but since FIG. 4 is also used for the measurement data 14 described later, the ozone concentration and chilled water temperature may have fractions. The table would be more accurate if the divisions were finer, but the database volume would be enormous, so the divisions of the table may be coarse and the fractions may be obtained by interpolating the values ​​before and after the table. Even if the divisions of the power density are coarse, the design generation efficiency at the concentration and water temperature can be calculated by linear interpolation after calculating each of the two power densities, the most recent upper and the most recent lower, respectively. In addition, since the generation efficiency hardly changes when the power density is below a certain value, the water temperature is below a certain value, and the concentration is below a certain value, the table may be omitted as the generation efficiency is the same below the above certain value.

[0039] Furthermore, in Figure 4, the unit of ozone concentration is assumed to be [wt%], but the unit of ozone concentration is [g / m 3 (N)], [g / m 3 (N)] units may be provided, or each time [g / m 3 (N)] to [wt%], and then use a table showing [wt%] to convert [g / m 3 (N)] units may be converted back to units.

[0040] The unit of design generation efficiency is [kWh / kg] and is defined as "the discharge power (output power of the power supply) required to produce 1 kg of ozone," so the smaller the number, the more efficient the ozone generation.

[0041] The maximum condition design generation efficiency emax is an ozone generation efficiency calculated using the rated ozone concentration and rated chilled water temperature included in the project-related information 12 and the maximum power density included in the project-specific information 13.

[0042] Next, in step S103, the measurement unit 4 executes a process of acquiring measurement data 14 indicating the operating status of the ozone generator 10. The measurement data 14 includes, for example, at least one of the discharge power E, the ozone concentration C, the ozone raw material gas flow rate f, and the cold water temperature of the ozone generator 10. Here, the cold water temperature of the ozone generator 10 refers to the inlet temperature and outlet temperature of the ozone generator 10, which are defined as the cold water inlet temperature ti and the cold water outlet temperature to, respectively. In the degradation diagnosis device 1 of this embodiment, the discharge power E (output power of the power supply device) [kW], the ozone concentration C (units are [wt%] or [g / m 3 (N)]), raw gas flow rate f (unit: [wt%] or [m 3 / h(N)]), chilled water inlet temperature ti [°C], etc. are assumed to have been acquired. The measurement data 14 at this time may be data in the smallest unit of sampling of on-site measurement data, but may also be thinned out appropriately, or an average value for several seconds, several minutes, or an hour may be calculated to obtain one set of data every several seconds, several minutes, or an hour. The measurement data 14 is assumed to input the first data of the target evaluation period, and to input up to the last data of the target evaluation period by repeating a loop up to step S107 described later. The evaluation target period, etc. may be determined in advance by being input separately, etc.

[0043] Next, in step S104, the diagnostic unit 5 uses the measurement data 14 to obtain the measured ozone generation amount Gm and the measured generation efficiency em of the ozone generator 10.

[0044] The measured ozone generation amount Gm is a value calculated from the raw material gas flow rate f and ozone concentration C included in the measurement data 14, and is obtained as shown in formula (5) and formula (6). The measured generation efficiency em is a value calculated using the discharge power E included in the measurement data 14 and the ozone generation amount Gm calculated by formula (5) or formula (6), and is obtained as shown in formula (7).

[0045]

number

[0046] In addition, the unit of the rated ozone concentration in formula (5) is [g / m 3 (N)], and equation (6) shows the case where the unit of the rated ozone concentration is [wt%].

[0047] Next, in step S105, the diagnosis unit 5 calculates the measured power density Dm of the ozone generator 10 using the measurement data 14. The measured power density Dm is a value calculated using the discharge power E included in the measurement data 14 and the discharge area S included in the case-specific information 13, and is calculated as shown in formula (8).

[0048]

number

[0049] In step S106, first, the measurement condition design generation efficiency em' is calculated in the same manner as the maximum condition design generation efficiency emax in step 102. At this time, the ozone concentration and the cold water inlet temperature are the values ​​of the measurement data 14, and the power density is the measured power density Dm calculated by equation (8). The measurement condition design generation efficiency em' can be calculated by referring to these values ​​and the corresponding values ​​in a database such as that shown in FIG.

[0050] Next, in step S106, an estimated value of the maximum ozone generation amount (estimated maximum ozone generation amount) at the rated ozone concentration and rated chilled water inlet temperature is calculated. The generation efficiency at this time is called the estimated generation efficiency. The estimated generation efficiency e can be calculated as shown in formula (9) by using the measurement condition design generation efficiency em', the maximum condition design generation efficiency emax included in the project-specific information 13, and the measured generation efficiency em calculated in step S104.

[0051]

number

[0052] Here, the design generation efficiency em' under measurement conditions is the design generation efficiency under the conditions of ozone concentration, cold water inlet temperature, and power density measured at a certain moment on-site. On the other hand, what is desired is the maximum amount of ozone generated at a certain moment by, for example, a deteriorated ozone generator under the conditions of rated ozone concentration and rated cold water (inlet) temperature. Since power supply devices generally do not deteriorate much, if we assume that the maximum discharge power that can be generated does not change over time, it is sufficient to know the generation efficiency at the maximum power density, which is designated as the maximum condition design generation efficiency emax.

[0053] In formula (9), the ratio of the maximum condition design generation efficiency emax to the measured condition design generation efficiency em' represents the rate of change (magnification factor) due to differences in ozone concentration, cold water inlet temperature, and power density (each of the three conditions is the difference between a measured value at a certain moment on-site and a constant operating condition), and by multiplying this ratio by the measured generation efficiency, the estimated generation efficiency of the ozone generator 10 under the desired condition (constant operating condition) can be obtained. The estimated maximum ozone generation amount G [kg / h] of the ozone generator 10 can be obtained as shown in formula (10) using this estimated generation efficiency e and the maximum discharge power Emax included in the case-related information 12.

[0054]

number

[0055] Next, in step S107, the diagnosis unit 5 calculates a performance evaluation index corresponding to certain operating conditions of the ozone generator 10, using the case-related information 12, the case-specific information 13, and the measurement data 14. If the case-specific information 13 is input as the case-related information 12, in step S107, the diagnosis unit 5 calculates a performance evaluation index corresponding to certain operating conditions of the ozone generator 10, using the case-related information 12 and the measurement data 14. On the other hand, instead of inputting the case-specific information 13 as the case-related information 12, the diagnosis unit 5 may calculate the case-specific information 13. Here, a calculation method of a generation amount index α [%] calculated from an estimated maximum ozone generation amount value G as a performance evaluation index and a rated ozone generation amount Gr included in the case-related information 12 is shown in the following formula (11).

[0056]

number

[0057] In this embodiment, the performance evaluation index is calculated as the generation amount index α, but the performance evaluation index may be an estimated value of the maximum ozone generation amount of the ozone generator, the ozone generation efficiency, the power consumption unit, etc., or may be a standardized value. Here, the power consumption unit [kWh / kg] is defined as the ozone generation efficiency [kWh / kg] divided by the "power supply efficiency [%] / 100", or in other words, "the input power of the power supply device required to produce 1 kg of ozone."

[0058] Next, in step S108, the diagnosis unit 5 determines whether input and calculation are complete up to the last data of the evaluation period. The evaluation period is usually the last (latest) data for which data exists, but may be set arbitrarily by the user. Until calculations for this evaluation period are completed, the degradation diagnosis device 1 of the present disclosure repeats steps S103 to S107 for each data.

[0059] FIG. 5 is a graph showing an example of the generation amount index and discharge power of the deterioration diagnosis device according to the first embodiment of the present disclosure. In step S109, the diagnosis unit 5 plots a graph with the horizontal axis representing time (year, month, and day) and the vertical axis representing the generation amount index, as shown in FIG. 5, and outputs the graph to a screen or the like such as the output device 28. At this time, the vertical axis may be simultaneously output with the discharge power E of the measurement data 14, as shown in FIG. 5. For example, in the state of FIG. 5, at the present time (the rightmost point of the graph), the generation amount index is about 95%, which is below 100%, and therefore it is found that the rated ozone generation amount cannot be obtained even if the maximum power is input under the conditions of the rated water temperature and rated concentration. If operation at the rated ozone generation amount is expected in the near future, it is difficult for the ozone generator 10 to operate at the rated ozone generation amount, and the ozone generator 10 is in a state in which a treatment such as maintenance is required. By performing the calculation in this manner, the deterioration state of the ozone generator 10 can be diagnosed by the performance evaluation index.

[0060] As described above, the degradation diagnosis device 1 of the present disclosure includes the case-related information acquisition unit 2, the measurement unit 4, and the diagnosis unit 5. Here, the degradation diagnosis device 1 of the present embodiment is shown as including the case-specific information calculation unit 3, but the function of the case-specific information calculation unit 3 may be included in the case-related information acquisition unit 2. The degradation diagnosis system 100 includes the ozone generator 10 and the degradation diagnosis device 1. In this case, the degradation diagnosis system 100 may include a monitoring and control device (not shown) that monitors the operating status of the ozone generator 10 and controls the ozone generator 10. Alternatively, the degradation diagnosis device 1 or the degradation diagnosis system 100 may be incorporated into a monitoring and control device that monitors and controls the entire ozone system, or may be incorporated into a monitoring and control system that monitors and controls the entire water purification plant, factory, etc. On the other hand, the degradation diagnosis device 1 may be located far away from the ozone generator 10, and in that case, the measurement data 14 of the ozone generator 10 may be exchanged online or offline.

[0061] The degradation diagnosis device 1, degradation diagnosis system 100, and degradation diagnosis method disclosed herein use the case-related information 12 and measurement data 14 to calculate a performance evaluation index that evaluates the performance of the ozone generator 10 in the current operating state from the viewpoint of how it will be when operated under certain operating conditions, and diagnoses the degradation state of the ozone generator 10 using the performance evaluation index. This enables degradation diagnosis according to a certain index from the past to the present, while taking into account the influence of changes in the operating state of the ozone generator.

[0062] In addition, as mentioned above, by calculating the performance evaluation index when operating under constant operating conditions while taking into consideration the operating method in the case of constant concentration and varying raw gas flow rate operation, it becomes possible to compare the performance of ozone generators under the same conditions even in situations where the operating conditions are not necessarily rated, such as on-site operation, and are constantly changing, and the deterioration over time can be seen at a glance. As a result, it becomes much easier to determine the timing of maintenance.

[0063] In addition, in the operation with constant concentration and varying raw gas flow rate, the rated ozone concentration and the rated cold water temperature are adopted as constant operating conditions. Therefore, even in a situation where the amount of ozone generated is large because the local water temperature is low and the ozone generation efficiency is high, the performance at the rated high water temperature can be estimated, and there is an effect of high practicality.

[0064] In addition, when calculating the ozone generation efficiency, two or more (all three in the above embodiment) of the three parameters that affect the ozone generation efficiency, namely, power density, ozone concentration, and cold water temperature, are used to determine the ozone generation efficiency, which has the effect of enabling a more accurate evaluation.

[0065] In addition, in general, in the initial design, an ozone generator is designed to generate more than the rated ozone generation amount when the maximum power is input, rather than just at the rated ozone generation amount. In this embodiment, the ozone generation amount at the maximum power density based on the maximum discharge power is used as the index, not the rated power, so that it is possible to determine how the performance has changed, including the so-called reserve capacity that can generate more than the rated ozone generation amount initially held, and it is possible to perform a practical evaluation suited to actual operation. This is why the generation amount index exceeds 100% at the initial stage (the point at the left end of the graph) in Figure 5.

[0066] In addition, in this embodiment, when diagnosing the deterioration of the ozone generator 10, a generation amount index, which is an index obtained by normalizing the estimated maximum ozone generation amount by the rated ozone generation amount, is used, but the estimated maximum ozone generation amount before normalization may also be used. Since the maximum discharge power [kW] is fixed depending on the case, the estimated generation efficiency used to calculate the estimated maximum ozone generation amount may also be used. Furthermore, since the power supply efficiency when the maximum discharge power is output is constant and uniquely determined, an estimated power consumption rate may be calculated using the estimated generation efficiency and power supply efficiency, and the same effect as the generation amount index is achieved even when these indices are used.

[0067] In addition, the flow rate of the raw gas and the flow rate of the ozone-containing gas are the same when measured in kg / h, but are expressed in m 3In the present embodiment, for simplicity, the amount of ozone generated is calculated using the flow rate of the raw gas. However, more accurately, the amount of ozone generated is calculated using the flow rate of the ozone-containing gas [m 3 / h(N)] and ozone concentration [g / m 3 (N)], and the value is determined by the product of the raw gas flow rate [m 3 / h(N)] to the ozone-containing gas flow rate [m 3 / h(N)] to calculate the performance evaluation index.

[0068] Embodiment 2 In the second embodiment, the same components as those in the first embodiment of the present disclosure are designated by the same reference numerals, and the description of the same or corresponding parts is omitted. Hereinafter, a degradation diagnosis device 1b and a degradation diagnosis system 100b according to the second embodiment will be described with reference to the drawings.

[0069] Fig. 6 is a schematic configuration diagram showing a degradation diagnosis device according to embodiment 2 of the present disclosure. As shown in Fig. 6, degradation diagnosis device 1b includes a determination unit 6 in addition to the configuration of degradation diagnosis device 1. In the following, description of degradation diagnosis device 1b that overlaps with embodiment 1 will be omitted, and differences will be mainly described.

[0070] The determination unit 6 determines the timing of maintenance of the ozone generator 10 by using the value of the performance evaluation index calculated by the diagnosis unit 5, the graph of Fig. 5, etc. As a method of determining the timing of maintenance of the ozone generator 10 by using the value of the generation amount index α, for example, there is a method in which the determination unit 6 notifies that maintenance is necessary when it is diagnosed that the rated ozone generation amount cannot be obtained from the value of the generation amount index α as shown in Fig. 5. In this case, by setting a threshold value for the performance evaluation index to determine whether maintenance is necessary, it is possible to make the determination by the operator easier and to automate the determination by the determination unit 6. Here, the maintenance work in this disclosure refers to open inspection, open cleaning, part replacement, repair, etc. that occur at a certain cycle.

[0071] The judgment unit 6 may also have a function of judging the timing of maintenance of the ozone generator 10 by using a load level, which is information indicating the load state of the ozone generator 10, and a performance evaluation index. The load level may be the discharge power E, the power supply device input power Ei, the output command value of the power supply device, etc. When viewed from the power supply device, the discharge power E, which corresponds to the output power, the power supply device input power Ei [kW], and the power supply efficiency er [%] have the relationship of the following formula (12).

[0072]

number

[0073] According to formula (12), for example, when the input power is obtained as the value of the measurement data 14, the input power can be regarded as the load level. If this load level is large, the load is high, and if it is small, the load is low. By simultaneously displaying such an index representing the load, it is highly possible to find a tendency that, for example, the performance degradation (decrease in the generation amount index) is faster during a period of relatively high load than during a period of low load, although this is not shown in the figure. Therefore, by observing the aging change in performance degradation including the load, it is possible to make judgments such as "high load is expected in the future, so early maintenance is necessary even if the performance degradation threshold has not been reached at present" or "low load is expected in the future, so the performance degradation threshold has been reached but maintenance is not necessary immediately". Such advanced judgments can be easily made by a human being by looking at a graph (such as FIG. 5) displayed by the diagnosis unit 5, for example, or can be made automatically by the judgment unit 6 using AI (artificial intelligence) or the like. In addition, by using a value obtained by accumulating the load level, it is possible to grasp the past usage status closer to the actual situation than a simple accumulated value of the operating time.

[0074] FIG. 7 is a graph showing an example of the generation amount index and discharge power of the deterioration diagnosis device according to the second embodiment of the present disclosure. The judgment unit 6 predicts the future performance evaluation index of the ozone generator 10 based on a value corresponding to the operating condition of the performance evaluation index, and judges the timing of maintenance of the ozone generator 10. In this embodiment, a case where a prediction is made for the generation amount index as an example of the performance evaluation index will be described. For example, as shown in FIG. 7, the judgment unit 6 first adds an approximation curve to the graph showing the aging change of the generation amount index in FIG. 5. The approximation curve is selected from linear approximation, quadratic function, cubic function, ..., etc., and the cubic function is selected here. Next, in FIG. 7, the future generation amount index is predicted by extending the approximation curve showing the trend of the generation amount index up to the present time. Therefore, it is possible to make a future prediction assuming that the performance deterioration trend will continue. Therefore, for example, in a case where the next maintenance time is decided, it is possible to predict how much the performance will deteriorate by the next maintenance time by extending the approximation curve to that time.

[0075] In order to set the approximation curve correctly, for example, during periods when operation was stopped, in other words, periods during which the generation index cannot be calculated, the values ​​are left blank instead of being set to zero. Furthermore, in Figure 7, for example, if the graph shows the entire period from the start of operation, the approximation curve is also set by approximating the entire period of the graph. However, the deterioration trend is not necessarily the same over the entire period. For example, if there is no performance degradation at all for about two years from the start of operation (the point at the left end of the graph), but a performance degradation trend is observed after two years, a more accurate future prediction can be made by setting the approximation curve only for the second year onwards. This kind of judgment is easy if a human looks at the graph and makes the judgment, and it is possible to use AI (artificial intelligence) to make it automatically by the system.

[0076] As in the first embodiment, the degradation diagnosis device 1b, degradation diagnosis system 100b, and degradation diagnosis method of the present embodiment use the case-related information 12 and measurement data 14 to calculate a performance evaluation index indicating an operating state of the ozone generator 10 according to certain operating conditions, and diagnose the degradation state of the ozone generator 10 using the performance evaluation index. This enables degradation diagnosis according to certain indexes from the past to the present, while taking into account the influence of changes in the operating state of the ozone generator.

[0077] Furthermore, in this embodiment, the judgment unit 6 judges the timing of maintenance of the ozone generator 10 using the value of the performance evaluation index, which has the effect of enabling a correct judgment of the timing of maintenance based on a definite trend of performance deterioration without being influenced by abnormal data or temporary fluctuations. Note that the judgment unit 6 may use performance evaluation indexes such as the generation amount index, the estimated maximum ozone generation amount, the estimated generation efficiency, and the estimated power consumption rate to judge the timing of maintenance, and threshold values ​​may be set for these indices to judge the timing of maintenance.

[0078] Furthermore, in this embodiment, the judgment unit 6 has a function of judging the timing of maintenance of the ozone generator 10 by using the load level, which is information indicating the load condition of the ozone generator 10, in addition to the performance evaluation index, so that an effect is achieved in that a judgment that is more suited to the actual situation can be made.

[0079] Furthermore, in this embodiment, the judgment unit 6 predicts the future performance evaluation index of the ozone generator 10 based on a value of the performance evaluation index corresponding to the operating status, and judges the timing of maintenance of the ozone generator 10, thereby making it possible to judge the future deterioration status, the timing when maintenance is required, etc.

[0080] Furthermore, the diagnostic unit 5 may perform a deterioration diagnosis of the ozone generator 10 using a load level, which is information indicating the load condition of the ozone generator 10, together with the performance evaluation index of the ozone generator 10. In this case as well, an effect of being able to make a judgment that is more appropriate to the actual situation can be obtained.

[0081] Embodiment 3 In the third embodiment, the same components as those in the first embodiment of the present disclosure are designated by the same reference numerals, and the description of the same or corresponding parts will be omitted. Hereinafter, a degradation diagnosis device 1c and a degradation diagnosis system 100c according to the third embodiment will be described with reference to the drawings.

[0082] FIG. 8 is a flowchart showing a degradation diagnosis method for a degradation diagnosis device according to embodiment 3 of the present disclosure. FIG. 8 differs from FIG. 3 in the contents of steps S301 and S302, but the rest is the same and so is given the same reference numerals. First, in step S301, the measurement unit 4 acquires measurement data 14. At this time, the measurement data 14 includes the input power Ei [kW] of the power supply device, the ozone concentration C ([wt%] or [g / m 3 (N)]), including the cold water outlet temperature to[℃].

[0083] Next, in step S302, the measurement data 14 acquired in step S301 is converted. At this time, the parameters to be converted are the input power and the chilled water outlet temperature. First, the power supply device input power can be converted into discharge power using equation (12). Here, the power supply efficiency may be stored as a database in the S / W in the form of a function of the power supply efficiency with respect to the input power, and the database may be in the form of a formula or a table.

[0084] Here, we have shown the case where the measurement data to be input is the input power of the power supply unit, but it is also possible to input the DC current I [A] and DC voltage V [V] of the power supply unit as measurement data and express it as in equation (13) using the ozone transformer efficiency β [%].

[0085]

number

[0086] The ozone transformer efficiency β in the formula (13) may be stored as a database in the S / W, for example, in the same manner as the power supply efficiency.

[0087] Furthermore, in step S302, the cold water inlet temperature ti is calculated from the cold water outlet temperature to, the discharge power E calculated from equation (12) or equation (13), and the rated cold water flow rate fw among the measurement data 14, resulting in, for example, equation (14). Here, "0.9" is the ratio of the discharge power that is dissipated as heat without contributing to ozone generation, and is, for example, a numerical value in the case of air as the feedstock. Furthermore, since the cold water flow rate is usually constant during operation, the rated cold water flow rate fw is used in equation (14), but in a system in which the cold water flow rate is measured, the measured value of the cold water flow rate may be used.

[0088]

number

[0089] By using the formulas (12) and (14), it is possible to perform a deterioration diagnosis of the ozone generator 10 even in the case of measurement data 14 different from that in the first embodiment.

[0090] The deterioration diagnosis apparatus 1c, deterioration diagnosis system 100c, and deterioration diagnosis method of the present embodiment, similarly to the first embodiment, use the case-related information 12 and the measurement data 14 to calculate a performance evaluation index corresponding to certain operating conditions of the ozone generator 10, and diagnose the deterioration state of the ozone generator 10 based on the performance evaluation index.

[0091] Furthermore, in this embodiment, the measurement data 14 includes the cold water outlet temperature of the ozone generator 10, and the cold water inlet temperature is calculated using the cold water outlet temperature to calculate the performance evaluation index. In typical on-site operation of ozone generators, the cold water outlet temperature is often measured to monitor for abnormalities using the cold water outlet temperature of the ozone generator, and therefore the cold water inlet temperature is often not measured. For this reason, using the cold water outlet temperature has the effect of making it possible to use data that is easy to measure or that has already been measured.

[0092] Furthermore, in this embodiment, the measurement data 14 includes the input power of the power supply device of the ozone generator 10, and the input power is used to calculate the discharge power to calculate the performance evaluation index. Alternatively, the measurement data 14 may include the DC current and DC voltage of the power supply device of the ozone generator 10, and the DC current and DC voltage may be used to calculate the discharge power to calculate the performance evaluation index. Since the discharge power E is difficult to measure at high voltage and high frequency, it may not be measured as measurement data, while the power supply device input power or the DC current [A] and DC voltage [V] of the power supply device may be measured. Therefore, according to this embodiment, there is an effect that it is possible to use data that is easy to measure or that has already been measured.

[0093] Embodiment 4 In the fourth embodiment, the same components as those in the first embodiment of the present disclosure are designated by the same reference numerals, and the description of the same or corresponding parts will be omitted. Hereinafter, a degradation diagnosis device 1d and a degradation diagnosis system 100d according to the fourth embodiment will be described with reference to the drawings.

[0094] FIG. 9 is a flowchart showing a degradation diagnosis method of a degradation diagnosis device according to embodiment 4 of the present disclosure. In FIG. 9, the contents of steps S401 and S402 are different from those of FIG. 3, but the rest are the same, so the same reference numerals are used. In this embodiment, the method of controlling an ozone generator is premised on a constant raw material gas flow rate and variable concentration. First, in step S401, calculation of the maximum condition design generation efficiency emax, which was in step S102 in FIG. 3, is not performed. This is because the concentration varies, and therefore the concentration under maximum conditions cannot be uniquely determined. Constant raw material gas flow rate and variable concentration control is used relatively often in domestic projects, and the concentration unit is g / m 3 Since the unit of concentration is often g / m (N), in this embodiment, 3 However, this is not limited to this example, since it is only a matter of units. Except for not calculating the maximum condition design generation efficiency emax, this is the same as step S102 in FIG.

[0095] The description of the same parts as in the first embodiment will be omitted, and the method of calculating the estimated maximum ozone generation amount in step S402 will be described. In the first embodiment, the concentration is constant and the raw material gas flow rate is changed, so the ozone concentration at the estimated maximum ozone generation amount can be determined in advance (the rated ozone concentration is sufficient). In contrast, in the present embodiment, since the raw material gas flow rate is constant and the concentration is changed, it is not known how much the ozone concentration will increase at the estimated maximum ozone generation amount, and the generation efficiency changes depending on the concentration, so it becomes necessary to find a solution by repeated calculations.

[0096] 10 is a flowchart showing a subroutine in the degradation diagnosis method for the degradation diagnosis device according to the fourth embodiment of the present disclosure. Fig. 10 is described as a subroutine of step S402, and first, in step S411, the measurement condition design generation efficiency em' is calculated. The ozone concentration, cold water inlet temperature, and discharge power are obtained from the measurement data 14, and the discharge power E is converted into the measured power density Dm by equation (8), and then, for example, similar to Fig. 4, but the ozone concentration is g / m 3 Use a table expressed in units of (N) to determine the design generation efficiency, and use this as the measurement condition design generation efficiency em' [kWh / kg].

[0097] Next, in step S412, an initial value of the ozone concentration is set. The ozone concentration at this time is a previously assumed value, the assumed ozone concentration C' [g / m 3 (N)], and for example, it may be started from a value close to zero, or may be set to about half the measured ozone concentration. Even if a high concentration is measured when the discharge power is high on-site and the local water temperature is low, and the ozone concentration assuming the rated water temperature is lower than the measured value, it is not usually considered that the estimated maximum concentration will be less than half the measured value.

[0098] Next, in step S413, the design generation efficiency e1 at the assumed concentration is calculated. The design generation efficiency at this time is calculated using the assumed ozone concentration, the rated chilled water temperature in the case-related information 12, and the maximum power density in the case-specific information 13. The method of calculating the design generation efficiency e1 at the assumed concentration is, for example, similar to that in FIG. 4, except that the ozone concentration is g / m3 A table expressed in units of (N) may be used. This corresponds to the maximum condition design generation efficiency emax that was not calculated in step S401, and is the maximum condition design generation efficiency emax in which only the ozone concentration is a variable.

[0099] Next, in step S414, the assumed discharge power E' [kW] is calculated using the values ​​assumed up to step S413. When the three parameters that determine the generation efficiency change from the conditions in step S411 (all measured data) to the conditions in step S413 (ozone concentration is assumed, water temperature is rated, and power density is maximum), the assumed generation efficiency e' [kWh / kg], which is the generation efficiency assumed from the measured generation efficiency em calculated in step S104 using the parameters actually measured, is expressed as shown in formula (15) using the ratio of the design generation efficiency e1 [kWh / kg] at the assumed concentration to the design generation efficiency em' under the measurement conditions.

[0100]

number

[0101] In addition, when the rated feed gas flow rate fr and the assumed ozone concentration C' are used, the assumed ozone generation rate G' [kg / h] is given by equation (16).

[0102]

number

[0103] The assumed discharge power E' [kW] is calculated using the assumed generation efficiency e' obtained by equation (15) and the assumed ozone generation amount G' obtained by equation (16) as shown in equation (17).

[0104]

number

[0105] The assumed concentration and assumed ozone generation amount when this assumed discharge power matches the maximum discharge power Emax of the case-related information 12 are the estimated maximum concentration and the estimated maximum ozone generation amount, respectively. Next, in step S416, the ozone concentration is increased by 0.1 [g / m 3 (N)] is increased in increments of 1 / 100, and calculations are repeated from step S413 to step S414. When step S415 becomes Yes, the estimated maximum concentration and the estimated maximum amount of ozone generated are obtained in step S417. After that, the process returns to step 402, and the same calculations as in the first and second embodiments are performed.

[0106] As in the first embodiment, the deterioration diagnosis device 1d, the deterioration diagnosis system 100d, and the deterioration diagnosis method of the present embodiment use the case-related information 12 and the measurement data 14 to calculate a performance evaluation index corresponding to certain operating conditions of the ozone generator 10, and diagnose the deterioration state of the ozone generator 10 based on the performance evaluation index.

[0107] Furthermore, in this embodiment, which takes into account the constant raw gas flow rate and variable concentration operation, the maximum ozone concentration is calculated under constant operating conditions, and this ozone concentration is used to calculate the performance evaluation index. Therefore, a performance evaluation index under constant operating conditions can be introduced, and the performance of ozone generators can be compared under the same conditions even in situations where the operating conditions are not always rated and are constantly changing, such as in on-site operation. Since the aging change can be seen at a glance, it has the effect of making it easier to determine the timing of maintenance. In particular, in the case of a constant raw gas flow rate and variable concentration, it is difficult to uniquely determine the maximum concentration because the ozone concentration, which affects the generation efficiency, changes. However, by assuming the initial concentration and calculating the maximum concentration, the maximum ozone generation amount during constant raw gas flow rate and variable concentration operation can be obtained.

[0108] In addition, in the operation with the constant raw gas flow rate and varying concentration, the rated raw gas flow rate and the rated cold water temperature are adopted as constant operating conditions. Therefore, even in a situation where the amount of ozone generated is large because the local water temperature is low and the ozone generation efficiency is high, the performance at the rated high water temperature can be estimated, and there is an effect of high practicality.

[0109] In the above embodiment, for example, in formula (16), the amount of ozone generated is calculated using the flow rate of the raw material gas for simplification. 3 / h(N), more accurately, the ozone-containing gas flow rate is used instead of the raw material gas flow rate. Although the rated ozone-containing gas flow rate may be used directly, it is preferable to convert the rated raw material gas flow rate and the assumed ozone concentration to the ozone-containing gas flow rate by a known method.

[0110] In the above embodiment, the source gas flow rate is constant and the concentration is variable, and it is assumed that the source gas flow rate is constant at the rated value. However, in reality, the source gas flow rate may unintentionally deviate from the rated value over time. In such a case, the measured value of the source gas flow rate may be used to correct the measured value of the ozone concentration. Although details are omitted, it is possible to calculate how the ozone concentration changes when the source gas flow rate changes under the same power density condition by using a table of power densities obtained from the measured values ​​in a table such as that in FIG. 4. Therefore, for example, if the ozone concentration is high because the measured value of the source gas flow rate has fallen below the rated value, it is possible to correct the ozone concentration by determining how much the ozone concentration will be when the source gas flow rate increases to the rated value.

[0111] In addition, the deterioration of the ozone generator 10 in this disclosure is not necessarily irreversible, but also includes cases where the deterioration can be restored by maintenance such as cleaning or part replacement.

[0112] In addition, this disclosure basically focuses on the change in the performance evaluation index over time. Although it is not specifically stated, the concept of time is included here, and the cumulative time during the operation period also has an impact.

[0113] Furthermore, generally, diagnosis often includes judgment, but in this disclosure, diagnosis is distinguished from judgment and is used as data processing, data output, etc. for judgment.

[0114] The configurations shown in the above embodiments are merely examples of the contents of the present disclosure, and may be combined with other known techniques. Furthermore, parts of the configurations may be omitted or modified without departing from the scope of the present disclosure.

[0115] Various aspects of the present disclosure are summarized below as appendices. (Appendix 1) a case-related information acquiring unit for acquiring case-related information including information on a certain operating condition of the ozone generator; a measurement unit for acquiring measurement data indicating an operating status of the ozone generator; a diagnosis unit that calculates a performance evaluation index indicating a performance of an ozone generator in the operating state corresponding to the certain operating condition based on the case-related information and the measurement data, and diagnoses a deterioration state of the ozone generator. (Appendix 2) 2. The deterioration diagnosis device according to claim 1, wherein the performance evaluation index includes at least one of an estimated maximum ozone generation amount of the ozone generator, an ozone generation efficiency, and a power consumption rate. (Appendix 3) 3. The deterioration diagnosis device according to claim 1, wherein the ozone generation efficiency used in calculating the performance evaluation index is determined using two or more of power density, ozone concentration, and cold water temperature. (Appendix 4) 4. The deterioration diagnosis device according to claim 1, wherein the constant operating conditions include a rated water temperature and a rated ozone concentration. (Appendix 5) 5. The degradation diagnosis device according to claim 1, wherein the constant operating conditions include a rated water temperature and a rated feed gas flow rate. (Appendix 6) 6. The deterioration diagnosis device according to claim 1, wherein the certain operating conditions include a condition under which the discharge power of the ozone generator is at a maximum. (Appendix 7) 7. The degradation diagnosis device according to claim 1, wherein the diagnosis unit outputs a load level, which is information indicating a load state of the ozone generator, and the performance evaluation index. (Appendix 8) and a determination unit that determines a timing for maintenance of the ozone generator using a value of the performance evaluation index. (Appendix 9) 9. The deterioration diagnosis device according to claim 8, wherein the judgment unit predicts a future performance evaluation index of the ozone generator based on a value of the performance evaluation index according to the operating state, and judges the timing of the maintenance of the ozone generator. (Appendix 10) 9. The deterioration diagnosis device according to claim 8, wherein the judgment unit judges the timing of the maintenance of the ozone generator using the performance evaluation index and a load level which is information indicating a load status of the ozone generator. (Appendix 11) 11. The degradation diagnosis device according to claim 1, wherein the measurement data includes a cold water outlet temperature of the ozone generator, and the performance evaluation index is calculated using the cold water outlet temperature. (Appendix 12) 12. The degradation diagnosis device according to claim 1, wherein the measurement data includes an input power of a power supply device of the ozone generator, and the performance evaluation index is calculated using the input power. (Appendix 13) 13. The degradation diagnosis device according to any one of appendices 1 to 12, wherein the measurement data includes a DC current and a DC voltage of a power supply device of the ozone generator, and the performance evaluation index is calculated by the diagnosis unit using the DC current and the DC voltage. (Appendix 14) 14. The deterioration diagnosis device according to claim 3, wherein the performance evaluation index is calculated based on an ozone concentration that is maximized based on the constant operating conditions. (Appendix 15) An ozone generator; a case-related information acquisition unit that acquires case-related information including information on a certain operating condition of the ozone generator; a measurement unit for acquiring measurement data indicating an operating status of the ozone generator; a diagnosis unit that calculates a performance evaluation index indicating performance of the ozone generator in the operating situation corresponding to the certain operating condition based on the case-related information and the measurement data, and diagnoses a deterioration state of the ozone generator. (Appendix 16) 16. The deterioration diagnosis system according to claim 15, further comprising a monitoring and control device that monitors the operating status of the ozone generator and controls the ozone generator. (Appendix 17) obtaining case-related information including information about certain operating conditions of the ozone generator; obtaining measurement data indicative of an operating condition of the ozone generator; calculating a performance evaluation index indicating performance of the ozone generator in the operating situation corresponding to the certain operating conditions based on the case-related information and the measurement data, and diagnosing a deterioration state of the ozone generator. [Explanation of symbols]

[0116] 1 1b 1c 1d Deterioration diagnosis device, 2 case-related information acquisition unit, 3 case-specific information calculation unit, 4 measurement unit, 5 diagnosis unit, 6 judgment unit, 10 ozone generator, 12 case-related information, 13 case-specific information, 14 measurement data, performance evaluation index 15 21 input device, 22 computer, 23 CPU, 24 main memory device, 25 auxiliary memory device, 26 network, 27 external memory device, 28 output device, 100 100b 100c 100d Deterioration diagnosis system

Claims

1. a case-related information acquiring unit for acquiring case-related information including information on a certain operating condition of the ozone generator; a measurement unit for acquiring measurement data indicating an operating status of the ozone generator; a diagnosis unit that calculates a performance evaluation index indicating performance of the ozone generator in the operating state corresponding to the certain operating condition based on the case-related information and the measurement data, and diagnoses a deterioration state of the ozone generator.

2. 2. The deterioration diagnostic device according to claim 1, wherein the performance evaluation index includes at least one of an estimated maximum ozone generation amount of the ozone generator, an ozone generation efficiency, and a power consumption rate.

3. 3. The deterioration diagnostic device according to claim 1, wherein the ozone generation efficiency used in calculating the performance evaluation index is determined using two or more of a power density, an ozone concentration, and a cold water temperature.

4. 3. The deterioration diagnosis device according to claim 1, wherein the certain operating conditions include a rated water temperature and a rated ozone concentration.

5. 3. The deterioration diagnosis device according to claim 1, wherein the constant operating conditions include a rated water temperature and a rated feed gas flow rate.

6. 3. The deterioration diagnosis device according to claim 1, wherein the certain operating conditions include a condition under which the discharge power of the ozone generator is maximized.

7. 3. The deterioration diagnosis device according to claim 1, wherein the diagnosis unit outputs a load level, which is information indicating a load state of the ozone generator, and the performance evaluation index.

8. 3. The deterioration diagnosis device according to claim 1, further comprising a determination unit that determines a time for maintenance of the ozone generator using the value of the performance evaluation index.

9. 9. The deterioration diagnosis device according to claim 8, wherein the judgment unit predicts a future performance evaluation index of the ozone generator based on a value of the performance evaluation index according to the operating state, and judges the timing of the maintenance of the ozone generator.

10. 9. The deterioration diagnosis device according to claim 8, wherein the determination unit determines the timing of the maintenance of the ozone generator by using the performance evaluation index and a load level which is information indicating a load state of the ozone generator.

11. 3. The deterioration diagnosis device according to claim 1, wherein the measurement data includes a cold water outlet temperature of the ozone generator, and the performance evaluation index is calculated using the cold water outlet temperature.

12. 3. The degradation diagnosis device according to claim 1, wherein the measurement data includes an input power of a power supply device of the ozone generator, and the performance evaluation index is calculated using the input power.

13. 13. The degradation diagnosis device according to claim 12, wherein the measurement data includes a DC current and a DC voltage of the power supply device of the ozone generator, and the performance evaluation index is calculated by the diagnosis unit using the DC current and the DC voltage.

14. 4. The deterioration diagnostic device according to claim 3, wherein the performance evaluation index is calculated based on an ozone concentration that is maximized under the constant operating conditions.

15. An ozone generator; a case-related information acquisition unit that acquires case-related information including information on a certain operating condition of the ozone generator; a measurement unit for acquiring measurement data indicating an operating status of the ozone generator; a diagnosis unit that calculates a performance evaluation index indicating performance of the ozone generator in the operating situation corresponding to the certain operating condition based on the case-related information and the measurement data, and diagnoses a deterioration state of the ozone generator.

16. The deterioration diagnosis system according to claim 15, further comprising a monitor and control device that monitors the operating condition of the ozone generator and controls the ozone generator.

17. obtaining case-related information including information about certain operating conditions of the ozone generator; obtaining measurement data indicative of an operating condition of the ozone generator; calculating a performance evaluation index indicating performance of the ozone generator in the operating situation corresponding to the certain operating conditions based on the case-related information and the measurement data, and diagnosing a deterioration state of the ozone generator.

Images