JPH0437338B2 - - Google Patents
Info
- Publication number
- JPH0437338B2 JPH0437338B2 JP59201894A JP20189484A JPH0437338B2 JP H0437338 B2 JPH0437338 B2 JP H0437338B2 JP 59201894 A JP59201894 A JP 59201894A JP 20189484 A JP20189484 A JP 20189484A JP H0437338 B2 JPH0437338 B2 JP H0437338B2
- Authority
- JP
- Japan
- Prior art keywords
- air conditioner
- failure
- blower
- air
- current value
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Lifetime
Links
- 238000001514 detection method Methods 0.000 claims description 8
- 230000007547 defect Effects 0.000 claims description 6
- 238000000034 method Methods 0.000 claims description 5
- 238000003745 diagnosis Methods 0.000 claims description 4
- 238000012544 monitoring process Methods 0.000 claims description 4
- 230000007257 malfunction Effects 0.000 claims 1
- 238000004378 air conditioning Methods 0.000 description 10
- 238000012423 maintenance Methods 0.000 description 8
- 238000010586 diagram Methods 0.000 description 7
- 230000007423 decrease Effects 0.000 description 6
- 230000005856 abnormality Effects 0.000 description 5
- 230000002950 deficient Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 230000002265 prevention Effects 0.000 description 2
- 230000002159 abnormal effect Effects 0.000 description 1
- 230000007797 corrosion Effects 0.000 description 1
- 238000005260 corrosion Methods 0.000 description 1
- 239000000428 dust Substances 0.000 description 1
- 238000005461 lubrication Methods 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Classifications
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/0001—Control or safety arrangements for ventilation
Landscapes
- Engineering & Computer Science (AREA)
- Chemical & Material Sciences (AREA)
- Combustion & Propulsion (AREA)
- Mechanical Engineering (AREA)
- General Engineering & Computer Science (AREA)
- Air Conditioning Control Device (AREA)
Description
【発明の詳細な説明】
本発明は、空気調和設備の運転状況の監視から
空気調和装置の故障を予知する故障診断方法に関
する。DETAILED DESCRIPTION OF THE INVENTION The present invention relates to a failure diagnosis method for predicting failure of an air conditioner from monitoring the operating status of the air conditioner.
ビル管理のうちの空調設備の管理に対しては、
温度、湿度、塵埃、還気、防災、振動、騒音、気
流、腐食、等の各種の管理技術が要求される。従
来、このような空調設備の管理技術は、メインテ
ナンス要員の個人的な経験と能力や知識に依存す
る割合が多く、空調設備の高度化と精密空調制御
に伴つて迅速且つ完全な管理を行うには限界が生
じてある。特に電算機室、半導体製造装置、医薬
品製造装置等の精密空調が要求されるところでの
ビル管理では、空調設備管理の重要性は極めて高
く、その管理技術は高度なものが要求され、完全
メンテナンスの維持が重要課題であるが、これを
個人的能力によつて維持するには問題がある。 For the management of air conditioning equipment in building management,
Various management techniques are required for temperature, humidity, dust, return air, disaster prevention, vibration, noise, airflow, corrosion, etc. Conventionally, management technology for such air conditioning equipment has largely depended on the personal experience, ability, and knowledge of maintenance personnel.As air conditioning equipment becomes more sophisticated and precision air conditioning control becomes more sophisticated, it has become increasingly difficult to manage it quickly and completely. There are limits to this. Especially in the management of buildings where precision air conditioning is required, such as computer rooms, semiconductor manufacturing equipment, pharmaceutical manufacturing equipment, etc., the importance of air conditioning equipment management is extremely high, and advanced management technology is required. Maintenance is an important issue, but there are problems in maintaining this through individual ability.
一般に、通常のビル管理において、防犯設備、
給排水設備、電気系統整備、防災設備などと共に
空調設備も一括して集中管理する管理室が設けら
れ、空調設備もその一環として集中管理システム
に組み込まれている場合が多い。このようなシス
テムにおいては、各種機器の自動制御に主眼がお
かれ、このシステムをメインテナンスのための不
良箇所の検出や故障予知に利用することは意図さ
れていないのが通常である。また、この集中管理
室に常駐する要員が空調設備の専門家である場合
は少なく、従つて彼等に適格なメインテナンス情
報を期待することもできない。 Generally, in normal building management, security equipment,
A control room is set up to centrally manage air conditioning equipment along with water supply and drainage equipment, electrical system maintenance, disaster prevention equipment, etc., and in many cases, air conditioning equipment is also incorporated into the central management system. In such systems, the main focus is on automatic control of various devices, and the system is usually not intended to be used for detecting defective parts or predicting failures for maintenance purposes. Furthermore, the personnel stationed in this central control room are rarely experts in air conditioning equipment, and therefore, it is not possible to expect them to provide qualified maintenance information.
このようなことから、不良や故障が許されない
空調設備に対して、その空調設備の故障予知シス
テムの開発が強く望まれている。 For these reasons, there is a strong desire to develop a failure prediction system for air conditioning equipment that cannot tolerate defects or failures.
本発明はこの要求を満足することを目的として
なされたものである。この目的を効果的に達成す
るシステムとして、本発明は、空気調和装置の運
転状況を検出する各種のセンサーから各検出信号
をコンピユータに入力して空気調和装置の運転状
況を監視するさいに、該検出信号として、空気調
和装置稼働中の送風機電動機の電流値（本明細書
では送風機電流値と略称する）と風量、並びに送
風機電動機の振動と温度を選択し、送風機電流値
と風量の相関値と空気調和装置の不良原因項目と
の間の相関情報、並びに送風機電動機の振動と温
度の相関値と空気調和装置の不良原因項目との間
の相関情報を予め求めておき、送風機電流値と風
量の検出信号、または送風機電動機の振動と温度
の検出信号が前記不良原因項目に対応する値に至
つたときにその不良原因項目をコンピユータが出
力し、空気調和装置が故障する前にその不良箇所
を予知する空気調和装置の故障診断方法を提供す
るものである。 The present invention has been made with the aim of satisfying this requirement. As a system that effectively achieves this objective, the present invention provides a system that monitors the operating status of an air conditioner by inputting each detection signal from various sensors that detect the operating status of the air conditioner into a computer. As the detection signals, the current value of the blower motor (abbreviated as the blower current value in this specification) and the air flow rate, as well as the vibration and temperature of the blower motor while the air conditioner is in operation are selected, and the correlation value between the blower current value and the air flow rate is determined. Correlation information between failure cause items of the air conditioner and correlation information between vibration and temperature of the blower motor and failure cause items of the air conditioner are obtained in advance, and correlation information between the failure cause items of the air conditioner and the blower current value and air volume are determined in advance. When the detection signal or the vibration and temperature detection signal of the blower motor reaches a value corresponding to the defect cause item, the computer outputs the defect cause item and predicts the defect location before the air conditioner breaks down. The present invention provides a failure diagnosis method for air conditioners.
以下に図面に従つて本発明の内容を具体的に説
明する。 The contents of the present invention will be specifically explained below with reference to the drawings.
第１図は、空気調和装置の運転状態から設備各
所の不良原因を検出するのに基礎とする送風機電
流値と風量の相関を示す。稼働中の空気調和装置
の送風機電流値を一方の入力情報、風量を他方の
入力情報としてこれを監視すると、両者の相関か
ら不良箇所を類別することができるのである。例
えば、既設の或る設備において、第１図に示すよ
うに、正常運転の帯域Ｎ（ハツチ部分）が定めら
れるが、両者の相関値がこの帯域から外れる程度
に従つて、また一方の入力情報が特異な値を示し
た場合に、不良原因がどこに存在するかを類別す
ることができる。 FIG. 1 shows the correlation between the blower current value and the air volume, which is used as a basis for detecting the cause of failure in various parts of the equipment from the operating state of the air conditioner. By monitoring the blower current value of an operating air conditioner as one input information and the air volume as the other input information, it is possible to classify the defective location based on the correlation between the two. For example, in some existing equipment, a band N (hatch area) of normal operation is determined as shown in Figure 1, but depending on the degree to which the correlation value of the two deviates from this band, If it shows a unique value, it is possible to classify where the cause of the defect exists.
より具体的には、送風機電流値と風量が共にＮ
より低下した場合には、その低下の傾向により、
Ａ フイルター目詰まり、
Ｂ ベルトスリツプ
Ｃ フリーアクセス抵抗大
Ｄ サージング現象（変動有り）
Ｅ ベルト切れ
などがその原因として挙げられ、さらにその低下
の程度が異常に大きくなると、電気系の異常と判
断される。 More specifically, both the blower current value and the air volume are N.
If the decrease is more than that, depending on the tendency of the decrease, A. Filter clogging, B. Belt slip, C. Large free access resistance, D. Surging phenomenon (variable), E. Belt breakage, etc., and the extent of the decrease can be further determined. If it becomes abnormally large, it is determined that there is an abnormality in the electrical system.
また、送風機電流値がＮより増加し、風量がＮ
より低下した場合には、その傾向に応じて、
Ｆ 軸受給油不足
Ｇ 軸受異常
がその原因として検出され、さらに送風機電流値
が異常に増加し風量が低下した場合には、電流値
破損、軸受破損が検出されることになる。 In addition, the blower current value increases from N, and the air volume decreases to N.
If it decreases further, F Insufficient bearing lubrication G Bearing abnormality is detected as the cause, and if the blower current increases abnormally and the air volume decreases, the current value is damaged or the bearing is damaged. will be detected.
また、送風機電流値と風量が共にＮより大きく
なつた場合には、
Ｈ 風量過大
の情報が入手される。 Further, when both the blower current value and the air volume become larger than N, information on excessive air volume is obtained.
送風機電流値は電流計から取り出されコンピユ
ータに入力され、送風機の電流と風量の特性から
求められる関係式により風量を出力し、この風量
と電流値との相関から前記のような判断を行う。 The blower current value is taken out from the ammeter and input to the computer, which outputs the airflow volume based on the relational expression determined from the characteristics of the blower current and airflow volume, and the above-mentioned judgments are made from the correlation between the airflow volume and the current value.
第２図は、送風機電動機の軸受１に振動センサ
ー２および表面温度センサー３を取付け、これら
で検出される値が域値を越えたとき励磁するリミ
ツトスイツチ（図示せず）が作動するようにし
て、そのON−OFF信号により故障の原因特性を
識別する状態図を示している。すなわち、第１図
の送風機電流値と風量の監視から、Ｆ、Ｇ、Ｈが
判断されたときに、この第２図のON−OFF信号
に基づいて電動機異常を類別して判断するのであ
る。 In Figure 2, a vibration sensor 2 and a surface temperature sensor 3 are attached to the bearing 1 of the blower motor, and a limit switch (not shown) is activated when the values detected by these sensors exceed a threshold value. A state diagram is shown in which the cause characteristic of a failure is identified based on the ON-OFF signal. That is, when F, G, and H are determined from the monitoring of the blower current value and air volume shown in FIG. 1, motor abnormalities are classified and determined based on the ON-OFF signals shown in FIG.
より具体的には、振動センサーと表面温度セン
サーの両者のリミツトスイツチが共にONの場合
には、
Ｉ 軸受摩耗または劣化
また、振動センサーのリミツトスイツチがON
で、表面温度センサーのリミツトスイツチが
OFFの場合には、
Ｊ ダイナミツクバランス異常、例えばシヤフ偏
芯またはブレード破損
更に、振動センサーのリミツトスイツチが
OFFで、表面温度センサーのリミツトスイツチ
がONの場合には、
Ｋ 軸受給油不足
をそれぞれ判断する。 More specifically, if the limit switches of both the vibration sensor and the surface temperature sensor are ON, then the limit switch of the vibration sensor is ON.
So, the limit switch of the surface temperature sensor is
If it is OFF, there is an abnormality in the J dynamic balance, such as shaft eccentricity or blade damage.In addition, the limit switch of the vibration sensor is
If it is OFF and the limit switch of the surface temperature sensor is ON, determine whether the K bearing is lubricated or not.
以上のような出力情報は全てコンピユータに入
力され、コンピユータはこのモニター情報を予め
登録されたストツク情報と対比判断して、警報メ
ツセージ、メインテナンスメツセージまたは異常
メツセージを選択して、警報ブザーやブラウン管
さらにはプランターが出力する。 All of the above output information is input to the computer, and the computer compares this monitor information with pre-registered stock information, selects an alarm message, maintenance message, or abnormality message, and sends an alarm buzzer, cathode ray tube, or even alarm message. Planter outputs.
第３図に、このコンピユータプログラミングの
一例を示す。第３図のフローにおけるAp、AL、
Amin、Amaxは、第４図の風量と送風機電流値
との関係図に示した値をそれぞれ表している。ま
たMDはモータダンパを、また、PACは本体故障
時のバツクアツプ用に備えられたパツケージ型空
気調和装置を表す。 FIG. 3 shows an example of this computer programming. A p , AL in the flow of Figure 3,
Amin and Amax each represent the values shown in the relation diagram between air volume and blower current value in FIG. 4. Also, MD stands for a motor damper, and PAC stands for a package type air conditioner that is provided for backup in case of main unit failure.
第３図のフローに示すように、送風機電流値と
風量の相関情報、並びに軸受の振動および温度の
情報から、各種の警報メツセージ（異常メツセー
ジを含む）とメインテナンスメツセージを選択し
て取り出すことができ、しかも、そのさいには故
障箇所の表示もできる。従つて、本発明法による
と、空気調和装置の故障の機器診断が確実且つ容
易に行うことが可能となり、その故障予知と、こ
れに基づくメインテナンスの実行を、従来の経験
則に代えて機器判断のもとに行うことができ、そ
の信頼性を大きく高めることができる。 As shown in the flowchart in Figure 3, various alarm messages (including abnormal messages) and maintenance messages can be selected and retrieved from the correlation information between the blower current value and air volume, as well as the vibration and temperature information of the bearing. Moreover, the location of the failure can also be displayed at this time. Therefore, according to the method of the present invention, equipment diagnosis of failures in air conditioners can be performed reliably and easily, and failure prediction and maintenance based on this can be performed based on equipment judgment instead of conventional empirical rules. It can be carried out under the following conditions, and its reliability can be greatly improved.
第１図は送風機電流値と風量から故障原因を判
断するための基本関係図、第２図は電動機の振動
と温度から故障原因を判断するための説明図、第
３図は本発明を実施するためのコンピユータプロ
グラミングの一例を示すフロー図、第４図は第３
図中の信号値を説明するための送風機電流値と風
量との関係図である。
１……軸受、２……振動センサー、３……表面
温度センサー。
Figure 1 is a basic relationship diagram for determining the cause of failure from the blower current value and air volume, Figure 2 is an explanatory diagram for determining the cause of failure from motor vibration and temperature, and Figure 3 is a diagram for implementing the present invention. A flow diagram showing an example of computer programming for
FIG. 3 is a relationship diagram between blower current value and air volume for explaining the signal values in the figure. 1...Bearing, 2...Vibration sensor, 3...Surface temperature sensor.
Claims (1)
ンサーから各検出信号をコンピユータに入力して
空気調和装置の運転状態を監視するさいに、該検
出信号として、空気調和装置稼働中の送風機電流
値と風量、並びに送風機電動機の振動と温度を選
択し、送風機電流値と風量の相関値と空気調和装
置の不良原因項目との間の相関情報、並びに送風
機電動機の振動と温度の相関値と空気調和装置の
不良原因項目との間の相関情報を予め求めてお
き、送風機電流値と風量の検出信号、または送風
機電動機の振動と温度の検出信号が前記不良原因
項目に対応する値に至つたときにその不良原因項
目をコンピユータが出力し、空気調和装置が故障
する前にその不良箇所を予知する空気調和装置の
故障診断方法。1. When monitoring the operating status of an air conditioner by inputting each detection signal from various sensors that detect the operating status of the air conditioner to a computer, the detection signal is the current value of the blower while the air conditioner is in operation. Select the air volume, the vibration and temperature of the blower motor, and obtain the correlation information between the correlation value of the blower current value and the air volume and the defect cause item of the air conditioner, as well as the correlation value of the vibration and temperature of the blower motor and the air conditioner. Correlation information between the failure cause items is obtained in advance, and when the detection signal of the blower current value and air volume, or the vibration and temperature detection signal of the blower motor reaches the value corresponding to the failure cause item, the correlation information is determined in advance. A failure diagnosis method for air conditioners in which a computer outputs the items causing the failure and predicts the location of the failure before the air conditioner malfunctions.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP59201894A JPS6183831A (en) | 1984-09-28 | 1984-09-28 | Failure diagnosing method of air conditioner |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP59201894A JPS6183831A (en) | 1984-09-28 | 1984-09-28 | Failure diagnosing method of air conditioner |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| JPS6183831A JPS6183831A (en) | 1986-04-28 |
| JPH0437338B2 true JPH0437338B2 (en) | 1992-06-19 |
Family
ID=16448584
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP59201894A Granted JPS6183831A (en) | 1984-09-28 | 1984-09-28 | Failure diagnosing method of air conditioner |
Country Status (1)
| Country | Link |
|---|---|
| JP (1) | JPS6183831A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101995311B1 (en) * | 2018-05-29 | 2019-09-24 | 경상대학교산학협력단 | Diagnosis method for air conditioning system and device thereof |
Families Citing this family (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH03255840A (en) * | 1990-03-06 | 1991-11-14 | Shimizu Corp | Air-conditioner with self-diagnosis |
| JP3321487B2 (en) * | 1993-10-20 | 2002-09-03 | 株式会社日立製作所 | Device / equipment diagnosis method and system |
| ITBO20030711A1 (en) * | 2003-11-24 | 2005-05-25 | Gd Spa | METHOD FOR PREDICTIVE MAINTENANCE OF A COMPONENT |
| DE102005012221A1 (en) * | 2005-03-15 | 2006-09-21 | Tlt-Turbo Gmbh | Method for checking the device status of a fan |
| CN106839334B (en) * | 2017-03-07 | 2019-12-03 | 青岛海尔空调器有限总公司 | A kind of air conditioner self-protecting device and the air conditioner with the self-protecting device |
| US12007133B2 (en) * | 2017-06-29 | 2024-06-11 | American Air Filter Company, Inc. | Sensor array environment for an air handling unit |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS5194652A (en) * | 1975-02-18 | 1976-08-19 | Kuchoyodendokino kanetsuhogokenyoshitsuonchosetsuki | |
| JPS5457209A (en) * | 1977-10-13 | 1979-05-08 | Toshiba Corp | Blower |
| JPS54141408A (en) * | 1978-04-26 | 1979-11-02 | Toshiba Corp | Filter clogging detecting device |
| JPS5623656A (en) * | 1979-08-01 | 1981-03-06 | Sanyo Electric Co Ltd | Air flow detecting system for air-conditioner |
| JPS5627850A (en) * | 1979-08-13 | 1981-03-18 | Sharp Corp | Filter clogging alarm |
-
1984
- 1984-09-28 JP JP59201894A patent/JPS6183831A/en active Granted
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS5194652A (en) * | 1975-02-18 | 1976-08-19 | Kuchoyodendokino kanetsuhogokenyoshitsuonchosetsuki | |
| JPS5457209A (en) * | 1977-10-13 | 1979-05-08 | Toshiba Corp | Blower |
| JPS54141408A (en) * | 1978-04-26 | 1979-11-02 | Toshiba Corp | Filter clogging detecting device |
| JPS5623656A (en) * | 1979-08-01 | 1981-03-06 | Sanyo Electric Co Ltd | Air flow detecting system for air-conditioner |
| JPS5627850A (en) * | 1979-08-13 | 1981-03-18 | Sharp Corp | Filter clogging alarm |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101995311B1 (en) * | 2018-05-29 | 2019-09-24 | 경상대학교산학협력단 | Diagnosis method for air conditioning system and device thereof |
Also Published As
| Publication number | Publication date |
|---|---|
| JPS6183831A (en) | 1986-04-28 |
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