A device health state analysis method and device health state analysis apparatus

Abstract

The application discloses a device health state analysis method and device health state analysis device, and the method comprises the following steps: acquiring point inspection data of a single device for several times within a preset time; judging whether there is point inspection data not meeting a preset standard in the point inspection data for all times according to amplitude data and temperature data of all measuring points; if all the point inspection data meets the preset standard, selecting point inspection data including maximum amplitude data as first target point inspection data; determining the health degree of each measuring point in the first target point inspection data within the preset time according to the amplitude data, the temperature data, a first amplitude weight, a first temperature weight, an actual operation time and a device maintenance time corresponding to each measuring point in the first target point inspection data; and determining the health degree of the single device within the preset time according to the total number of measuring points in the first target point inspection data and the health degree of each measuring point within the preset time, so that the health state of the measuring points and the device is analyzed.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of equipment health assessment, in particular to an equipment health state analysis method and an equipment health state analysis device. BACKGROUND

[0002] During the use of equipment in different environments and continuously, the performance of the parts and the whole will gradually change due to use and natural reasons, and cannot reach the original state. Generally speaking, as shown in the P-F curve, A is the failure initiation point, P is the potential failure point, F is the functional failure point, T is the time interval, and the equipment performance degradation process meets the curve representing the development from potential failure to functional failure. Figure 1

[0003] The existing point inspection system mainly forms a report by collecting the vibration, temperature and running parameters of the equipment, manually checks the report data, and judges whether the equipment has a fault and the severity of the fault through the threshold alarm of each parameter. However, there is no comprehensive evaluation method for analyzing the health state of the equipment, and different equipment cannot be compared in multiple dimensions. Therefore, there is an urgent need for a new equipment health state analysis method to more comprehensively and accurately analyze the state of the equipment. SUMMARY

[0004] The present application aims to provide an equipment health state analysis method and an equipment health state analysis device to integrate multiple-dimensional parameters of point inspection data, calculate the health degree of the measuring point within a preset time, and further realize comprehensive and accurate health state analysis of the equipment according to multiple measuring points.

[0005] The first aspect of the present application discloses an equipment health state analysis method, comprising the following steps:

[0006] Obtaining point inspection data of a single equipment within a preset time, each equipment comprising a plurality of measuring points;

[0007] Each point inspection data comprises amplitude data, temperature data and actual running time of all measuring points;

[0008] Judging whether there is point inspection data that does not meet the preset standard in all point inspection data according to the amplitude data and the temperature data of all measuring points;

[0009] If all point inspection data meets the preset standard, selecting point inspection data comprising the largest amplitude data as the first target point inspection data;

[0010] Determining the health degree of each measuring point in the first target point inspection data within the preset time according to the amplitude data, the temperature data, the first amplitude weight, the first temperature weight, the actual running time and the equipment maintenance time of each measuring point in the first target point inspection data.​

[0011] According to the total number of measuring points in the first target point inspection data and the health degree of each measuring point in the preset time, the health degree of the single device in the preset time is determined.

[0012] Further, the device health state analysis method further comprises the following steps:

[0013] If there is at least one point inspection data that does not meet the preset standard, the latest measured point inspection data is selected as the second target point inspection data from all point inspection data that does not meet the preset standard;

[0014] According to the total number of measuring points in the second target point inspection data, the number of measuring points in the second target point inspection data that does not meet the preset standard, the second amplitude weight, and the second temperature weight, the health degree of the single device in the preset time is determined.

[0015] Preferably, according to the respective amplitude data and temperature data of each measuring point in the first target point inspection data, the first amplitude weight, the first temperature weight, the actual running time, and the device maintenance time, the health degree of each measuring point in the first target point inspection data in the preset time is determined, comprising:

[0016] According to the respective amplitude data of each measuring point in the first target point inspection data and the preset amplitude health degree level, the initial amplitude health degree V of the measuring point is determined, and according to the respective temperature data of each measuring point in the first target point inspection data and the preset temperature health degree level, the initial temperature health degree T of the measuring point is determined;

[0017] According to formula (1), the health degree of each measuring point in the target point inspection data in the preset time is calculated;

[0018] G = x1*(V-Time*V d )+y1*(T-Time*T d ) Formula (1)

[0019] Wherein, G is the health degree of each measuring point in the target point inspection data in the preset time, V d is the difference value of the preset adjacent amplitude health degree level, T d is the difference value of the preset adjacent temperature health degree level, Time is the use and repair time coefficient of the device determined according to the actual running time and the device maintenance time, V-Time*V d is the final amplitude health degree of each measuring point in the preset time, T-Time*T d is the final temperature health degree of each measuring point in the preset time, x1 is the first amplitude weight, and y1 is the first temperature weight.

[0020] Preferably, the use and repair time coefficient Time of the device is determined according to formula (2).

[0021]

[0022] wherein Time1 is the maintenance time of the equipment, and Time2 is the actual running time of the equipment.

[0023] Preferably, determining the health degree of the single equipment in the preset time according to the total number of the measuring points in the first target point inspection data and the health degree of each measuring point in the preset time comprises calculating the health degree of the single equipment in the preset time by using the average value of the health degrees of all the measuring points in the first target point inspection data in the preset time.

[0024] and / or,

[0025] According to the total number of the measuring points in the second target point inspection data, the number of the measuring points not meeting the preset standard in the second target point inspection data, the second amplitude weight, and the second temperature weight, the health degree of the single equipment in the preset time is determined by calculating the health degree of the single equipment in the preset time according to formula (3).

[0026]

[0027] The preset standard comprises an amplitude preset standard and a temperature preset standard.

[0028] wherein P is the health degree of the single equipment in the preset time, V min is the health degree corresponding to the preset minimum amplitude health degree level, T min is the health degree corresponding to the preset minimum temperature health degree level, a is the total number of the measuring points in the target point inspection data, b is the number of the measuring points not meeting the amplitude preset standard in the target point inspection data, c is the number of the measuring points not meeting the temperature preset standard in the target point inspection data, x2 is the second amplitude weight, and y2 is the second temperature weight.

[0029] Preferably, the equipment health state analysis method further comprises:

[0030] When the absolute difference between the initial amplitude health degree and the initial temperature health degree is less than the preset value, the preset amplitude weight is used as the first amplitude weight, and the preset temperature weight is used as the first temperature weight.

[0031] and / or,

[0032] When the absolute difference between the initial amplitude health degree and the initial temperature health degree is greater than the preset value, the preset amplitude weight and the preset temperature weight are dynamically adjusted according to the size relationship between the initial amplitude health degree and the initial temperature health degree and the size of the absolute difference to obtain the first amplitude weight and the first temperature weight.

[0033] Preferably, the dynamic adjustment of the preset amplitude weight and the preset temperature weight according to the size relationship and the absolute difference between the initial amplitude health degree and the initial temperature health degree to obtain the first amplitude weight and the first temperature weight comprises:

[0034] determining a grade difference according to a preset amplitude health degree corresponding to the initial amplitude health degree and a preset temperature health degree corresponding to the initial temperature health degree;

[0035] determining a target weight adjustment value corresponding to the grade difference according to a preset grade difference and weight adjustment value corresponding relationship, and adjusting the preset amplitude weight and the preset temperature weight in opposite directions according to the target weight adjustment value to obtain the first amplitude weight and the first temperature weight.

[0036] Preferably, the preset amplitude weight and the preset temperature weight are determined by the following process:

[0037] obtaining historical amplitude data, historical temperature data, historical actual running time, historical equipment maintenance time and historical health degree of all measuring points in historical point inspection data of sample equipment;

[0038] determining historical initial amplitude health degrees of the measuring points according to the historical amplitude data and the preset amplitude health degree corresponding to each measuring point, and determining historical initial temperature health degrees of the measuring points according to the historical temperature data and the preset temperature health degree corresponding to each measuring point; determining a use and maintenance time coefficient of the equipment according to the historical actual running time and the historical equipment maintenance time;

[0039] inputting the historical initial amplitude health degrees, the historical initial temperature health degrees, the use and maintenance time coefficient of the equipment as sample input data, and the historical health degree as sample output data into a preset network model for training to obtain preset amplitude weight and preset temperature weight corresponding to the target network model.

[0040] Preferably, the first amplitude weight is the same as the second amplitude weight, and the first temperature weight is the same as the second temperature weight.

[0041] The second aspect of the present application discloses a device health state analysis device, comprising:

[0042] a point inspection data acquisition unit configured to acquire all point inspection data of a single device within a preset time; each point inspection data comprises amplitude data, temperature data and actual running time of all measuring points;

[0043] a point inspection data judgment unit configured to determine whether there is point inspection data not meeting a preset standard in all point inspection data according to the amplitude data and the temperature data of all measuring points;

[0044] The point inspection data selection unit is configured to select, when all the point inspection data meet the preset standard, point inspection data with the largest amplitude value as the first target point inspection data from all the point inspection data.

[0045] The measuring point health degree determination unit is configured to determine, according to the amplitude data, the temperature data, the first amplitude weight, the first temperature weight, the actual running time and the device maintenance time of each measuring point in the first target point inspection data, the health degree of each measuring point in the first target point inspection data within the preset time.

[0046] The device health degree determination unit is configured to determine, according to the number of measuring points in the first target point inspection data and the health degree of each measuring point within the preset time, the health degree of a single device within the preset time.

[0047] The device health analysis method provided in the present application obtains amplitude data, temperature data and actual running time of all measuring points in several times of point inspection data of a single device within a preset time, judges whether there is point inspection data not meeting the preset standard according to the amplitude data and the temperature data of all the measuring points, selects point inspection data including the largest amplitude data as the first target point inspection data if all the point inspection data meet the preset standard, determines the health degree of each measuring point in the first target point inspection data within the preset time according to the amplitude data, the temperature data, the first amplitude weight, the first temperature weight, the actual running time and the device maintenance time of each measuring point in the first target point inspection data, and further determines the health degree of a single device within the preset time in combination with the total number of measuring points. The health state of the measuring points and the device is analyzed by comprehensively analyzing the amplitude data, the temperature data and the actual running time of the measuring points in multiple dimensions, the health state of the device is reflected by the health degree, the information management of the device health is realized, and the user can more intuitively know whether the device is healthy.

[0048] Further, when the absolute difference between the initial amplitude health degree and the initial temperature health degree is greater than the preset value, the preset amplitude weight and the preset temperature weight are dynamically adjusted according to the size relationship between the initial amplitude health degree and the initial temperature health degree and the size of the absolute difference to obtain the first amplitude weight and the first temperature weight, thereby avoiding the problem that when a characteristic parameter (such as the initial amplitude health degree or the initial temperature health degree) deviates seriously from the normal value, the overall health degree finally calculated is still in the normal range due to the small weight coefficient of the characteristic parameter, and the real health state of the measuring point cannot be accurately reflected, and the balance between the characteristic parameters is improved. BRIEF DESCRIPTION OF DRAWINGS

[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed in the embodiments. Obviously, the drawings described below only illustrate some of the embodiments of the present application, and all other drawings obtained by those of ordinary skill in the art without creative effort based on these drawings belong to the protection scope of the present application.

[0050] Figure 1 is a P-F curve diagram of a device performance degradation process provided by the present application;

[0051] Figure 2 is a flowchart of an embodiment of a device health state analysis method provided by the present application;

[0052] Figure 3 is a flowchart of an embodiment of a device health state analysis method provided by the present application, which acquires temperature value data of a measuring point;

[0053] Figure 4 is a flowchart of an embodiment of a device health state analysis method provided by the present application, which acquires air temperature value data of a measuring point;

[0054] Figure 5 is a temperature alarm flowchart of an embodiment of a device health state analysis method provided by the present application;

[0055] Figure 6 is a schematic diagram of a computer device provided by another embodiment of the present application. DETAILED DESCRIPTION

[0056] In order to make the objects, technical solutions and advantages of the present application clearer, the following will further specifically describe the present application with reference to the embodiments and the accompanying drawings. It should be understood that these descriptions are only exemplary and are not intended to limit the scope of the present application. In addition, in the following description, the description of the known structures and technologies is omitted to avoid unnecessary confusion of the concepts of the present application.

[0057] The technical solutions of the present application will be described clearly and completely below with reference to the accompanying drawings. Obviously, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort belong to the protection scope of the present application.

[0058] In the description of the present application, it should be noted that the directions or positional relationships belonging to "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer" and the like are the directions or positional relationships described based on the drawings, which are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the present application. In addition, "first", "second" are only for the purpose of description and cannot be understood as indicating or implying relative importance.

[0059] In the description of the present application, it should be noted that, unless otherwise explicitly specified and limited, "mounting", "connection", "connection" should be understood in a broad sense, for example, it can be fixedly connected, or it can be detachably connected, or integrally connected; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium; it can be the communication inside two elements. For those skilled in the art, the specific meaning of the above-mentioned terms in the present application can be understood according to the specific circumstances.

[0060] In addition, the technical features involved in the different embodiments of the present application described below can be combined with each other as long as there is no conflict.

[0061] At present, the vibration, temperature and running time of the measuring points of single equipment in the factory are measured, but these data are not integrated, there is no analysis method for comprehensively evaluating the health status of the equipment, so it is impossible to compare the health conditions of different equipment in multiple dimensions. Based on this, the present application provides an equipment health analysis method and an equipment health status analysis device, wherein the method is to obtain the amplitude data, temperature data and actual running time of all measuring points in several times of point inspection data of a single equipment within a preset time, determine whether there is point inspection data that does not meet the preset standard in the point inspection data according to the amplitude data and temperature data of all measuring points; if all point inspection data meets the preset standard, select the point inspection data with the largest amplitude value in all point inspection data as the first target point inspection data; determine the health degree of each measuring point in the first target point inspection data within the preset time according to the amplitude data, temperature data, first amplitude weight, first temperature weight, actual running time and equipment maintenance time corresponding to each measuring point in the first target point inspection data, and further determine the health degree of the single equipment within the preset time in combination with the total number of measuring points. By comprehensively analyzing the amplitude data, temperature data and actual running time of the measuring points in multiple dimensions, the analysis of the health status of the measuring points and the equipment as a whole is realized, the health status of the equipment is reflected by the health degree, the information management of the equipment health is realized, and the user can more intuitively understand whether the equipment is healthy. The present application will be described in detail through the embodiments.

[0062] Embodiment one

[0063] The application provides an embodiment of a device health state analysis method, point inspection is performed on all measuring points of a single device, the point inspection result is taken as a data source, the health degree of the measuring points within a preset time is calculated based on the point inspection data, and the health state of the device is analyzed through the health degree of the measuring points.

[0064] A device health state analysis method, as shown in the figure, the method comprises the following steps: Figure 2

[0065] Obtain point inspection data of a single device within a preset time, each device comprises a plurality of measuring points; wherein, the point inspection data of each time comprises amplitude data, temperature data and actual running time of all measuring points.

[0066] Specifically, in this embodiment, the preset time is set to one day.

[0067] In order to analyze the state of the device, the operating parameters of the device need to be obtained first, specifically through device point inspection to obtain the operating parameters, point inspection refers to selecting at least one measuring point of the device and detecting the operating parameters of the measuring point. In order to make the final analysis result more accurate, in this application, multiple point inspections are taken on the device every day, and multiple measuring points are selected for point inspection each time.

[0068] For example, obtain the amplitude data of three measuring points in three directions (X-axis direction, Y-axis direction and Z-axis direction), the temperature data of the three measuring points respectively and the actual running time. The measuring direction of the measuring point data in this application is not limited, and the amplitude data of the measuring point in any direction can be obtained. After obtaining the multiple point inspection data of the device in one day, the health state of the device can be analyzed according to the point inspection data. In order to make the analysis more accurate and the calculation less, this application provides an optimal analysis method, specifically, whether there is point inspection data that does not meet the preset standard in all the point inspection data is judged according to the amplitude data and the temperature data of all the measuring points.

[0069] In order to measure the operating parameters, in this application, the health degree level standard is divided for each operating parameter. When the operating parameter is in a relatively extreme level, it represents that the state of the device is very good or very bad. When it is in a very bad level, it represents that the state of the device is in a critical condition, and this kind of parameter should be analyzed first and focused on. Therefore, in this application, the health degree level standard is divided for each operating parameter, and whether the level standard of the point inspection data meets the preset standard is judged.

[0070] ​The preset standard can be, for example, that the point inspection data does not generate a preset level of alarm, such as a D-level alarm. An alarm is usually used to remind personnel to pay attention to the state of the equipment to prevent accidents or prevent further damage. The alarm can be based on various sensors, monitoring equipment, and equipment control systems to monitor the running state of the equipment in real time, and trigger an alarm when an abnormal situation is detected. Common alarms include, but are not limited to, equipment failure, operation error, safety risk, and system anomaly.

[0071] In an embodiment of the present application, the equipment to be inspected is a large machine with a rated power greater than 300 kW and less than 50 MW, and a motor with a shaft height H≥315 mm, see Table 1 for amplitude classification standards. Before starting the inspection, the support type, physical characteristics, and mechanical structure characteristics of the equipment are first determined to have a comprehensive understanding of the equipment and improve the accuracy of the inspection.

[0072]

[0073]

[0074] Table 1

[0075] As shown in Table 1, A1, B1, C1, and D1 are preset amplitude health levels. The boundary between A1 and B1 corresponds to a displacement root mean square value of 29 μm, which is the boundary value between A1 and B1. In the present application, the range of displacement root mean square values is used to estimate the amplitude health level of the vibration amplitude of the measuring point.

[0076] When the support type is rigid, the displacement root mean square value interval corresponding to A1 is (0, 29], the displacement root mean square value interval corresponding to B1 is (29, 57], the displacement root mean square value interval corresponding to C1 is (57, 90], and the displacement root mean square value interval corresponding to D1 is (90, ∞). When the support type is flexible, the displacement root mean square value interval corresponding to A1 is (0, 45], the displacement root mean square value interval corresponding to B1 is (45, 90], the displacement root mean square value interval corresponding to C1 is (90, 140], and the displacement root mean square value interval corresponding to D1 is (140, ∞). The amplitude data of the measuring point is compared with the above intervals to obtain the interval to which the amplitude data of the measuring point belongs, and then the amplitude health level corresponding to the amplitude data of the measuring point is obtained.

[0077] For example, the support type of the equipment under inspection is rigid, the sensor measures the amplitude data of a measuring point in the inspection data as 14 μm, and the amplitude health degree level of the measuring point is A1 compared with the interval of the root mean square value of displacement, representing that the vibration state of the measuring point is extremely excellent. In another example, the support type of the equipment under inspection is flexible, the sensor measures the amplitude data of a measuring point in the inspection data as 155 μm, and the amplitude health degree level of the measuring point is D1 compared with the interval of the root mean square value of displacement, representing that the vibration state of the measuring point is extremely poor and needs emergency maintenance.

[0078]

[0079] Table 2

[0080] As shown in Table 2, B2, C2 and D2 are preset temperature health degree levels. Among them, the region boundary B2 / C2 corresponds to a temperature value of current air temperature value + 50 ℃, representing that the boundary value of B2 and C2 levels is current air temperature value + 50 ℃. In the present application, the range of temperature values is used to estimate the temperature health degree level of the temperature value of the measuring point. The temperature value interval corresponding to B2 is (current air temperature value, current air temperature value + 50], the temperature value interval corresponding to C2 is (current air temperature value + 50, current air temperature value + 85], and the temperature value interval corresponding to D2 is (current air temperature value + 85, ∞). The temperature data of the measuring point is compared with the above interval to obtain the interval to which the temperature data of the measuring point belongs, and further obtain the temperature health degree level corresponding to the temperature data of the measuring point.

[0081] For example, assuming that the current air temperature value is 28 ℃, the sensor measures the temperature data of a measuring point in the inspection data as 50 ℃, and the temperature health degree level of the measuring point is B2 compared with the temperature value interval, representing that the temperature state of the measuring point is extremely excellent. In another example, assuming that the current air temperature value is 30 ℃, the sensor measures the temperature data of a measuring point in the inspection data as 130 ℃, and the temperature health degree level of the measuring point is D2 compared with the temperature interval, representing that the temperature state of the measuring point is extremely poor and needs cooling treatment urgently.

[0082] Therefore, by judging whether the inspection data meets the preset standard, the abnormal situation existing in the equipment can be found in time. For example, the amplitude or temperature of a measuring point exceeds the set threshold, which may mean that the equipment has a fault or a risk of health state decline, and timely discovery of abnormal situation can effectively avoid the loss caused by equipment failure. And after judgment, two different situations often occur, and corresponding maintenance means and improvement measures are taken according to different situations to improve the reliability and service life of the equipment.

[0083] If all the point inspection data meets the preset standard, i.e. no data seriously deviates from the normal state, the point inspection data with the largest amplitude value is selected as the first target point inspection data from all the point inspection data; the health degree of each measuring point in the first target point inspection data in one day is determined according to the amplitude data, the temperature data, the first amplitude weight, the first temperature weight, the actual running time and the equipment maintenance time corresponding to each measuring point in the first target point inspection data; and the health degree of the single equipment in one day is determined according to the number of measuring points in the first target point inspection data and the health degree of each measuring point in one day.

[0084] The method can analyze the health condition of the equipment and comprehensively consider all the measuring point data, and then obtain the overall health degree of the equipment. Through the health degree of each measuring point and the health degree of the equipment, the abnormality and failure of the equipment can be found in time, and corresponding maintenance can be performed to improve the reliability and stability of the equipment.

[0085] If there is at least one point inspection data that does not meet the preset standard, i.e. data seriously deviates from the normal state, the latest measured point inspection data is selected as the second target point inspection data from all the point inspection data that does not meet the preset standard; the health degree of the single equipment in one day is determined according to the number of all measuring points in the second target point inspection data, the number of measuring points that do not meet the preset standard in the second target point inspection data, the second amplitude weight and the second temperature weight.

[0086] The method can find the abnormality of the equipment in time according to the point inspection data that does not meet the preset standard, and can more intuitively understand the overall health state of the equipment by comprehensively considering the number and weight of the measuring points that do not meet the preset standard, so as to take appropriate maintenance measures.

[0087] Further, the health degree of each measuring point in the first target point inspection data in one day is determined according to the amplitude data, the temperature data, the first amplitude weight, the first temperature weight, the actual running time and the equipment maintenance time corresponding to each measuring point in the first target point inspection data, which includes:

[0088] The initial amplitude health degree V of the measuring point is determined according to the amplitude data and the preset amplitude health degree grade corresponding to each measuring point in the first target point inspection data, and the initial temperature health degree T of the measuring point is determined according to the temperature data and the preset temperature health degree grade corresponding to each measuring point in the first target point inspection data; wherein each amplitude data of the measuring point corresponds to a preset amplitude health degree grade, each preset amplitude health degree grade corresponds to an initial amplitude health degree V, each temperature data of the measuring point corresponds to a preset temperature health degree grade, and each preset temperature health degree grade corresponds to an initial temperature health degree T.

[0089] The health degree of each measuring point in the target point inspection data in one day is calculated according to formula (1);

[0090] G = x1*(V - Time*V d ) + y1*(T - Time*T d ) Formula (1)

[0091] wherein, G is the health degree of each measuring point of the target point inspection data in a day, V d is the preset difference of adjacent amplitude health degree levels, T d is the preset difference of adjacent temperature health degree levels, Time is the use maintenance time coefficient of the equipment determined according to the actual running time and the equipment maintenance time, V - Time*V d is the final amplitude health degree of each measuring point in a day, T - Time*T d is the final temperature health degree of each measuring point in a day, x1 is the first amplitude weight, and y1 is the first temperature weight.

[0092] Further, the use maintenance time coefficient Time of the equipment is determined according to Formula (2):

[0093]

[0094] wherein, Time1 is the maintenance time of the equipment, and Time2 is the actual running time of the equipment.

[0095] In the point inspection process, the amplitude data, the temperature data and the actual running time of each measuring point are measured by using the multifunctional sensor equipment, the amplitude data is compared with the root mean square value interval to obtain the preset amplitude health degree level, and then the initial amplitude health degree corresponding to the amplitude health degree level is obtained, the temperature data is compared with the temperature value interval to obtain the preset temperature health degree level, and then the initial temperature health degree corresponding to the temperature health degree level is obtained, in combination with the analysis of Table 1 amplitude classification standard, Table 2 temperature classification standard, Table 3 initial amplitude health degree, and Table 4 initial temperature health degree.

[0096] In the embodiment of the present application, the scoring standard of the health degree is the percentage system.

[0097] Pre-set amplitude health grade Initial amplitude health (V) [A1] 100 <B1> 85 [C2] 70 70 [D1] 55

[0098] Table 3

[0099] As shown in Table 3, the preset difference V d of adjacent amplitude health degree levels is 15.

[0100] Pre-set temperature health grade Initial temperature health (T) [B2] 100 [C2] 80 [D2] 60

[0101] As shown in Table 4, the preset difference T d of adjacent temperature health degree levels is 20.

[0102] Specifically, the preset criteria include an amplitude preset criterion and a temperature preset criterion; the preset criteria are criteria for no D-level alarm, wherein the D-level alarm includes D1-level alarm and D2-level alarm; wherein the amplitude preset criterion and the temperature preset criterion correspond to no D1-level alarm and no D2-level alarm respectively. The alarm is because the amplitude value or the temperature value of the measuring point exceeds the threshold value of the corresponding lowest level. For example, the support type of the equipment is rigid, the current air temperature value is 26℃, the amplitude value of one of the measuring points in the point inspection data is 100μm, and the temperature value is 150℃, then the measuring point has D-level alarm, and both D1-level alarm and D2-level alarm, which means that the vibration and temperature state of the measuring point are both very poor, and need to be maintained in time. In another example, the support type of the equipment is rigid, the current air temperature value is 26℃, the amplitude value of one of the measuring points in the point inspection data is 54μm, and the temperature value is 70℃, then the preset amplitude health degree level of the measuring point is B1, the initial amplitude health degree V is 85, the preset temperature health degree level is B2, and the initial temperature health degree T is 100, and the state of the measuring point is good in comprehensive consideration of the two health degrees.

[0103] Preferably, a temperature sensor is used to detect the temperature data of the measuring point; the temperature data includes temperature value data and air temperature value data. If the current temperature value of the measuring point can be detected, the temperature value is taken as the temperature value data; if the current temperature value of the measuring point cannot be detected, the temperature value calculated from the temperature values in a certain time period in the past of the current time is taken as the temperature value of the current time, specifically, the average of all the temperature values collected in a certain time period in the past can be taken as the current temperature value. Of course, considering the temperature difference of the equipment at different time periods in a day, the temperature value of the same time of the previous day as the current time can also be taken as the current temperature value. The present application does not make specific limitations on this.

[0104] In an embodiment of the present application, as shown in Figure 3 a specific method for obtaining the temperature value data of the measuring point is provided as follows:

[0105] obtaining the current temperature value of the measuring point;

[0106] when the temperature value of the measuring point at the current time is obtained, the temperature value of the current time is taken as the temperature value data;

[0107] when the temperature value of the measuring point at the current time cannot be obtained, the temperature value in q to q+1 hours before the current time is obtained;

[0108] if the temperature value in q to q+1 hours before the current time cannot be obtained, the temperature value in q+1 to q+2 hours before the current time is obtained:

[0109] until,

[0110] If the temperature value within q+1 to q+2 hours before the current time cannot be obtained, no D2 level alarm is triggered.

[0111] If the temperature value within q to q+1 hours before the current time is obtained, the subsequent operation is stopped, the 97% confidence interval of all temperature values in this time period is taken, and the average value of the temperature values in this interval is used as the temperature value data.

[0112] wherein 0≤q≤46, q is an integer.

[0113] Through the above operation process, historical temperature can still be used for analysis when real-time temperature value cannot be obtained, reducing the situation that related analysis cannot be performed due to the absence of current temperature value. Meanwhile, taking the 97% confidence interval of temperature value in the method helps to provide the estimation range of temperature value, increasing the credibility of temperature value data.

[0114] The alarm level cannot be determined according to the temperature value data of the measuring point, and the result can be obtained only by comparing with the current air temperature value data.

[0115] In an embodiment of the present application, as shown in Figure 4 the method for obtaining the current air temperature value data is as follows:

[0116] obtaining the air temperature value at the current time;

[0117] when the air temperature value at the current time is obtained, using the air temperature value at the current time as the air temperature value data;

[0118] when the air temperature value at the current time cannot be obtained, using 25℃ as the air temperature value data.

[0119] Further, the temperature value data is compared with the air temperature value data, as shown in Figure 5 when the temperature value≤50℃+air temperature value, it indicates that the current temperature is within the normal range, and the measuring point does not alarm;

[0120] when 50℃+air temperature value<temperature value≤85℃+air temperature value, it indicates that the measuring point currently appears high temperature, triggering high temperature alarm, i.e. C2 level alarm;

[0121] when temperature value>85℃+air temperature value, it indicates that the measuring point currently appears high high temperature, triggering high high temperature alarm, i.e. D2 level alarm.

[0122] Through the above temperature alarm comparison method, the temperature state of the measuring point can be judged in real time and the corresponding alarm can be triggered, realizing the rapid response and processing of temperature abnormal situation, taking timely measures and performing temperature adjustment or troubleshooting to ensure the normal operation of the equipment. Meanwhile, the alarm threshold and level can be flexibly adjusted according to the actual situation to adapt to the needs in different scenes.

[0123] Further, the method for determining the health degree of the single device in one day according to the number of the measuring points in the first target inspection data and the health degree of each measuring point in one day comprises calculating the health degree of the single device in one day by using the average value of the health degrees of all the measuring points in one day in the first target inspection data.

[0124] The method comprehensively considers the health degrees of all the measuring points in a simple and intuitive manner, obtains the health degree of the device in the form of the average value, and facilitates the analysis of the overall health condition of the device.

[0125] and / or,

[0126] The method for determining the health degree of the single device in one day according to the number of the measuring points in the second target inspection data, the number of the measuring points not meeting the preset standard in the second target inspection data, the second amplitude weight and the second temperature weight comprises calculating the health degree of the single device in one day according to formula (3).

[0127]

[0128] The preset standard comprises an amplitude preset standard and a temperature preset standard.

[0129] wherein, P is the health degree of the single device in one day, V min is the health degree corresponding to the minimum amplitude health degree level, T min is the health degree corresponding to the minimum temperature health degree level, a is the number of all the measuring points in the target inspection data, b is the number of the measuring points not meeting the amplitude preset standard in the target inspection data, c is the number of the measuring points not meeting the temperature preset standard in the target inspection data, x2 is the second amplitude weight, and y2 is the second temperature weight.

[0130] The method comprehensively considers the importance of the health degrees of different measuring points in different states according to the weights and the preset standard, and the calculation of the health degree is more accurate, which facilitates the comprehensive analysis of the health state of the device.

[0131] Embodiment Two

[0132] In the analysis of the health state of the device, when a certain characteristic parameter (amplitude or temperature) deviates from the normal value seriously, it often indicates that the performance of a certain part of the device has decreased sharply, and the monitoring needs to be strengthened or even the device needs to be shut down for maintenance. However, in the health degree calculation model, the overall health degree may still be in the normal range due to the small weight, and the real state of the device cannot be reflected. Therefore, the present application provides an embodiment two of the method for analyzing the health state of the device. On the basis of the embodiment one, the determination method of the weight in the formula is provided, and the weight is adjusted to improve the accuracy of the formula calculation and the reliability of the health state score of the device.

[0133] The initial amplitude health degree and the initial temperature health degree can reflect the amplitude state and the temperature state of the measuring point, and the absolute difference between the two can reflect the influence degree of the amplitude state and the temperature state on the equipment to some extent.

[0134] In an embodiment of the present application, when the absolute difference between the initial amplitude health degree and the initial temperature health degree is less than a preset value, a preset amplitude weight is used as the first amplitude weight, and a preset temperature weight is used as the first temperature weight.

[0135] In this case, the difference between the initial amplitude health degree and the initial temperature health degree is small, and the preset amplitude weight and the preset temperature weight are directly used to evaluate the importance of each other, and the result of the health degree is mainly affected by the preset weight distribution.

[0136] and / or,

[0137] When the absolute difference between the initial amplitude health degree and the initial temperature health degree is greater than the preset value, the preset amplitude weight and the preset temperature weight are dynamically adjusted according to the size relationship between the initial amplitude health degree and the initial temperature health degree and the size of the absolute difference to obtain the first amplitude weight and the first temperature weight.

[0138] In this case, the difference between the initial amplitude health degree and the initial temperature health degree is large, and the weight needs to be dynamically adjusted according to the actual situation, so as to more accurately reflect the influence of the two weight indexes on the health degree of the equipment.

[0139] In an embodiment of the present application, when there is at least one point inspection data that does not meet the preset standard, the latest point inspection data is selected as the target point inspection data among all the point inspection data that does not meet the preset standard. Assuming that there are D1 level alarms and D2 level alarms at the same time, the health degree corresponding to the preset minimum amplitude health degree level is set to 55, the health degree corresponding to the preset minimum temperature health degree level is set to 60, the number of all measuring points in the target point inspection data is set to 100, the number of measuring points meeting the amplitude preset standard in the target point inspection data is 40, the number of measuring points meeting the temperature preset standard in the target point inspection data is 30, the first amplitude weight is configured as 0.8, and the first temperature weight coefficient is configured as 0.2. According to formula (3), the health degree of a single device in one day is

[0140] Further, dynamically adjusting the preset amplitude weight and the preset temperature weight according to the size relationship between the initial amplitude health degree and the initial temperature health degree and the size of the absolute difference to obtain the first amplitude weight and the first temperature weight includes:

[0141] determining a level difference according to the level corresponding to the initial amplitude health degree and the level corresponding to the initial temperature health degree.

[0142] The target weight adjustment value corresponding to the grade difference is determined according to a preset correspondence between the grade difference and the weight adjustment value, and the preset amplitude weight and the preset temperature weight are oppositely adjusted according to the target weight adjustment value to obtain a first amplitude weight and a first temperature weight.

[0143] The grade difference is used to describe the difference degree of the initial amplitude health degree and the initial temperature health degree; the preset correspondence between the grade difference and the weight adjustment value can be defined in advance, so that the target weight adjustment value corresponding to the grade difference can be quickly obtained according to the actual situation; the preset amplitude weight and the preset temperature weight are oppositely adjusted according to the target weight adjustment value, so that the amplitude weight and the temperature weight are adaptively adjusted according to the specific situation, and the influence of the amplitude and the temperature on the equipment health degree is more accurately reflected.

[0144] Further, the preset amplitude weight and the preset temperature weight are determined by the following process:

[0145] The historical amplitude data, the historical temperature data, the historical actual running time, the historical equipment maintenance time and the historical health degree of all measuring points in the historical point inspection data of the sample equipment are obtained.

[0146] The historical initial amplitude health degree of each measuring point is determined according to the historical amplitude data corresponding to each measuring point and the preset amplitude health degree grade, and the historical initial temperature health degree of each measuring point is determined according to the historical temperature data corresponding to each measuring point and the preset temperature health degree grade; the use and maintenance time coefficient of the equipment is determined according to the historical actual running time and the historical equipment maintenance time.

[0147] The historical initial amplitude health degree, the historical initial temperature health degree and the use and maintenance time coefficient of the equipment are input as sample input data, and the historical health degree is input as sample output data, and then the preset network model is trained to obtain the preset amplitude weight and the preset temperature weight corresponding to the target network model.

[0148] Through the above training process, the preset network model learns the rules of the historical initial amplitude health degree, the historical initial temperature health degree, the historical equipment use and maintenance coefficient and the historical health degree in the historical data, and the preset amplitude weight and the preset temperature weight corresponding to the target network model are fitted, so as to accurately reflect the real state of the measuring point and the equipment and improve the balance between the feature parameters.

[0149] Preferably, the first amplitude weight is the same as the second amplitude weight, and the first temperature weight is the same as the second temperature weight.

[0150] Embodiment three

[0151] After the health degree of the measuring point and the equipment in a day is calculated, the health degree of all the equipment in a region or a larger range cannot be reflected by the health degree of a single equipment in a day. The application provides a method for analyzing the health state of equipment. Based on the second embodiment, the health degree of a region or a factory in a day or several days is calculated. The analysis result of the health state is reflected by the health degree. The information management of the health degree of the region and the factory is realized. The user can more intuitively know whether the equipment is healthy.

[0152] The health degree of a single region in a day is obtained by using the health degree of all the equipment in the single region in a day.

[0153] The health degree of a single factory in a day is obtained by using the health degree of all the regions in the single factory in a day.

[0154] The average value of the health degree of a single equipment in several preset times is used as the health degree of the single equipment in each preset time.

[0155] The average value of the health degree of a single region in several preset times is used as the health degree of the single region in each preset time.

[0156] The average value of the health degree of a single factory in several preset times is used as the health degree of the single factory in each preset time.

[0157] Further, the health degree of a single region in a day is obtained by using the health degree of all the equipment in the single region in a day. The health degree of the single region in a day is calculated by using the average value of the health degree of all the equipment in the single region in a day. The health degree of the single region is determined to be abnormal when the number of the equipment whose health degree does not conform to the preset health degree standard exceeds the tenth threshold value.

[0158] Further, the health degree of a single factory in a day is obtained by using the health degree of all the regions in the single factory in a day. The health degree of the single factory in a day is calculated by using the average value of the health degree of all the regions in the single factory in a day. The health degree of the single factory is determined to be abnormal when the number of the region whose health degree is abnormal exceeds the ninth threshold value.

[0159] Further, the average of the health degrees of the single device in the plurality of preset time is taken as the health degree of the single device in each preset time, including: calculating the health degree of the single device in each preset time by using the average of the health degrees of the single device in the plurality of preset time; and / or, obtaining the number of days of abnormal health degree of the single device, and when the number of days of abnormal health degree of the single device exceeds the eighth threshold value, determining that the health degree of the single device is abnormal; and / or, obtaining the number of consecutive days of abnormal health degree of the single device, and when the number of consecutive days of abnormal health degree of the single device exceeds the seventh threshold value, determining that the health degree of the single device is abnormal.

[0160] Further, the average of the health degrees of the single area in the plurality of preset time is taken as the health degree of the single area in each preset time, including: calculating the health degree of the single area in each preset time by using the average of the health degrees of the single area in the plurality of preset time; and / or, obtaining the number of days of abnormal health degree of the single area, and when the number of days of abnormal health degree of the single area exceeds the sixth threshold value, determining that the health degree of the single area is abnormal; and / or, obtaining the number of consecutive days of abnormal health degree of the single area, and when the number of consecutive days of abnormal health degree of the single area exceeds the fifth threshold value, determining that the health degree of the single area is abnormal.

[0161] Further, the average of the health degrees of the single factory in the plurality of preset time is taken as the health degree of the single factory in each preset time, including: calculating the health degree of the single factory in each preset time by using the average of the health degrees of the single factory in the plurality of preset time; and / or, obtaining the number of days of abnormal health degree of the single factory, and when the number of days of abnormal health degree of the single factory exceeds the fourth threshold value, determining that the health degree of the single factory is abnormal; and / or, obtaining the number of consecutive days of abnormal health degree of the single factory, and when the number of consecutive days of abnormal health degree of the single factory exceeds the third threshold value, determining that the health degree of the single factory is abnormal.

[0162] Wherein, the average of the health degrees of the single device / area / factory in the plurality of preset time is actually the average health degree of the single device / area / factory.

[0163] Preferably, when calculating the average, the extreme value method is used to remove one highest score and one lowest score before calculation, so as to eliminate the influence of individual abnormal value on the average, thereby obtaining more accurate representative value.

[0164] Preferably, when the health degree of the device measuring point, the single device or the like object is not lower than a first preset threshold value and not higher than a second preset threshold value, the score distribution index, the lowest score proportion and the highest score proportion of the health degree of the object in a day and / or in a plurality of days are obtained.

[0165] When the absolute difference between the highest score proportion and the lowest score proportion is not more than the third preset threshold value, the object corresponding to the highest health degree and the lowest health degree is displayed.

[0166] The object includes a measuring point, a device, an area, and a factory.

[0167] In an embodiment of the present application, there are 100 measuring points in the target point inspection data, the health degrees of 20 measuring points are 65, the health degrees of 40 measuring points are 75, the health degrees of 30 measuring points are 80, and the health degrees of 10 measuring points are 90; the first preset threshold value and the second preset threshold value are preset, and in this embodiment, they are respectively set to 70 and 95, so that the health degrees of a total of 80 measuring points meet the condition of not being lower than the first preset threshold value and not being higher than the second preset threshold value. The score distribution index of the measuring points in one day is that the health degrees of 40 measuring points are 75, the health degrees of 30 measuring points are 80, and the health degrees of 10 measuring points are 90, the lowest score proportion is 1 / 2, and the highest score proportion is 1 / 8.

[0168] The absolute difference between the highest score proportion and the lowest score proportion is 3 / 8, the third preset threshold value is artificially set to 5 / 8, the absolute difference between the highest score proportion and the lowest score proportion is less than the third preset threshold value, and the measuring points with the highest health degree and the lowest health degree are displayed.

[0169] Embodiment Four

[0170] In the embodiment four, the present application further provides a device health degree analysis device, wherein the device comprises:

[0171] A point inspection data acquisition unit is configured to acquire all point inspection data of a single device in one day, which is helpful to collect the running state information of the device and provide a data basis for subsequent analysis; the point inspection data of each time includes amplitude data, temperature data, and actual running time of all measuring points.

[0172] A point inspection data judgment unit is configured to judge whether the point inspection data of all times includes point inspection data not meeting the preset standard according to the amplitude data and the temperature data of all measuring points; by the judgment, the point inspection data meeting the requirement can be selected, and the point inspection data not meeting the requirement can be excluded, so as to improve the accuracy and reliability of the data.

[0173] A point inspection data selection unit is configured to select, when all point inspection data meet the preset standard, the point inspection data with the largest amplitude value from all point inspection data as the first target point inspection data, so as to provide a reference for subsequent health degree analysis.

[0174] The measurement point health determination unit is used to determine the health of each measurement point in the first target inspection data for one day based on the amplitude data, temperature data, first amplitude weight, first temperature weight, actual running time, and equipment maintenance time corresponding to each measurement point in the first target inspection data. By comprehensively considering factors such as amplitude, temperature, and actual running time, the health of each measurement point of the equipment can be monitored and analyzed.

[0175] The equipment health determination unit is used to determine the health status of a single piece of equipment on a daily basis based on the number of measuring points in the first target inspection data and the health status of each measuring point on a daily basis, thereby obtaining the overall health status of the equipment and making corresponding equipment maintenance based on the health status.

[0176] By combining the above units, this device can analyze the health status of the measuring points and the equipment as a whole. The health level reflects the health status of the equipment, allowing users to understand more intuitively whether the equipment is healthy.

[0177] The device described in this application corresponds to the method embodiments of the above-described embodiments one to three. For related content, please refer to embodiments one to three, which will not be described in detail here.

[0178] Example 5

[0179] Corresponding to the above embodiments, this application also provides a fifth embodiment of a computer device, including a processor and a memory. The memory stores a computer program that can run on the processor. When the computer program is executed by the processor, it executes the device health status analysis method provided in any of the above embodiments.

[0180] Among them, such as Figure 6 The computer device shown may specifically include a processor 1510, a video display adapter 1511, a disk drive 1512, an input / output interface 1513, a network interface 1514, and a memory 1520. The processor 1510, video display adapter 1511, disk drive 1512, input / output interface 1513, network interface 1514, and memory 1520 can communicate with each other via a communication bus 1530.

[0181] The processor 1510 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solution provided in this application.

[0182] The memory 1520 can be implemented in the form of a ROM (Read Only Memory), a RAM (Random Access Memory), a static storage device, a dynamic storage device, etc. The memory 1520 can store an operating system 1521 for controlling the electronic device to operate, a basic input / output system 1522 for controlling low-level operations of the electronic device. In addition, a web browser 1523, a data storage management system 1524, and a device identification information processing system 1525, etc. can also be stored. The device identification information processing system 1525 can be an application program that specifically implements the foregoing steps in the embodiments of the present application. In summary, when the technical solutions provided by the present application are implemented by software or firmware, the relevant program codes are stored in the memory 1520 and executed by the processor 1510.

[0183] The input / output interface 1513 is configured to connect an input / output module to realize information input and output. The input / output module can be configured as a component in the device (not shown in the figure) or externally connected to the device to provide corresponding functions. The input device can include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output device can include a display, a speaker, a vibrator, an indicator light, etc.

[0184] The network interface 1514 is configured to connect a communication module (not shown in the figure) to realize communication interaction between the device and other devices. The communication module can realize communication through a wired manner (such as USB, network cable, etc.) or a wireless manner (such as mobile network, WIFI, Bluetooth, etc.).

[0185] The communication bus 1530 includes a path for transmitting information between various components (such as the processor 1510, the video display adapter 1511, the disk drive 1512, the input / output interface 1513, the network interface 1514, and the memory 1520) of the device.

[0186] In addition, the electronic device can also obtain information of the specific obtaining condition from the virtual resource object obtaining condition information database to be used for condition judgment, etc.

[0187] It should be noted that although the above device only shows the processor 1510, the video display adapter 1511, the disk drive 1512, the input / output interface 1513, the network interface 1514, the memory 1520, the communication bus 1530, etc., in the specific implementation process, the device can also include other components necessary for normal operation. In addition, those skilled in the art can understand that the above device can also only contain the components necessary to implement the solutions of the present application, and does not necessarily contain all the components shown in the figure.

[0188] Embodiment six

[0189] Corresponding to the above-mentioned embodiments, the present application also provides an embodiment six of a computer-readable storage medium, wherein, in the present embodiment, the same or similar contents as the above-mentioned embodiments one to three can be referred to the above description, and the subsequent will not be described in detail.

[0190] A computer-readable storage medium, having stored thereon a computer program, the computer program being executed by a processor to implement the method steps of the above-mentioned embodiments one to three.

[0191] From the above description of the embodiments, those skilled in the art can clearly understand that the present application can be implemented by means of software plus necessary general hardware platforms. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product, which can be stored in a storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute the methods of the various embodiments or some parts of the embodiments.

[0192] Each of the embodiments in the specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment mainly describes the difference from other embodiments. In particular, for the system or system embodiments, since it is basically similar to the method embodiments, it is described more simply, and the relevant parts can be referred to the part of the method embodiments. The above-described system and system embodiments are only illustrative, and the units described as separate components can be or can not be physically separated, and the components displayed as units can be or can not be physical units, that is, they can be located in one place, or can be distributed to multiple network units. According to the actual needs, some or all of the modules can be selected to achieve the purpose of the present embodiment. Those skilled in the art can understand and implement without creative labor.

[0193] It should be understood that the above specific embodiments of the present application are only used for illustrative or explanatory purposes of the principles of the present application, and do not constitute a limitation of the present application. Therefore, any modification, equivalent replacement, improvement, etc. made without departing from the spirit and scope of the present application shall be included in the protection scope of the present application. In addition, the claims of the present application are intended to cover all variations and modifications falling within the scope and boundary of the appended claims, or the equivalent forms of such scope and boundary.

Claims

1. A method for analyzing the health status of equipment, characterized in that, Includes the following steps: Acquire inspection data of a single device at several times within a preset time period, wherein each device includes several measurement points; The inspection data for each instance includes amplitude data, temperature data, and actual running time for all the measured points; Based on the amplitude data and temperature data of all the measuring points, determine whether there are any inspection data that do not meet the preset standard in all the inspection data; If all the inspection data meet the preset standard, then the inspection data including the largest amplitude data is selected as the first target inspection data; The health status of each measuring point in the first target inspection data within a preset time period is determined based on the amplitude data, temperature data, first amplitude weight, first temperature weight, actual operating time, and equipment maintenance time corresponding to each measuring point in the first target inspection data, including: The initial amplitude health of each measuring point is determined based on the amplitude data corresponding to each measuring point in the first target point inspection data and the preset amplitude health level. The initial temperature health level of each measuring point is determined based on the temperature data corresponding to each measuring point in the first target point inspection data and the preset temperature health level. ; The health status of each measuring point in the target inspection data within a preset time period is calculated according to formula (1); Formula (1) in, The health status of each measuring point in the target inspection data within a preset time period. The difference between the preset adjacent amplitude health levels, This is the difference between preset adjacent temperature health levels. This is a usage and maintenance time coefficient for the equipment, determined based on the actual operating time and the required maintenance time. The final amplitude health status of each measurement point within a preset time period. The final temperature health status of each measuring point within a preset time period. This is the first amplitude weight. The first temperature weight; The equipment's usage and maintenance time coefficient Determined according to formula (2); Formula (2) in, The maintenance interval for the equipment is as follows. The actual operating time of the device; The health status of a single device within a preset time period is determined based on the total number of measuring points in the first target inspection data and the health status of each measuring point within a preset time period. The method further includes the following steps: If at least one of the inspection data does not meet the preset standard, then the most recently measured inspection data is selected from all the inspection data that does not meet the preset standard as the second target inspection data. The health status of a single device within a preset time period is determined based on the total number of measuring points in the second target inspection data, the number of measuring points in the second target inspection data that do not meet the preset standard, the second amplitude weight, and the second temperature weight, including: The health status of a single device within a preset time period is calculated according to formula (3); Formula (3) The preset standards include amplitude preset standards and temperature preset standards; in, The health status of a single device within a preset time period. This represents the health level corresponding to the preset minimum amplitude health level. The health level corresponding to the preset minimum temperature health level. The total number of measurement points in the target point inspection data. The number of measurement points in the target inspection data that do not conform to the preset amplitude standard. The number of measurement points in the target inspection data that do not meet the preset temperature standard. This is the second amplitude weight. This is the second temperature weight.

2. The equipment health status analysis method according to claim 1, characterized in that, Determining the health of a single device within a preset time period based on the total number of measuring points in the first target inspection data and the health status of each measuring point within a preset time period includes calculating the health status of a single device within a preset time period using the average health status of all measuring points in the first target inspection data within a preset time period.

3. The equipment health status analysis method according to claim 1, characterized in that, The method further includes: When the absolute difference between the initial amplitude health and the initial temperature health is less than a preset value, a preset amplitude weight is used as the first amplitude weight, and a preset temperature weight is used as the first temperature weight. And / or, When the absolute difference between the initial amplitude health and the initial temperature health is greater than a preset value, the preset amplitude weight and preset temperature weight are dynamically adjusted according to the relationship between the initial amplitude health and the initial temperature health and the magnitude of the absolute difference to obtain the first amplitude weight and the first temperature weight.

4. The equipment health status analysis method according to claim 3, characterized in that, The preset amplitude weight and preset temperature weight are dynamically adjusted based on the relationship between the initial amplitude health and the initial temperature health and the magnitude of the absolute difference to obtain the first amplitude weight and the first temperature weight, including: The level difference is determined based on the preset amplitude health level corresponding to the initial amplitude health level and the preset temperature health level corresponding to the initial temperature health level; The target weight adjustment value corresponding to the level difference is determined according to the preset correspondence between the level difference and the weight adjustment value, and the preset amplitude weight and the preset temperature weight are adjusted in opposite ways according to the target weight adjustment value to obtain the first amplitude weight and the first temperature weight.

5. The equipment health status analysis method according to claim 3, characterized in that, The preset amplitude weight and the preset temperature weight are determined through the following process: Acquire the historical amplitude data, historical temperature data, historical actual operating time, historical equipment maintenance time, and historical health status of all the measured points in the historical inspection data of the sample equipment; The historical initial amplitude health of each measuring point is determined based on the historical amplitude data corresponding to each measuring point and the preset amplitude health level, and the historical initial temperature health of each measuring point is determined based on the historical temperature data corresponding to each measuring point and the preset temperature health level. The equipment's usage and maintenance time coefficient is determined based on the historical actual operating time and the historical equipment maintenance time. The historical initial amplitude health, the historical initial temperature health, and the equipment usage and maintenance time coefficient are used as sample input data, and the historical health is used as sample output data. These data are then input into a preset network model for training to obtain the preset amplitude weight and the preset temperature weight corresponding to the target network model.

6. The equipment health status analysis method according to claim 1, characterized in that, The first amplitude weight is the same as the second amplitude weight, and the first temperature weight is the same as the second temperature weight.

7. A device for analyzing the health status of equipment, characterized in that, The device includes: The inspection data acquisition unit is used to acquire inspection data of a single device within a preset time period; each inspection data includes amplitude data, temperature data and actual running time of all measuring points. The inspection data judgment unit is used to determine whether there are any inspection data that do not meet the preset standard in all the inspection data based on the amplitude data and temperature data of all the measuring points. The inspection data selection unit is used to select the inspection data with the largest amplitude value from all the inspection data as the first target inspection data when all the inspection data meet the preset standard. The measuring point health determination unit is used to determine the health of each measuring point in the first target inspection data within a preset time period based on the amplitude data, temperature data, first amplitude weight, first temperature weight, actual operating time, and equipment maintenance time corresponding to each measuring point in the first target inspection data, including: The initial amplitude health of each measuring point is determined based on the amplitude data corresponding to each measuring point in the first target point inspection data and the preset amplitude health level. The initial temperature health level of each measuring point is determined based on the temperature data corresponding to each measuring point in the first target point inspection data and the preset temperature health level. ; The health status of each measuring point in the target inspection data within a preset time period is calculated according to formula (1); Formula (1) in, The health status of each measuring point in the target inspection data within a preset time period. The difference between the preset adjacent amplitude health levels, This is the difference between preset adjacent temperature health levels. This is a usage and maintenance time coefficient for the equipment, determined based on the actual operating time and the required maintenance time. The final amplitude health status of each measurement point within a preset time period. The final temperature health status of each measuring point within a preset time period. This is the first amplitude weight. The first temperature weight; The equipment's usage and maintenance time coefficient Determined according to formula (2); Formula (2) in, The maintenance interval for the equipment is as follows. The actual operating time of the device; The equipment health determination unit is used to determine the health of a single device within a preset time based on the total number of measuring points in the first target inspection data and the health of each measuring point within a preset time. The inspection data selection unit is also used to select the latest measured inspection data as the second target inspection data if at least one of the inspection data does not meet the preset standard. The measuring point health determination unit is further configured to determine the health of a single device within a preset time period based on the total number of measuring points in the second target inspection data, the number of measuring points in the second target inspection data that do not meet the preset standard, the second amplitude weight, and the second temperature weight, including: The health status of a single device within a preset time period is calculated according to formula (3); Formula (3) The preset standards include amplitude preset standards and temperature preset standards; in, The health status of a single device within a preset time period. This represents the health level corresponding to the preset minimum amplitude health level. The health level corresponding to the preset minimum temperature health level. The total number of measurement points in the target point inspection data. The number of measurement points in the target inspection data that do not conform to the preset amplitude standard. The number of measurement points in the target inspection data that do not meet the preset temperature standard. This is the second amplitude weight. This is the second temperature weight.

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