CN100430309C

CN100430309C - The elevator device

Info

Publication number: CN100430309C
Application number: CNB2004100456326A
Authority: CN
Inventors: 冈田浩二
Original assignee: Mitsubishi Electric Corp
Current assignee: Mitsubishi Electric Corp
Priority date: 2004-03-02
Filing date: 2004-05-21
Publication date: 2008-11-05
Anticipated expiration: 2024-05-21
Also published as: CN1663900A; JP2005247468A

Abstract

This invnetion provides an elevator device capable of determining occurrence of abnormality of a hoisting machine with high reliability by simultaneously detecting noise and vibration of the hoisting machine. In the rope type elevator device, a car 3 is lifted by driving the hoisting machine 1. The elevator device is provided with an elevator control board 8 for driving/controlling the hoisting machine 1; a noise sensor 6 for detecting noise level Dn of the hoisting machine 1; a vibration sensor 7 for detecting vibration level Dv of the hoisting machine 1; and a hoisting machine abnormality determination means 9 for inputting a failure signal E of the hoisting machine 1 to the elevator control panel 8 based on the noise level Dn and the vibration level Dv. The elevator control panel 8 has a monitoring informing unit 8a and drives the monitoring informing unit 8 in response to the failure signal E.

Description

Lift appliance

Technical field

The present invention relates to the cable type lift appliance that drives winch and make car carry out lifting, relates in particular to the technology of judging unusually that high reliability ground takes place winch.

Background technology

Generally, in the lift appliance of cable type,, in fact before becoming the fail to start state, can not find the generation of fault to winch because of the bearing of winch or the insufficient lubrication of gear etc. cause under the situation that degradation failure takes place.

Therefore, as lift appliance in the past, in order to realize in early days repairing when unusual the generation, proposed that operation noise when detecting abnormal vibrations writes down and the motion of carrying out safety inspection reliably (for example, with reference to patent documentation 1: Japanese patent laid-open 9-175749 communique).

In lift appliance in the past owing to only abnormal vibrations is detected, so existence can not high reliability problem that unusual generation state is differentiated.

Summary of the invention

The objective of the invention is to, obtain the lift appliance of judging unusually that energy high reliability ground takes place winch.

Lift appliance of the present invention is to drive winch and make car carry out the lift appliance of the cable type of lifting, has: the control board for elevator of drive controlling winch; Detect the sensor noise of the noise level of winch; Detect the vibration sensor of the vibration level of winch; The winch abnormity determining device of the breakdown signal of winch being imported to control board for elevator according to noise level and vibration level, control board for elevator, has the supervision alarm device, responsively the supervision alarm device is driven with breakdown signal, described winch abnormity determining device comprises and will carry out frequency analysis respectively from the noise level of described sensor noise with from the vibration level of described vibration sensor, generates the frequency analyzer of feature of noise point data and vibration performance point data; Store the common unique point memory device of common feature of noise point data and common vibration performance point data respectively; The noise level evaluator that described feature of noise point data and described common feature of noise point data are compared; The vibration level evaluator that described vibration performance point data and described common vibration performance point data are compared; The abnormal patterns data memory of the cooresponding abnormal patterns data of each evaluation result of storage and described noise level evaluator and described vibration level evaluator; And, under situation about the fault of described winch being differentiated, generate the fault distinguishing device of described breakdown signal according to described each evaluation result with reference to described abnormal patterns data.

The effect of invention

Adopt the present invention, detect by noise and the vibration to winch simultaneously, can high reliability ground judging unusually to the winch generation.

Description of drawings

Fig. 1 is the frame assumption diagram of the lift appliance of expression the invention process form 1.

Fig. 2 is the block scheme of the functional structure of the winch abnormity determining device in the presentation graphs 1.

Fig. 3 is the diagram of circuit of concrete action of the winch abnormity determining device of expression the invention process form 1.

Fig. 4 is the instruction diagram of abnormal patterns (pattern) data of expression the invention process form 1.

Fig. 5 is the block scheme of winch abnormity determining device of the lift appliance of expression the invention process form 2.

Fig. 6 is the diagram of circuit of concrete action of the winch abnormity determining device of expression the invention process form 2.

Fig. 7 is the instruction diagram of the abnormal patterns data of expression the invention process form 2.

Nomenclature

The 1-winch; The 2-hawser; The 3-car; 6-microphone (sensor noise); 7-acceleration pick-up (vibration sensor); The 8-control board for elevator; The 8a-monitor scope; 9,9A-winch abnormity determining device; The common noise memory device of 10-; The common feature of noise point memory device of 10A-; 11,11A-noise level evaluator; 12-vibrates memory device usually; The common vibration performance point memory device of 12A-; 13,13A-vibration level evaluator; 14,14A-abnormal patterns data memory; 15,15A-fault distinguishing device; The common quantitative data input switch of SW-; The Dn-noise level; The Dv-vibration level; Dfn-feature of noise point data; Dfv-vibration performance point data; F (n)-noise evaluation result; F (v)-the vibration evaluation result; The E-breakdown signal; The M-connection signal; Δ Dn-noise level deviation; Δ Dv-vibration level deviation

The specific embodiment

Example 1

Among Fig. 1, lift appliance has: be arranged on the winch 1 in the Machine Room of the building the superiors; Be wound on the hawser 2 on the winch 1; Two ends bonded assembly car 3 and counterweight 4 with hawser 2; Hawser 2 is carried out the deflector sheave 5 that local derviation is used.

Recently, also use not to be provided with the Machine Room and equipment is provided in machine room-less elevator device in the hoist trunk, in such machine room-less elevator device, also can use the present invention certainly.

Again, the lift appliance of cable type shown in Figure 1 in order to drive winch 1 and to make car 3 liftings, has: as the microphone sensor 6 of the sensor noise function of winch 1; Play the acceleration pick-up 7 of the vibration sensor effect of winch 1; Electrical motor (not shown) in the drive controlling winch 1 and the control board for elevator 8 that car 3 liftings are moved; Be located at the monitor scope 8a on the control board for elevator 8; Winch abnormity determining device 9 to control board for elevator 8 input fault signal E takes place when unusual at winch 1; Common quantitative data input switch SW.

Microphone sensor 6 (sensor noise) and acceleration pick-up 7 (vibration sensor) often detect noise level Dn and vibration level Dv, import to winch abnormity determining device 9 as noise measuring value and vibration detection value respectively.

Winch abnormity determining device 9, it is no abnormal to judge that according to noise level Dn and vibration level Dv winch 1 has, and is being judged to be when error state takes place breakdown signal E to control board for elevator 8 inputs.

Monitor scope 8a as monitoring the alarm device function is driven under the control of control board for elevator 8, when winch 1 generation is unusual, shows generation error state (comprising fault content etc.) with breakdown signal E response.

Again, with the common quantitative data input switch SW of winch abnormity determining device 9 bonded assemblys, be arranged to and operate from the outside, when the input pattern of common data (for example, during the normal operation of elevator) carry out making operation by the operator, just with connection signal M to 9 inputs of winch abnormity determining device.

Fig. 2 is the block scheme of the concrete functional structure of the winch abnormity determining device 9 in the presentation graphs 1.

Among Fig. 2, winch abnormity determining device 9 has: common noise memory device 10; Noise level evaluator 11; Usually vibrate memory device 12; Vibration level evaluator 13; Abnormal patterns data memory 14 and fault distinguishing device 15.From the connection signal M that common quantitative data input switch SW is come, noise level evaluator 11 in winch abnormity determining device 9 and 13 inputs of vibration level evaluator.

Usually noise memory device 10 and connection signal M response, and will store as common noise level (data usually) from the noise level Dn of microphone sensor 6.

Equally, vibrate memory device 12 and connection signal M response usually, and the vibration level Dv of self-acceleration sensor 7 stores as common vibration level (data usually) in the future.

Noise level evaluator 11 compares the common noise level in the common noise memory device 10 with noise level Dn from microphone sensor 6, calculate both noise level deviation delta Dn.

Equally, vibration level evaluator 13 compares the common vibration level of vibrating usually in the memory device 12 with vibration level Dv from acceleration pick-up 7, calculate both vibration level deviation delta Dv.

Abnormal patterns data memory 14, the cooresponding abnormal patterns data of each evaluation result of storage and noise level evaluator 11 and vibration level evaluator 13.

Fault distinguishing device 15, with reference to the abnormal patterns data in the abnormal patterns data memory 14, noise level deviation delta Dn and vibration level deviation delta Dv than the big situation of specified value α n, α v under, differentiate and be winch 1 et out of order state, generate breakdown signal E and to control board for elevator 8 inputs.

Then, with reference to Fig. 3 and Fig. 4, the concrete action of the elevator control gear of the invention process form 1 illustrated in figures 1 and 2 is described.

In common noise memory device 10 and common vibration memory device 12, preestablish the initial value of each common level again.

Fig. 3 is the diagram of circuit of the processing action of expression winch abnormity determining device 9, and Fig. 4 is the instruction diagram of the abnormal patterns data in the expression abnormal patterns data memory 14.

Among Fig. 4, the longitudinal axis is common noise level (data usually) and the noise level deviation delta Dn that detects noise level Dn (detection data), and transverse axis is common vibration level (data usually) and the vibration level deviation delta Dv that detects vibration level Dv (detection data).

Abnormal patterns data shown in Figure 4, its a plurality of fault zones related with each specified value α n, α v are made of 2 dimension figure.

Among Fig. 3, at first, whether noise level evaluator 11 and vibration level evaluator 13 in the winch abnormity determining device 9 are carried out making operation (generating connection signal M) to common quantitative data input switch SW and are judged (step S1).

In step S1, generate connection signal M (being YES) if be judged to be, each evaluator 11,13 reflection present situation is in the input pattern of common data, the detected value (noise level Dn, vibration level Dv) of each

sensor

6,7 that will import from present moment is as level storage is in each memory device 10,12 (step S2) usually, and the handler of Fig. 3 finishes.

On the other hand, in step S1, do not generate connection signal M (being NO) if be judged to be, each evaluator 11,13 reflection present situation is in the abnormality juding pattern, to compare from detected value Dn, the Dv of each

sensor

6,7 and the common data in each

memory device

10,12, noise level deviation delta Dn and vibration level deviation delta Dv will be carried out computing (step S3).

In Fig. 3, noise level deviation delta Dn and vibration level deviation delta Dv are expressed as deviation delta D with being referred to as again.

Then, fault distinguishing device 15 in the winch abnormity determining device 9, noise level deviation delta Dn and vibration level deviation delta Dv and the specified value α n, the α v that become abnormality juding benchmark are separately compared, the condition that whether satisfies Δ Dn≤α n and Δ Dv≤α v is judged (step S4).

In Fig. 3, with specified value α n, the α v of each deviation delta Dn, Δ Dv are expressed as specified value α with being referred to as relatively.

In step S4, if be judged to be the condition (being YES) that satisfies Δ Dn≤α n and Δ Dv≤α v, fault distinguishing device 15 reflection winchs 1 are normal condition, finish the handler of Fig. 3 immediately.

On the other hand, in step S4,, reflect that then winch 1 is that error state takes place, and with reference to abnormal patterns data (with reference to Fig. 4), infers fault content (step S5) according to each deviation delta Dn and Δ Dv if be judged to be Δ Dn＞α n and Δ Dv＞α v (being NO).

At this moment, fault distinguishing device 15 is according to which the regional corresponding fault content of inferring of 2 dimension figure in the value of each deviation delta Dn, Δ Dv and Fig. 4.

That is to say, among Fig. 4, if each deviation delta Dn, Δ Dv are specified value α n, below the α v, then are judged to be no abnormal (normally).

Again, noise level deviation delta Dn only than the big situation of specified value α n under, be estimated as " the insufficient lubrication state of lubricating oil " or " slipping state of hawser 2 ", vibration level deviation delta Dv only than the big situation of specified value α v under, be estimated as " defective mode of bearing " or " the release defective mode of drg ".

Again, each deviation delta Dn, Δ Dv all than the big situation of specified value α n, α v under, be estimated as " damaged condition of gear " or " oscillatory regime of control system ".

As shown in Figure 4, be stored in the abnormal patterns data (2 dimension figure) in the abnormal patterns data memory 14, because it is corresponding that, fault distinguishing device 15 and 2 corresponding with each evaluation result of noise level evaluator 11 and vibration level evaluator 13 tieed up a plurality of zones of figure, so can infer individual other fault content.

At last, fault distinguishing device 15, according to the abnormal patterns data with fault content (fault cause) infer the result with breakdown signal E to control board for elevator 8 input (step S6), finish the handler of Fig. 3.

Thus, control board for elevator 8 drives monitor scope 8a, shows error state and fault cause etc. take place, and utilize remote supervision system (not shown) etc. to circulating a notice of the need maintenance position, and impel winch 1 promptly to reply by the operator.

Like this, owing to be provided with microphone sensor 6, acceleration pick-up 7 and winch abnormity determining device 9, noise level Dn and vibration level Dv are analyzed in combination, and normal data (noise level just often and vibration level) compared with detecting data Dn, Dv, so can whether the unusual correct judgement of carrying out be arranged to winch 1.

Again, owing to reference to abnormal patterns data (Fig. 4), one side noise level Dn and vibration level Dv are analyzed in combination on one side, so can infer the fault content of winch 1 clearly.

Therefore, can promptly handle in the deterioration of to state of elevator fail to start etc., discovering part.

Again, the abnormal patterns data of Fig. 4 are only represented an example of fault content, and are not limited thereto.

Here,, also can whether judge unusual having or not according to detecting level Dn, Dv above any multiple (for example, 1.5 times) of common level though judge unusual having or not with the deviation delta Dn, the Δ Dv that detect level according to common level again.

Example 2

In above-mentioned example 1,, also the result of frequency analysis can be estimated as feature point extraction ground though noise level Dn and vibration level Dv have been done evaluation respectively again.

Below, the example of the present invention 2 that carries out abnormality juding from detection data frequency analysis result is described.

Fig. 5 is the block scheme of winch abnormity determining device 9A of the lift appliance of expression the invention process form 2, to putting on symbol as hereinbefore or put on " A ", detailed behind symbol with aforementioned (with reference to Fig. 2) same part.

The integral structure of the lift appliance of example 2 of the present invention, as shown in Figure 1, the local structure difference in the winch abnormity determining device 9A only.

Among Fig. 5, winch abnormity determining device 9A, frequency analyzer 16,17 with the outgoing side that is inserted in each

sensor

6,7 also has the common feature of noise point memory device 10A related with each evaluator 11A, 13A and common vibration performance point memory device 12A replaces aforesaid common noise memory device 10 and vibrates memory device 12 usually.

Frequency analyzer 16 carries out frequency analysis and generates feature of noise point data Dfn the noise level Dn from microphone sensor 6, and imports to noise level evaluator 11A.

Equally, frequency analyzer 17 carries out frequency analysis and generates vibration performance point data Dfv the vibration level Dv from acceleration pick-up 7, and imports to vibration level evaluator 13A.

Usually feature of noise point memory device 10A and vibration performance point memory device 12A usually with the connection signal M response, store with common feature of noise point data with after the vibration performance point data is upgraded respectively usually.

Noise level evaluator 11A compares feature of noise point data Dfn, and feature of noise point data Dfn and comparative result (aftermentioned) is imported to fault distinguishing device 15A as noise evaluation result f (n) with common feature of noise point data.

Equally, vibration level evaluator 13A compares vibration performance point data Dfv with common vibration performance point data, and vibration performance point data Dfv and comparative result (aftermentioned) (are v) imported to fault distinguishing device 15A as vibration evaluation result f.

Abnormal patterns data memory 14A, each evaluation result f (n), f (v) cooresponding abnormal patterns data (with reference to Fig. 7) of storage and each evaluator 11A, 13A.

Fault distinguishing device 15A with reference to the abnormal patterns data, (is v) generating breakdown signal E from each evaluation result f (n), f under the situation that the fault of winch 1 is differentiated.

When the winch abnormity determining device 9A in Fig. 5 is described more specifically, frequency analyzer 16,17, (for example, frequency f N=10) and frequency peak fp extract as feature of noise point data Dfn and vibration performance point data Dfv, and import to each evaluator 11A, 13A with stated number N.

Each unique

point memory device

10A, 12A with the connection signal M response from common quantitative data input switch SW, will store as common feature of noise point data and common vibration performance point data respectively from each characteristic point data of frequency analyzer 16,17.

Noise level evaluator 11A, calculate the feature of noise point data Dfn of stated number N and the feature of noise point deviation delta Dfn of common feature of noise point data, generate feature of noise point data Dfn and the feature of noise point deviation delta Dfn of stated number N as noise evaluation result f (n).

Equally, vibration level evaluator 13A, calculate the vibration performance point data Dfv of stated number N and the vibration performance point deviation delta Dfv of common vibration performance point data, f (v) generates vibration performance point data Dfv and the vibration performance point deviation delta Dfv of stated number N as the vibration evaluation result.

Fault distinguishing device 15A, in the feature of noise point deviation delta Dfn and vibration performance point deviation delta Dfv of stated number N, from big 3 point data of in turn extracting, at least 1 feature of noise point deviation delta Dfn in 3 point data or vibration performance point deviation delta Dfv generate breakdown signal E than under the big situation of specified value β n (β fn, β fpn), β v (β fv, β fpv).

Abnormal patterns data memory 14A, to store as abnormal patterns data (Fig. 7) with the cooresponding 2 dimension figure of each evaluation result of each evaluator 11A, 13A, fault distinguishing device 15A, corresponding with a plurality of zones of 2 dimension figure, equally individual other fault content is differentiated with aforementioned.

Then, on one side with reference to Fig. 6 and Fig. 7, one side describes the concrete processing action of the lift appliance of the invention process form 2 shown in Figure 5.

In each unique

point memory device

10A, 12A, preestablish the initial value of each common characteristic point data again.

Fig. 6 is the diagram of circuit of the processing action of expression winch abnormity determining device 9A, and Fig. 7 is the instruction diagram of the abnormal patterns data in the expression abnormal patterns data memory 14A.

Among Fig. 7, the longitudinal axis is noise level frequency f n, and transverse axis is oscillation frequency fv, and a plurality of fault zones that will be related with 3 point data fv1～fv3 of 3 point data fn1～fn3 of frequency noise and oscillation frequency constitute as the abnormal patterns data of 2 dimension figure.

In Fig. 6, step S11～S16 is the processing same with each step S1～S6 of aforementioned (with reference to Fig. 3).

At first, frequency analyzer 16,17 in the winch abnormity determining device 9A, detection data (noise level Dn, vibration level Dv) from each

sensor

6,7 are carried out frequency analysis, extract frequency f n, fv and frequency peak fpn, the fpv of stated number N respectively, and import (step S10) to each evaluator 11A, 13A as each characteristic point data Dfn, Dfv.

At this moment, because of the difference at lift facility and vibration position (bearing, gear, electrical motor etc.), and because different natural frequency mutually takes place, so each characteristic point data Dfn, Dfv indication equipment and vibration position.

Then, each evaluator 11A, 13A, to whether judging (step S11) from common quantitative data input switch SW generation connection signal M, generate connection signal M (being YES) if be judged to be, then owing to be reflected as the input pattern of common data, so each characteristic point data Dfn, Dfv that present moment is imported are stored among each

memory device

10A, 12A (step S12) as common characteristic point data, finish the handler of Fig. 3.

At this moment, because the store predetermined characteristic point data of counting N only, so can alleviate the capacity of each

memory device

10A, 12A.

On the other hand, in step S11, if do not generate connection signal M (being NO), then because each evaluator 11,13 is reflected as the abnormality juding pattern, so the common characteristic point data in each characteristic point data Dfn, Dfv and each memory device 10A, the 12A is compared, each unique point deviation delta Dfn, Δ Dfv are carried out computing, and fault distinguishing device 15A in turn extracts 3 point data (step S3) from the big side of each unique point deviation delta Dfn, Δ Dfv.

At this moment, extract owing to be defined in 3 point data ground, so can reduce as the sample of judging object.But, be not limited to 3 point data, can set data number arbitrarily as required for.

Again, in Fig. 6, frequency deviation fn, the Δ fv relevant with vibration with noise are expressed as deviation delta f with being referred to as, frequency peak deviation delta fpn, the Δ fpv relevant with vibration with noise are expressed as deviation delta fp with being referred to as.

Then, fault distinguishing device 15A, deviation delta f, the Δ fp of 3 point data relevant with vibration with noise are compared with the specified value β (β f, β fp) that becomes abnormality juding benchmark separately, and the condition whether all deviations satisfy below the specified value β is judged (step S14).

Among Fig. 6, with the specified value general designation of relative each deviation be expressed as β.

In step S14, if be judged to be all deviations (being YES) below specified value β, then fault distinguishing device 15A reflection winch 1 is a normal condition, finishes the handler of Fig. 6 immediately.

On the other hand, in step S14, if be judged to be each 3 point data wantonly 1 than specified value β big (being NO), then be reflected as winch 1 generation error state, with reference to abnormal patterns data (with reference to Fig. 7), infer fault content (step S15) according to the abnormal data (frequency f) in each 3 point data.

At this moment, fault distinguishing device 15, according to abnormal data whether with Fig. 7 in which regional corresponding fault content of inferring of 2 dimension figure.

Among Fig. 7, the abnormal patterns data representation extracts one of the situation example of trouble location pattern of point of crossing of 3 point data fv1～fv3 of the 3 point data fn1～fn3 be positioned at frequency noise and oscillation frequency.

For example, under the situation with the point of crossing " fn2, fv1 " shown in the stain, " fn1, fv3 " in Fig. 7,, be judged to be and " lubricating " or " bearing " relevant unfavorable condition as the fault content.

As shown in Figure 7, be stored in the abnormal patterns data (2 dimension figure) among the abnormal patterns data memory 14A, because it is corresponding with each evaluation result of noise level evaluator 11 and vibration level evaluator 13, so fault distinguishing device 15A can infer other fault content accordingly with a plurality of zones of 2 dimension figure.

At last, fault distinguishing device 15A, according to the abnormal patterns data with fault content (fault cause) infer the result with breakdown signal E to control board for elevator 8 input (step S16), finish the handler of Fig. 6.

Like this, the breakdown signal E and the fault content result of determination that send to control board for elevator 8 are shown on monitor scope 8a, and impel winch 1 promptly to reply by the operator.

Like this, frequency analysis according to noise and vibration level Dn, Dv compares each characteristic point data and characteristic point data just often, owing to (v) having or not with content of fault differentiated, so can carry out correct judgement to the error state of winch 1 from each evaluation result f (n), f.

Again, owing to can with reference to abnormal patterns data (Fig. 7), one side frequency noise fn and oscillation frequency fv be analyzed in combination on one side, so can infer the fault content of winch 1 clearly.

Therefore, can to the state of elevator fail to start etc., discover the deterioration of part and can promptly handle.

Claims

1. a lift appliance is to drive the cable type lift appliance that winch makes the car lifting, it is characterized in that,

Have

The control board for elevator of the described winch of drive controlling;

Detect the sensor noise of the noise level of described winch;

Detect the vibration sensor of the vibration level of described winch; And

According to described noise level and described vibration level with the breakdown signal of described winch winch abnormity determining device to described control board for elevator input,

Described control board for elevator has the supervision alarm device, responds described breakdown signal, described supervision alarm device is driven,

Described winch abnormity determining device comprises

To carry out frequency analysis respectively from the noise level of described sensor noise with from the vibration level of described vibration sensor, generate the frequency analyzer of feature of noise point data and vibration performance point data;

Store the common unique point memory device of common feature of noise point data and common vibration performance point data respectively;

The noise level evaluator that described feature of noise point data and described common feature of noise point data are compared;

The vibration level evaluator that described vibration performance point data and described common vibration performance point data are compared;

The abnormal patterns data memory of the cooresponding abnormal patterns data of each evaluation result of storage and described noise level evaluator and described vibration level evaluator; And

With reference to described abnormal patterns data, under situation about the fault of described winch being differentiated, generate the fault distinguishing device of described breakdown signal according to described each evaluation result.

2. lift appliance as claimed in claim 1 is characterized in that,

Described frequency analyzer, the frequency and the frequency peak of extraction defined amount, as described feature of noise point data and described vibration performance point data,

Described noise level evaluator calculates the feature of noise point data of described defined amount and the feature of noise point deviation of described common feature of noise point data,

Described vibration level evaluator calculates the vibration performance point data of described stated number and the vibration performance point deviation of described common vibration performance point data,

Described fault distinguishing device extracts 3 point data in order from a big side in the feature of noise point deviation of described defined amount and vibration performance point deviation, under the big situation of at least 1 feature of noise point deviation in described 3 point data or vibration performance point deviation ratio specified value, generate described breakdown signal.

3. lift appliance as claimed in claim 1 is characterized in that,

Have the common quantitative data input switch that when the input pattern of common data, generates connection signal,

Described common unique point memory response will be stored as described common feature of noise point data and described common vibration performance point data respectively from the feature of noise point data and the vibration performance point data of described frequency analyzer from the connection signal of described common quantitative data input switch.

4. lift appliance as claimed in claim 1 is characterized in that,

Described abnormal patterns data memory will be stored as described abnormal patterns data with the cooresponding 2 dimension figure of each evaluation result of described noise level evaluator and described vibration level evaluator,

Cooresponding other fault content of described fault distinguishing device pair and a plurality of zones of described 2 dimension figure inferred, and the result that infers of described fault content is imported to described control board for elevator with described breakdown signal.