JP4313734B2 - Monitoring and diagnosis system - Google Patents

Description

  The present invention relates to a monitoring diagnostic system for detecting an abnormality of each part of an internal combustion engine and diagnosing a failure based on performance data detected by a surface vibration sensor installed at a specific part of the internal combustion engine and a conventional sensor such as temperature and pressure. About.

    Conventionally, an apparatus for predicting a failure of an internal combustion engine has been proposed (see, for example, Patent Document 1).

  This failure prediction device includes a plurality of sensors for detecting vibration, temperature, generated sound, etc. of each part of the engine, and standard values in which changes in detection values of these sensors are set in advance according to various abnormalities. When a tendency corresponding to a combination of specific change trends is shown in comparison with a change trend, a determination unit that determines that the part corresponding to the change trend is abnormal, and a determination result by the determination unit is output as a prediction signal Output means.

According to the failure prediction apparatus having such a configuration, for example, one vibration sensor is provided on the main bearing metal, two on the cylinder block, one on the gear case, and one on the exhaust manifold, and the temperature sensor is provided on the main bearing metal. By attaching the necessary sensors to the necessary locations such as one on the back side and one on the exhaust pipe of each cylinder, one in the lubricating oil system, and arranging the sound sensor in the vicinity of the engine, for example, the main bearing The wear state of the main bearing metal can be determined by the vibration sensor and temperature sensor attached to the metal, and the presence or absence of cracks in the crankshaft can be determined by the vibration sensor attached to the cylinder block and the temperature sensor attached to the main bearing metal. It is possible to determine whether there is an abnormality in the torsional damper by using a vibration sensor attached to the gear case and a sound sensor arranged in the vicinity of the engine. It has become to so that.
Japanese Patent No. 3053304

  However, in the above-described conventional failure prediction apparatus, although it is possible to predict failure of each part by using various sensors attached to each part, for example, detection of an abnormality by a sensor at one part is not effective for other parts. Therefore, it is not configured to be able to predict even the failure of other parts. That is, a sensor (for example, a vibration sensor) directly attached to each part is used only for predicting a failure of the part mainly by detecting the vibration of each part. Considering comprehensively, it has not been done to comprehensively judge the location of failure and the content of failure of the internal combustion engine.

  In addition, when the state of each part is directly detected by a sensor, there is a problem that the number of sensors increases, which inevitably leads to an increase in cost.

  By the way, a skilled engineer evaluates the state of the engine by using a change of a solid sound (vibration) of the engine by using a listening rod. In other words, it can be said that the state of the engine can be grasped using the engine surface vibration. Therefore, it is considered that the following two merits are born by incorporating the signal from the engine surface vibration sensor as a new detection item into the monitoring diagnosis system constructed using the signal from the conventional sensor such as temperature and pressure as the detection item. . The first merit is that the number of items detected by the vibration sensor is increased compared to the items detected by the conventional sensor, so that the diagnostic accuracy can be improved. The second merit is that the engine cannot be detected by the conventional sensor. If it becomes possible to detect the slight change of the metal, for example, wear of metal or the like, it is possible to implement a higher level of preventive maintenance than the monitoring diagnosis system using only conventional sensors.

  Here, the present inventors have already proposed a monitoring diagnosis system composed of conventional sensors such as the above-mentioned temperature and pressure (Japanese Patent Application No. 2003-1554928). This diagnostic monitoring system is configured based on detection means for detecting temperature, pressure and the like attached to each detection part of the internal combustion engine, and performance set based on initial operation data during normal operation after the internal combustion engine is installed. Normal range value data storage means for storing normal range values of data in advance, and performance data and normal range value data obtained by detecting the value of each detection part by each detection means by a direct or indirect technique By comparing the normal range value stored in the storage means with the abnormality detection means for detecting an abnormality when the performance data obtained from each detection means deviates from the normal range value, On the basis of the detection result, a failure diagnosis means for diagnosing the failure location and the failure content of the internal combustion engine is provided.

  In other words, the normal range value of each measurement item has a correlation with the engine output once in a state in which the internal combustion engine (hereinafter also simply referred to as “engine”) is operating normally and in the case of a ship (after marine public test in the case of ship use) It is set by measuring and calculating. From the relational expression thus obtained, the engine output is constantly monitored to obtain the normal value of each measurement item in real time.

  Therefore, considering the integration of the engine surface vibration analysis algorithm into the above-described monitoring / diagnosis system composed of conventional sensors (temperature sensors, pressure sensors), each vibration value is a normal range value in correlation with the engine output. Must be set and displayed in real time.

  Here, the present inventors performed the following tests in order to demonstrate that there is a correlation between the engine output and the surface vibration.

  The items to be detected for minute changes inside the engine by the surface vibration analysis of the engine are the following three items.

(1) Valve system wear (2) Main bearing metal wear (3) Piston wear These items are difficult to detect with conventional sensors such as temperature, pressure, flow rate, etc. In addition, it is set based on what requires a lot of man-hours such as engine stoppage for maintenance.

  In this test, one actual engine (details of specifications are omitted) was prepared for a pseudo failure test. In addition, in order to detect abnormalities with the surface vibration of the engine for the above three items, measurement was finally attempted at the following measurement positions.

(1) Surface of the block next to the center of the liner (hereinafter referred to as “cylinder horizontal block”) (2) Surface of the cylinder head (hereinafter referred to as “cylinder head”) (3) Block next to the main bearing (hereinafter referred to as “main bearing”) Surface of “Horizontal Block”)) The measurement position is shown in FIG. FIG. 70 is an overview of a 6-cylinder engine.

  As a result of investigating the change due to the load at each measurement position, it was confirmed that the vibration increased with the increase in the load at any measurement position. Incidentally, the respective measurement results of loads 0%, 50% and 100% when the measurement position is the surface of the second cylinder horizontal block are shown in FIGS. Such measurement results are the same at other measurement positions, although not shown. Incidentally, in each figure of FIG. 71, the symbol of the combination of one number and two alphabets shown in the figure shows the number of each cylinder at the beginning, and “FT” is the firing top ( “Cylinder explosion”, “EC” means exhaust valve closing (exhaust valve seating), and “SC” means suction valve closing (intake valve seating). For example, “1FT” in the figure indicates the explosion timing position of the first cylinder, “6EC” indicates the exhaust valve seating timing position of the sixth cylinder, and “2SC” indicates the intake valve seating timing position of the second cylinder. ing. The meaning of such symbols is the same in the measurement results of each figure that appears later.

  From the above results, it was proved that the vibration value of each detection target part can be displayed in real time by setting a normal range value by correlation with the output of the engine.

  The present invention was devised in view of such verification results, and the purpose of the present invention is to provide surface vibration sensors for surface vibration performance data detected by surface vibration sensors attached to specific parts of the internal combustion engine surface. By detecting the presence or absence of abnormality by a predetermined method while taking into account the characteristics etc., if abnormality is found, by comprehensively judging from the type of abnormality and diagnosing the failure location and failure content, An object of the present invention is to provide a monitoring / diagnosis system capable of quickly and accurately diagnosing a failure of an internal combustion engine.

In order to solve the above-described problems, an internal combustion engine monitoring and diagnosis system according to the present invention stores in advance a normal range value of vibration performance data of a detection target portion set based on operation data during normal operation of the internal combustion engine. Normal range value data storage means, a surface vibration sensor attached to one or a plurality of vibration measurement parts on the surface of the internal combustion engine, and a signal of a vibration waveform by the surface vibration sensor in units of a period of one combustion cycle of the cylinder In addition to capturing, the frequency analysis is performed on the data of the captured period unit, and an effective value is obtained from the analysis result, and the effective value obtained by the filter processing means and the normal range value data storage means are stored. An abnormality detection means for detecting an abnormality when the effective value deviates from the normal range value by comparing with a normal range value; Based on the in abnormality detection means detection result, a failure diagnosis means for diagnosing a fault condition and fault location of the internal combustion engine, it may be configured to include.

Further, the internal combustion engine monitoring and diagnosis system according to the present invention is a normal range value data in which normal range values of vibration performance data of a detection target portion set based on operation data during normal operation of the internal combustion engine are stored in advance. A storage means, a surface vibration sensor attached to one or a plurality of vibration measurement parts on the surface of the internal combustion engine, and a vibration waveform signal from the surface vibration sensor are sequentially taken in a unit of period of one combustion cycle of the cylinder, and this vibration Time gate means for cutting out the signal waveform at a predetermined timing that can further detect vibration of the detection target part from the waveform signal, and a filter for performing frequency analysis on the data cut out by the time gate means and obtaining an effective value from the analysis result Stored in the processing means, the effective value obtained by the filter processing means, and the normal range value data storage means. Comparing with a normal range value, an abnormality detection means for detecting an abnormality when the effective value is out of the normal range value, and a failure location of the internal combustion engine based on the detection result of the abnormality detection means And failure diagnosis means for diagnosing the failure content . That is, in the monitoring diagnosis system having the above-described configuration , a time gate means is further added.

  When the internal combustion engine is a four-cycle engine, for example, one combustion cycle corresponds to two rotations of the crankshaft (crank angle 720 degrees). As a result, the phenomenon can be captured in time series based on the timing chart within one cycle. That is, the target phenomenon can be processed in units of one cycle.

  Specifically, time data that is continuously input is triggered by a first cylinder combustion top signal (rotational top pulse: 1 FTDC) as a trigger, and the time data is divided so that processing can be performed for each combustion cycle. The vibration waveform signal from the surface vibration sensor is taken in cycle units. In this case, the time data may be further cut out from the time data divided for each combustion cycle by the time gate means in any necessary section with 1FTDC as a reference. A frequency waveform analysis (filtering process) is performed on the vibration waveform signal of the time data cut out in this way, and a bandpass filter is applied to the frequency analysis result on the frequency axis to obtain a partial sum (partial overall: effective value RMS). And the RMS value is input to the abnormality detection means.

  On the other hand, the abnormality detection means applies the following algorithm in order to obtain an appropriate normal value in real time. First, as shown in FIG. 72, the correlation between the engine output (electric power) and each measured value is obtained in advance. After that, if the output is measured in real time, the normal value of each measurement item is obtained at the same time.

  For example, as shown in FIG. 73, the normal value 101 calculated from the engine output is in the normal range of the upper and lower limits as indicated by hatching in the figure (actually detected at two levels of “caution” and “alarm”). If the measured value exceeds this range, it is considered abnormal.

  The failure diagnosis means diagnoses the failure location and the failure content of the internal combustion engine with reference to a diagnosis map and a guidance map described later based on the detection result of the abnormality detection means.

  Here, the vibration measurement part to which the surface vibration sensor is attached is one of the horizontal blocks of the cylinder located in the center among the three cylinders arranged adjacent to each other, and the surface vibration attached to this part. The site to be detected by the sensor is the vibration of the valve train of the three cylinders arranged adjacent to each other. The vibration measurement part to which the surface vibration sensor is attached is one part of the head of each cylinder, and the detection target part by the surface vibration sensor attached to this part is vibration of the valve train of each cylinder. Further, the vibration measurement part to which the surface vibration sensor is attached is one place of the main bearing lateral block of an arbitrary cylinder (more preferably, a cylinder located at the center of the plurality of cylinders), and the vibration measurement part is attached to this part. The portion to be detected by the surface vibration sensor is vibration of the main bearing metal portion of each cylinder. The relationship between the vibration measurement region and the detection target region of these surface vibration sensors is obtained by a pseudo failure test described later.

  The vibration measurement part to which the surface vibration sensor is attached is one part of the liner of the cylinder, and the part to be detected by the surface vibration sensor attached to this part is vibration of the piston part of the cylinder. The vibration measurement part to which the surface vibration sensor is attached is one part of the horizontal block of the cylinder, and the detection target part by the surface vibration sensor attached to this part is vibration of the piston part of the cylinder. The relationship between the vibration measurement region and the detection target region of these surface vibration sensors is obtained by a pseudo failure test described later.

The monitoring and diagnosis system for an internal combustion engine according to the present invention includes a first detection means for detecting temperature, pressure and the like attached to each detection portion inside the internal combustion engine, and one or more vibrations on the surface of the internal combustion engine. A second detection means for detecting surface vibration attached to the measurement site, and a normal range value of performance data set based on initial operation data during normal operation after the internal combustion engine is installed; The normal waveform value data storage means and the vibration waveform signal from the second detection means are sequentially fetched in units of periods of one combustion cycle of the cylinder, the frequency data of the fetched period units is analyzed, and the effective value is obtained from the analysis result. Filter processing means for obtaining the performance data obtained by detecting the value of each detection site by the first detection means by a direct or indirect technique. By comparing the normal range value stored in the normal range value data storage means and the performance data obtained from each detection means is out of the normal range value, the abnormality is detected, Abnormality is detected when the effective value deviates from the normal range value by comparing the effective value obtained by the filter processing means with the normal range value stored in the normal range value data storage means. It is also possible to have a configuration comprising an abnormality detecting means for performing the diagnosis and a failure diagnosing means for diagnosing the failure location and content of the internal combustion engine based on the detection result of the abnormality detecting means .

Such a configuration and to lever, the data of the normal range values stored in the normal range value data storage means, set based on the initial operation data during normal operation after the engine is installed in the workplace of production Has been. As a result, an appropriate normal range value according to the installation status of each internal combustion engine is set, and the normal range value such as pressure and temperature set in this way, and each of the pressure sensor and temperature sensor etc. The performance data related to pressure and temperature obtained from one detection means is compared, and the set normal range value of vibration and the performance data related to surface vibration obtained from each second detection means which is a surface vibration sensor. By comparing, it is possible to improve the accuracy of abnormality detection of the internal combustion engine.

The monitoring and diagnosis system for an internal combustion engine according to the present invention includes a first detection means for detecting temperature, pressure and the like attached to each detection portion inside the internal combustion engine, and one or more vibrations on the surface of the internal combustion engine. second detection means for detecting a surface vibration, which is attached to the measurement site, moving average processing on the detected operating initialized data in the respective first detecting means at the time of normal operation after the engine is installed the determined normal time data to match the time variation of the engine output by the facilities Succoth, with stores in advance a normal range value of the performance data set an allowable width in this normal state data, the internal combustion engine is installed normal range stored in advance a normal range value set an allowable width in a normal time data obtained by the correlation between the engine output detected vibration values in the respective second detector means during normal operation after the The signal of the vibration waveform from the data storage means and the second detection means is sequentially fetched in units of one cycle of combustion of the cylinder, and the signal at a predetermined timing at which the vibration of the detection target portion can be further detected from the vibration waveform signal. The time gate means for cutting out the waveform, the frequency analysis of the data cut out by the time gate means, the filter processing means for obtaining the effective value from the analysis result, and the value of each detection site directly by the first detection means Alternatively, by comparing the performance data obtained by detection by an indirect method with the normal range value stored in the normal range value data storage means, the performance data obtained from each of the first detection means is An abnormality is detected when the value falls outside the normal range value, and the effective value obtained by the filter processing means and the positive value are detected. By comparing the normal range value of the vibration that is stored in the value range data storage means, and abnormality detection means for the effective value to detect an abnormality if they deviate from the normal range value, the abnormality detecting means And a failure diagnosing means for diagnosing the failure location and the failure content of the internal combustion engine based on the detection result at 1.

  According to the present invention having such a feature, the data of the normal range value stored in the normal range value data storage means is the initial operation data during normal operation after the internal combustion engine is installed in the work site that is actually operated. Is set based on. As a result, an appropriate normal range value according to the installation status of each internal combustion engine is set, and the normal range value such as pressure and temperature set in this way, and each of the pressure sensor and temperature sensor etc. The performance data related to pressure and temperature obtained from one detection means is compared, and the set normal range value of vibration and the performance data related to surface vibration obtained from each second detection means which is a surface vibration sensor. By comparing, it is possible to improve the accuracy of abnormality detection of the internal combustion engine.

  According to the monitoring diagnosis system of the present invention, the detection accuracy can be improved by adding a signal from the engine surface vibration sensor as a new detection item to a detection item of a signal from a conventional sensor such as a temperature sensor or a pressure sensor. In addition to being able to improve, it is possible to detect minute changes inside the engine that cannot be detected by conventional sensors alone, such as wear of metal, etc., and thus have a unique effect that a higher level of preventive maintenance can be practiced. .

  Embodiments of the present invention will be described below with reference to the drawings.

  The monitoring diagnosis system of the present invention exhibits a more excellent effect by being incorporated in the basic monitoring diagnosis system (hereinafter referred to as “basic monitoring diagnosis system”) previously proposed by the present inventors. Therefore, in the present embodiment, the whole of the basic monitoring diagnostic system will be described first, and then the characteristics of the monitoring diagnostic system of the present invention (part added to the basic monitoring diagnostic system) will be described.

-Explanation of basic monitoring and diagnosis system-
FIG. 2 is a functional block diagram showing the system configuration of the basic monitoring diagnosis system.

  This basic monitoring / diagnostic system can be broadly divided into various sensor groups 1 to 4 provided in a detection part of a driven machine (hereinafter referred to as “internal combustion engine”) 10 such as an internal combustion engine and a generator, and a data collection unit 5. , An abnormality detection unit 6, a failure diagnosis unit 7, a normal range value data storage unit 8, a diagnosis map storage unit 9a, and a guidance map storage unit 9b.

  Each temperature sensor 1a in the temperature sensor group 1 is attached to the required number of parts such as the back side of the main bearing metal, the exhaust pipe of each cylinder, the lubricating oil system, and the cooling water system. Are attached to the required locations such as the lubricating oil system, the cooling water system, the intake air system, the fuel supply system, and the crank chamber of the cylinder block, etc. A required number is attached to a required part such as a fuel supply system, and each vibration sensor 4a of the vibration sensor group 4 is attached to a required part such as a main bearing metal, a cylinder block, a gear case, and an exhaust manifold.

  Such attachment of the sensor groups 1 to 4 has been performed conventionally in the field of internal combustion engines, and is not particularly new. In addition, collecting data from each of the sensors 1a to 4a itself is also conventionally performed. However, in this basic monitoring / diagnosis system, as will be described later, the method of detecting performance data based on detection by an arbitrary sensor is devised.

  The performance data detected by each of the sensor groups 1 to 4 is collected by the data collection unit 5 and then sent to the abnormality detection unit 6.

  In the abnormality detection unit 6, the normal range value stored in the normal range value data storage unit 8 is obtained by performing weighted moving average processing on the performance data and outputs from the sensors 1 a to 4 a obtained via the data collection unit 5. (This will be described later), and an abnormality is detected when the performance data obtained from the sensors 1a to 4a is out of the normal range value.

  The failure diagnosis unit 7 refers to the diagnosis map (which will be described later) stored in the diagnosis map storage unit 9a based on the detection result of the abnormality detection unit 6, and describes the failure location and failure of the internal combustion engine 10. Diagnose the contents and output the diagnosis result. Further, the failure diagnosis unit 7 extracts countermeasure information from a guidance map (which will be described later) stored in the guidance map storage unit 9b based on the failure name retrieved from the diagnosis map, and outputs it as a diagnosis result.

  FIG. 3 shows an example of the structure of the internal combustion engine 10 in the present embodiment.

  The internal combustion engine 10 of the present embodiment is a so-called packaged generator in which an engine unit 11 and a generator 12 are integrally incorporated in a housing 20. A suction port 21 for taking in external air into the housing 20 is provided in the upper right part of the housing (package) 20, and a part of the air taken in from the suction port 21 passes through the air cleaner 13. After the fuel is burned by the engine unit 11, the fuel is guided to the turbocharger (T / C) 14. The engine unit 11 houses an FO pump (not shown), an FO filter, an LO (lubricating oil) filter, a feed pump (not shown), a radiator, and the like, and is driven via a crankshaft of the engine unit 11. A radiator fan 15 is attached, and a housing (package) 20 on the downstream side of the radiator fan 15 is provided with a lead-out port 22 for releasing internal air to the outside.

<Description of Normal Range Value Stored in Normal Range Value Data Storage Unit 8>
The normal range value data stored in the normal range value data storage unit 8 is set based on initial operation data during normal operation after the internal combustion engine 10 is installed. That is, the internal combustion engine 10 has different operation data obtained during normal operation depending on the installation location, installation environment, and the like. For example, the operation data obtained during normal operation is naturally different between when used in severe Hokkaido in winter and when used in hot Okinawa in summer. Therefore, in this basic monitoring diagnosis system, the normal range value data stored in the normal range value data storage unit 8 is set based on the initial operation data obtained during normal operation after the internal combustion engine 10 is installed. Thereby, an appropriate normal range value according to the installation state of the internal combustion engine 10 is set.

  This normal range value setting method will be specifically described by paying attention to the relationship between the exhaust temperature of the internal combustion engine 10 and the engine output.

  The data of the normal range value is expressed as the normal value based on the external environmental conditions (atmospheric temperature, atmospheric pressure, humidity, cooling water temperature, etc.) of the installed internal combustion engine 10 and the output level of the internal combustion engine 10. Formulated as (1) to (4).

そして、この数式（１）〜（４）と、内燃機関１０が設置された後の正常運転時の運転初期データとを用いて正常値を計算により求め、適正な許容値を考慮して、正常範囲幅を設定する。これにより、内燃機関１０の設置場所に応じて係数を決めることができるため、正常範囲値（正常範囲幅）をより適正に設定することができる。

A normal value is obtained by calculation using the mathematical formulas (1) to (4) and initial operation data during normal operation after the internal combustion engine 10 is installed. Set the range width. Thereby, since a coefficient can be determined according to the installation place of the internal combustion engine 10, a normal range value (normal range width) can be set more appropriately.

  The abnormality detection method based on the normal range value is not limited to the exhaust gas temperature of the internal combustion engine 10 described above, but the supply air pressure, the temperature and pressure of cooling water, the pressure of seawater, the temperature and pressure of lubricating oil, Applies to most data to detect, such as fuel oil pressure and flow rate.

<Description of abnormality detection unit 6>
FIG. 4 is an example of initial operation data obtained during normal operation of the internal combustion engine 10, and shows the relationship between the exhaust temperature (° C.) and the output (kW) of the internal combustion engine 10. Conventionally, an upper limit temperature is set based on the exhaust temperature with respect to the maximum output, and when this upper limit temperature is exceeded, it is determined that there is an abnormality. In this embodiment, this initial operation data is represented by the above formulas (1) to (1) to (3). The normal range value (normal range width) is calculated by applying (4).

  FIG. 5 is a graph in which normal range values obtained by calculation (width shown by hatching in the figure) are superimposed on the initial operation data shown in FIG. That is, in the abnormality detection unit 6 of the present embodiment, when the exhaust temperature is within the normal range value (shaded portion) with respect to the output of the internal combustion engine 10 (hereinafter also referred to as “engine output”). Is determined to be normal, and an abnormality is detected when the normal range value is exceeded.

<Description of weighted moving average>
Here, when the engine output is not stable and the time change of the output is large, the normal range value of the performance data with time delay is simply used from the output with the fast change, using the above formulas (1) to (4). Thus, the error is large, and the accuracy of abnormality detection is reduced. Therefore, in this embodiment, the accuracy of abnormality detection is improved as follows.

  That is, performance data obtained from the temperature sensor 1a and data obtained by weighted moving average processing on the output used for normal value calculation are used. In this case, the weighted moving average process is set so that the performance data obtained from the temperature sensor 1a matches the time change of the output. For performance data with a large time delay (slow change) with respect to the output, the moving average processing is performed with a small moving average number, while the output used for normal value calculation is configured to perform the moving average processing with a large moving average number. . In this way, by matching the change in performance and output with time, errors in the normal range are reduced, and the accuracy of abnormality detection is improved.

  FIG. 6 shows a timing chart of the engine output (kW) and the exhaust temperature. Exhaust temperature, which is performance data for engine output with large load fluctuations, is data with a time delay. The time delay is particularly noticeable when the engine is started and stopped (ie, in a transient state). Therefore, in a transient state where the output change is large, including when the engine is started and stopped, correct abnormality detection cannot be performed unless this time delay is taken into consideration.

  FIG. 7 is a graph showing the relationship between the engine output and the exhaust gas temperature when the load fluctuation is large in the graph shown in FIG. 6 (the portion surrounded by a broken line in FIG. 6) with the time axis expanded. This is the state before processing. Incidentally, the moving average (output: 1, exhaust temperature: 1) in the figure indicates that neither the output nor the exhaust temperature is subjected to the moving average process (that is, the moving average number is 1 for both the output and the exhaust temperature). Yes. Here, the normal range value (normal range width) of the exhaust temperature with respect to the engine output calculated using the above formulas (1) to (4) is the fluctuation of the engine output as shown by the thin solid line waveform width in FIG. It fluctuates irregularly depending on. When the exhaust temperature data (indicated by reference numeral 81 in the figure) detected by the temperature sensor that detects the exhaust temperature is superimposed on this graph, even if there is no abnormality in the exhaust temperature, As a result of the exhaust temperature data protruding from the normal range value at the black circle portion, an abnormality is detected (false detection) at this portion.

  On the other hand, FIG. 8 shows a result of performing the moving average process with the same number of both engine output and exhaust temperature (the same moving average number for both output and exhaust temperature). As a result of the moving average process, the actual exhaust gas temperature data 81 and the change in output are averaged, and the number of false detections is reduced compared to the case shown in FIG. However, in the moving average process with the same number of performance and output, the time changes of the two do not coincide, and as a result of the exhaust temperature data 81 protruding from the normal range value at the black circle portion in the figure, an abnormality is detected at this portion ( False detection).

  On the other hand, FIG. 9 shows the result of performing the moving average process with different numbers of both engine output and exhaust temperature (moving average number of outputs = 60, moving average number of exhaust temperatures = 1). As a result of such weighted moving average processing, the actual exhaust gas temperature data and the time delay of the change in the normal range value are almost the same, and the accuracy of abnormality detection is higher than that shown in FIG. Is greatly improved, the number of false detections is 0, and the accuracy of abnormality detection when the output fluctuation is large is improved. In FIG. 9, the engine output (indicated by reference numeral 98) that has not been subjected to moving average processing is also shown for reference.

  Incidentally, FIG. 10 shows another example, which shows the relationship between the engine output and the exhaust temperature when the engine is started.

  FIG. 11 shows the start-up time of FIG. 10 (the portion surrounded by a broken line) with the time axis enlarged, and both the engine output and the exhaust temperature are moved by the same number (moving average number of both the output and the exhaust temperature = 10). The result of the average processing is shown. In this case, as a result of the exhaust temperature data 82 protruding from the normal range value at the white circle portion 83 in the figure, an abnormality is detected (false detection) at this portion.

  On the other hand, FIG. 12 shows the result of performing the moving average process on the engine output and the exhaust temperature by the weighted moving average process (moving average number of outputs = 20, moving average number of exhaust temperatures = 1). . As a result of performing the weighted moving average process in this way, the change in the normal range value takes into account the time delay of the actual measured data 82 of the exhaust temperature. That is, the accuracy of abnormality detection is greatly improved as compared to the case shown in FIG. 11, and the number of false detections is 0, so that the accuracy of abnormality detection is improved.

<Description of this embodiment regarding detection of performance data>
(1) Detection of fuel oil pressure in the fuel supply system When the pressure sensor 2a provided in the fuel supply system detects the fuel pressure without considering the pressure fluctuation associated with the fuel (FO) pump injection of the fuel in the pipe Misdetection will occur frequently.

  FIG. 13 is a schematic diagram of a fuel supply system of the engine unit 11 shown in FIG.

  In the fuel supply system, a fuel tank (not shown) and an input side of a feed pump 32 provided in a fuel pump (FO pump) 31 are connected by a first pipe 34, and an output side of the feed pump 32 and an input side of the FO filter 33 are connected. Are connected by a second pipe 35, and the output side of the FO filter 33 and the input side of the FO pump 31 are connected by a third pipe 36. The output side of the FO pump 31 is connected to a fuel tank (not shown) via the fourth pipe 37.

  In the fuel supply system having such a configuration, a pressure sensor 2a for measuring fuel oil pressure is attached to an arbitrary pipe (for example, the third pipe 36). However, the fuel oil pressure after the FO filter 33 has a large pressure fluctuation due to the spill. Therefore, due to this pressure fluctuation, the accuracy of pressure measurement is reduced and the life of the pressure sensor 2a is also reduced.

  Therefore, in the present embodiment, the third pipe 36 immediately after the FO filter 33 is branched, and a pressure extraction pipe 38 with a restriction φ0.3 is connected, and the pressure sensor 2 a is connected to the pressure extraction pipe 38. In other words, the pressure take-out pipe 38 is provided with a narrow portion 38a having a restriction φ0.3 so that the pressure fluctuation associated with the fuel pump 31 injection of fuel in the pipe is attenuated to measure the average fuel pressure.

  FIG. 14 shows an example of the result of measuring the fuel oil pressure in the pipe by the pressure sensor 2a. When the pore 38a is not provided in the pressure extraction pipe 38, as shown by the reference numeral 91 in the figure, pressure fluctuation occurs in the range of 0.2 to 0.4 MPa. When the portion 38a is provided, the pressure fluctuation is improved as shown by reference numeral 92 in the figure, and the average fuel pressure can be measured. In this example, the pressure fluctuation can be reduced to 0.02 MPa or less by providing the pressure extracting pipe 38 with the narrow hole 38a having the restriction φ0.3. Thus, by attenuating the pressure fluctuation accompanying the injection of fuel in the pipe by the fuel pump 31, the detection accuracy of the fuel pressure and the durability of the pressure sensor 2a can be improved.

(2) Blow-by detection by crank chamber pressure When the pressure sensor 2a that measures the pressure in the crank chamber of the engine 11 detects the crank chamber pressure without considering the pressure fluctuations associated with the piston and crank motion in the crank chamber. Misdetection will occur frequently.

  FIG. 15 is a schematic diagram of a system for measuring the pressure in the crank chamber. As an example of the present invention, a fuel supply port 41 portion to a crank chamber (not shown) of the engine 11 is branched to provide a pressure extraction pipe having a restriction φ0.2. 42 is connected, and the pressure sensor 2 a is connected to the pressure extraction pipe 42. In other words, the pressure take-out pipe 42 is provided with a narrow hole portion 42a having a restriction φ of 0.2, thereby attenuating pressure fluctuations accompanying the movement of the piston and crank in the crank chamber and measuring the average crank chamber pressure.

  FIG. 16 shows the result of measuring the pressure in the crank chamber by the pressure sensor 2a. When the pore 42a is not provided in the pressure extraction pipe 42, as shown by the reference numeral 95 in the figure, pressure fluctuation occurs in the range of 0.0 to 0.9 kPa. In the case where the portion 42a is provided, as shown by the reference numeral 96 in the figure, the pressure fluctuation is improved, and the average crank chamber pressure can be measured. By attenuating the pressure fluctuation in this way, the detection accuracy of the crank chamber pressure and the durability of the pressure sensor 2a can be improved.

  Thereby, as shown in FIG. 17, the abnormality detection unit 6 determines the difference between the blowby gas amount obtained in advance and the pressure difference with respect to the pressure difference between the average crank chamber pressure and the atmospheric pressure outside the device. From the relationship, it is possible to estimate the blow-by gas amount with high accuracy, and it is possible to accurately perform failure diagnosis in the failure diagnosis unit 7 described later.

(3) Detection of the air flow rate of the radiator fan When detecting the air flow rate of the radiator fan 15 (see FIG. 3) of the internal combustion engine 10, the package generator shown in FIG. The air flow rate of the radiator fan 15 is estimated from the temperature difference from the air temperature detected by the temperature sensor 1a installed before or after, and an abnormality of the cooling system is detected. This is because, in a packaged generator, the amount of heat released from the internal combustion engine 10 or the radiator is proportional to the product of the air flow rate and the temperature difference (air temperature difference x air flow rate (engine + generator) heat release amount). Therefore, this relationship is used to utilize the fact that the air temperature difference increases when the air flow rate decreases due to a failure such as a radiator fan damage or a radiator clogging.

  FIG. 18 is a graph showing how the cooling system abnormality is detected from the air temperature difference. In this example, when the air flow rate decreases and the air temperature difference exceeds 8 ° C. (circled in the figure). Part), it is judged that the cooling system is abnormal. That is, it is considered that a failure such as damage to the radiator fan 15 or clogging of the radiator has occurred.

  By configuring the processing in the abnormality detection unit 6 as described above, it is possible to detect abnormality with higher accuracy, and to provide accurate abnormality detection data to the failure diagnosis unit 7 in the next stage. The diagnostic accuracy in the unit 7 can be improved.

  As for the abnormality detection processing other than that described above, the abnormality detection processing conventionally performed for the internal combustion engine 10 can also be used in the present invention. The description of the abnormality detection process based on the performance data of the pressure sensor, the vibration sensor, and the flow rate sensor is omitted.

<Description of Failure Diagnosis Unit 7>
The failure diagnosis unit 7 performs failure diagnosis using a diagnosis map stored in a diagnosis map storage unit 9a in which each detection item by the abnormality detection unit 6 is associated with a failure name of each part of the internal combustion engine 10, A diagnosis result is output using the guidance map stored in the guidance map storage unit 9b in which the failure name of each part of the internal combustion engine is associated with the countermeasure information corresponding to the failure name.

  FIG. 19 shows a data configuration example of the diagnostic map.

  This diagnostic map has a data structure in which failure names are listed in the vertical items, abnormality detection names are listed in the horizontal items, and the locations of the failure names estimated from the abnormality detection names are circled. .

  Here, the meaning of the contents described in each item of the abnormality detection name is summarized in a list form in FIG.

  The failure diagnosis unit 7 searches the diagnosis name stored in the diagnosis map storage unit 9a based on the detection result of the abnormality detection unit 6 for a failure name including the detection item determined to be abnormal, and uses this as the diagnosis result. Output as.

  Specifically, referring to the diagnosis map shown in FIG. 19, for example, when the abnormality detection items are three items of “exhaust exhaust temperature high”, “low fuel oil pressure”, and “high fuel flow rate”, the failure name is If “Fuel supply pipe oil leakage / breakage” is specified and the abnormality detection items are “Exhaust exhaust temperature high” and “Fuel oil pressure low”, the failure name is “Fuel supply pipe oil leakage / breakage”. , “Fuel feed pump abnormality / damage” and “Fuel strainer clogging” are selected.

  As described above, the failure diagnosis unit 7 according to the present embodiment searches for a failure name that matches the detection result of the abnormality detection unit 6 from a diagnosis map prepared in advance, so that a failure that comprehensively takes the detection result into consideration. I have a diagnosis.

  In addition, the failure diagnosis unit 7 further narrows down the corresponding failure names by taking into account the time change rate of the performance data of the detection item determined to be abnormal in addition to the detection result of the abnormality detection unit 6. Yes.

  For example, even when a decrease in fuel oil pressure is detected, if the rate of change is small (if it changes slowly), for example, the fuel strainer may be clogged, and if the rate of change is large (changes suddenly) Case), the fuel supply pipe may be leaked or damaged, or the fuel feed pump may be abnormal or damaged. In FIG. 19, a fault name having a large change rate is indicated by ◯, and a small fault name is indicated by ●.

  In this way, by adding the magnitude of the time change rate of the performance data, it is possible to distinguish between clogged fuel strainers that could not be distinguished until now, oil leakage or damage of the fuel feed pump, etc. Thus, the accuracy of failure diagnosis is further improved.

  FIGS. 21A to 21C show data configuration examples of the guidance map.

  This guidance map stores countermeasure information for each fault name, and includes items of defect factor, inspection, repair and maintenance.

  The failure diagnosis unit 7 extracts countermeasure information from the guidance map based on the failure name retrieved from the diagnosis map, and outputs it as a diagnosis result.

  Specifically, referring to the guidance map shown in FIG. 21, when the failure name retrieved from the diagnosis map is, for example, “fuel supply pipe oil leakage / damage” (see FIG. 21A), , “Fitting joint seal failure”, “Fracture breakage due to large vibration”, and “Damage due to large spill pressure”. ”Failure of fuel pipe, large vibration and crack of fuel pipe”, “Excessive spill pressure” and “Large vibration of fuel pipe and crack” are associated with each other. , “Packing replacement”, “Stabilization enhancement, piping replacement”, “Pressure reduction device installation: damping valve, etc.”, “Fuel piping reinforcement / resting, replacement” are associated with each other. As a result of the diagnosis, such a list itself may be displayed on a display unit (not shown), or may be printed out from an output unit such as a printer, or only the contents further narrowed down from the cause of failure are displayed. Alternatively, it may be printed out. In this case, contents such as “abnormal content, abnormality detection, final state” described at the top of each table may be displayed or printed out together. However, the output form is not limited to such a list form, and can be processed into various forms as necessary.

  In the above embodiment, the diagnosis map and the guidance map are configured as separate files and stored in separate storage units 9a and 9b. However, the diagnosis / guidance map is configured as a single file and stored in one storage unit. Can be stored.

-Description of the monitoring diagnosis system according to the present invention-
FIG. 1 is a functional block diagram showing a system configuration of a monitoring diagnosis system according to the present invention.

  This monitoring and diagnosis system is roughly classified into various sensor groups 1 to 4 provided at a detection part of the internal combustion engine 10, a surface vibration sensor group 61 provided at a detection part of the surface of the internal combustion engine 10, a time gate unit 62, The filter processing unit 63, the data collection unit 5, the abnormality detection unit 6, the failure diagnosis unit 7, the normal range value data storage unit 8, the diagnosis map storage unit 9a, and the guidance map storage unit 9b are configured.

  That is, the difference from the basic monitoring and diagnosis system shown in FIG. 2 is that a surface vibration sensor group 61 is added in addition to the various sensor groups 1 to 4, and a time gate unit 62 and a filter corresponding to the surface vibration sensor group 61 are added. The processing unit 63 is added, and the other configuration is exactly the same as the basic monitoring diagnosis system shown in FIG. However, since the surface vibration sensor group 61 is added, the abnormality detection processing in the abnormality detection unit 6 and the failure diagnosis processing in the failure diagnosis unit 7 are naturally processing that takes into account the detection result of the surface vibration sensor 61, and the normal range. The value data storage unit 8 also stores the normal range value (normal range value shown in FIG. 73) of the vibration performance data of the detection target portion set based on the operation data during normal operation of the internal combustion engine. The storage unit 9a also lists failure names corresponding to the detection results of the surface vibration sensor. Further, instead of adding the surface vibration sensor 61, the conventional vibration sensor group 4 attached to the inside of the internal combustion engine can be omitted.

  The time gate unit 62 sequentially takes in a vibration waveform signal from the surface vibration sensor 61a in units of a period of one combustion cycle of the cylinder, and at a predetermined timing that can further detect vibration of the detection target portion from the vibration waveform signal. This is a block for cutting out the waveform. The filter processing unit 63 is a block that performs frequency analysis on the data cut out by the time gate unit 62 and obtains an effective value RMS from the analysis result.

  In the monitoring / diagnosis system of the present invention, an important point is the position where the surface vibration sensor 61 is mounted on the engine surface, that is, the engine surface measurement position. Whether it can be detected, that is, a detection target part is determined.

  In this case, it is necessary to perform appropriate signal processing in order to accurately detect an internal abnormality based on the surface vibration of the engine without being affected by a signal from a portion other than the part to be detected. For this reason, in this pseudo-fault test, in order to prioritize the construction of a practical system using surface vibration analysis and to simplify the process without using complicated programming, the measurement position is optimized, We tried to measure minute changes with a simple process with high accuracy.

  The target organization is a 4-cycle engine. In the case of a 4-cycle engine, one combustion cycle corresponds to two crankshaft rotations (crank angle 720 degrees). As a result, the phenomenon can be captured in time series based on the timing chart within one cycle. That is, according to the procedure shown in the flowchart of FIG. 22, the target phenomenon can be processed in units of one cycle.

  Specifically, as shown in FIG. 23, the time data that is continuously input is triggered by the first cylinder combustion top signal (rotary top pulse: 1 FTDC) as a trigger so that processing can be performed for each combustion cycle. The data is divided (time T1 in FIG. 23), and a vibration waveform signal (hereinafter referred to as “vibration time data”) from the surface vibration sensor 61a is taken in one cycle of combustion (time T1). In this case, the vibration time data is further cut out from the vibration time data divided for each combustion cycle by a time gate unit 62 in a necessary section (time T2 in FIG. 23) on the basis of 1FTDC. Then, the filter processing unit 63 performs frequency analysis on the vibration time data cut out in this way, and obtains a partial sum (partial overall: effective value RMS) by applying a band pass filter on the frequency analysis result. . Then, the obtained RMS value is sent to the abnormality detection unit 6 in real time via the data collection unit 5.

  On the other hand, the normal range value data storage unit 8 stores data of normal range values as shown in FIG. 73, as already described in [Means for Solving the Problems]. The abnormality detection unit 6 detects the presence / absence of an abnormality in the detection target portion based on the normal range value data stored in the normal range value data storage unit 8 and the RMS value filtered by the filter processing unit 63.

<Verification of detection technology by the monitoring diagnosis system of the present invention>
As already explained, there are two merits in detecting abnormalities due to engine surface vibrations. The first of these is the addition of items detected by surface vibration sensors to items detected by conventional sensors. Thus, the diagnostic accuracy can be improved. In other words, failure names can be narrowed down by detecting surface vibrations.

  In the present embodiment, the contents are verified by performing a pseudo failure test described later.

  Here, as an example of the pseudo failure test, examples of “fuel supply pipe oil leakage and breakage” and “fuel pressure regulation valve abnormality” are shown. FIG. 24 shows a diagnostic map that defines the correspondence of detection items for detecting these fault names.

  As shown in the diagnostic map of FIG. 24, for any failure name, only the “exhaust temperature deviation” and “fuel pressure drop” are detected by the conventional sensor, and further failure names cannot be narrowed down.

  On the other hand, when the combustion imbalance occurs due to “abnormality of the fuel pressure regulation valve”, the vibration value of the 0.5th-order component of the rotation is as shown in the graph of the vibration change due to the combustion imbalance in FIG. To increase. Therefore, by adding the detection name “increase in block vibration” of the engine surface vibration to the detection result of the conventional sensor, as shown in the diagnosis map of FIG. 24, one failure name “fuel pressure regulation valve abnormality” is obtained. Can be narrowed down. In this way, it becomes possible to narrow down the fault names that could not be separated by the conventional sensor alone.

<Explanation of pseudo failure test>
Based on the above verification, the present inventors detect an abnormality inside the engine from the engine surface vibration in order to more specifically obtain the relationship between the vibration measurement position on the engine surface of the surface vibration sensor 61a and the detection target part. A pseudo failure test was conducted. The contents of the pseudo failure test will be described below.

  In this pseudo failure test, the following three items are the detection target items (detection target portions) of minute changes inside the engine by the surface vibration analysis of the engine.

(1) Valve system wear (2) Main bearing metal wear (3) Piston wear These items are difficult to detect with conventional sensors such as temperature, pressure, flow rate, etc. In addition, it is set based on what requires a lot of man-hours such as engine stoppage for maintenance.

  In this simulated fault test, one actual engine (details are omitted for specification) was prepared for the simulated fault test. Further, in order to detect abnormalities in the above three items by surface vibration of the engine, measurement was finally attempted at five vibration measurement positions shown in FIG. Specifically, there are five locations: the second cylinder head surface, the second cylinder lateral block surface, the second cylinder liner (inside), the fifth cylinder lateral block surface, and the fourth main bearing lateral block surface. However, as shown in FIG. 70, the sample engine is a 6-cylinder engine.

[Explanation of valve system wear detection test]
Assuming that the valve system wears, etc., the pseudo-failure test was conducted by increasing the valve clearance of the second cylinder from the normal state and seating outside the ramp area during seating. There are three vibration measurement positions: the second cylinder head surface, the second cylinder lateral block surface, and the fifth cylinder lateral block surface.

(1) When the surface vibration sensor 61a is attached to the surface of the second cylinder head FIG. 26 shows that the valve train when the surface vibration sensor 61a is attached to the surface of the second cylinder head (load 0%) is normal. FIG. 27 shows vibration time data for one combustion cycle when the valve train is worn when the surface vibration sensor 61a is attached to the surface of the second cylinder head (load 0%). is there. FIG. 28 shows a result of comparing the vibration time data at normal time shown in FIG. 26 with the vibration time data at the time of wear shown in FIG. 27 without a time gate, and FIG. 29 shows the result after frequency analysis. The comparison result of the RMS value at the normal time and the RMS value at the time of wear is shown.

  From these results, when the surface vibration sensor 61a is attached to the surface of the second cylinder head, the seating timing of the intake valve and the exhaust valve (circle portion indicated by reference numeral 110 in FIG. 27) is seen in the normal state. Absent vibration was detected. That is, when the surface vibration sensor 61a is attached to the surface of the second cylinder head, the valve system wear is not shown in FIG. 28 and FIG. 29 without applying the time gate at the seating timing of the valve system. I was able to capture this phenomenon.

  On the other hand, a frequency analysis was performed by taking a time gate at the timing of intake valve seating to obtain an RMS value. FIG. 30 shows the result of comparing the normal vibration time data shown in FIG. 26 with the wear vibration time data shown in FIG. 27 by applying a time gate at the intake valve seating timing. Shows the comparison result between the RMS value at normal time and the RMS value at the time of wear after frequency analysis with a time gate. As with the case where no time gate was applied, the valve system wear phenomenon was noticeable.

(2) When the surface vibration sensor 61a is attached to the surface of the second cylinder lateral block FIG. 32 shows a normal valve system when the surface vibration sensor 61a is attached to the surface of the second cylinder lateral block (load 0%). Fig. 33 shows vibration time data of one combustion cycle when the valve train is worn when the surface vibration sensor 61a is attached to the surface of the second cylinder horizontal block (load 0%). It is time data. FIG. 34 shows the result of comparing the normal vibration time data shown in FIG. 32 with the wear time vibration data shown in FIG. 33 without a time gate, and FIG. 35 shows the result after frequency analysis. The comparison result of the RMS value at the normal time and the RMS value at the time of wear is shown.

  From these results, when the surface vibration sensor 61a is attached to the surface of the second cylinder horizontal block, as in the second cylinder head described above, the seating timing of the intake valve and the exhaust valve (reference numeral in FIG. 33) In a round portion indicated by 120 and a round portion indicated by reference numeral 121 in FIG. 34, vibration that was not observed in the normal state was detected on the time data. However, when the RMS value is obtained by frequency analysis of the vibration of the second cylinder horizontal block without applying a time gate, as shown in FIG. 34 and FIG. Did not come out.

  Therefore, a frequency analysis was performed by applying a time gate at the timing of seating of the intake valve, and an RMS value was obtained. FIG. 36 shows the result of comparing the vibration time data at normal time shown in FIG. 32 and the vibration time data at the time of wear shown in FIG. 33 by applying a time gate at the seating timing of the intake valve. These show the comparison results of the RMS value at the normal time and the RMS value at the time of wear after frequency analysis. As shown in FIG. 36, the valve system wear phenomenon can be grasped at the second cylinder intake valve seating timing (the circle portion indicated by reference numeral 123 in FIG. 36), and the RMS value is obtained as shown in FIG. A significant difference was obtained.

(3) When the surface vibration sensor 61a is attached to the surface of the fifth cylinder horizontal block FIG. 38 shows a normal valve system when the surface vibration sensor 61a is attached to the surface of the fifth cylinder horizontal block (load 0%). 39 is vibration time data for one combustion cycle, and FIG. 39 shows vibration for one combustion cycle when the valve train is worn when the surface vibration sensor 61a is attached to the surface of the fifth cylinder horizontal block (load 0%). It is time data. FIG. 40 shows a result of comparison between normal vibration time data shown in FIG. 38 and wear vibration data shown in FIG. 39 without a time gate, and FIG. 41 shows a result after frequency analysis. The comparison result of the RMS value at the normal time and the RMS value at the time of wear is shown.

  From these results, when the surface vibration sensor 61a is attached to the surface of the fifth cylinder horizontal block, the time axis data is taken at the timing of seating of the intake valve and the exhaust valve (circled portion 130 in FIG. 39). However, there was no significant difference, but in order to compare with the RMS value, frequency analysis was first performed without a time gate. However, there was no significant difference as indicated by the circled portion 131 in FIG. 40 and FIG.

  Therefore, a frequency analysis was performed by taking a time gate at the timing of intake valve seating to obtain an RMS value. FIG. 42 shows a result of comparing the vibration time data at normal time shown in FIG. 38 with the vibration time data at the time of wear shown in FIG. 39 by applying a time gate at the timing of seating of the intake valve, and FIG. Shows the comparison result between the RMS value at normal time and the RMS value at the time of wear after frequency analysis with a time gate. As shown in FIGS. 42 and 43, no significant difference was obtained. Therefore, since the fifth cylinder side block is separated from the second cylinder, it is considered difficult to detect valve system wear of the second cylinder.

  The results obtained by measuring and analyzing the valve system wear of the second cylinder at the three locations are summarized in Table 1 below.

［主軸受メタル磨耗の検知試験の説明］
主軸受メタル磨耗が発生した場合を想定して、主軸受メタルとクランク軸とのクリアランスを広げるために、全ての主軸受メタル厚さを正常状態から−３０μｍ（オーバーレイ相当：磨耗限度) にし、疑似故障試験を実施した。振動計測位置は、第５気筒横ブロック、第４主軸受横ブロックの２箇所である。

[Explanation of main bearing metal wear detection test]
To increase the clearance between the main bearing metal and the crankshaft, assuming that main bearing metal wear has occurred, all main bearing metal thicknesses are set to -30 μm (equivalent to overlay: wear limit) from the normal state. A failure test was performed. There are two vibration measurement positions: the fifth cylinder lateral block and the fourth main bearing lateral block.

(1) When the surface vibration sensor 61a is attached to the surface of the fifth cylinder horizontal block FIG. 44 shows that the main bearing metal is normal when the surface vibration sensor 61a is attached to the surface of the fifth cylinder horizontal block (load 0%). 45 is vibration time data of one combustion cycle, and FIG. 45 shows vibration of one combustion cycle when the main bearing metal is worn when the surface vibration sensor 61a is attached to the surface of the fifth cylinder horizontal block (load 0%). It is time data. FIG. 46 shows a result of comparison between normal vibration time data shown in FIG. 44 and wear vibration data shown in FIG. 45 without a time gate, and FIG. 47 shows a result after frequency analysis. The comparison result of the RMS value at the normal time and the RMS value at the time of wear is shown.

  From these results, in the fifth cylinder horizontal block, no significant difference appeared in the phenomenon regardless of whether time axis data or frequency analysis was performed.

  On the other hand, when the main bearing metal is worn out, it is considered that a change appears in the vibration at the explosion timing in each cylinder. Therefore, a time gate is applied at the timing of the fourth cylinder explosion (4FTDC). FIG. 48 shows the result of comparing the normal vibration time data shown in FIG. 44 with the wear vibration time data shown in FIG. 45 by applying a time gate at the timing of the fourth cylinder explosion (4FTDC). FIG. 49 shows a comparison result between the RMS value at the normal time and the RMS value at the time of wear after the frequency analysis using the time gate. As apparent from FIGS. 48 and 49, the RMS value was obtained from the partial overall after frequency analysis, but no significant difference was obtained.

  From the above, since the state (wear) of the main bearing metal cannot be detected in the fifth cylinder horizontal block, it is necessary to perform evaluation at another measurement position while considering the structure of the mounting portion of the vibration sensor on the engine surface.

(2) When the surface vibration sensor 61a is attached to the surface of the fourth main bearing lateral block FIG. 50 shows the main bearing metal when the surface vibration sensor 61a is attached to the surface of the fourth main bearing lateral block (load 0%). Is vibration time data for one combustion cycle under normal conditions, and FIG. 51 shows combustion 1 when the main bearing metal is worn when the surface vibration sensor 61a is attached to the surface of the fourth main bearing lateral block (load 0%). This is vibration time data of the cycle. FIG. 52 shows a result of comparing the vibration time data at normal time shown in FIG. 50 with the vibration time data at the time of wear shown in FIG. 51 without a time gate, and FIG. 53 shows the result after frequency analysis. The comparison result of the RMS value at the normal time and the RMS value at the time of wear is shown.

  From these results, in the fourth main bearing lateral block, as shown in FIG. 51, the high-frequency signal increases as a whole in the time axis data, and in particular, the combustion timing of each cylinder (indicated by reference numeral 151 in FIG. 51). It was confirmed that the vibration increased remarkably in the round part). As a result, in the fourth main bearing lateral block, a significant difference was obtained during wear, as shown in FIGS. 52 and 53, without applying a time gate at the combustion timing of each cylinder.

  On the other hand, a time gate was applied at the combustion timing of the fourth cylinder. FIG. 54 shows the result of comparing the normal vibration time data shown in FIG. 50 with the wear time vibration data shown in FIG. 51 by applying a time gate at the combustion timing of the fourth cylinder. Shows the comparison result between the RMS value at normal time and the RMS value at the time of wear after frequency analysis with a time gate. As shown in FIG. 54 and FIG. 55, the phenomenon can be remarkably captured as in the case where the time gate is not applied.

  Furthermore, the following comparison was performed in order to investigate the possibility of detecting the change in the vibration of the other bearing by the vibration in the fourth bearing block.

(Comparison 1) Frequency analysis result after applying time gate in second cylinder explosion phase from signal of fourth bearing block (see FIG. 56)
(Comparison 2) Frequency analysis result after applying time gate in the second cylinder explosion phase from the signal of the second bearing block (see FIG. 57)
As a result, as shown in FIGS. 56 and 57, a spectrum having similar characteristics was obtained particularly in a wide band of a high frequency of 3 kHz or more. Thus, it was confirmed that it was possible to detect the vibration change of the other bearing from the fourth bearing block. That is, it becomes possible to detect the main bearing metal wear of other bearings by the vibration of the fourth bearing block located at the center of the block.

  The results obtained by measuring and analyzing the main bearing metal wear at the two locations are summarized in Table 2 below.

＜ピストン磨耗の検知試験の説明＞
ピストンが磨耗した場合を想定して、市場の実機（１５カ月運転）のピストンを回収し、疑似故障試験を実施した。磨耗量は３〜５μｍ程度であり、標準のピストン表面のデフリックコートの厚さが２０〜３０μｍ程度あることを考えると、今回供試品として用いたピストンの磨耗量はかなり小さいといえる。振動計測位置は、第２気筒シリンダライナ、第２気筒横ブロックの２箇所である。各々の振動計測位置については、ピストンとライナ間でのスラップにより発生する振動を計測することで磨耗による影響が検知できるとの想定のもとに決定した。

<Description of piston wear detection test>
Assuming that the piston is worn, the piston of the actual machine (15 months operation) was collected and a pseudo failure test was conducted. The amount of wear is about 3 to 5 μm, and the amount of wear of the piston used as the test sample this time can be said to be quite small considering that the thickness of the deflick coat on the standard piston surface is about 20 to 30 μm. There are two vibration measurement positions: the second cylinder cylinder liner and the second cylinder horizontal block. Each vibration measurement position was determined on the assumption that the influence of wear could be detected by measuring the vibration generated by the slap between the piston and the liner.

(1) When the surface vibration sensor 61a is attached to be embedded in the surface of the second cylinder cylinder liner The influence of direct slap was investigated with the signal of the second cylinder cylinder liner.

  FIG. 58 shows vibration time data for one combustion cycle when the piston is normal when the surface vibration sensor 61a is mounted in a form embedded in the surface of the second cylinder cylinder liner (load 0%), and FIG. This is vibration time data of one combustion cycle when the piston is worn when the vibration sensor 61a is attached in a form embedded in the surface of the second cylinder cylinder liner (load 0%). FIG. 60 shows the result of comparing the normal vibration time data shown in FIG. 58 and the wear vibration time data shown in FIG. 59 without a time gate.

  From these results, as shown in FIGS. 58 and 59, there was no significant difference in the time axis data through one combustion cycle. Furthermore, in order to compare with the RMS value, frequency analysis was performed without a time gate. As shown in FIG. 60, there was no significant difference.

  On the other hand, on the thrust side (large vibration side) of the second cylinder liner, slap is generated three times with the piston as follows in one combustion cycle.

a) Upper dead center of second cylinder explosion (No2FTDL)
b) Second cylinder overlap 60 ° before top dead center (60 ° before No2 FTDL)
c) Second cylinder overlap 110 ° after top dead center (110 ° after No2 FTDL)
Therefore, a frequency analysis was performed by applying a time gate at the timing of a slap generated three times in one cycle, and an RMS value was obtained. 61 shows the result of comparing the vibration time data at normal time shown in FIG. 58 and the vibration time data at the time of wear shown in FIG. 59 by applying a time gate at the timing of the top dead center of the second cylinder. 62, the vibration time data at normal time shown in FIG. 58 and the vibration time data at the time of wear shown in FIG. 59 are compared by applying a time gate at the timing of 60 ° before the second cylinder overlap top dead center. FIG. 63 shows the results of normal time vibration time data shown in FIG. 58 and wear time vibration time data shown in FIG. 59 at a time gate of 110 ° after the second cylinder overlap top dead center. The results of comparison are shown. Although there was a change at each timing, there was no common remarkable tendency on the frequency axis.

  The vibration of the liner is thought to measure the slap phenomenon itself against the wear of the piston, but at the same time, the influence on the surface vibration was confirmed by the second cylinder transverse block vibration.

(2) When the surface vibration sensor 61a is attached to the surface of the second cylinder horizontal block The influence of direct slap was investigated by the signal of the second cylinder cylinder liner.

  FIG. 64 shows vibration time data of one combustion cycle when the piston is normal when the surface vibration sensor 61a is attached to be embedded in the surface of the second cylinder horizontal block (load 0%), and FIG. 65 shows the surface vibration. This is vibration time data for one combustion cycle when the piston is worn when the sensor 61a is attached to the surface of the second cylinder horizontal block (load 0%). FIG. 66 shows the result of comparing the normal vibration time data shown in FIG. 64 with the wear time vibration data shown in FIG. 65 without a time gate. FIG. 67 shows the result after frequency analysis. The comparison result of the RMS value at the normal time and the RMS value at the time of wear is shown.

  From these results, there was no significant difference in the time axis data in the second cylinder horizontal block (see FIGS. 64 and 65). Further, in order to compare with the RMS value, there was no significant difference even if the frequency analysis was performed without the time gate (see FIGS. 66 and 67).

  Next, frequency analysis was performed by applying a time gate at the timing of the slap at the explosion top dead center, and the RMS value was obtained. FIG. 68 shows the result of comparing the vibration time data at normal time shown in FIG. 64 and the vibration time data at the time of wear shown in FIG. 65 by applying a time gate at the timing of slap at the explosion top dead center. FIG. 69 shows a comparison result between the RMS value at the normal time and the RMS value at the time of wear after the frequency analysis with the time gate.

  Even if a time gate is used, a wide band change on the frequency axis is not seen, but evaluation was possible in a narrow band. However, the difference in RMS value between normal and worn was small.

  In conclusion, although it is somewhat severe to evaluate the piston wear by the surface vibration of the second cylinder lateral block, if the normal range value shown in FIG. 73 is set narrow, it is also possible to evaluate the piston wear. Also, in this pseudo-fault test, as described above, the amount of wear of the piston used as the test sample was too small, so there was a high possibility that the phenomenon did not appear significantly, and the amount of wear of the piston was a little larger It is speculated that it is possible to capture the phenomenon.

  The results obtained by measuring and analyzing the piston wear at the two locations are summarized in Table 3 below.

表３中の「△」の評価の意味は、ピストン磨耗を評価するのは若干厳しいものの、正常範囲値を狭く設定する等すれば、ピストン磨耗を評価することも十分可能であることを示している。

The meaning of the evaluation of “△” in Table 3 indicates that although it is somewhat difficult to evaluate piston wear, it is possible to evaluate piston wear sufficiently if the normal range value is set narrow. Yes.

  As described above, the pseudo failure test was performed to verify the detection technology at each vibration measurement position in each of (1) valve system wear, (2) main bearing metal wear, and (3) piston wear. As a result, it was found that vibration data necessary for detecting each abnormality can be obtained at the vibration measurement positions shown in Table 4 below.

以上説明したように、本発明の監視診断システムによれば、表面振動解析により診断精度向上につながる検知技術と機関内部微小変化の検知技術を、疑似故障試験で検証し、従来センサによる監視診断システムと統合させることによって、監視診断システムの検知能力を飛躍的に伸ばすことができ、より高い安全性を得ることができた。

As described above, according to the monitoring diagnosis system of the present invention, the detection technology that improves the accuracy of diagnosis by surface vibration analysis and the detection technology of minute changes in the engine are verified by a pseudo failure test, and the monitoring diagnosis system using conventional sensors By integrating with the system, the detection capability of the monitoring and diagnosis system can be drastically increased and higher safety can be obtained.

It is a functional block diagram which shows the system configuration | structure of the monitoring diagnosis system concerning this invention. It is a functional block diagram which shows the system configuration | structure of the basic monitoring diagnostic system concerning this invention. It is a schematic structure figure showing an example of an internal-combustion engine in this embodiment. It is a graph which shows an example of the driving | operation initial data obtained at the time of normal driving | operation of an internal combustion engine. It is the graph which showed the normal range value calculated | required by calculation superimposed on the driving | operation initial data shown in FIG. It is a timing chart which shows the relationship between engine output (kW) and exhaust temperature. FIG. 7 is a graph in a case where an abnormality is detected in a state where the time axis is expanded and the moving average process is not performed on the relationship between the engine output and the exhaust temperature when the load fluctuation is large in the graph shown in FIG. It is a graph which shows the result of having performed the same number moving average process about both engine output and exhaust temperature. It is a graph which shows the result of having performed the weighted moving average process by making engine output and exhaust gas temperature into different moving average numbers. FIG. 7 is a graph showing a relationship between an engine output and an exhaust temperature when starting the engine in a case different from the graph shown in FIG. 6. It is a graph which shows the result of having performed the moving average process by the same number of both engine output and exhaust temperature. It is a graph which shows the result of having performed the weighted moving average process about both engine output and exhaust temperature. It is the schematic of the fuel supply system of an engine part. It is a graph which shows the result of having measured the fuel oil pressure in piping by a pressure sensor. It is the schematic of the system which measures the pressure of a crank chamber. It is a graph which shows the result of having measured the pressure of the crankcase with the pressure sensor. It is a graph which shows the relationship between a crank chamber pressure and blow-by gas amount. It is the graph which showed a mode that abnormality of a cooling system was detected from an air temperature difference. It is explanatory drawing which shows an example of a data structure of a diagnostic map. It is explanatory drawing which put together the meaning of the content described in each item of an abnormality detection name in list format. It is explanatory drawing which shows the data structural example of a guidance map. It is a flowchart of the characteristic part of the monitoring diagnostic system concerning this invention. It is a wave form diagram which shows the vibration time data (signal of a vibration waveform) input continuously. It is explanatory drawing which shows the other example of the data structure of a diagnostic map. It is a graph which shows the change of vibration by combustion imbalance. It is a wave form diagram which shows the vibration time data of 1 cycle of combustion when a valve system is normal when a surface vibration sensor is attached to the surface of a 2nd cylinder head (load 0%). It is a wave form diagram which shows the vibration time data of 1 cycle of combustion when a valve operating system is worn when a surface vibration sensor is attached to the surface of a 2nd cylinder head (load 0%). It is a wave form diagram which shows the result of having compared the vibration time data at the time of normal shown in FIG. 26 and the vibration time data at the time of wear shown in FIG. 27 without a time gate. It is a graph which shows the comparison result of the RMS value at the time of normal and the RMS value at the time of wear after frequency analysis. FIG. 28 is a waveform diagram showing a result of comparing the vibration time data at normal time shown in FIG. 26 and the vibration time data at wear shown in FIG. 27 by applying a time gate at the timing of seating of the intake valve. It is a graph which shows the comparison result of the RMS value at the time of normal, and the RMS value at the time of wear after performing frequency analysis using a time gate. It is a wave form diagram which shows the vibration time data of 1 cycle of combustion when a valve system is normal when a surface vibration sensor is attached to the surface of a 2nd cylinder horizontal block (load 0%). It is a wave form diagram which shows the vibration time data of 1 cycle of combustion when a valve operating system is worn when a surface vibration sensor is attached to the surface of a 2nd cylinder horizontal block (load 0%). It is a wave form diagram which shows the result of having compared the vibration time data at the time of normal shown in FIG. 32, and the vibration time data at the time of wear shown in FIG. 33 without a time gate. It is a graph which shows the comparison result of the RMS value at the time of normal and the RMS value at the time of wear after frequency analysis. FIG. 34 is a waveform diagram showing the result of comparing the normal vibration time data shown in FIG. 32 with the wear vibration time data shown in FIG. 33 by applying a time gate at the timing of seating of the intake valve. It is a graph which shows the comparison result of the RMS value at the time of normal and the RMS value at the time of wear after frequency analysis. It is a wave form diagram which shows the vibration time data of 1 cycle of combustion when a valve operating system is normal when a surface vibration sensor is attached to the surface of a 5th cylinder horizontal block (load 0%). It is a wave form diagram which shows the vibration time data of 1 cycle of combustion when a valve operating system is worn when a surface vibration sensor is attached to the surface of a 5th cylinder horizontal block (load 0%). It is a wave form diagram which shows the result of having compared the vibration time data at the time of normal shown in FIG. 38, and the vibration time data at the time of wear shown in FIG. 39 without a time gate. It is a graph which shows the comparison result of the RMS value at the time of normal and the RMS value at the time of wear after frequency analysis. It is a wave form diagram which shows the result of having compared the vibration time data at the time of normal shown in FIG. 38, and the vibration time data at the time of wear shown in FIG. 39 using a time gate at the timing of seating of the intake valve. It is a graph which shows the comparison result of the RMS value at the time of normal, and the RMS value at the time of wear after performing frequency analysis using a time gate. It is a wave form diagram which shows the vibration time data of 1 cycle of combustion when the main bearing metal is normal when a surface vibration sensor is attached to the surface of the fifth cylinder horizontal block (load 0%). It is a wave form diagram which shows the vibration time data of 1 cycle of combustion at the time of abrasion of the main bearing metal when a surface vibration sensor is attached to the surface of a 5th cylinder horizontal block (load 0%). It is a wave form diagram which shows the result of having compared the vibration time data at the time of normal shown in FIG. 44, and the vibration time data at the time of wear shown in FIG. 45 without a time gate. It is a graph which shows the comparison result of the RMS value at the time of normal and the RMS value at the time of wear after frequency analysis. It is a wave form diagram which shows the result of having compared the vibration time data at the time of normal shown in FIG. 44, and the vibration time data at the time of wear shown in FIG. 45 by applying a time gate at the timing of the fourth cylinder explosion (4FTDC). It is a graph which shows the comparison result of the RMS value at the time of normal, and the RMS value at the time of wear after performing frequency analysis using a time gate. It is a wave form diagram which shows the vibration time data of 1 cycle of combustion when the main bearing metal is normal when a surface vibration sensor is attached to the surface of the 4th main bearing horizontal block (load 0%). It is a wave form diagram which shows the vibration time data of 1 cycle of combustion at the time of abrasion of the main bearing metal when the surface vibration sensor 61a is attached to the surface of the 4th main bearing horizontal block (load 0%). It is a wave form diagram which shows the result of having compared the vibration time data at the time of normal shown in FIG. 50, and the vibration time data at the time of wear shown in FIG. 51 without a time gate. It is a graph which shows the comparison result of the RMS value at the time of normal and the RMS value at the time of wear after frequency analysis. FIG. 52 is a waveform diagram showing a result of comparing the vibration time data at the normal time shown in FIG. 50 and the vibration time data at the time of wear shown in FIG. 51 by applying a time gate at the combustion timing of the fourth cylinder. It is a graph which shows the comparison result of the RMS value at the time of normal, and the RMS value at the time of wear after performing frequency analysis using a time gate. It is a wave form diagram which shows the frequency analysis result after applying a time gate by the 2nd cylinder explosion phase from the signal of the 4th bearing block. It is a wave form diagram which shows the frequency analysis result after applying a time gate by the 2nd cylinder explosion phase from the signal of the 2nd bearing block. It is a wave form diagram which shows the vibration time data of 1 cycle of combustion when a piston is normal when a surface vibration sensor is attached so that it may embed in the inside of the surface of a 2nd cylinder liner (load 0%). It is a wave form diagram which shows the vibration time data of 1 cycle of combustion at the time of wear of a piston when a surface vibration sensor is attached in the form embedded in the inside of the surface of a 2nd cylinder cylinder liner (load 0%). FIG. 60 is a waveform diagram showing a result of comparison between normal vibration time data shown in FIG. 58 and wear vibration time data shown in FIG. 59 without a time gate. FIG. 60 is a waveform diagram showing a result of comparing the vibration time data at normal time shown in FIG. 58 and the vibration time data at the time of wear shown in FIG. 59 by applying a time gate at the timing of the second cylinder explosion top dead center. 58 is a waveform diagram showing a result of comparing the vibration time data at normal time shown in FIG. 58 and the vibration time data at the time of wear shown in FIG. 59 by applying a time gate at a timing of 60 ° before the second cylinder overlap top dead center. It is. 58 is a waveform diagram showing a result of comparing the normal vibration time data shown in FIG. 58 and the wear vibration time data shown in FIG. 59 by applying a time gate at a timing of 110 ° after the second cylinder overlap top dead center. It is. It is a wave form diagram which shows the vibration time data of 1 cycle of combustion when a piston is normal when a surface vibration sensor is attached in the form embedded in the surface of a 2nd cylinder horizontal block (load 0%). It is a wave form diagram which shows the vibration time data of 1 cycle of combustion at the time of abrasion of a piston when a surface vibration sensor is attached in the form embedded in the surface of a 2nd cylinder horizontal block (load 0%). FIG. 66 is a waveform diagram showing a result of comparison between normal vibration time data shown in FIG. 64 and wear vibration time data shown in FIG. 65 without a time gate. It is a graph which shows the comparison result of the RMS value at the time of normal and the RMS value at the time of wear after frequency analysis. FIG. 66 is a waveform diagram showing a result of comparing the normal vibration time data shown in FIG. 64 with the wear vibration time data shown in FIG. 65 by applying a time gate at the timing of the slap at the explosion top dead center. It is a graph which shows the comparison result of the RMS value at the time of normal, and the RMS value at the time of wear after performing frequency analysis using a time gate. It is the general view seen from the front of the 6-cylinder engine which is an internal combustion engine which shows the measurement position for detecting abnormality by the surface vibration of an engine by a pseudo failure test. It is a wave form diagram which shows each measurement result of load 0%, 50%, and 100% when a measurement position is the surface of a 2nd cylinder horizontal block. It is a graph which shows the correlation of an engine output (electric power) and each measured value. It is the graph which showed the normal range value calculated | required by calculation superimposed on the correlation data of the engine output (electric power) and each measured value shown in FIG.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Temperature sensor group 1a Temperature sensor 2 Pressure sensor group 2a Pressure sensor 3 Flow rate sensor group 3a Flow rate sensor 4 Vibration sensor group 4a Vibration sensor 5 Data collection part 6 Abnormality detection part 7 Fault diagnosis part 8 Normal range value data storage part 9a Diagnostic map Storage unit 9b Guidance map storage unit 10 Internal combustion engine 11 Engine unit 12 Generator 13 Air cleaner 14 Turbocharger (T / C)
15 Radiator fan 20 Housing 21 Suction port 22 Outlet port 31 Fuel pump (FO pump)
32 Feed pump 33 FO filter 34 1st piping 35 2nd piping 36 3rd piping 37 4th piping 38 Pressure extraction pipe 41 Oil supply port 42 Pressure extraction pipe 61 Surface vibration sensor group 61a Surface vibration sensor 62 Time gate part 63 Filter processing part

Claims (4)

In a monitoring and diagnosis system for an internal combustion engine,
First detection means for detecting temperature, pressure and the like attached to each detection site inside the internal combustion engine;
Second detection means for detecting surface vibrations attached to one or more vibration measurement sites on the surface of the internal combustion engine;
Normal state data to match the moving average processing time changes in the engine output by the facilities Succoth to the initial stage of operation data detected by the first detecting means at the time of normal operation after the engine is installed The normal range value of the performance data in which the allowable range is set in the normal time data is stored in advance , and the vibration detected by each of the second detection means during normal operation after the internal combustion engine is installed Normal range value data storage means for storing in advance a normal range value in which a tolerance range is set in normal time data obtained by correlation between the value and the engine output ;
A time gate that sequentially captures the vibration waveform signal by the second detection means in units of one cycle of combustion of the cylinder and cuts out the signal waveform at a predetermined timing at which the vibration of the detection target portion can be further detected from the vibration waveform signal. Means,
Filter processing means for frequency-analyzing the data cut out by the time gate means and obtaining an effective value from the analysis result;
Comparing the performance data obtained by detecting the value of each detection part by the first detection means by a direct or indirect method and the normal range value stored in the normal range value data storage means; Thus, when the performance data obtained from each of the first detection means deviates from the normal range value, an abnormality is detected, and the effective value obtained by the filter processing means and the normal range value data storage means An abnormality detection means for detecting an abnormality when the effective value is out of the normal range value by comparing the stored normal range value of the vibration ;
A monitoring diagnosis system comprising failure diagnosis means for diagnosing a failure location and a failure content of the internal combustion engine based on a detection result of the abnormality detection means. The vibration measurement part to which the surface vibration sensor is attached is one place of a main bearing horizontal block of an arbitrary cylinder, and the detection target part by the surface vibration sensor attached to this part is a main bearing metal of each cylinder. The monitoring diagnosis system according to claim 1, wherein the monitoring diagnosis system is a vibration of a portion . The monitoring / diagnosis system according to claim 2, wherein the vibration measurement site is a main bearing lateral block of a cylinder located in a central portion of the plurality of cylinders . The vibration measurement part to which the surface vibration sensor is attached is one part of a lateral block of a cylinder, and the detection target part by the surface vibration sensor attached to this part is vibration of a piston part of the cylinder. The monitoring diagnosis system according to Item 1 .

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