WO2020006971A1 - 一种机械密封多尺度实时监测分析方法 - Google Patents

一种机械密封多尺度实时监测分析方法 Download PDF

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WO2020006971A1
WO2020006971A1 PCT/CN2018/117060 CN2018117060W WO2020006971A1 WO 2020006971 A1 WO2020006971 A1 WO 2020006971A1 CN 2018117060 W CN2018117060 W CN 2018117060W WO 2020006971 A1 WO2020006971 A1 WO 2020006971A1
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scale
seal
analysis
time
acoustic
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French (fr)
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黄伟峰
刘向锋
尹源
刘莹
李德才
李永健
索双富
王子羲
贾晓红
郭飞
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Tsinghua University
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Tsinghua University
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M3/00—Investigating fluid-tightness of structures
    • G01M3/02—Investigating fluid-tightness of structures by using fluid or vacuum
    • G01M3/04—Investigating fluid-tightness of structures by using fluid or vacuum by detecting the presence of fluid at the leakage point
    • G01M3/24—Investigating fluid-tightness of structures by using fluid or vacuum by detecting the presence of fluid at the leakage point using infrasonic, sonic or ultrasonic vibrations
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
    • F16J—PISTONS; CYLINDERS; SEALINGS
    • F16J15/00—Sealings
    • F16J15/16—Sealings between relatively-moving surfaces
    • F16J15/34—Sealings between relatively-moving surfaces with slip-ring pressed against a more or less radial face on one member
    • F16J15/3492—Sealings between relatively-moving surfaces with slip-ring pressed against a more or less radial face on one member with monitoring or measuring means associated with the seal
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M13/00—Testing of machine parts
    • G01M13/005—Sealing rings

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  • the invention belongs to the field of fluid seal and acoustic emission monitoring technology, and particularly relates to a multi-scale real-time monitoring and analysis method for a mechanical seal.
  • Mechanical seal is a common form of shaft end seal in rotating machinery.
  • the paired moving ring and static ring rotate relative to each other to form a sealed friction pair, which greatly reduces leakage while avoiding or even eliminating contact.
  • the mechanical seal has a compact structure, which makes it difficult for the user to grasp the information about the working status of the seal. This means that when the seal performance is poor or even fails, the cause cannot be accurately judged, and the risk of seal failure can not be well predicted to take countermeasures. .
  • some people have proposed to use active control to adjust the working state of the seal in real time, and such technology must also be implemented based on the accurate grasp of the working state of the seal. In view of the above-mentioned needs for maintenance and development of mechanical seals, real-time monitoring of mechanical seals is particularly necessary.
  • the existing mechanical seal monitoring technologies mainly include end face temperature monitoring, eddy current monitoring, reflected ultrasonic monitoring, and acoustic emission monitoring.
  • acoustic emission monitoring is not only convenient for engineering applications, but also carries a wealth of information about the state of the sealing friction pair, so it has great application potential, but it is very difficult to interpret a large amount of information in the acoustic emission signal.
  • a number of cutting-edge scientific studies have expounded the corresponding relationship between the characteristics of acoustic emission signals in specific aspects and the working state of mechanical seals from different angles, but have not formed a systematic method of comprehensively analyzing acoustic emission signals.
  • the present invention provides a multi-scale real-time monitoring and analysis method for a mechanical seal, which measures the acoustic emission signal generated by the friction pair on the end face of the mechanical seal, according to the characteristics of the acoustic emission signal at different scales. Physical connotation, combined with other auxiliary information on multiple scales for analysis, so as to judge the real-time working status of the seal and give an expectation of the performance change of the seal.
  • a multi-scale real-time monitoring and analysis method for mechanical seals It measures the acoustic emission signals generated by friction pairs on the end faces of mechanical seals. According to the different physical connotations of the characteristics of acoustic emission signals at different scales, it is combined with other auxiliary information at multiple scales Analysis, so as to judge the real-time working status of the seal and give an expectation of the performance change of the seal.
  • the multi-scale implementation method is: performing analysis on a certain time scale (referred to as the N-th time scale) can obtain a specific result.
  • This result has a physical meaning as well as a longer time scale.
  • the analysis object of the first-level (i.e. (N + 1) -level) time scale-analyzing the change of the result of the N-th level over time on the (N + 1) -level time scale will yield another result
  • this result not only has physical meaning in itself, but also can be used as the analysis object of the (N + 2) th time scale, and so on.
  • the results on a longer time scale can also be fed back to a shorter time scale.
  • the method for measuring the acoustic emission signal generated by the friction pair on the end face of the mechanical seal is to generate an acoustic emission signal on the end face of the mechanical seal through the stress wave generated by the internal energy release of the material.
  • the scale is an acoustic scale, a dynamic scale, and a service scale.
  • a specific sound source generates signals in specific frequency bands.
  • the scale for collecting and identifying these signals is called an acoustic scale; due to dynamics during the sealing operation, The motion caused by the above action results in the change of the acoustic emission signal.
  • This feature is reflected on a time scale equivalent to the rotation cycle.
  • This scale is called the dynamic scale.
  • the performance of the seal during long-term service includes running-in, wear, Cumulative performance changes occur due to the aging of elastic components. This feature requires the long-term evolution of acoustic emission signals.
  • This scale is called the service scale.
  • the specific steps / methods for carrying out the analysis in combination with other auxiliary information on multiple scales are to determine the real-time working status of the seal and give an expected change in the performance of the seal;
  • Acoustic scale analysis consists of a short period of acoustic emission waveforms combined with auxiliary information (which can be equipment-specific information, results from the other two scales, or non-acoustic measurement results) to obtain a series of corresponding friction pairs.
  • auxiliary information which can be equipment-specific information, results from the other two scales, or non-acoustic measurement results
  • the amount of characterization of the aspect state is to perform preprocessing such as filtering the frequency spectrum and introducing auxiliary information correction, and then transform the frequency spectrum into a series of physical representations through a preset mapping function established according to the correspondence between the frequency band and the physical process.
  • these characterizations have the function of showing the sealing working state to the user, on the other hand, they are also the basis of dynamic scale analysis.
  • Dynamic scale When the seal moving ring rotates with the shaft, it periodically generates excitation to the seal system, which causes the seal system to generate a periodic dynamic response.
  • the specific form of this periodic response is closely related to the friction severity and circumferential non-uniformity (such as deflection, waviness, etc.) of the sealing system.
  • the typical situation of the relationship between the dynamic change pattern of acoustic characterization and the sealed state can be obtained in advance through experimental tests or computer simulations, which can be used to further infer the measured equipment on the basis of acoustic scale analysis.
  • the invention measures the acoustic emission signal generated by the friction pair on the end face of a mechanical seal, according to the different physical connotations of the characteristics of the acoustic emission signal on different scales, and combines other auxiliary information to perform analysis on multiple scales, thereby determining the real-time working status of the seal.
  • the performance change of the seal is expected.
  • Figure 1 is a schematic diagram of the acoustic emission sensor installation.
  • FIG. 2 is a schematic flowchart of the present invention.
  • Figure 3 is a schematic diagram of the acoustic scale.
  • Figure 4 is a schematic diagram of the kinetic scale.
  • Figure 5 is a schematic diagram of service scale.
  • the static ring 1 of the mechanical seal is floatingly supported on the static ring seat 4, and is matched with a movable ring 3 which is fixedly connected to the shaft and rotates with it.
  • a miniature acoustic emission sensor 4 is connected to the back of the static ring 1 so as to convert the acoustic emission signal generated by the sealed friction pair into an electrical signal in real time.
  • the analysis method of this example starts from the acoustic emission original signal 5, which is mainly based on auxiliary information and an algorithm calibrated by experimental data through the acoustic scale, dynamic scale and service scale. Processing on three different time scales yields a series of information about the working state of the seal. Specifically, a targeted analysis method is used on each time scale to obtain physical representations and transfer them to longer time scales (in this case, the acoustic scale transfers friction power, maximum contact depth, and leakage rate to the dynamic scale). , The dynamic scale transfers the wear rate to the service scale), and each scale can get a meaningful result for the analysis of the working state of the seal. At the same time, part of the auxiliary information of the acoustic scale analysis in this example also comes from the results of the service scale analysis.
  • the pre-processing algorithm is used to pre-process the initial feature vector to obtain the pre-processed feature vector 8.
  • the pre-processing mainly includes three purposes: 1 noise reduction, 2 smoothing the power spectrum (avoiding different results without actual physical meaning caused by extremely small frequency differences), 3 correction based on the speed and cumulative wear, 4 Perform the necessary non-linear mapping for subsequent linear analysis.
  • a three-dimensional acoustic scale physical representation vector 9 is calculated from each acoustic scale analysis section 6.
  • the typical state library 11 of corresponding seal type, pressure and speed is called for comparison calculation.
  • the typical state library includes dozens of typical states, and each typical state records the change sequence of its acoustic scale representation vector in a cycle with the same T (1) (denoted as j is a typical state number, called a typical sequence), and simultaneously records the wear status (wear form and wear rate) and the existence of the fault source (whether there is a fault, and if there is a fault, what is the cause of the fault)
  • the wear amount in the sealing operation can be calculated: For the stable working process, a period of time for the dynamic scale analysis period D (2) is selected , The time difference between the midpoints of the adjacent dynamic scale analysis segments is T (2) , and the wear rate obtained by the analysis segment represents the wear rate in the T (2) time interval with the midpoint of the analysis segment as the midpoint; The speed of the work process, directly calculate the amount of wear in the process. For each seal ring, calculate its cumulative wear amount 12;
  • each reliability index 13 of the seal ring can be obtained. These reliability indicators can be used as a basis for evaluating the risk of continued service of the seal and if it is expected to be scrapped after continued service in order to develop a production plan.

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  • Engineering & Computer Science (AREA)
  • General Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Mechanical Engineering (AREA)
  • Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)
  • Mechanical Sealing (AREA)

Abstract

一种用于机械密封的实时监测分析的方法，其测量机械密封端面摩擦副产生的声发射信号，特定的声源会在特定的若干个频段上产生信号，采集并识别这些信号的尺度称为声学尺度；密封运行过程中因动力学上的作用而产生运动，导致声发射信号随之变化，这一特征在与旋转周期相当的时间尺度上体现，这一尺度称为动力学尺度；密封长期服役过程中性能因磨合、磨损、弹性元件老化原因发生累积性的性能变化，这一特征需要考察声发射信号长期的变化历程，这一尺度称为服役尺度，根据声发射信号在不同尺度上的特征所具备的不同物理内涵，在多个尺度上结合其他辅助信息开展分析，从而判断密封的实时工作状态并给出密封的性能变化预期。

Description

一种机械密封多尺度实时监测分析方法 技术领域
本发明属于流体密封领域和声发射监测技术领域，特别涉及一种机械密封多尺度实时监测分析方法。
背景技术
机械密封是旋转机械设备中的一种常见轴端密封形式。其配对的动环和静环相对旋转，形成密封的摩擦副，在极大地减少泄漏的同时避免甚至消除接触。
机械密封结构紧凑，导致使用者很难掌握关于密封工作状态的信息，这意味着当密封性能不佳甚至发生故障时无法准确地判断原因，也无法很好地预知密封的失效风险从而采取应对措施。同时，已有人提出采用主动调控的方式来实时地调整密封的工作状态，而这样的技术也须基于对密封工作状态的准确掌握来实施。针对上述机械密封维护和发展的需要，对机械密封进行实时监测尤为必要。
目前已有的机械密封监测技术主要包括端面温度监测、电涡流监测、反射超声监测和声发射监测等。其中，声发射监测不仅工程应用便利，而且其携带了关于密封摩擦副状态的丰富的信息，因而具有很大的应用潜力，但解读出声发射信号中的大量信息非常困难。多项前沿的科学研究已经分别从不同的角度阐述了声发射信号在特定方面的特征与机械密封工作状态的对应关系，但未形成综合分析声发射信号的系统性方法。
发明内容
为了克服上述现有技术的不足，本发明提供一种机械密封多尺度实时监测分析 方法，其测量机械密封端面摩擦副产生的声发射信号，根据声发射信号在不同尺度上的特征所具备的不同物理内涵，在多个尺度上结合其他辅助信息开展分析，从而判断密封的实时工作状态并给出密封的性能变化预期。
为了实现上述目的，本发明采用的技术方案是：
一种机械密封多尺度实时监测分析方法，测量机械密封端面摩擦副产生的声发射信号，根据声发射信号在不同尺度上的特征所具备的不同物理内涵，在多个尺度上结合其他辅助信息开展分析，从而判断密封的实时工作状态并给出密封的性能变化预期。
所述多尺度的实现方法是：在某个时间尺度(称为第N级时间尺度)上进行分析可以得到特定的结果，这一结果除本身具有物理意义外，还作为时间上更长的下一级(即第(N+1)级)时间尺度的分析对象——在第(N+1)级时间尺度上分析第N级的结果随时间的变化，将会得出另一方面的结果，并且类似地，这一结果不仅本身具有物理意义，还可以作为第(N+2)级时间尺度的分析对象，依此类推。同时，在特定的条件下，较长的时间尺度下的结果也可以反馈给较短的时间尺度。
所述的测量机械密封端面摩擦副产生的声发射信号的方法是通过材料内部能量释放产生的应力波，使机械密封的端面上会产生声发射信号。
所述尺度为声学尺度、动力学尺度和服役尺度，其中，特定的声源会在特定的若干个频段上产生信号，采集并识别这些信号的尺度称为声学尺度；密封运行过程中因动力学上的作用而产生运动，导致声发射信号随之变化，这一特征在与旋转周期相当的时间尺度上体现，这一尺度称为动力学尺度；密封长期服役过程中性能因包括磨合、磨损、弹性元件老化在内的原因发生累积性的性能变化，这一特征需要考察声发射信号长期的变化历程，这一尺度称为服役尺度。
在多个尺度上结合其他辅助信息开展分析，从而判断密封的实时工作状态并给出密封的性能变化预期的具体步骤/方法是；
声学尺度：声学尺度的分析由一段时间很短的声发射波形结合辅助信息(可以是设备固有的信息、其他两个尺度输出的结果或非声发射的测量结果)获得一系列对应于摩擦副各方面状态的表征量。一种典型的方法是，对频率谱进行滤波、引入辅助信息修正等预处理，然后经由预设的根据频带与物理过程的对应关系建立的映射函数将频率谱变换为一系列物理表征量。这些表征量一方面本身具有向用户展示密封工作状态的作用，另一方面也是动力学尺度分析的基础。
动力学尺度：密封动环随轴旋转时，对密封系统产生周期性的激励，从而导致密封系统产生周期性的动力学响应。而这种周期性响应的具体形式则与密封系统的摩擦剧烈程度和周向不均匀性(如偏斜、波度等)等有密切的关系。通过实验测试或计算机模拟预先得到声学表征量动态变化模式与密封状态的关系的典型情况，即可反过来对被测量的设备在声学尺度分析的基础上进行进一步推断。
服役尺度：密封运行过程中，密封环不可避免地会产生磨损(即使是正常工作的非接触式密封也会在起停过程中发生磨损)，弹簧和副密封也可能在长时间使用的过程中性能下降。由于已经可以通过动力学尺度的分析来判断摩擦的剧烈程度，那么在此基础上得到磨损率，再利用预先建立的累计磨损率与密封劣化进度的关系，即可预估未来的性能变化和失效风险。同时，劣化进度本身也可以作为声学尺度和动力学尺度分析的参考。
本发明的有益效果：
本发明测量机械密封端面摩擦副产生的声发射信号，根据声发射信号在不同尺度上的特征所具备的不同物理内涵，在多个尺度上结合其他辅助信息开展分析，从 而判断密封的实时工作状态并给出密封的性能变化预期。
附图说明
图1是声发射传感器安装示意图。
图2是本发明的流程示意图。
图3是声学尺度示意图。
图4是动力学尺度示意图。
图5是服役尺度示意图。
具体实施方式
下面结合附图对本发明作进一步详细说明。
实施例1
参见图1。机械密封的静环1浮动支承在静环座4上，与之配对的是固联于轴上随之旋转的动环3。一个微型声发射传感器4被联接在静环1的背部，从而实时地将密封摩擦副产生的声发射信号转换为电信号，经放大器放大后，由采集系统(包括采集卡、采集软件及它们所依托的计算机)以f s＝2MHz的采样率采集信号U (0)，其称为原始信号。
参见图2，总的来说，本例的分析方法从声发射原始信号5出发，以其为主，辅以辅助信息和由经过实验数据标定的算法，经由声学尺度、动力学尺度和服役尺度三个不同的时间尺度上的处理，得到一系列关于密封工作状态的信息。具体来讲，在各个时间尺度上采用针对性的分析方法，得出物理表征量并传给时间更长的尺度(本例中声学尺度向动力学尺度传递摩擦功耗、最大接触深度和泄漏率，动力学尺度向服役尺度传递磨损率)，同时每个尺度都能各自得到对分析密封工作状态有意义的结果。同时，本例中声学尺度分析的部分辅助信息也来自服役尺度分析的结果。
声学尺度：
参见图3，在原始信号5中取连续的M＝256个采样点划分为一个声学尺度分析段6，则每个声学尺度分析段对应的时间长度为D (1)＝128μs。对每个声学尺度分析段，进行下面的处理流程：
(1)进行快速傅立叶变换，计算功率谱7。将各频率上的功率表示为M/2＝128维的初始特征向量。
(2)采用预处理算法对初始特征向量进行预处理，得到预处理后的特征向量8。预处理主要包括三个目的：①降噪，②使功率谱平滑化(避免极微小的频率差异带来的不具有实际物理意义的差异性结果)，③依据转速和累积磨损量进行修正，④进行必要的非线性映射以便后续线性分析开展。
(3)用转换矩阵将预处理后的初始特征向量8转换为一组具备实际意义的物理表征向量9：摩擦功耗、最大接触深度和泄漏率，将它们组装为3维向量U (1)。
这样便由每个声学尺度分析段6推算得到一个3维的声学尺度的物理表征向量9。
在原始信号中均匀地取声学尺度分析段，使每两个相邻的声学尺度分析段中点的时间间隔为T (1)＝512μs(本例中T (1)＞D (1)，故两个相邻的声学尺度分析段中存在被舍弃的数据，这样的取法可以减少计算量。T (1)＞D (1)并非必然的选择，计算资源充足的情况下也可采用T (1)＝D (1)甚至T (1)＜D (1)的方式以提高分析准确性)。这样，由各个声学尺度分析段得到的物理表征向量9便形成了相邻项时间间隔为T (1)＝512μs的序列10。
动力学尺度：
参见图4，动力学尺度的分析是对前述的声学尺度表征向量序列进行的，请参见图2：
(1)选取一段时长D (2)满足D (2)/T (1)为整数，且D (2)≥KT (s)并且D (2)尽量小。其中T (s)为旋转周期；K为整数且K≥2，以(2～10)为佳，本例取K＝3。例如，转速为6000rpm，则旋转周期为T (s)＝10ms，那么取长度为D (2)＝59T (1)＝30.208ms的时段。提取该时段的声学尺度表征向量序列(称为实测序列)，记为U (1)(i),i＝0,1,…,58；
(2)调取相应的密封型号、压强和转速的典型状态库11用于比对计算。典型状态库中包括数十个典型状态，每个典型状态以同样的T (1)记录了其声学尺度表征向量在一个周期内的变化序列(记为
Figure PCTCN2018117060-appb-000001
j为典型状态编号，称为典型序列)，同时记录了磨损状况(磨损形式和磨损率)和故障源存在情况(是否存在故障、若存在故障那么故障原因是什么)；
(3)计算选取时段的实测物理表征量序列与各个典型状态的一致度。将典型状态的物理表征量序列
Figure PCTCN2018117060-appb-000002
自我首尾相接共K-1＝2次，得到
Figure PCTCN2018117060-appb-000003
按下式计算一致度
Figure PCTCN2018117060-appb-000004
找出一致度最高的典型状态，将其磨损状况和故障源存在情况判断为密封此时最可能处于的状态。当存在多个典型状态的一致度都很高而差别不大时，则认为它们都有较大可能。近似认为累积磨损量是决定密封端面的劣化过程的主要因素，将磨损率记为U (2)用于服役尺度的分析。
服役尺度：
参见图5。本例中服役尺度的分析围绕密封环的磨损过程中其可靠性的变化来进行。参见图3：
(1)由于动力学分析可以获得磨损率U (2)，那么便可以计算密封运行中的磨损量：对于稳定工作过程，每隔一段时间选取一段时长为D (2)的动力学尺度分析段，相邻动力学尺度分析段中点时间差为T (2)，以该分析段求得的磨损率代表以该分析段中点为中点的T (2)时间区间内的磨损率；对于变转速工作过程，直接计算其过程中的磨损量。对于每个密封环，计算其累积磨损量12；
(2)通过可靠性测试实验分析，建立密封环累积磨损量与各可靠性指标(如密封环90％可靠度寿命、未来3个月损坏概率)的对应关系。
对照(1)(2)之结果，即可得到密封环的各可靠性指标13。这些可靠性指标可作为评价密封继续服役的风险、如果继续服役预计需要在多长时间后报废的依据，以便制定生产计划。
同时，累积磨损量一旦求得，便被接下来一段时间内的声学尺度分析所采用。

Claims (7)

  1. 一种机械密封多尺度实时监测分析方法，其特征在于，测量机械密封端面摩擦副产生的声发射信号，根据声发射信号在不同尺度上的特征所具备的不同物理内涵，在多个尺度上结合其他辅助信息开展分析，从而判断密封的实时工作状态并给出密封的性能变化预期。
  2. 根据权利要求1所述的一种机械密封多尺度实时监测分析方法，其特征在于，所述多尺度的实现方法是：在某个时间尺度(称为第N级时间尺度)上进行分析可以得到特定的结果，这一结果除本身具有物理意义外，还作为时间上更长的第(N+1)级时间尺度的分析对象——在第(N+1)级时间尺度上分析第N级的结果随时间的变化，将会得出另一方面的结果，并且类似地，这一结果不仅本身具有物理意义，还可以作为第(N+2)级时间尺度的分析对象，依此类推；
    在特定的条件下，较长的时间尺度下的结果也可以反馈给较短的时间尺度。
  3. 根据权利要求2所述的一种机械密封多尺度实时监测分析方法，其特征在于，所述尺度为声学尺度、动力学尺度和服役尺度，其中，特定的声源会在特定的若干个频段上产生信号，采集并识别这些信号的尺度称为声学尺度；密封运行过程中因动力学上的作用而产生运动，导致声发射信号随之变化，这一特征在与旋转周期相当的时间尺度上体现，这一尺度称为动力学尺度；密封长期服役过程中性能因包括磨合、磨损、弹性元件老化在内的原因发生累积性的性能变化，这一特征需要考察声发射信号长期的变化历程，这一尺度称为服役尺度。
  4. 根据权利要求3所述的一种机械密封多尺度实时监测分析方法，其特征在于，在声学尺度上结合其他辅助信息开展分析，从而判断密封的实时工作状态并给出密封的性能变化预期的具体步骤是；声学尺度的分析由一段时间很短的声发射波形结 合辅助信息获得一系列对应于摩擦副各方面状态的表征量，一种典型的方法是，对频率谱进行滤波、引入辅助信息修正等预处理，然后经由预设的根据频带与物理过程的对应关系建立的映射函数将频率谱变换为一系列物理表征量，这些表征量一方面本身具有向用户展示密封工作状态的作用，另一方面也是动力学尺度分析的基础。
  5. 根据权利要求3所述的一种机械密封多尺度实时监测分析方法，其特征在于，在动力学尺度上结合其他辅助信息开展分析，从而判断密封的实时工作状态并给出密封的性能变化预期的具体步骤是；密封动环随轴旋转时，对密封系统产生周期性的激励，从而导致密封系统产生周期性的动力学响应，而这种周期性响应的具体形式则与密封系统的摩擦剧烈程度和周向不均匀性等有密切的关系，通过实验测试或计算机模拟预先得到声学表征量动态变化模式与密封状态的关系的典型情况，即可反过来对被测量的设备在声学尺度分析的基础上进行进一步推断。
  6. 根据权利要求3所述的一种机械密封多尺度实时监测分析方法，其特征在于，在服役尺度上结合其他辅助信息开展分析，从而判断密封的实时工作状态并给出密封的性能变化预期的具体步骤是；密封运行过程中，密封环不可避免地会产生磨损，弹簧和副密封也可能在长时间使用的过程中性能下降，由于已经可以通过动力学尺度的分析来判断摩擦的剧烈程度，那么在此基础上得到磨损率，再利用预先建立的累计磨损率与密封劣化进度的关系，即可预估未来的性能变化和失效风险。
  7. 根据权利要求6所述的一种机械密封多尺度实时监测分析方法，其特征在于，将劣化进度本身作为声学尺度和动力学尺度分析的参考。
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